From e866c6e00c8d0eb8e8a85bea6ec5bf442fd9edba Mon Sep 17 00:00:00 2001 From: Tamir Date: Thu, 23 Mar 2023 00:28:15 -0300 Subject: [PATCH 001/265] Ignore changes to .lock --- .gitignore | 1 + 1 file changed, 1 insertion(+) diff --git a/.gitignore b/.gitignore index 4734f531a..b2973e34b 100644 --- a/.gitignore +++ b/.gitignore @@ -140,3 +140,4 @@ dmypy.json notebooks/ /tests/ +poetry.lock From c2a2dd0a07fa3c847ce3b7db271689195a977af7 Mon Sep 17 00:00:00 2001 From: Tamir Date: Thu, 23 Mar 2023 01:21:48 -0300 Subject: [PATCH 002/265] Add base as reference --- br_denatran_frota/README.md | 20 ++ br_denatran_frota/code/download_frota.R | 121 ++++++++ br_denatran_frota/code/download_frota_old.R | 106 +++++++ br_denatran_frota/code/frota_municipio_tipo.R | 137 +++++++++ br_denatran_frota/code/frota_uf_tipo.R | 97 +++++++ br_denatran_frota/code/utils.R | 207 ++++++++++++++ br_denatran_frota/dataset_config.yaml | 69 +++++ br_denatran_frota/municipio_tipo/publish.sql | 50 ++++ .../municipio_tipo/schema-prod.json | 1 + .../municipio_tipo/schema-staging.json | 1 + .../municipio_tipo/table_config.yaml | 268 ++++++++++++++++++ .../municipio_tipo/table_description.txt | 67 +++++ br_denatran_frota/uf_tipo/publish.sql | 49 ++++ br_denatran_frota/uf_tipo/schema-prod.json | 1 + br_denatran_frota/uf_tipo/table_config.yaml | 263 +++++++++++++++++ .../uf_tipo/table_description.txt | 67 +++++ 16 files changed, 1524 insertions(+) create mode 100644 br_denatran_frota/README.md create mode 100644 br_denatran_frota/code/download_frota.R create mode 100644 br_denatran_frota/code/download_frota_old.R create mode 100644 br_denatran_frota/code/frota_municipio_tipo.R create mode 100644 br_denatran_frota/code/frota_uf_tipo.R create mode 100644 br_denatran_frota/code/utils.R create mode 100644 br_denatran_frota/dataset_config.yaml create mode 100644 br_denatran_frota/municipio_tipo/publish.sql create mode 100644 br_denatran_frota/municipio_tipo/schema-prod.json create mode 100644 br_denatran_frota/municipio_tipo/schema-staging.json create mode 100644 br_denatran_frota/municipio_tipo/table_config.yaml create mode 100644 br_denatran_frota/municipio_tipo/table_description.txt create mode 100644 br_denatran_frota/uf_tipo/publish.sql create mode 100644 br_denatran_frota/uf_tipo/schema-prod.json create mode 100644 br_denatran_frota/uf_tipo/table_config.yaml create mode 100644 br_denatran_frota/uf_tipo/table_description.txt diff --git a/br_denatran_frota/README.md b/br_denatran_frota/README.md new file mode 100644 index 000000000..feaeb233b --- /dev/null +++ b/br_denatran_frota/README.md @@ -0,0 +1,20 @@ +# Frota de Veículos + +Como capturar os dados de br_denatran_frota? + +1. Para capturar esses dados, basta verificar o link dos dados originais indicado em `dataset_config.yaml` no item `website`. + +2. Caso tenha sido utilizado algum código de captura ou tratamento, estes estarão contidos em `code/`. Se o dado publicado for em sua versão bruta, não existirá a pasta `code/`. + +Os dados publicados estão disponíveis em: https://basedosdados.org/dataset/br-denatran-frota + +## Download e Leitura + +Dependências: + +- [unrar](https://www.rarlab.com/rar_add.htm) para extrair os arquivos `.rar` via cli. + +Ubuntu e Debian: +```sh +sudo apt-get install unrar +``` \ No newline at end of file diff --git a/br_denatran_frota/code/download_frota.R b/br_denatran_frota/code/download_frota.R new file mode 100644 index 000000000..0734e7526 --- /dev/null +++ b/br_denatran_frota/code/download_frota.R @@ -0,0 +1,121 @@ +library(rvest) +library(httr) +library(archive) # +library(magrittr) +library(stringr) +library(tibble) +library(dplyr) +library(purrr) + +download_frota <- function(key = NULL, prefix = NULL, month, year, tempdir = tempdir(), dir = getwd()) { + + months <- c( + "janeiro" = 1, + "fevereiro" = 2, + "marco" = 3, + "abril" = 4, + "maio" = 5, + "junho" = 6, + "julho" = 7, + "agosto" = 8, + "setembro" = 9, + "outubro" = 10, + "novembro" = 11, + "dezembro" = 12 + ) + + if (year > 2012) { + url <- paste0("https://www.gov.br/infraestrutura/pt-br/assuntos/transito/conteudo-denatran/frota-de-veiculos-", year) + } else { + # Antes de 2013 os dados vem em um arquivo unico zip + stop("Utilize a função download_frota_old()") + } + + if (!dir.exists(tempdir)) dir.create(tempdir, recursive = T) + if (!dir.exists(dir)) dir.create(dir, recursive = T) + + download_file <- function(i) { + if (i$filetype %in% c("rar", "zip")) handle_compact(i) + if (i$filetype %in% c("xlsx", "xls")) handle_xl(i) + } + + make_filename <- function(i, ext = TRUE) { + stringi::stri_trans_general(i$txt, id = "Latin-ASCII; lower") %>% + stringr::str_replace_all("\\s+", "_") %>% + paste0(., "_", i$mes, "-", i$ano, ifelse(ext, paste0(".", i$filetype), as.character(""))) + } + + handle_xl <- function(i) { + dest_path_file <- paste0(dir, "/", prefix, "_", i$mes, "-", i$ano, paste0(".", i$filetype)) + if (!file.exists(dest_path_file)) { + utils::download.file( + url = i$href, + destfile = dest_path_file + ) + } + } + + handle_compact <- function(i) { + path_file_zip <- paste0(tempdir, "/", make_filename(i)) + dir_file <- paste0(tempdir, "/", make_filename(i, ext = F)) + + if (!file.exists(path_file_zip)) { + utils::download.file(url = i$href, destfile = path_file_zip) + } + + # archive package has a bug + if (i$filetype == "rar") { + if (!dir.exists(dir_file)) dir.create(dir_file) + system(paste0("unrar -o+ -inul x ", path_file_zip, " ", dir_file)) + } else { + archive::archive_extract(path_file_zip, dir = dir_file) + } + + # Remove rar, zip files. Keep only xls or xlsx + list.files(dir_file, full.names = T, pattern = "rar|zip") %>% purrr::walk(~file.remove(.x)) + + file <- list.files(dir_file) %>% .[!is.na(.)] + + if (length(file) == 0) { + stop(paste0("File not found on dir")) + } + + file_ext <- stringr::str_extract(file, ".(xlsx|xls)") + + # String multibyte is invalid + # file.rename( + # from = paste0(dir_file, "/", file), + # to = paste0(dir_file, "/", prefix, "_", month, "-", year, file_ext) + # ) + + if (!dir.exists(dir)) dir.create(dir) + + file.copy( + overwrite = TRUE, + from = paste0(dir_file, "/", file), + to = paste0(dir, "/", prefix, "_", i$mes, "-", i$ano, file_ext) + ) + + } + + get_html <- xml2::read_html(httr::GET(url, httr::user_agent("httr"))) + nodes <- get_html %>% rvest::html_nodes("p > a") + + tibble::tibble( + txt = nodes %>% rvest::html_text(), + href = nodes %>% rvest::html_attr("href") + ) %>% + dplyr::filter(stringr::str_ends(href, "xls|xlsx|rar|zip")) %>% + dplyr::mutate( + mes_name = stringr::str_match(href, regex(stringr::str_c(names(months), collapse = "|"))) %>% as.vector(), + ano = stringr::str_match(href, "\\d{4}") %>% as.vector() %>% as.numeric(), + mes = months[mes_name], + filetype = stringr::str_match(href, "[a-z]+$") %>% as.vector() + ) %>% + dplyr::filter( + stringr::str_detect(txt, regex(key, ignore_case = TRUE)), + mes %in% month + ) %>% + purrr::transpose() %>% + purrr::walk(~download_file(.x)) +} \ No newline at end of file diff --git a/br_denatran_frota/code/download_frota_old.R b/br_denatran_frota/code/download_frota_old.R new file mode 100644 index 000000000..61d645616 --- /dev/null +++ b/br_denatran_frota/code/download_frota_old.R @@ -0,0 +1,106 @@ +library(archive) # +library(stringr) +library(stringi) + +download_frota_old <- function(key = NULL, prefix = NULL, year, tempdir = tempdir(), dir = getwd()) { + + if (year > 2012) { + stop("Utilize download_frota()") + } + + mi_url <- paste0( + "https://www.gov.br/infraestrutura/pt-br/assuntos/transito/arquivos-denatran/estatisticas/renavam/", + year, + "/frota", + ifelse(year > 2008, "_", ""), + year, + ".zip" + ) + + if (!dir.exists(tempdir)) dir.create(tempdir, recursive = T) + if (!dir.exists(dir)) dir.create(dir, recursive = T) + + dir_temp <- paste0(tempdir, "/", "frota__", year) + path_file <- paste0(dir_temp, ".zip") + + if (!file.exists(path_file)) { + tryCatch( + utils::download.file( + url = mi_url, + destfile = path_file + ), + error = function(e) { + if (file.exists(path_file)) { + file.remove(path_file) + } + } + ) + + utils::unzip( + path_file, + exdir = paste0(tempdir, "/", "frota__", year) + ) + } + + months <- c( + "jan" = 1, + "fev" = 2, + "mar" = 3, + "abr" = 4, + "mai" = 5, + "jun" = 6, + "jul" = 7, + "ago" = 8, + "set" = 9, + "out" = 10, + "nov" = 11, + "dez" = 12 + ) + + list.files(path = dir_temp, full.names = T, recursive = T) %>% + purrr::walk(function(i) { + if (stringr::str_ends(i, ".zip")) { + utils::unzip(i, exdir = paste0(dirname(i), "/")) + } + }) + + list.files(path = dir_temp, full.names = T, recursive = T) %>% + purrr::walk(function(i) { + + get_by <- list( + regiao = "(frota tipo uf)|(frota uf)|(frota regiao uf)|(frota regiao tipo uf)", + municipio = "(frota munic)|(frota mun)" + ) + + new_name <- basename(i) %>% + stringi::stri_trans_general(id = "Latin-ASCII; lower") %>% + stringr::str_replace("regi�es", "regiao") %>% + stringr::str_replace_all("\\s+", "_") %>% + stringr::str_replace_all("_|-", " ") %>% + stringr::str_replace("^(\\d\\_|\\d)+", "") %>% + stringr::str_replace_all("internet|^\\s", "") + + # Match jan|fev|... or number of month (two digits) + get_month <- stringr::str_match( + new_name, + regex(paste0(stringr::str_c(names(months), collapse = "|"), "|\\d{2}(?=\\d{4})"), ignore_case = T) + ) + + month_i <- ifelse( + stringr::str_count(get_month) == 2, + as.numeric(get_month), + months[get_month] + ) + + file_ext <- stringr::str_extract(new_name, ".[a-zA-Z0-9]+$") + + if (stringr::str_detect(new_name, regex(get_by[[key]], ignore_case = T)) & + stringr::str_ends(new_name, "(xls|xlsx)$")) { + # print(paste0(paste0(dir, "/", prefix, "-", month_i, "-", year, file_ext), "--", i)) + file.copy( + from = i, + to = paste0(dir, "/", prefix, "_", month_i, "-", year, file_ext) + ) + } + }) +} \ No newline at end of file diff --git a/br_denatran_frota/code/frota_municipio_tipo.R b/br_denatran_frota/code/frota_municipio_tipo.R new file mode 100644 index 000000000..4f935e17b --- /dev/null +++ b/br_denatran_frota/code/frota_municipio_tipo.R @@ -0,0 +1,137 @@ +library(janitor) +library(lubridate) +library(xlsx) # +library(readxl) +library(dplyr) +library(tidyr) +library(magrittr) +library(purrr) +library(readr) +library(stringr) +library(stringdist) + +source("code/download_frota.R") +source("code/download_frota_old.R") +source("code/utils.R") + +PATH_TEMP <- paste0(getwd(), "/tmp") +PATH_DOWNLOAD_MUN <- paste0(getwd(), "/input/frota_municipio_tipo") +PREFIX_FROTA_MUN <- "frota_mun_tipo" + +# Download da frota de 2004 a 2012 por municipio +2003:2012 %>% purrr::walk( + ~download_frota_old( + key = "municipio", + prefix = PREFIX_FROTA_MUN, + year = .x, + tempdir = PATH_TEMP, + dir = PATH_DOWNLOAD_MUN + ) +) + +2014:2020 %>% purrr::walk( + ~download_frota( + key = "Frota por Munic", + prefix = PREFIX_FROTA_MUN, + month = 1:12, + year = .x, + tempdir = PATH_TEMP, + dir = PATH_DOWNLOAD_MUN + ) +) + +2021 %>% purrr::walk( + ~download_frota( + key = "Frota por Munic", + prefix = PREFIX_FROTA_MUN, + month = 1:3, + year = .x, + tempdir = PATH_TEMP, + dir = PATH_DOWNLOAD_MUN + ) +) + +list.files(PATH_DOWNLOAD_MUN, full.names = T) %>% + purrr::map( + ~read_xl(.x, type = "uf") %>% + dplyr::select(!total) %>% + dplyr::rename(sigla_uf = uf, municipio_original = municipio) %>% + dplyr::filter(sigla_uf %in% names(siglas_uf)) %>% + dplyr::mutate( + dplyr::across(!c(sigla_uf, municipio_original), as.numeric), + id_municipio = purrr::map2_chr(sigla_uf, municipio_original, ~get_ibge_info(.x, .y)) + ) %>% + dplyr::relocate(c(id_municipio, ano, mes), .after = municipio_original) + ) -> frota_municipios + + +# Cada tibble deve ter 28 colunas +frota_municipios %>% purrr::map_lgl(~ncol(.x) == 26) %>% all(T) + +# Unnest a lista de tibbles, padroniza as colunas, soma e salva como csv e rds +frota_municipios %>% + purrr::map_dfr(~tidyr::unnest(.)) %>% + dplyr::mutate( + chassiplataforma = na.omit( + dplyr::c_across(dplyr::any_of(c("chassiplataforma", "chassiplatafaforma", "chassiplataf"))) + )[1], + tratoresteira = na.omit( + dplyr::c_across(dplyr::any_of(c("tratoresteira", "tratorestei"))) + )[1] + ) %>% + dplyr::select(-dplyr::any_of(c("chassiplatafaforma", "chassiplataf", "tratorestei"))) %>% + dplyr::mutate( + total = rowSums(dplyr::across(automovel:chassiplataforma)) + ) -> df_municipios + +# Filter municipios que não foram encontrados na tabela do IBGE +df_municipios %>% + filter(is.na(id_municipio)) %>% + group_by(municipio_original, sigla_uf) %>% + summarise() + +## Fix nome dos municipios +# ASSU, RN -> AÇU, 2400208 +# BOA SAUDE, RN -> Januário Cicco, 2405306 +# BOM JESUS, GO -> Bom Jesus de Goiás, 5203500 +# EMBU, SP -> Embu das Artes, "3515004" +# ITABIRINHA DE MANTENA, MG -> Itabirinha, 3131802 +# ITAMARACA, PE -> Ilha de Itamaracá, "2607604" +# JAMARI, RO -> Candeias do Jamari, "1100809" +# LIVRAMENTO DO BRUMADO, BA -> Livramento de Nossa Senhora, "2919504" +# SANTA ROSA, AC -> Santa Rosa do Purus, "1200435" +# SAO BENTO DE POMBAL, PB -> São Bentinho, "2513927" +# VILA ALTA, PR -> Alto Paraíso, "4128625" +# VILA NOVA DO MAMORE, RO -> Nova Mamoré, "1100338" + +df_municipios %>% + dplyr::mutate( + id_municipio = + dplyr::case_when( + municipio_original == "ASSU" & sigla_uf == "RN" ~ "2400208", + municipio_original == "BOA SAUDE" & sigla_uf == "RN" ~ "2405306", + municipio_original == "BOM JESUS" & sigla_uf == "GO" ~ "5203500", + municipio_original == "EMBU" & sigla_uf == "SP" ~ "3515004", + municipio_original == "ITABIRINHA DE MANTENA" & sigla_uf == "MG" ~ "3131802", + municipio_original == "ITAMARACA" & sigla_uf == "PE" ~ "2607604", + municipio_original == "JAMARI" & sigla_uf == "RO" ~ "1100809", + municipio_original == "LIVRAMENTO DO BRUMADO" & sigla_uf == "BA" ~ "2919504", + municipio_original == "SANTA ROSA" & sigla_uf == "AC" ~ "1200435", + municipio_original == "SAO BENTO DE POMBAL" & sigla_uf == "PB" ~ "2513927", + municipio_original == "VILA ALTA" & sigla_uf == "PR" ~ "4128625", + municipio_original == "VILA NOVA DO MAMORE" & sigla_uf == "RO" ~ "1100338", + TRUE ~ id_municipio + ) + ) -> frota_municipios_dist + + +frota_municipios_dist %>% + filter(is.na(id_municipio)) %>% + group_by(municipio_original, sigla_uf) %>% + summarise() + +frota_municipios_dist %>% + dplyr::filter(!is.na(id_municipio)) %>% + dplyr::select(!municipio_original) %>% + readr::write_rds(file = "output/municipio_tipo.rds") %T>% + readr::write_csv(file = "output/municipio_tipo.csv") \ No newline at end of file diff --git a/br_denatran_frota/code/frota_uf_tipo.R b/br_denatran_frota/code/frota_uf_tipo.R new file mode 100644 index 000000000..b92aede98 --- /dev/null +++ b/br_denatran_frota/code/frota_uf_tipo.R @@ -0,0 +1,97 @@ +library(janitor) +library(lubridate) +library(xlsx) # +library(readxl) +library(dplyr) +library(tidyr) +library(stringr) +library(magrittr) +library(purrr) +library(readr) +library(stringdist) + +source("code/download_frota.R") +source("code/download_frota_old.R") +source("code/utils.R") + +PATH_TEMP <- paste0(getwd(), "/tmp") +PATH_DOWNLOAD_REG <- paste0(getwd(), "/input/frota_regiao_tipo") + +PREFIX_FROTA_REG <- "frota_regiao_tipo" + +# Download da frota por regiao de 2003 a 2012 +2003:2012 %>% purrr::walk( + ~download_frota_old( + key = "regiao", + prefix = PREFIX_FROTA_REG, + year = .x, + tempdir = PATH_TEMP, + dir = PATH_DOWNLOAD_REG + ) +) + +# Download da frota por regiao e tipo em 2013 +## Demais meses de agosto a key é "Frota por Tipo" +2013 %>% + purrr::walk(~download_frota( + key = "Frota por tipo", + prefix = PREFIX_FROTA_REG, + month = c(1:7, 10:12), + year = .x, + tempdir = PATH_TEMP, + dir = PATH_DOWNLOAD_REG + )) + +## Agosto e setembro de 2013 a key é "Frota por Região" +2013 %>% + purrr::walk(~download_frota( + key = "Frota por Região", + prefix = PREFIX_FROTA_REG, + month = 8:9, + year = .x, + tempdir = PATH_TEMP, + dir = PATH_DOWNLOAD_REG + )) + + +# Download da frota de 2014 a 2020 por região e tipo veículo +2014:2020 %>% purrr::walk(~download_frota( + key = "Frota por UF e Tipo", + prefix = PREFIX_FROTA_REG, + month = 1:12, + year = .x, + tempdir = PATH_TEMP, + dir = PATH_DOWNLOAD_REG +)) + + +2021 %>% purrr::walk(~download_frota( + key = "Frota por UF e Tipo", + prefix = PREFIX_FROTA_REG, + month = 1:12, + year = .x, + tempdir = PATH_TEMP, + dir = PATH_DOWNLOAD_REG +)) + +list.files(PATH_DOWNLOAD_REG, full.names = T) %>% + purrr::map( + ~read_xl(.x, type = "grandes reg|uf") %>% + dplyr::rename("sigla_uf" = 1) %>% + dplyr::filter(sigla_uf %in% unname(siglas_uf)) %>% + dplyr::select(sigla_uf, ano, mes, automovel:utilitario) %>% + dplyr::rowwise() %>% + dplyr::mutate( + dplyr::across(!c(sigla_uf), as.numeric), + sigla_uf = sigla_uf %>% stringr::str_trim() %>% get_sigla_uf(), + total = rowSums(across(automovel:utilitario)) + ) + ) -> frota_regiao + +# Cada tibble deve ter 25 colunas e 27 linhas +frota_regiao %>% purrr::map_lgl(~ncol(.x) == 25 & nrow(.x) == 27) %>% all(T) + +frota_regiao %>% + purrr::map_dfr(~tidyr::unnest(.)) %>% + readr::write_csv(file = "output/uf_tipo.csv") %T>% + readr::write_rds(file = "output/uf_tipo.rds") \ No newline at end of file diff --git a/br_denatran_frota/code/utils.R b/br_denatran_frota/code/utils.R new file mode 100644 index 000000000..93e136d0d --- /dev/null +++ b/br_denatran_frota/code/utils.R @@ -0,0 +1,207 @@ +find_sheet <- function(x, date) { + read_sheet <- tryCatch( + readxl::excel_sheets(x), + error = function(e) { + xlsx::getSheets(xlsx::loadWorkbook(x)) %>% names() + } + ) + + sheet_names <- read_sheet %>% + stringr::str_subset(., "^(?!.*Glossário).*$") + + if (length(sheet_names) == 1) { + sheet_names[[1]] + } else { + month_name <- lubridate::month(date, label = T) + + query_sheet <- stringr::str_subset( + sheet_names, + regex(paste0("\\d{2}(?=\\d{4}$)", "|", month_name), ignore_case = T) + ) + + if (length(query_sheet) == 0) { + return(sheet_names[[1]]) + } + + if (length(query_sheet) > 1) { + # Exceções + if (date == "01-04-2010") { + return(query_sheet[[1]]) + } + stop(paste(date, ", more than one sheet found")) + } + query_sheet + } +} + +row_of_header <- function(x, key_of_header) { + # Return number of row than is the header of tibble + # x is vector of first colunm + # key_of_header is string + match <- stringr::str_subset(x, stringr::regex(key_of_header, ignore_case = T)) + result <- which(x == match) + + if (length(result) == 0) { + return(0) + } + + if (length(result) > 1) { + result[2] + } else { + result + } +} + +set_header <- function(x, key_of_header) { + number_of_header <- row_of_header(x[[1]], key_of_header) + if (number_of_header == 0) { + return(x) + } + janitor::row_to_names(x, row_number = number_of_header) +} + +# Some xls file can't be read by readxl package using read_xls() function, see this issue +read_old_xls <- function(x, date) { + sheet_name <- find_sheet(x, date) + start_row <- 1 + + while (start_row <= 5) { + result <- try( + xlsx::read.xlsx2( + x, + sheetName = sheet_name, + startRow = start_row, + endRow = 10 + ), + silent = T + ) + # Number of column can be more than 23 + if (!is.null(result) && ncol(result) >= 23 && class(result) != "try-error") { + break + } + start_row <- start_row + 1 + } + xlsx::read.xlsx2(x, sheetName = sheet_name, startRow = start_row) %>% + tibble::as_tibble() +} + +read_xl <- function(x, type) { + date <- stringr::str_match(x, "\\d{1,2}-\\d{4}") %>% + paste0("01-", .) %>% + lubridate::dmy() + + read <- function(pl) { + tryCatch( + readxl::read_excel(pl, sheet = find_sheet(pl, date)), + error = function(e) read_old_xls(x, date) + ) + } + + read(x) %>% + set_header(., key_of_header = type) %>% + janitor::clean_names() %>% + dplyr::rename_with(.fn = function(x) stringr::str_replace(x, pattern = "_|\\.|-", replacement = "")) %>% + dplyr::select(!starts_with("na")) %>% + dplyr::mutate( + ano = lubridate::year(date), + mes = lubridate::month(date) + ) +} + +# Tabela com os id dos estados e municipios +download_utils_files <- function() { + if (!dir.exists("input")) dir.create("input/ibge_cods", recursive = T) + utils::download.file( + url = "ftp://geoftp.ibge.gov.br/organizacao_do_territorio/estrutura_territorial/divisao_territorial/2018/DTB_2018.zip", + destfile = paste0("input/ibge_cods/ibge_cods.zip") + ) + utils::unzip("input/ibge_cods/ibge_cods.zip", exdir = paste0("input/ibge_cods/")) +} + +download_utils_files() + +ibge_ids <- readxl::read_excel("input/ibge_cods/RELATORIO_DTB_BRASIL_DISTRITO.xls") %>% + janitor::clean_names() + +ufs <- ibge_ids %>% + dplyr::group_by(nome_uf, uf) %>% + dplyr::summarise() %>% + dplyr::ungroup() %>% + dplyr::mutate(uf = as.numeric(uf)) %>% + dplyr::rename(id_uf = uf) + +municipios <- ibge_ids %>% + dplyr::group_by( + uf, + nome_uf, + codigo_municipio_completo, + nome_municipio + ) %>% + dplyr::summarise() %>% + dplyr::mutate( + name_upper = stringi::stri_trans_general(nome_municipio, id = "Latin-ASCII; upper"), + codigo_municipio_completo = as.numeric(codigo_municipio_completo), + uf = as.numeric(uf) + ) %>% + dplyr::ungroup() %>% + dplyr::rename( + id_uf = uf, + uf = nome_uf, + id_municipio = codigo_municipio_completo, + municipio = nome_municipio + ) + +siglas_uf <- c( + "AC" = "Acre", + "AL" = "Alagoas", + "AP" = "Amapá", + "AM" = "Amazonas", + "BA" = "Bahia", + "CE" = "Ceará", + "DF" = "Distrito Federal", + "ES" = "Espírito Santo", + "GO" = "Goiás", + "MA" = "Maranhão", + "MT" = "Mato Grosso", + "MS" = "Mato Grosso do Sul", + "MG" = "Minas Gerais", + "PA" = "Pará", + "PB" = "Paraíba", + "PR" = "Paraná", + "PE" = "Pernambuco", + "PI" = "Piauí", + "RJ" = "Rio de Janeiro", + "RN" = "Rio Grande do Norte", + "RS" = "Rio Grande do Sul", + "RO" = "Rondônia", + "RR" = "Roraima", + "SC" = "Santa Catarina", + "SP" = "São Paulo", + "SE" = "Sergipe", + "TO" = "Tocantins" +) + +get_ibge_info <- function(uf, name, tolerance = 0.60) { + state <- siglas_uf[uf] + result <- municipios %>% + dplyr::filter(uf == state) %>% + dplyr::mutate(dist = stringdist::stringsim(name_upper, name)) %>% + dplyr::arrange(dplyr::desc(dist)) %>% + dplyr::slice(1L) %>% + as.list() + + if (length(result[[1]]) == 0 || result$dist < tolerance) { + return(NA) + } + as.character(result$id_municipio) +} + +get_uf_name <- function(x) { + if (nchar(x) != 2) return(x) + unname(siglas_uf[x]) +} + +get_sigla_uf <- function(uf_name) { + purrr::keep(siglas_uf, ~.x == uf_name) %>% + names() +} diff --git a/br_denatran_frota/dataset_config.yaml b/br_denatran_frota/dataset_config.yaml new file mode 100644 index 000000000..d8db54254 --- /dev/null +++ b/br_denatran_frota/dataset_config.yaml @@ -0,0 +1,69 @@ +dataset_id: br_denatran_frota # AUTO GENERATED + +url_ckan: https://basedosdados.org/dataset/br-denatran-frota +url_github: https://github.com/basedosdados/mais/tree/master/bases/br_denatran_frota + +# Descreva a base. +# Ela é sobre o que? +# Quais as principais fontes de dados? +# Há links para FAQs e explicações? +description: | # REQUIRED + Frota de Veículos por tipo, estado e município + +# Qual organização disponibiliza os dados originais? +# Opções: escolher dessa lista -> https://basedosdados.org/api/3/action/organization_list +organization: Departamento Nacional de Trânsito # REQUIRED + +# Qual departamento/grupo/pessoa mantém os dados originais? +author: + name: Departamento Nacional de Trânsito + email: + +# Onde encontrar os dados originais e mais informações? +website: + - https://www.gov.br/infraestrutura/pt-br/assuntos/transito/conteudo-denatran/estatisticas-frota-de-veiculos-denatran + +# Quais grupos caracterizam a base? +# Opções: escolher dessa lista -> https://basedosdados.org/api/3/action/group_list +groups: + - infra-transp + +# Quais etiquetas caracterizam a base? +# Opções: escolher dessa lista -> https://basedosdados.org/api/3/action/tag_list +# Caso crie etiquetas novas, as regras são: +# - letras minúsculas +# - sem acentos +# - não repita nomes de grupos (ex. educacao, saude, meio ambiente, economia, etc.) +tags: + - veiculo + - trafego + +# Em quais línguas a base (ou a fonte original) está disponível? +# Regras: minúsculo, sem acentos. +# Opções: portugues, ingles, espanhol, frances, chines, russo, hindi, alemao, etc. +languages: + - portugues + +# Os dados originais estão disponíveis de graça? +free: sim + +# Are microdata available for download? +microdata: sim + +# Existe uma API na fonte original? +API: não + +# É necessário registrar um usuário para baixar os dados originais? +registration: não + +# Como os dados originais estão disponibilizados? +availability: online + +# A fonte original requer IP brasileiro para acesso? +brazilian_IP: não + +# Essa base está sob qual licença? +# A licença MIT se aplica a bases públicas. +# Caso não seja pública, ver opções aqui: https://help.data.world/hc/en-us/articles/115006114287-Common-license-types-for-datasets +license: + name: MIT # REQUIRED diff --git a/br_denatran_frota/municipio_tipo/publish.sql b/br_denatran_frota/municipio_tipo/publish.sql new file mode 100644 index 000000000..f4e74c045 --- /dev/null +++ b/br_denatran_frota/municipio_tipo/publish.sql @@ -0,0 +1,50 @@ +/* + +Query para publicar a tabela. + +Esse é o lugar para: + - modificar nomes, ordem e tipos de colunas + - dar join com outras tabelas + - criar colunas extras (e.g. logs, proporções, etc.) + +Qualquer coluna definida aqui deve também existir em `table_config.yaml`. + +# Além disso, sinta-se à vontade para alterar alguns nomes obscuros +# para algo um pouco mais explícito. + +TIPOS: + - Para modificar tipos de colunas, basta substituir STRING por outro tipo válido. + - Exemplo: `SAFE_CAST(column_name AS NUMERIC) column_name` + - Mais detalhes: https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types + +*/ + +CREATE VIEW basedosdados-312117.br_denatran_frota.municipio_tipo AS +SELECT +SAFE_CAST(sigla_uf AS STRING) sigla_uf, +SAFE_CAST(id_municipio AS STRING) id_municipio, +SAFE_CAST(ano AS INT64) ano, +SAFE_CAST(mes AS INT64) mes, +SAFE_CAST(automovel AS INT64) automovel, +SAFE_CAST(bonde AS INT64) bonde, +SAFE_CAST(caminhao AS INT64) caminhao, +SAFE_CAST(caminhaotrator AS INT64) caminhaotrator, +SAFE_CAST(caminhonete AS INT64) caminhonete, +SAFE_CAST(camioneta AS INT64) camioneta, +SAFE_CAST(ciclomotor AS INT64) ciclomotor, +SAFE_CAST(microonibus AS INT64) microonibus, +SAFE_CAST(motocicleta AS INT64) motocicleta, +SAFE_CAST(motoneta AS INT64) motoneta, +SAFE_CAST(onibus AS INT64) onibus, +SAFE_CAST(quadriciclo AS INT64) quadriciclo, +SAFE_CAST(reboque AS INT64) reboque, +SAFE_CAST(semireboque AS INT64) semireboque, +SAFE_CAST(sidecar AS INT64) sidecar, +SAFE_CAST(outros AS INT64) outros, +SAFE_CAST(tratoresteira AS INT64) tratoresteira, +SAFE_CAST(tratorrodas AS INT64) tratorrodas, +SAFE_CAST(triciclo AS INT64) triciclo, +SAFE_CAST(utilitario AS INT64) utilitario, +SAFE_CAST(chassiplataforma AS INT64) chassiplataforma, +SAFE_CAST(total AS INT64) total +from basedosdados-312117.br_denatran_frota_staging.municipio_tipo as t \ No newline at end of file diff --git a/br_denatran_frota/municipio_tipo/schema-prod.json b/br_denatran_frota/municipio_tipo/schema-prod.json new file mode 100644 index 000000000..ecd58455f --- /dev/null +++ b/br_denatran_frota/municipio_tipo/schema-prod.json @@ -0,0 +1 @@ +[{"name": "sigla_uf", "description": "Sigla da Unidade da Federa\u00e7\u00e3o original da base", "is_in_staging": true, "is_partition": false, "type": "STRING", "mode": "NULLABLE"}, {"name": "id_municipio", "description": "ID Munic\u00edpio - IBGE 7 D\u00edgitos", "is_in_staging": true, "is_partition": false, "type": "STRING", "mode": "NULLABLE"}, {"name": "ano", "description": "Ano", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "mes", "description": "M\u00eas", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "automovel", "description": "Autom\u00f3vel", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "bonde", "description": "Bonde", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "caminhao", "description": "Caminh\u00e3o", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "caminhaotrator", "description": "Caminh\u00e3o Trator", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "caminhonete", "description": "Caminhonete", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "camioneta", "description": "Camioneta", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "chassiplataforma", "description": "Chassi Plataforma", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "ciclomotor", "description": "Ciclo Motor", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "microonibus", "description": "Micro\u00f4nibus", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "motocicleta", "description": "Motocicleta", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "motoneta", "description": "Motoneta", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "onibus", "description": "\u00d4nibus", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "quadriciclo", "description": "Quadriciclo", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "reboque", "description": "Reboque", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "semireboque", "description": "Semi-reboque", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "sidecar", "description": "Side-car", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "outros", "description": "Argumento que n\u00e3o se enquadra em nenhuma defini\u00e7\u00e3o estabelecida", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "tratoresteira", "description": "Trator esteira", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "tratorrodas", "description": "Trator rodas", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "triciclo", "description": "Triciclo", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "utilitario", "description": "Utilit\u00e1rio", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "total", "description": "Total", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}] \ No newline at end of file diff --git a/br_denatran_frota/municipio_tipo/schema-staging.json b/br_denatran_frota/municipio_tipo/schema-staging.json new file mode 100644 index 000000000..43cc3a6ef --- /dev/null +++ b/br_denatran_frota/municipio_tipo/schema-staging.json @@ -0,0 +1 @@ +[{"name": "sigla_uf", "description": "Sigla da Unidade da Federa\u00e7\u00e3o", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "ano", "description": "Ano", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "mes", "description": "M\u00eas", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "automovel", "description": "Autom\u00f3vel", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "bonde", "description": "Bonde", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "caminhao", "description": "Caminh\u00e3o", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "caminhaotrator", "description": "Caminh\u00e3o Trator", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "caminhonete", "description": "Caminhonete", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "camioneta", "description": "Camioneta", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "chassiplataforma", "description": "Chassi Plataforma", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "ciclomotor", "description": "Ciclo Motor", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "microonibus", "description": "Micro\u00f4nibus", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "motocicleta", "description": "Motocicleta", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "motoneta", "description": "Motoneta", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "onibus", "description": "\u00d4nibus", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "quadriciclo", "description": "Quadriciclo", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "reboque", "description": "Reboque", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "semireboque", "description": "Semi-reboque", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "sidecar", "description": "Side-car", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "outros", "description": "Argumento que n\u00e3o se enquadra em nenhuma defini\u00e7\u00e3o estabelecida", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "tratoresteira", "description": "Trator esteira", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "tratorrodas", "description": "Trator rodas", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "triciclo", "description": "Triciclo", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "utilitario", "description": "Utilit\u00e1rio", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "total", "description": "Total", "is_in_staging": true, "is_partition": false, "type": "STRING"}] \ No newline at end of file diff --git a/br_denatran_frota/municipio_tipo/table_config.yaml b/br_denatran_frota/municipio_tipo/table_config.yaml new file mode 100644 index 000000000..2ab4752e2 --- /dev/null +++ b/br_denatran_frota/municipio_tipo/table_config.yaml @@ -0,0 +1,268 @@ +source_bucket_name: basedosdadosdev +project_id_staging: basedosdados-312117 +project_id_prod: basedosdados-312117 +table_id: municipio_tipo # AUTO GENERATED +dataset_id: br_denatran_frota # AUTO GENERATED + +url_ckan: https://basedosdados.org/dataset/br-denatran-frota # AUTO GENERATED +url_github: https://github.com/basedosdados/mais/tree/master/bases/br_denatran_frota # AUTO GENERATED + +version: v1.3 # REQUIRED + +last_updated: 2021-05-28 # AUTO GENERATED + +# Descreva a tabela. Essas são as primeiras frases que um usuário vai ver. +# Você não precisa ser muito conciso. Sinta-se a vontade para dar exemplos de +# como usar os dados. +# Se souber, liste também aplicações: pesquisa, apps, etc. que usem os dados. +description: | # REQUIRED + Frota de veículos por município e tipo + +# Quem está completando esse arquivo config? +published_by: + name: Pedro Castro # REQUIRED + code_url: https://github.com/basedosdados/mais/tree/master/bases/br_denatran_frota/code # REQUIRED + website: https://github.com/pedrocastroo + email: pdesacastro@gmail.com + +# Qual organização/departamento/pessoa tratou os dados? +# As vezes há um ponto intermediário entre os dados originais e subir na Base dos Dados. +# Se essa pessoa é você, preencha abaixo com suas informações. +treated_by: + name: Pedro Castro + code_url: https://github.com/basedosdados/mais/tree/master/bases/br_denatran_frota/code + website: https://basedosdados.org/ + email: pdesacastro@gmail.com + +# Se houve passos de tratamento, limpeza e manipulação de dados, descreva-os aqui. +treatment_description: | + Padronização das colunas. Nova coluna, id_municipio. Remoção das linhas "MUNICIPIO NAO INFORMADO". + +# Com qual frequência a base é atualizada? +# Opções: hora | dia | semana | mes | 1 ano | 2 anos | 5 anos | 10 anos | unico | recorrente +data_update_frequency: mes # REQUIRED + +# Nível da observação (qual é a granularidade de cada linha na tabela) +# Escolha todas as opções necessárias. +# Regras: +# - minúsculo, sem acento, singular. +# - em portugues (ou seja, não use os nomes de colunas abaixo) +# Exemplos: pais, estado, municipio, cidade, hora, dia, semana, mes, ano, etc. +observation_level: #REQUIRED + - municipio + - mes + +# Quais colunas identificam uma linha unicamente? +# Preencha com os nomes de colunas. Ex: id_municipio, ano. +# Pode ser vazio pois certas tabelas não possuem identificadores. +primary_keys: + - id_municipio + - ano + - mes + +# Qual é a cobertura espacial da tabela? +# Regras: +# - minúsculo, sem acento, singular +# - descer até o menor nível administrativo cuja cobertura abaixo seja 'todos' +# Exemplo 1: tabela que cubra todos os municípios nos estados de SP e GO +# - brasil +# - SP, GO +# Exemplo 2: tabela que cubra países inteiros na América Latina +# - brasil, argentina, peru, equador +coverage_geo: + - brasil + +# Qual é a cobertura temporal (em anos) da tabela? +# Opções: ..., 1990, 1991, ..., 1999, 2000, 2001, ..., 2019, 2020, ... +coverage_time: + - 2003 + - 2004 + - 2005 + - 2006 + - 2007 + - 2008 + - 2009 + - 2010 + - 2011 + - 2012 + - 2013 + - 2014 + - 2015 + - 2016 + - 2017 + - 2018 + - 2019 + - 2020 + - 2021 + +# Liste as colunas da tabela que representam partições. +# Não esqueça de deletar essas colunas nas tabelas .csv na hora de subir para o BigQuery. +# Isso poupará muito tempo e dinheiro às pessoas utilizando essa tabela. +# Se não houver partições, não modifique abaixo. +partitions: # REQUIRED + +# Quais são as colunas? Certifique-se de escrever uma boa descrição, as pessoas vão gostar +# para saber sobre o que é a coluna. +# Adicionar todas as colunas manualmente pode ser bastante cansativo, por isso, quando +# inicializando este arquivo de configuração, você pode apontar a função para uma amostra de dados que +# preencherá automaticamente as colunas. +# Algumas colunas existirão apenas na tabela final, você as construirá em `publish.sql`. +# Para esses, defina is_in_staging como False. +# Além disso, você deve adicionar as colunas de partição aqui e definir is_partition como True. +columns: # REQUIRED + + - + name: sigla_uf + description: Sigla da Unidade da Federação original da base + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: id_municipio + description: ID Município - IBGE 7 Dígitos + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: ano + description: Ano + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: mes + description: Mês + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: automovel + description: Automóvel + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: bonde + description: Bonde + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: caminhao + description: Caminhão + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: caminhaotrator + description: Caminhão Trator + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: caminhonete + description: Caminhonete + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: camioneta + description: Camioneta + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: chassiplataforma + description: Chassi Plataforma + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: ciclomotor + description: Ciclo Motor + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: microonibus + description: Microônibus + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: motocicleta + description: Motocicleta + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: motoneta + description: Motoneta + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: onibus + description: Ônibus + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: quadriciclo + description: Quadriciclo + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: reboque + description: Reboque + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: semireboque + description: Semi-reboque + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: sidecar + description: Side-car + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: outros + description: Argumento que não se enquadra em nenhuma definição estabelecida + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: tratoresteira + description: Trator esteira + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: tratorrodas + description: Trator rodas + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: triciclo + description: Triciclo + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: utilitario + description: Utilitário + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: total + description: Total + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. \ No newline at end of file diff --git a/br_denatran_frota/municipio_tipo/table_description.txt b/br_denatran_frota/municipio_tipo/table_description.txt new file mode 100644 index 000000000..7ca0fad1e --- /dev/null +++ b/br_denatran_frota/municipio_tipo/table_description.txt @@ -0,0 +1,67 @@ +Frota de veículos por município e tipo + + +Para saber mais acesse: +Website: https://basedosdados.org/dataset/br-denatran-frota +Github: https://github.com/basedosdados/mais/tree/master/bases/br_denatran_frota + +Ajude a manter o projeto :) +Apoia-se: https://apoia.se/basedosdados + +Publicado por +------------- +Nome: Pedro Castro +Código: https://github.com/basedosdados/mais/tree/master/bases/br_denatran_frota/code +Website: https://github.com/pedrocastroo +Email: pdesacastro@gmail.comTratado por +----------- +Nome: Pedro Castro +Código: https://github.com/basedosdados/mais/tree/master/bases/br_denatran_frota/code +Website: https://basedosdados.org/ +Email: pdesacastro@gmail.com + +Nível da Observação (i.e. a granularidade da linha) +------------------- +- municipio +- mes + +Colunas identificando linhas unicamente +------------------- +- id_municipio +- ano +- mes + +Cobertura Temporal +------------------ +- 2003 +- 2004 +- 2005 +- 2006 +- 2007 +- 2008 +- 2009 +- 2010 +- 2011 +- 2012 +- 2013 +- 2014 +- 2015 +- 2016 +- 2017 +- 2018 +- 2019 +- 2020 +- 2021 + +Cobertura Espacial +------------------ +- brasil + +Tratamento +---------- +Padronização das colunas. Nova coluna, id_municipio. Remoção das linhas "MUNICIPIO NAO INFORMADO". + +Frequencia de Atualização +------------------------- +mes + diff --git a/br_denatran_frota/uf_tipo/publish.sql b/br_denatran_frota/uf_tipo/publish.sql new file mode 100644 index 000000000..016ef11b3 --- /dev/null +++ b/br_denatran_frota/uf_tipo/publish.sql @@ -0,0 +1,49 @@ +/* + +Query para publicar a tabela. + +Esse é o lugar para: + - modificar nomes, ordem e tipos de colunas + - dar join com outras tabelas + - criar colunas extras (e.g. logs, proporções, etc.) + +Qualquer coluna definida aqui deve também existir em `table_config.yaml`. + +# Além disso, sinta-se à vontade para alterar alguns nomes obscuros +# para algo um pouco mais explícito. + +TIPOS: + - Para modificar tipos de colunas, basta substituir STRING por outro tipo válido. + - Exemplo: `SAFE_CAST(column_name AS NUMERIC) column_name` + - Mais detalhes: https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types + +*/ + +CREATE VIEW basedosdados-312117.br_denatran_frota.uf_tipo AS +SELECT +SAFE_CAST(sigla_uf AS STRING) sigla_uf, +SAFE_CAST(ano AS INT64) ano, +SAFE_CAST(mes AS INT64) mes, +SAFE_CAST(automovel AS INT64) automovel, +SAFE_CAST(bonde AS INT64) bonde, +SAFE_CAST(caminhao AS INT64) caminhao, +SAFE_CAST(caminhaotrator AS INT64) caminhaotrator, +SAFE_CAST(caminhonete AS INT64) caminhonete, +SAFE_CAST(camioneta AS INT64) camioneta, +SAFE_CAST(chassiplataforma AS INT64) chassiplataforma, +SAFE_CAST(ciclomotor AS INT64) ciclomotor, +SAFE_CAST(microonibus AS INT64) microonibus, +SAFE_CAST(motocicleta AS INT64) motocicleta, +SAFE_CAST(motoneta AS INT64) motoneta, +SAFE_CAST(onibus AS INT64) onibus, +SAFE_CAST(quadriciclo AS INT64) quadriciclo, +SAFE_CAST(reboque AS INT64) reboque, +SAFE_CAST(semireboque AS INT64) semireboque, +SAFE_CAST(sidecar AS INT64) sidecar, +SAFE_CAST(outros AS INT64) outros, +SAFE_CAST(tratoresteira AS INT64) tratoresteira, +SAFE_CAST(tratorrodas AS INT64) tratorrodas, +SAFE_CAST(triciclo AS INT64) triciclo, +SAFE_CAST(utilitario AS INT64) utilitario, +SAFE_CAST(total AS INT64) total +from basedosdados-312117.br_denatran_frota_staging.uf_tipo as t diff --git a/br_denatran_frota/uf_tipo/schema-prod.json b/br_denatran_frota/uf_tipo/schema-prod.json new file mode 100644 index 000000000..9179eec10 --- /dev/null +++ b/br_denatran_frota/uf_tipo/schema-prod.json @@ -0,0 +1 @@ +[{"name": "sigla_uf", "description": "Sigla da Unidade da Federa\u00e7\u00e3o", "is_in_staging": true, "is_partition": false, "type": "STRING", "mode": "NULLABLE"}, {"name": "ano", "description": "Ano", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "mes", "description": "M\u00eas", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "automovel", "description": "Autom\u00f3vel", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "bonde", "description": "Bonde", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "caminhao", "description": "Caminh\u00e3o", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "caminhaotrator", "description": "Caminh\u00e3o Trator", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "caminhonete", "description": "Caminhonete", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "camioneta", "description": "Camioneta", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "chassiplataforma", "description": "Chassi Plataforma", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "ciclomotor", "description": "Ciclo Motor", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "microonibus", "description": "Micro\u00f4nibus", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "motocicleta", "description": "Motocicleta", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "motoneta", "description": "Motoneta", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "onibus", "description": "\u00d4nibus", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "quadriciclo", "description": "Quadriciclo", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "reboque", "description": "Reboque", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "semireboque", "description": "Semi-reboque", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "sidecar", "description": "Side-car", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "outros", "description": "Argumento que n\u00e3o se enquadra em nenhuma defini\u00e7\u00e3o estabelecida", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "tratoresteira", "description": "Trator esteira", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "tratorrodas", "description": "Trator rodas", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "triciclo", "description": "Triciclo", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "utilitario", "description": "Utilit\u00e1rio", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "total", "description": "Total", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}] \ No newline at end of file diff --git a/br_denatran_frota/uf_tipo/table_config.yaml b/br_denatran_frota/uf_tipo/table_config.yaml new file mode 100644 index 000000000..08424b33c --- /dev/null +++ b/br_denatran_frota/uf_tipo/table_config.yaml @@ -0,0 +1,263 @@ +source_bucket_name: basedosdadosdev +project_id_staging: basedosdados-312117 +project_id_prod: basedosdados-312117 +table_id: uf_tipo # AUTO GENERATED +dataset_id: br_denatran_frota # AUTO GENERATED + + +url_ckan: https://basedosdados.org/dataset/br-denatran-frota # AUTO GENERATED +url_github: https://github.com/basedosdados/mais/tree/master/bases/br_denatran_frota # AUTO GENERATED + +version: v1.2 # REQUIRED + +last_updated: 2021-05-28 # AUTO GENERATED + +# Descreva a tabela. Essas são as primeiras frases que um usuário vai ver. +# Você não precisa ser muito conciso. Sinta-se a vontade para dar exemplos de +# como usar os dados. +# Se souber, liste também aplicações: pesquisa, apps, etc. que usem os dados. +description: | # REQUIRED + Frota veículos por estado e tipo + +# Quem está completando esse arquivo config? +published_by: + name: Pedro Castro # REQUIRED + code_url: https://github.com/basedosdados/mais/tree/master/bases/br_denatran_frota/code # REQUIRED + website: https://github.com/pedrocastroo + email: pdesacastro@gmail.com + +# Qual organização/departamento/pessoa tratou os dados? +# As vezes há um ponto intermediário entre os dados originais e subir na Base dos Dados. +# Se essa pessoa é você, preencha abaixo com suas informações. +treated_by: + name: Pedro Castro + code_url: https://github.com/basedosdados/mais/tree/master/bases/br_denatran_frota/code + website: https://basedosdados.org/ + email: pdesacastro@gmail.com + +# Se houve passos de tratamento, limpeza e manipulação de dados, descreva-os aqui. +treatment_description: | + Padronização dos nomes das colunas. Remoção das linhas do total dos estados. + +# Com qual frequência a base é atualizada? +# Opções: hora | dia | semana | mes | 1 ano | 2 anos | 5 anos | 10 anos | unico | recorrente +data_update_frequency: mes # REQUIRED + +# Nível da observação (qual é a granularidade de cada linha na tabela) +# Escolha todas as opções necessárias. +# Regras: + # - minúsculo, sem acento, singular. +# - em portugues (ou seja, não use os nomes de colunas abaixo) +# Exemplos: pais, estado, municipio, cidade, hora, dia, semana, mes, ano, etc. +observation_level: #REQUIRED + - unidade da federação + - mes + +# Quais colunas identificam uma linha unicamente? +# Preencha com os nomes de colunas. Ex: id_municipio, ano. +# Pode ser vazio pois certas tabelas não possuem identificadores. +primary_keys: + - ano + - mes + - sigla_uf + +# Qual é a cobertura espacial da tabela? +# Regras: + # - minúsculo, sem acento, singular +# - descer até o menor nível administrativo cuja cobertura abaixo seja 'todos' +# Exemplo 1: tabela que cubra todos os municípios nos estados de SP e GO +# - brasil +# - SP, GO +# Exemplo 2: tabela que cubra países inteiros na América Latina +# - brasil, argentina, peru, equador +coverage_geo: + - brasil + +# Qual é a cobertura temporal (em anos) da tabela? +# Opções: ..., 1990, 1991, ..., 1999, 2000, 2001, ..., 2019, 2020, ... +coverage_time: + - 2003 + - 2004 + - 2005 + - 2006 + - 2007 + - 2008 + - 2009 + - 2010 + - 2011 + - 2012 + - 2013 + - 2014 + - 2015 + - 2016 + - 2017 + - 2018 + - 2019 + - 2020 + - 2021 + +# Liste as colunas da tabela que representam partições. +# Não esqueça de deletar essas colunas nas tabelas .csv na hora de subir para o BigQuery. +# Isso poupará muito tempo e dinheiro às pessoas utilizando essa tabela. +# Se não houver partições, não modifique abaixo. +partitions: # REQUIRED + +# Quais são as colunas? Certifique-se de escrever uma boa descrição, as pessoas vão gostar +# para saber sobre o que é a coluna. +# Adicionar todas as colunas manualmente pode ser bastante cansativo, por isso, quando +# inicializando este arquivo de configuração, você pode apontar a função para uma amostra de dados que +# preencherá automaticamente as colunas. +# Algumas colunas existirão apenas na tabela final, você as construirá em `publish.sql`. +# Para esses, defina is_in_staging como False. +# Além disso, você deve adicionar as colunas de partição aqui e definir is_partition como True. +columns: # REQUIRED + + - + name: sigla_uf + description: Sigla da Unidade da Federação + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: ano + description: Ano + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: mes + description: Mês + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: automovel + description: Automóvel + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: bonde + description: Bonde + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: caminhao + description: Caminhão + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: caminhaotrator + description: Caminhão Trator + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: caminhonete + description: Caminhonete + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: camioneta + description: Camioneta + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: chassiplataforma + description: Chassi Plataforma + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: ciclomotor + description: Ciclo Motor + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: microonibus + description: Microônibus + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: motocicleta + description: Motocicleta + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: motoneta + description: Motoneta + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: onibus + description: Ônibus + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: quadriciclo + description: Quadriciclo + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: reboque + description: Reboque + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: semireboque + description: Semi-reboque + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: sidecar + description: Side-car + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: outros + description: Argumento que não se enquadra em nenhuma definição estabelecida + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: tratoresteira + description: Trator esteira + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: tratorrodas + description: Trator rodas + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: triciclo + description: Triciclo + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: utilitario + description: Utilitário + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partition. + + - + name: total + description: Total + is_in_staging: True # Bool [True, False], whether the column is in the staging table + is_partition: False # Bool [True, False], whether the column is a partitio \ No newline at end of file diff --git a/br_denatran_frota/uf_tipo/table_description.txt b/br_denatran_frota/uf_tipo/table_description.txt new file mode 100644 index 000000000..982522203 --- /dev/null +++ b/br_denatran_frota/uf_tipo/table_description.txt @@ -0,0 +1,67 @@ +Frota veículos por estado e tipo + + +Para saber mais acesse: +Website: https://basedosdados.org/dataset/br-denatran-frota +Github: https://github.com/basedosdados/mais/tree/master/bases/br_denatran_frota + +Ajude a manter o projeto :) +Apoia-se: https://apoia.se/basedosdados + +Publicado por +------------- +Nome: Pedro Castro +Código: https://github.com/basedosdados/mais/tree/master/bases/br_denatran_frota/code +Website: https://github.com/pedrocastroo +Email: pdesacastro@gmail.comTratado por +----------- +Nome: Pedro Castro +Código: https://github.com/basedosdados/mais/tree/master/bases/br_denatran_frota/code +Website: https://basedosdados.org/ +Email: pdesacastro@gmail.com + +Nível da Observação (i.e. a granularidade da linha) +------------------- +- unidade da federação +- mes + +Colunas identificando linhas unicamente +------------------- +- ano +- mes +- sigla_uf + +Cobertura Temporal +------------------ +- 2003 +- 2004 +- 2005 +- 2006 +- 2007 +- 2008 +- 2009 +- 2010 +- 2011 +- 2012 +- 2013 +- 2014 +- 2015 +- 2016 +- 2017 +- 2018 +- 2019 +- 2020 +- 2021 + +Cobertura Espacial +------------------ +- brasil + +Tratamento +---------- +Padronização dos nomes das colunas. Remoção das linhas do total dos estados. + +Frequencia de Atualização +------------------------- +mes + From 959b3f9d4d76068bd3c32a92c46ec4939d7a8db9 Mon Sep 17 00:00:00 2001 From: Tamir Date: Thu, 23 Mar 2023 02:08:24 -0300 Subject: [PATCH 003/265] Add package and base python code --- br_denatran_frota/code/download_frota.py | 93 ++ poetry.lock | 1535 +++------------------- pyproject.toml | 1 + 3 files changed, 282 insertions(+), 1347 deletions(-) create mode 100644 br_denatran_frota/code/download_frota.py diff --git a/br_denatran_frota/code/download_frota.py b/br_denatran_frota/code/download_frota.py new file mode 100644 index 000000000..c75ef01e4 --- /dev/null +++ b/br_denatran_frota/code/download_frota.py @@ -0,0 +1,93 @@ +import os +import re +import tempfile +from urllib.request import urlopen, urlretrieve +from zipfile import ZipFile +from rarfile import RarFile +from bs4 import BeautifulSoup +from collections import defaultdict + + +def download_frota(key=None, prefix=None, month=None, year=None, tempdir=None, dir=None): + months = { + "janeiro": 1, + "fevereiro": 2, + "marco": 3, + "abril": 4, + "maio": 5, + "junho": 6, + "julho": 7, + "agosto": 8, + "setembro": 9, + "outubro": 10, + "novembro": 11, + "dezembro": 12, + } + + if year > 2012: + url = f"https://www.gov.br/infraestrutura/pt-br/assuntos/transito/conteudo-denatran/frota-de-veiculos-{year}" + else: + raise ValueError("Utilize a função download_frota_old()") + + if not tempdir: + tempdir = tempfile.gettempdir() + if not dir: + dir = os.getcwd() + + def make_filename(i, ext=True): + txt = i["txt"] + mes = i["mes"] + ano = i["ano"] + filetype = i["filetype"] + filename = re.sub("\\s+", "_", txt, flags=re.UNICODE).lower() + filename = f"{filename}_{mes}-{ano}" + if ext: + filename += f".{filetype}" + return filename + + def handle_xl(i): + dest_path_file = os.path.join(dir, f"{prefix}_{i['mes']}-{i['ano']}.{i['filetype']}") + if not os.path.isfile(dest_path_file): + urlretrieve(i["href"], dest_path_file) + + def handle_compact(i): + path_file_zip = os.path.join(tempdir, make_filename(i)) + dir_file = os.path.join(tempdir, make_filename(i, ext=False)) + + if not os.path.isfile(path_file_zip): + urlretrieve(i["href"], path_file_zip) + + if i["filetype"] == "rar": + with RarFile(path_file_zip) as rar_file: + rar_file.extractall(dir_file) + else: + with ZipFile(path_file_zip) as zip_file: + zip_file.extractall(dir_file) + + for filename in os.listdir(dir_file): + filepath = os.path.join(dir_file, filename) + if os.path.isfile(filepath): + if filename.endswith((".xlsx", ".xls")): + dest_path_file = os.path.join( + dir, f"{prefix}_{i['mes']}-{i['ano']}.{filename.split('.')[-1]}" + ) + if not os.path.isfile(dest_path_file): + os.rename(filepath, dest_path_file) + else: + os.remove(filepath) + + soup = BeautifulSoup(urlopen(url), "html.parser") + nodes = soup.select("p > a") + + data = defaultdict(list) + for node in nodes: + txt = node.text + href = node.attrib["href"] + match = re.search("(?i)xls|xlsx|rar|zip$", href) + if match and re.search(key, txt, re.IGNORECASE) and months.get(match.group(1)) in month: + filetype = match.group().lower() + mes_name = re.search("(%s)" % "|".join(months.keys()), href).group(1) + mes = months[mes_name] + ano = int(re.search("\d{4}", href).group()) + info = {'txt': txt, 'href': href, 'mes_name': mes_name, 'mes': mes, 'ano': ano, 'filetype': filetype} + download_file(info) diff --git a/poetry.lock b/poetry.lock index c9a17db19..60a414b94 100644 --- a/poetry.lock +++ b/poetry.lock @@ -23,10 +23,10 @@ optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" [package.extras] -dev = ["cloudpickle", "coverage[toml] (>=5.0.2)", "furo", "hypothesis", "mypy", "pre-commit", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "six", "sphinx", "sphinx-notfound-page", "zope.interface"] -docs = ["furo", "sphinx", "sphinx-notfound-page", "zope.interface"] -tests = ["cloudpickle", "coverage[toml] (>=5.0.2)", "hypothesis", "mypy", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "six", "zope.interface"] -tests_no_zope = ["cloudpickle", "coverage[toml] (>=5.0.2)", "hypothesis", "mypy", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "six"] +dev = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "mypy", "pytest-mypy-plugins", "zope.interface", "furo", "sphinx", "sphinx-notfound-page", "pre-commit", "cloudpickle"] +docs = ["furo", "sphinx", "zope.interface", "sphinx-notfound-page"] +tests = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "mypy", "pytest-mypy-plugins", "zope.interface", "cloudpickle"] +tests_no_zope = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "mypy", "pytest-mypy-plugins", "cloudpickle"] [[package]] name = "basedosdados" @@ -117,7 +117,6 @@ python-versions = "*" docopt = "*" python-slugify = ">=1.0" requests = "*" -setuptools = "*" six = ">=1.9,<2.0" [[package]] @@ -149,7 +148,7 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" [[package]] name = "coverage" -version = "6.4.4" +version = "7.2.2" description = "Code coverage measurement for Python" category = "dev" optional = false @@ -202,7 +201,7 @@ complete = ["bokeh (>=1.0.0,!=2.0.0)", "distributed (==2021.11.2)", "jinja2", "n dataframe = ["numpy (>=1.18)", "pandas (>=1.0)"] diagnostics = ["bokeh (>=1.0.0,!=2.0.0)", "jinja2"] distributed = ["distributed (==2021.11.2)"] -test = ["pre-commit", "pytest", "pytest-rerunfailures", "pytest-xdist"] +test = ["pytest", "pytest-rerunfailures", "pytest-xdist", "pre-commit"] [[package]] name = "db-dtypes" @@ -241,7 +240,7 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" wrapt = ">=1.10,<2" [package.extras] -dev = ["PyTest", "PyTest (<5)", "PyTest-Cov", "PyTest-Cov (<2.6)", "bump2version (<1)", "configparser (<5)", "importlib-metadata (<3)", "importlib-resources (<4)", "sphinx (<2)", "sphinxcontrib-websupport (<2)", "tox", "zipp (<2)"] +dev = ["tox", "bump2version (<1)", "sphinx (<2)", "importlib-metadata (<3)", "importlib-resources (<4)", "configparser (<5)", "sphinxcontrib-websupport (<2)", "zipp (<2)", "PyTest (<5)", "PyTest-Cov (<2.6)", "pytest", "pytest-cov"] [[package]] name = "dill" @@ -278,7 +277,6 @@ jinja2 = "*" msgpack = ">=0.6.0" psutil = ">=5.0" pyyaml = "*" -setuptools = "*" sortedcontainers = "<2.0.0 || >2.0.0,<2.0.1 || >2.0.1" tblib = ">=1.6.0" toolz = ">=0.8.2" @@ -300,7 +298,7 @@ websocket-client = ">=0.32.0" [package.extras] ssh = ["paramiko (>=2.4.2)"] -tls = ["cryptography (>=3.4.7)", "idna (>=2.0.0)", "pyOpenSSL (>=17.5.0)"] +tls = ["pyOpenSSL (>=17.5.0)", "cryptography (>=3.4.7)", "idna (>=2.0.0)"] [[package]] name = "docopt" @@ -319,7 +317,7 @@ optional = false python-versions = ">=3.7" [package.extras] -codecs = ["lz4", "python-snappy", "zstandard"] +codecs = ["python-snappy", "zstandard", "lz4"] lz4 = ["lz4"] snappy = ["python-snappy"] zstandard = ["zstandard"] @@ -345,9 +343,9 @@ optional = false python-versions = ">=3.7" [package.extras] -all = ["brotli (>=1.0.1)", "brotlicffi (>=0.8.0)", "fs (>=2.2.0,<3)", "lxml (>=4.0,<5)", "lz4 (>=1.7.4.2)", "matplotlib", "munkres", "scipy", "skia-pathops (>=0.5.0)", "sympy", "uharfbuzz (>=0.23.0)", "unicodedata2 (>=14.0.0)", "xattr", "zopfli (>=0.1.4)"] +all = ["fs (>=2.2.0,<3)", "lxml (>=4.0,<5)", "zopfli (>=0.1.4)", "lz4 (>=1.7.4.2)", "matplotlib", "sympy", "skia-pathops (>=0.5.0)", "uharfbuzz (>=0.23.0)", "brotlicffi (>=0.8.0)", "scipy", "brotli (>=1.0.1)", "munkres", "unicodedata2 (>=14.0.0)", "xattr"] graphite = ["lz4 (>=1.7.4.2)"] -interpolatable = ["munkres", "scipy"] +interpolatable = ["scipy", "munkres"] lxml = ["lxml (>=4.0,<5)"] pathops = ["skia-pathops (>=0.5.0)"] plot = ["matplotlib"] @@ -356,7 +354,7 @@ symfont = ["sympy"] type1 = ["xattr"] ufo = ["fs (>=2.2.0,<3)"] unicode = ["unicodedata2 (>=14.0.0)"] -woff = ["brotli (>=1.0.1)", "brotlicffi (>=0.8.0)", "zopfli (>=0.1.4)"] +woff = ["zopfli (>=0.1.4)", "brotlicffi (>=0.8.0)", "brotli (>=1.0.1)"] [[package]] name = "fsspec" @@ -371,7 +369,7 @@ abfs = ["adlfs"] adl = ["adlfs"] arrow = ["pyarrow (>=1)"] dask = ["dask", "distributed"] -dropbox = ["dropbox", "dropboxdrivefs", "requests"] +dropbox = ["dropboxdrivefs", "requests", "dropbox"] entrypoints = ["importlib-metadata"] fuse = ["fusepy"] gcs = ["gcsfs"] @@ -380,7 +378,7 @@ github = ["requests"] gs = ["gcsfs"] gui = ["panel"] hdfs = ["pyarrow (>=1)"] -http = ["aiohttp", "requests"] +http = ["requests", "aiohttp"] libarchive = ["libarchive-c"] oci = ["ocifs"] s3 = ["s3fs"] @@ -417,7 +415,6 @@ packaging = ">=14.3" protobuf = {version = ">=3.12.0", markers = "python_version > \"3\""} pytz = "*" requests = ">=2.18.0,<3.0.0dev" -setuptools = ">=40.3.0" six = ">=1.13.0" [package.extras] @@ -452,11 +449,10 @@ python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*" cachetools = ">=2.0.0,<5.0" pyasn1-modules = ">=0.2.1" rsa = {version = ">=3.1.4,<5", markers = "python_version >= \"3.6\""} -setuptools = ">=40.3.0" six = ">=1.9.0" [package.extras] -aiohttp = ["aiohttp (>=3.6.2,<4.0.0dev)", "requests (>=2.20.0,<3.0.0dev)"] +aiohttp = ["requests (>=2.20.0,<3.0.0dev)", "aiohttp (>=3.6.2,<4.0.0dev)"] pyopenssl = ["pyopenssl (>=20.0.0)"] reauth = ["pyu2f (>=0.1.5)"] @@ -508,11 +504,11 @@ python-dateutil = ">=2.7.2,<3.0dev" requests = ">=2.18.0,<3.0.0dev" [package.extras] -all = ["Shapely (>=1.6.0,<2.0dev)", "geopandas (>=0.9.0,<1.0dev)", "google-cloud-bigquery-storage (>=2.0.0,<3.0.0dev)", "grpcio (>=1.38.1,<2.0dev)", "opentelemetry-api (>=0.11b0)", "opentelemetry-instrumentation (>=0.11b0)", "opentelemetry-sdk (>=0.11b0)", "pandas (>=0.24.2)", "pyarrow (>=3.0.0,<7.0dev)", "tqdm (>=4.7.4,<5.0.0dev)"] +all = ["google-cloud-bigquery-storage (>=2.0.0,<3.0.0dev)", "grpcio (>=1.38.1,<2.0dev)", "pyarrow (>=3.0.0,<7.0dev)", "geopandas (>=0.9.0,<1.0dev)", "Shapely (>=1.6.0,<2.0dev)", "pandas (>=0.24.2)", "tqdm (>=4.7.4,<5.0.0dev)", "opentelemetry-api (>=0.11b0)", "opentelemetry-sdk (>=0.11b0)", "opentelemetry-instrumentation (>=0.11b0)"] bignumeric_type = ["pyarrow (>=3.0.0,<7.0dev)"] bqstorage = ["google-cloud-bigquery-storage (>=2.0.0,<3.0.0dev)", "grpcio (>=1.38.1,<2.0dev)", "pyarrow (>=3.0.0,<7.0dev)"] -geopandas = ["Shapely (>=1.6.0,<2.0dev)", "geopandas (>=0.9.0,<1.0dev)"] -opentelemetry = ["opentelemetry-api (>=0.11b0)", "opentelemetry-instrumentation (>=0.11b0)", "opentelemetry-sdk (>=0.11b0)"] +geopandas = ["geopandas (>=0.9.0,<1.0dev)", "Shapely (>=1.6.0,<2.0dev)"] +opentelemetry = ["opentelemetry-api (>=0.11b0)", "opentelemetry-sdk (>=0.11b0)", "opentelemetry-instrumentation (>=0.11b0)"] pandas = ["pandas (>=0.24.2)", "pyarrow (>=3.0.0,<7.0dev)"] tqdm = ["tqdm (>=4.7.4,<5.0.0dev)"] @@ -683,9 +679,9 @@ python-versions = ">=3.7" zipp = ">=0.5" [package.extras] -docs = ["jaraco.packaging (>=9)", "rst.linker (>=1.9)", "sphinx"] +docs = ["sphinx", "jaraco.packaging (>=9)", "rst.linker (>=1.9)"] perf = ["ipython"] -testing = ["flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.0.1)", "pytest-flake8", "pytest-mypy (>=0.9.1)", "pytest-perf (>=0.9.2)"] +testing = ["pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-flake8", "pytest-cov", "pytest-enabler (>=1.0.1)", "packaging", "pyfakefs", "flufl.flake8", "pytest-perf (>=0.9.2)", "pytest-black (>=0.3.7)", "pytest-mypy (>=0.9.1)", "importlib-resources (>=1.3)"] [[package]] name = "iniconfig" @@ -746,7 +742,7 @@ colorama = {version = ">=0.3.4", markers = "sys_platform == \"win32\""} win32-setctime = {version = ">=1.0.0", markers = "sys_platform == \"win32\""} [package.extras] -dev = ["Sphinx (>=4.1.1)", "black (>=19.10b0)", "colorama (>=0.3.4)", "docutils (==0.16)", "flake8 (>=3.7.7)", "isort (>=5.1.1)", "pytest (>=4.6.2)", "pytest-cov (>=2.7.1)", "sphinx-autobuild (>=0.7.1)", "sphinx-rtd-theme (>=0.4.3)", "tox (>=3.9.0)"] +dev = ["colorama (>=0.3.4)", "docutils (==0.16)", "flake8 (>=3.7.7)", "tox (>=3.9.0)", "pytest (>=4.6.2)", "pytest-cov (>=2.7.1)", "black (>=19.10b0)", "isort (>=5.1.1)", "Sphinx (>=4.1.1)", "sphinx-autobuild (>=0.7.1)", "sphinx-rtd-theme (>=0.4.3)"] [[package]] name = "markupsafe" @@ -765,9 +761,9 @@ optional = false python-versions = ">=3.6" [package.extras] -dev = ["flake8 (==4.0.1)", "flake8-bugbear (==21.9.2)", "mypy (==0.910)", "pre-commit (>=2.4,<3.0)", "pytest", "pytz", "simplejson", "tox"] -docs = ["alabaster (==0.7.12)", "autodocsumm (==0.2.7)", "sphinx (==4.3.0)", "sphinx-issues (==1.2.0)", "sphinx-version-warning (==1.1.2)"] -lint = ["flake8 (==4.0.1)", "flake8-bugbear (==21.9.2)", "mypy (==0.910)", "pre-commit (>=2.4,<3.0)"] +dev = ["pytest", "pytz", "simplejson", "mypy (==0.910)", "flake8 (==4.0.1)", "flake8-bugbear (==21.9.2)", "pre-commit (>=2.4,<3.0)", "tox"] +docs = ["sphinx (==4.3.0)", "sphinx-issues (==1.2.0)", "alabaster (==0.7.12)", "sphinx-version-warning (==1.1.2)", "autodocsumm (==0.2.7)"] +lint = ["mypy (==0.910)", "flake8 (==4.0.1)", "flake8-bugbear (==21.9.2)", "pre-commit (>=2.4,<3.0)"] tests = ["pytest", "pytz", "simplejson"] [[package]] @@ -782,9 +778,9 @@ python-versions = ">=3.6" marshmallow = ">=3.0.0,<4.0.0" [package.extras] -dev = ["flake8 (==3.9.2)", "flake8-bugbear (==21.4.3)", "mock", "pre-commit (>=2.7,<3.0)", "pytest", "tox"] +dev = ["pytest", "mock", "flake8 (==3.9.2)", "flake8-bugbear (==21.4.3)", "pre-commit (>=2.7,<3.0)", "tox"] lint = ["flake8 (==3.9.2)", "flake8-bugbear (==21.4.3)", "pre-commit (>=2.7,<3.0)"] -tests = ["mock", "pytest"] +tests = ["pytest", "mock"] [[package]] name = "matplotlib" @@ -837,9 +833,6 @@ category = "main" optional = false python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*" -[package.dependencies] -setuptools = "*" - [[package]] name = "numpy" version = "1.21.4" @@ -925,7 +918,6 @@ numpy = ">=1.16.6" pandas = ">=0.24.2" pyarrow = ">=3.0.0,<8.0dev" pydata-google-auth = "*" -setuptools = "*" [package.extras] tqdm = ["tqdm (>=4.23.0)"] @@ -960,7 +952,7 @@ locket = "*" toolz = "*" [package.extras] -complete = ["blosc", "numpy (>=1.9.0)", "pandas (>=0.19.0)", "pyzmq"] +complete = ["numpy (>=1.9.0)", "pandas (>=0.19.0)", "pyzmq", "blosc"] [[package]] name = "pendulum" @@ -995,8 +987,8 @@ optional = false python-versions = ">=3.7" [package.extras] -docs = ["furo (>=2021.7.5b38)", "proselint (>=0.10.2)", "sphinx (>=4)", "sphinx-autodoc-typehints (>=1.12)"] -test = ["appdirs (==1.4.4)", "pytest (>=6)", "pytest-cov (>=2.7)", "pytest-mock (>=3.6)"] +docs = ["furo (>=2021.7.5b38)", "proselint (>=0.10.2)", "sphinx-autodoc-typehints (>=1.12)", "sphinx (>=4)"] +test = ["appdirs (==1.4.4)", "pytest-cov (>=2.7)", "pytest-mock (>=3.6)", "pytest (>=6)"] [[package]] name = "pluggy" @@ -1057,26 +1049,26 @@ urllib3 = ">=1.24.3" [package.extras] airtable = ["airtable-python-wrapper (>=0.11,<0.12)"] -all_extras = ["PyGithub (>=1.51,<2.0)", "Pygments (>=2.2,<3.0)", "airtable-python-wrapper (>=0.11,<0.12)", "atlassian-python-api (>=2.0.1)", "azure-cosmos (>=3.1.1,<3.2)", "azure-storage-blob (>=12.1.0,<13.0)", "azureml-sdk (>=1.0.65,<1.1)", "black", "boto3 (>=1.9,<2.0)", "confluent-kafka (>=1.7.0)", "dask-cloudprovider[aws] (>=0.2.0)", "dask-kubernetes (>=0.8.0)", "dropbox (>=9.0,<10.0)", "dulwich (>=0.19.7)", "feedparser (>=5.0.1,<6.0)", "flaky (>=3.0)", "google-auth (>=2.0,<3.0)", "google-cloud-aiplatform (>=1.4.0,<2.0)", "google-cloud-bigquery (>=1.6.0,<3.0)", "google-cloud-secret-manager (>=2.4.0)", "google-cloud-storage (>=1.13,<2.0)", "graphviz (>=0.8)", "graphviz (>=0.8.3)", "great-expectations (>=0.11.1)", "gspread (>=3.6.0)", "hvac (>=0.10)", "jinja2 (>=2.0,<4.0)", "jira (>=2.0.0)", "kubernetes (>=9.0.0a1,<=13.0)", "mypy (>=0.600,<0.813)", "nbconvert (>=6.0.7)", "pandas (>=1.0.1)", "papermill (>=2.2.0)", "prometheus-client (>=0.9.0)", "psycopg2-binary (>=2.8.2)", "pushbullet.py (>=0.11.0)", "pyarrow 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"dask-cloudprovider[aws] (>=0.2.0)", "black", "graphviz (>=0.8)", "jinja2 (>=2.0,<4.0)", "mypy (>=0.600,<0.813)", "Pygments (>=2.2,<3.0)", "pytest (>=6.0)", "testfixtures (>=6.10.3)", "pytest-env (>=0.6.0)", "pytest-xdist (>=2.0)", "flaky (>=3.0)", "responses (>=0.14.0)", "dropbox (>=9.0,<10.0)", "great-expectations (>=0.11.1)", "google-cloud-bigquery (>=1.6.0,<3.0)", "google-cloud-secret-manager (>=2.4.0)", "google-cloud-storage (>=1.13,<2.0)", "google-cloud-aiplatform (>=1.4.0,<2.0)", "google-auth (>=2.0,<3.0)", "dulwich (>=0.19.7)", "PyGithub (>=1.51,<2.0)", "python-gitlab (>=2.5.0,<3.0)", "gspread (>=3.6.0)", "jira (>=2.0.0)", "papermill (>=2.2.0)", "nbconvert (>=6.0.7)", "confluent-kafka (>=1.7.0)", "dask-kubernetes (>=0.8.0)", "kubernetes (>=9.0.0a1,<=13.0)", "pandas (>=1.0.1)", "psycopg2-binary (>=2.8.2)", "prometheus-client (>=0.9.0)", "pymysql (>=0.9.3)", "pyodbc (>=4.0.30)", "pushbullet.py (>=0.11.0)", "redis (>=3.2.1)", "feedparser (>=5.0.1,<6.0)", 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"pytest (>=6.0)", "testfixtures (>=6.10.3)", "pytest-env (>=0.6.0)", "pytest-xdist (>=2.0)", "flaky (>=3.0)", "responses (>=0.14.0)", "pandas (>=1.0.1)", "jira (>=2.0.0)"] bitbucket = ["atlassian-python-api (>=2.0.1)"] dask_cloudprovider = ["dask-cloudprovider[aws] (>=0.2.0)"] -dev = ["Pygments (>=2.2,<3.0)", "black", "flaky (>=3.0)", "graphviz (>=0.8)", "jinja2 (>=2.0,<4.0)", "mypy (>=0.600,<0.813)", "pytest (>=6.0)", "pytest-env (>=0.6.0)", "pytest-xdist (>=2.0)", "responses (>=0.14.0)", "testfixtures (>=6.10.3)"] +dev = ["black", "graphviz (>=0.8)", "jinja2 (>=2.0,<4.0)", "mypy (>=0.600,<0.813)", "Pygments (>=2.2,<3.0)", "pytest (>=6.0)", "testfixtures (>=6.10.3)", "pytest-env (>=0.6.0)", "pytest-xdist (>=2.0)", "flaky (>=3.0)", "responses (>=0.14.0)"] dremio = ["pyarrow (>=5.0.0)"] dropbox = ["dropbox (>=9.0,<10.0)"] exasol = ["pyexasol (>=0.16.1)"] -gcp = ["google-auth (>=2.0,<3.0)", "google-cloud-aiplatform (>=1.4.0,<2.0)", "google-cloud-bigquery (>=1.6.0,<3.0)", "google-cloud-secret-manager (>=2.4.0)", "google-cloud-storage (>=1.13,<2.0)"] +gcp = ["google-cloud-bigquery (>=1.6.0,<3.0)", "google-cloud-secret-manager (>=2.4.0)", "google-cloud-storage (>=1.13,<2.0)", "google-cloud-aiplatform (>=1.4.0,<2.0)", "google-auth (>=2.0,<3.0)"] ge = ["great-expectations (>=0.11.1)"] git = ["dulwich (>=0.19.7)"] github = ["PyGithub (>=1.51,<2.0)"] gitlab = ["python-gitlab (>=2.5.0,<3.0)"] -google = ["google-auth (>=2.0,<3.0)", "google-cloud-aiplatform (>=1.4.0,<2.0)", "google-cloud-bigquery (>=1.6.0,<3.0)", "google-cloud-secret-manager (>=2.4.0)", "google-cloud-storage (>=1.13,<2.0)"] +google = ["google-cloud-bigquery (>=1.6.0,<3.0)", "google-cloud-secret-manager (>=2.4.0)", "google-cloud-storage (>=1.13,<2.0)", "google-cloud-aiplatform (>=1.4.0,<2.0)", "google-auth (>=2.0,<3.0)"] gsheets = ["gspread (>=3.6.0)"] jira = ["jira (>=2.0.0)"] -jupyter = ["nbconvert (>=6.0.7)", "papermill (>=2.2.0)"] +jupyter = ["papermill (>=2.2.0)", "nbconvert (>=6.0.7)"] kafka = ["confluent-kafka (>=1.7.0)"] kubernetes = ["dask-kubernetes (>=0.8.0)", "kubernetes (>=9.0.0a1,<=13.0)"] mysql = ["pymysql (>=0.9.3)"] @@ -1091,9 +1083,9 @@ snowflake = ["snowflake-connector-python (>=1.8.2,<2.5)"] sodasql = ["soda-sql (>=2.0.0b25)"] spacy = ["spacy (>=2.0.0,<3.0.0)"] sql_server = ["pyodbc (>=4.0.30)"] -task_library_ci = ["PyGithub (>=1.51,<2.0)", "Pygments (>=2.2,<3.0)", "airtable-python-wrapper (>=0.11,<0.12)", "atlassian-python-api (>=2.0.1)", "azure-cosmos (>=3.1.1,<3.2)", "azure-storage-blob (>=12.1.0,<13.0)", "azureml-sdk (>=1.0.65,<1.1)", "black", "boto3 (>=1.9,<2.0)", "confluent-kafka (>=1.7.0)", "dask-kubernetes (>=0.8.0)", "dropbox (>=9.0,<10.0)", "dulwich (>=0.19.7)", "feedparser (>=5.0.1,<6.0)", "flaky (>=3.0)", "google-auth (>=2.0,<3.0)", "google-cloud-aiplatform (>=1.4.0,<2.0)", "google-cloud-bigquery (>=1.6.0,<3.0)", "google-cloud-secret-manager (>=2.4.0)", "google-cloud-storage (>=1.13,<2.0)", "graphviz (>=0.8)", "graphviz (>=0.8.3)", "great-expectations (>=0.11.1)", "gspread (>=3.6.0)", "hvac (>=0.10)", "jinja2 (>=2.0,<4.0)", "jira (>=2.0.0)", "kubernetes (>=9.0.0a1,<=13.0)", "mypy (>=0.600,<0.813)", "nbconvert (>=6.0.7)", "pandas (>=1.0.1)", "papermill (>=2.2.0)", "prometheus-client (>=0.9.0)", "psycopg2-binary (>=2.8.2)", "pushbullet.py (>=0.11.0)", "pyarrow (>=5.0.0)", "pyexasol (>=0.16.1)", "pymysql (>=0.9.3)", "pytest (>=6.0)", "pytest-env (>=0.6.0)", "pytest-xdist (>=2.0)", "python-gitlab (>=2.5.0,<3.0)", "redis (>=3.2.1)", "responses (>=0.14.0)", "sendgrid (>=6.7.0)", "snowflake-connector-python (>=1.8.2,<2.5)", "soda-sql (>=2.0.0b25)", "spacy (>=2.0.0,<3.0.0)", "testfixtures (>=6.10.3)", "tweepy (>=3.5,<4.0)"] +task_library_ci = ["airtable-python-wrapper (>=0.11,<0.12)", "boto3 (>=1.9,<2.0)", "azure-storage-blob (>=12.1.0,<13.0)", "azureml-sdk (>=1.0.65,<1.1)", "azure-cosmos (>=3.1.1,<3.2)", "atlassian-python-api (>=2.0.1)", "black", "graphviz (>=0.8)", "jinja2 (>=2.0,<4.0)", "mypy (>=0.600,<0.813)", "Pygments (>=2.2,<3.0)", "pytest (>=6.0)", "testfixtures (>=6.10.3)", "pytest-env (>=0.6.0)", "pytest-xdist (>=2.0)", "flaky (>=3.0)", "responses (>=0.14.0)", "dropbox (>=9.0,<10.0)", "great-expectations (>=0.11.1)", "google-cloud-bigquery (>=1.6.0,<3.0)", "google-cloud-secret-manager (>=2.4.0)", "google-cloud-storage (>=1.13,<2.0)", "google-cloud-aiplatform (>=1.4.0,<2.0)", "google-auth (>=2.0,<3.0)", "dulwich (>=0.19.7)", "PyGithub (>=1.51,<2.0)", "python-gitlab (>=2.5.0,<3.0)", "gspread (>=3.6.0)", "jira (>=2.0.0)", "papermill (>=2.2.0)", "nbconvert (>=6.0.7)", "confluent-kafka (>=1.7.0)", "dask-kubernetes (>=0.8.0)", "kubernetes (>=9.0.0a1,<=13.0)", "pandas (>=1.0.1)", "psycopg2-binary (>=2.8.2)", "prometheus-client (>=0.9.0)", "pymysql (>=0.9.3)", "pushbullet.py (>=0.11.0)", "redis (>=3.2.1)", "feedparser (>=5.0.1,<6.0)", "snowflake-connector-python (>=1.8.2,<2.5)", "spacy (>=2.0.0,<3.0.0)", "hvac (>=0.10)", "graphviz (>=0.8.3)", "tweepy (>=3.5,<4.0)", "pyarrow (>=5.0.0)", "pyexasol (>=0.16.1)", "soda-sql (>=2.0.0b25)", "sendgrid (>=6.7.0)"] templates = ["jinja2 (>=2.0,<4.0)"] -test = ["flaky (>=3.0)", "pytest (>=6.0)", "pytest-env (>=0.6.0)", "pytest-xdist (>=2.0)", "responses (>=0.14.0)", "testfixtures (>=6.10.3)"] +test = ["pytest (>=6.0)", "testfixtures (>=6.10.3)", "pytest-env (>=0.6.0)", "pytest-xdist (>=2.0)", "flaky (>=3.0)", "responses (>=0.14.0)"] twitter = ["tweepy (>=3.5,<4.0)"] vault = ["hvac (>=0.10)"] viz = ["graphviz (>=0.8.3)"] @@ -1129,7 +1121,7 @@ optional = false python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" [package.extras] -test = ["enum34", "ipaddress", "mock", "pywin32", "unittest2", "wmi"] +test = ["ipaddress", "mock", "unittest2", "enum34", "pywin32", "wmi"] [[package]] name = "py" @@ -1191,7 +1183,6 @@ python-versions = "*" [package.dependencies] google-auth = "*" google-auth-oauthlib = "*" -setuptools = "*" [[package]] name = "pymssql" @@ -1248,7 +1239,7 @@ coverage = {version = ">=5.2.1", extras = ["toml"]} pytest = ">=4.6" [package.extras] -testing = ["fields", "hunter", "process-tests", "pytest-xdist", "six", "virtualenv"] +testing = ["fields", "hunter", "process-tests", "six", "pytest-xdist", "virtualenv"] [[package]] name = "python-box" @@ -1259,9 +1250,9 @@ optional = false python-versions = ">=3.6" [package.extras] -all = ["msgpack", "ruamel.yaml", "toml"] +pyyaml = ["pyyaml"] +all = ["ruamel.yaml", "toml", "msgpack"] msgpack = ["msgpack"] -pyyaml = ["PyYAML"] "ruamel.yaml" = ["ruamel.yaml"] toml = ["toml"] yaml = ["ruamel.yaml"] @@ -1323,6 +1314,14 @@ category = "main" optional = false python-versions = ">=3.6" +[[package]] +name = "rarfile" +version = "4.0" +description = "RAR archive reader for Python" +category = "main" +optional = false +python-versions = "*" + [[package]] name = "redis" version = "4.3.4" @@ -1444,19 +1443,6 @@ numpy = ">=1.15" pandas = ">=0.23" scipy = ">=1.0" -[[package]] -name = "setuptools" -version = "65.6.3" -description = "Easily download, build, 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+importlib-metadata = [] +iniconfig = [] +ipeadatapy = [] +jinja2 = [] +kiwisolver = [] +locket = [] +loguru = [] +markupsafe = [] +marshmallow = [] +marshmallow-oneofschema = [] +matplotlib = [] +more-itertools = [] +msgpack = [] +mypy-extensions = [] +nodeenv = [] +numpy = [] +oauth2client = [] +oauthlib = [] +packaging = [] +pandas = [] +pandas-gbq = [] +pandavro = [] +partd = [] +pendulum = [] +pillow = [] +platformdirs = [] +pluggy = [] +pre-commit = [] +prefect = [] +proto-plus = [] +protobuf = [] +psutil = [] +py = [] +pyaml = [] +pyarrow = [] +pyasn1 = [] +pyasn1-modules = [] +pydata-google-auth = [] +pymssql = [] +pyparsing = [] +pytest = [] +pytest-cov = [] +python-box = [] +python-dateutil = [] +python-slugify = [] +pytz = [] +pytzdata = [] +pywin32 = [] +pyyaml = [] +rarfile = [] +redis = [] +redis-pal = [] +requests = [] +requests-oauthlib = [] +rsa = [] +"ruamel.yaml" = [] +"ruamel.yaml.clib" = [] +scipy = [] +seaborn = [] +setuptools-scm = [] +six = [] +sortedcontainers = [] +soupsieve = [] +tabulate = [] +tblib = [] +text-unidecode = [] +toml = [] +tomli = [] +tomlkit = [] +toolz = [] +tornado = [] +tqdm = [] +tweepy = [] +unidecode = [] +uritemplate = [] +urllib3 = [] +virtualenv = [] +websocket-client = [] +wget = [] +win32-setctime = [] +wrapt = [] +zict = [] +zipp = [] diff --git a/pyproject.toml b/pyproject.toml index 065c65fae..5160e0077 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -97,6 +97,7 @@ google-analytics-data = "0.12.1" google-api-python-client = "^2.58.0" oauth2client = "^4.1.3" redis-pal = "^1.0.0" +rarfile = "^4.0" [tool.poetry.dev-dependencies] pytest_cov = "^3.0.0" From c5a1bf175c609004c3c4a687fae4dfb8be54b5e2 Mon Sep 17 00:00:00 2001 From: Tamir Date: Thu, 23 Mar 2023 02:21:29 -0300 Subject: [PATCH 004/265] Missing function --- br_denatran_frota/code/download_frota.py | 8 +++++++- 1 file changed, 7 insertions(+), 1 deletion(-) diff --git a/br_denatran_frota/code/download_frota.py b/br_denatran_frota/code/download_frota.py index c75ef01e4..ff6e0cd94 100644 --- a/br_denatran_frota/code/download_frota.py +++ b/br_denatran_frota/code/download_frota.py @@ -75,7 +75,13 @@ def handle_compact(i): os.rename(filepath, dest_path_file) else: os.remove(filepath) - + + def download_file(i): + if i['filetype'] in ['rar', 'zip']: + handle_compact(i) + elif i['filetype'] in ['xlsx', 'xls']: + handle_xl(i) + soup = BeautifulSoup(urlopen(url), "html.parser") nodes = soup.select("p > a") From bef1e58ab6a0aff4b67169aacdc7f46e55dc84f1 Mon Sep 17 00:00:00 2001 From: Tamir Date: Thu, 23 Mar 2023 18:18:16 -0300 Subject: [PATCH 005/265] Converted code from R to Python --- br_denatran_frota/code/download_frota.R | 4 +- br_denatran_frota/code/download_frota_gpt.py | 101 +++++++++++++++++++ 2 files changed, 104 insertions(+), 1 deletion(-) create mode 100644 br_denatran_frota/code/download_frota_gpt.py diff --git a/br_denatran_frota/code/download_frota.R b/br_denatran_frota/code/download_frota.R index 0734e7526..b9ce2930c 100644 --- a/br_denatran_frota/code/download_frota.R +++ b/br_denatran_frota/code/download_frota.R @@ -118,4 +118,6 @@ download_frota <- function(key = NULL, prefix = NULL, month, year, tempdir = tem ) %>% purrr::transpose() %>% purrr::walk(~download_file(.x)) -} \ No newline at end of file +} + +download_frota(year = 2013, month = 1, tempdir = 'p') diff --git a/br_denatran_frota/code/download_frota_gpt.py b/br_denatran_frota/code/download_frota_gpt.py new file mode 100644 index 000000000..d12cd9856 --- /dev/null +++ b/br_denatran_frota/code/download_frota_gpt.py @@ -0,0 +1,101 @@ +import os +import re +import tempfile +from urllib.request import urlopen, urlretrieve +from zipfile import ZipFile +from rarfile import RarFile +from bs4 import BeautifulSoup +from collections import defaultdict + + +def download_frota( month=None, year=None, tempdir=None, dir=None): + months = { + "janeiro": 1, + "fevereiro": 2, + "marco": 3, + "abril": 4, + "maio": 5, + "junho": 6, + "julho": 7, + "agosto": 8, + "setembro": 9, + "outubro": 10, + "novembro": 11, + "dezembro": 12, + } + + if year > 2012: + url = f"https://www.gov.br/infraestrutura/pt-br/assuntos/transito/conteudo-Senatran/frota-de-veiculos-{year}" + else: + raise ValueError("Utilize a função download_frota_old()") + + if not tempdir: + tempdir = tempfile.gettempdir() + if not dir: + dir = os.getcwd() + + def make_filename(i, ext=True): + txt = i["txt"] + mes = i["mes"] + ano = i["ano"] + filetype = i["filetype"] + filename = re.sub("\\s+", "_", txt, flags=re.UNICODE).lower() + filename = f"{filename}_{mes}-{ano}" + if ext: + filename += f".{filetype}" + return filename + + def handle_xl(i): + dest_path_file = os.path.join(dir, f"{i['mes']}-{i['ano']}.{i['filetype']}") + if not os.path.isfile(dest_path_file): + urlretrieve(i["href"], dest_path_file) + + def handle_compact(i): + path_file_zip = os.path.join(tempdir, make_filename(i)) + dir_file = os.path.join(tempdir, make_filename(i, ext=False)) + + if not os.path.isfile(path_file_zip): + urlretrieve(i["href"], path_file_zip) + + if i["filetype"] == "rar": + with RarFile(path_file_zip) as rar_file: + rar_file.extractall(dir_file) + else: + with ZipFile(path_file_zip) as zip_file: + zip_file.extractall(dir_file) + + for filename in os.listdir(dir_file): + filepath = os.path.join(dir_file, filename) + if os.path.isfile(filepath): + if filename.endswith((".xlsx", ".xls")): + dest_path_file = os.path.join( + dir, f"{i['mes']}-{i['ano']}.{filename.split('.')[-1]}" + ) + if not os.path.isfile(dest_path_file): + os.rename(filepath, dest_path_file) + else: + os.remove(filepath) + + def download_file(i): + if i['filetype'] in ['rar', 'zip']: + handle_compact(i) + elif i['filetype'] in ['xlsx', 'xls']: + handle_xl(i) + + soup = BeautifulSoup(urlopen(url), "html.parser") + nodes = soup.select("p > a") + + data = defaultdict(list) + for node in nodes: + txt = node.text + href = node.get('href') + match = re.search(r"(?i)\/([\w-]+)\/(\d{4})\/(\w+)\/([\w-]+)\.(?:xls|xlsx|rar|zip)$", href) + if match: + matched_month = match.group(3) + matched_year = match.group(2) + if months.get(matched_month) == month and matched_year == str(year): + filetype = match.group(0).split('.')[-1].lower() + info = {'txt': txt, 'href': href, 'mes_name': matched_month, 'mes': month, 'ano': year, 'filetype': filetype} + download_file(info) + +download_frota(year=2022, month = 12) \ No newline at end of file From 62b6ddbd99fd255774bcfb9e1151410ed0fbea5e Mon Sep 17 00:00:00 2001 From: Tamir Date: Thu, 23 Mar 2023 18:22:51 -0300 Subject: [PATCH 006/265] Simply files --- br_denatran_frota/code/download_frota.py | 28 ++--- br_denatran_frota/code/download_frota_gpt.py | 101 ------------------- 2 files changed, 15 insertions(+), 114 deletions(-) delete mode 100644 br_denatran_frota/code/download_frota_gpt.py diff --git a/br_denatran_frota/code/download_frota.py b/br_denatran_frota/code/download_frota.py index ff6e0cd94..d12cd9856 100644 --- a/br_denatran_frota/code/download_frota.py +++ b/br_denatran_frota/code/download_frota.py @@ -8,7 +8,7 @@ from collections import defaultdict -def download_frota(key=None, prefix=None, month=None, year=None, tempdir=None, dir=None): +def download_frota( month=None, year=None, tempdir=None, dir=None): months = { "janeiro": 1, "fevereiro": 2, @@ -25,7 +25,7 @@ def download_frota(key=None, prefix=None, month=None, year=None, tempdir=None, d } if year > 2012: - url = f"https://www.gov.br/infraestrutura/pt-br/assuntos/transito/conteudo-denatran/frota-de-veiculos-{year}" + url = f"https://www.gov.br/infraestrutura/pt-br/assuntos/transito/conteudo-Senatran/frota-de-veiculos-{year}" else: raise ValueError("Utilize a função download_frota_old()") @@ -46,7 +46,7 @@ def make_filename(i, ext=True): return filename def handle_xl(i): - dest_path_file = os.path.join(dir, f"{prefix}_{i['mes']}-{i['ano']}.{i['filetype']}") + dest_path_file = os.path.join(dir, f"{i['mes']}-{i['ano']}.{i['filetype']}") if not os.path.isfile(dest_path_file): urlretrieve(i["href"], dest_path_file) @@ -69,7 +69,7 @@ def handle_compact(i): if os.path.isfile(filepath): if filename.endswith((".xlsx", ".xls")): dest_path_file = os.path.join( - dir, f"{prefix}_{i['mes']}-{i['ano']}.{filename.split('.')[-1]}" + dir, f"{i['mes']}-{i['ano']}.{filename.split('.')[-1]}" ) if not os.path.isfile(dest_path_file): os.rename(filepath, dest_path_file) @@ -88,12 +88,14 @@ def download_file(i): data = defaultdict(list) for node in nodes: txt = node.text - href = node.attrib["href"] - match = re.search("(?i)xls|xlsx|rar|zip$", href) - if match and re.search(key, txt, re.IGNORECASE) and months.get(match.group(1)) in month: - filetype = match.group().lower() - mes_name = re.search("(%s)" % "|".join(months.keys()), href).group(1) - mes = months[mes_name] - ano = int(re.search("\d{4}", href).group()) - info = {'txt': txt, 'href': href, 'mes_name': mes_name, 'mes': mes, 'ano': ano, 'filetype': filetype} - download_file(info) + href = node.get('href') + match = re.search(r"(?i)\/([\w-]+)\/(\d{4})\/(\w+)\/([\w-]+)\.(?:xls|xlsx|rar|zip)$", href) + if match: + matched_month = match.group(3) + matched_year = match.group(2) + if months.get(matched_month) == month and matched_year == str(year): + filetype = match.group(0).split('.')[-1].lower() + info = {'txt': txt, 'href': href, 'mes_name': matched_month, 'mes': month, 'ano': year, 'filetype': filetype} + download_file(info) + +download_frota(year=2022, month = 12) \ No newline at end of file diff --git a/br_denatran_frota/code/download_frota_gpt.py b/br_denatran_frota/code/download_frota_gpt.py deleted file mode 100644 index d12cd9856..000000000 --- a/br_denatran_frota/code/download_frota_gpt.py +++ /dev/null @@ -1,101 +0,0 @@ -import os -import re -import tempfile -from urllib.request import urlopen, urlretrieve -from zipfile import ZipFile -from rarfile import RarFile -from bs4 import BeautifulSoup -from collections import defaultdict - - -def download_frota( month=None, year=None, tempdir=None, dir=None): - months = { - "janeiro": 1, - "fevereiro": 2, - "marco": 3, - "abril": 4, - "maio": 5, - "junho": 6, - "julho": 7, - "agosto": 8, - "setembro": 9, - "outubro": 10, - "novembro": 11, - "dezembro": 12, - } - - if year > 2012: - url = f"https://www.gov.br/infraestrutura/pt-br/assuntos/transito/conteudo-Senatran/frota-de-veiculos-{year}" - else: - raise ValueError("Utilize a função download_frota_old()") - - if not tempdir: - tempdir = tempfile.gettempdir() - if not dir: - dir = os.getcwd() - - def make_filename(i, ext=True): - txt = i["txt"] - mes = i["mes"] - ano = i["ano"] - filetype = i["filetype"] - filename = re.sub("\\s+", "_", txt, flags=re.UNICODE).lower() - filename = f"{filename}_{mes}-{ano}" - if ext: - filename += f".{filetype}" - return filename - - def handle_xl(i): - dest_path_file = os.path.join(dir, f"{i['mes']}-{i['ano']}.{i['filetype']}") - if not os.path.isfile(dest_path_file): - urlretrieve(i["href"], dest_path_file) - - def handle_compact(i): - path_file_zip = os.path.join(tempdir, make_filename(i)) - dir_file = os.path.join(tempdir, make_filename(i, ext=False)) - - if not os.path.isfile(path_file_zip): - urlretrieve(i["href"], path_file_zip) - - if i["filetype"] == "rar": - with RarFile(path_file_zip) as rar_file: - rar_file.extractall(dir_file) - else: - with ZipFile(path_file_zip) as zip_file: - zip_file.extractall(dir_file) - - for filename in os.listdir(dir_file): - filepath = os.path.join(dir_file, filename) - if os.path.isfile(filepath): - if filename.endswith((".xlsx", ".xls")): - dest_path_file = os.path.join( - dir, f"{i['mes']}-{i['ano']}.{filename.split('.')[-1]}" - ) - if not os.path.isfile(dest_path_file): - os.rename(filepath, dest_path_file) - else: - os.remove(filepath) - - def download_file(i): - if i['filetype'] in ['rar', 'zip']: - handle_compact(i) - elif i['filetype'] in ['xlsx', 'xls']: - handle_xl(i) - - soup = BeautifulSoup(urlopen(url), "html.parser") - nodes = soup.select("p > a") - - data = defaultdict(list) - for node in nodes: - txt = node.text - href = node.get('href') - match = re.search(r"(?i)\/([\w-]+)\/(\d{4})\/(\w+)\/([\w-]+)\.(?:xls|xlsx|rar|zip)$", href) - if match: - matched_month = match.group(3) - matched_year = match.group(2) - if months.get(matched_month) == month and matched_year == str(year): - filetype = match.group(0).split('.')[-1].lower() - info = {'txt': txt, 'href': href, 'mes_name': matched_month, 'mes': month, 'ano': year, 'filetype': filetype} - download_file(info) - -download_frota(year=2022, month = 12) \ No newline at end of file From c10bd930dd5e606bf452512fe3928a103ff55ae7 Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 28 Mar 2023 17:54:43 -0300 Subject: [PATCH 007/265] Installable package + test --- br_denatran_frota/code/__init__.py | 0 br_denatran_frota/code/setup.py | 11 + .../code/test/download_frota_test.py | 39 + poetry.lock | 1552 ++++++++++++++--- pyproject.toml | 1 + 5 files changed, 1402 insertions(+), 201 deletions(-) create mode 100644 br_denatran_frota/code/__init__.py create mode 100644 br_denatran_frota/code/setup.py create mode 100644 br_denatran_frota/code/test/download_frota_test.py diff --git a/br_denatran_frota/code/__init__.py b/br_denatran_frota/code/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/br_denatran_frota/code/setup.py b/br_denatran_frota/code/setup.py new file mode 100644 index 000000000..4a1e6d3ad --- /dev/null +++ b/br_denatran_frota/code/setup.py @@ -0,0 +1,11 @@ +from setuptools import setup + +setup( + name='download_frota', + version='1.0', + py_modules=['download_frota'], + install_requires=[ + 'beautifulsoup4', + 'rarfile', + ], +) diff --git a/br_denatran_frota/code/test/download_frota_test.py b/br_denatran_frota/code/test/download_frota_test.py new file mode 100644 index 000000000..f88ce1e99 --- /dev/null +++ b/br_denatran_frota/code/test/download_frota_test.py @@ -0,0 +1,39 @@ +import os +import tempfile +import unittest +from unittest.mock import patch +from urllib.error import HTTPError +from download_frota import * + + +class TestDownloadFrota(unittest.TestCase): + + def setUp(self): + self.test_dir = tempfile.mkdtemp() + + def tearDown(self): + os.rmdir(self.test_dir) + + def test_download_frota_with_valid_args(self): + with patch('urllib.request.urlretrieve') as mock_urlretrieve: + download_frota(month=2, year=2022, dir=self.test_dir) + mock_urlretrieve.assert_called_once() + + def test_download_frota_with_invalid_year(self): + with self.assertRaises(ValueError): + download_frota(month=1, year=2010) + + def test_download_frota_with_invalid_month(self): + with self.assertRaises(HTTPError): + download_frota(month=13, year=2022, dir=self.test_dir) + + def test_download_frota_with_missing_directory(self): + with self.assertRaises(FileNotFoundError): + download_frota(month=1, year=2022, dir='invalid_directory') + + def test_download_frota_with_missing_temp_directory(self): + with self.assertRaises(FileNotFoundError): + download_frota(month=1, year=2022, tempdir='invalid_directory') + +if __name__ == '__main__': + unittest.main() diff --git a/poetry.lock b/poetry.lock index 60a414b94..ac53e631b 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,3 +1,5 @@ +# This file is automatically @generated by Poetry 1.4.1 and should not be changed by hand. + [[package]] name = "async-timeout" version = "4.0.2" @@ -5,6 +7,10 @@ description = "Timeout context manager for asyncio programs" category = "main" optional = false python-versions = ">=3.6" +files = [ + {file = "async-timeout-4.0.2.tar.gz", hash = "sha256:2163e1640ddb52b7a8c80d0a67a08587e5d245cc9c553a74a847056bc2976b15"}, + {file = "async_timeout-4.0.2-py3-none-any.whl", hash = "sha256:8ca1e4fcf50d07413d66d1a5e416e42cfdf5851c981d679a09851a6853383b3c"}, +] [[package]] name = "atomicwrites" @@ -13,6 +19,10 @@ description = "Atomic file writes." category = "dev" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" +files = [ + {file = "atomicwrites-1.4.0-py2.py3-none-any.whl", hash = "sha256:6d1784dea7c0c8d4a5172b6c620f40b6e4cbfdf96d783691f2e1302a7b88e197"}, + {file = "atomicwrites-1.4.0.tar.gz", hash = "sha256:ae70396ad1a434f9c7046fd2dd196fc04b12f9e91ffb859164193be8b6168a7a"}, +] [[package]] name = "attrs" @@ -21,12 +31,16 @@ description = "Classes Without Boilerplate" category = "dev" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" +files = [ + {file = "attrs-21.4.0-py2.py3-none-any.whl", hash = "sha256:2d27e3784d7a565d36ab851fe94887c5eccd6a463168875832a1be79c82828b4"}, + {file = "attrs-21.4.0.tar.gz", hash = "sha256:626ba8234211db98e869df76230a137c4c40a12d72445c45d5f5b716f076e2fd"}, +] [package.extras] -dev = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "mypy", "pytest-mypy-plugins", "zope.interface", "furo", "sphinx", "sphinx-notfound-page", "pre-commit", "cloudpickle"] -docs = ["furo", "sphinx", "zope.interface", "sphinx-notfound-page"] -tests = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "mypy", "pytest-mypy-plugins", "zope.interface", "cloudpickle"] -tests_no_zope = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "mypy", "pytest-mypy-plugins", "cloudpickle"] +dev = ["cloudpickle", "coverage[toml] (>=5.0.2)", "furo", "hypothesis", "mypy", "pre-commit", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "six", "sphinx", "sphinx-notfound-page", "zope.interface"] +docs = ["furo", "sphinx", "sphinx-notfound-page", "zope.interface"] +tests = ["cloudpickle", "coverage[toml] (>=5.0.2)", "hypothesis", "mypy", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "six", "zope.interface"] +tests-no-zope = ["cloudpickle", "coverage[toml] (>=5.0.2)", "hypothesis", "mypy", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "six"] 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[[package]] name = "pytest" -version = "6.0.2" +version = "7.2.2" description = "pytest: simple powerful testing with Python" category = "dev" optional = false -python-versions = ">=3.5" +python-versions = ">=3.7" files = [ - {file = "pytest-6.0.2-py3-none-any.whl", hash = "sha256:0e37f61339c4578776e090c3b8f6b16ce4db333889d65d0efb305243ec544b40"}, - {file = "pytest-6.0.2.tar.gz", hash = "sha256:c8f57c2a30983f469bf03e68cdfa74dc474ce56b8f280ddcb080dfd91df01043"}, + {file = "pytest-7.2.2-py3-none-any.whl", hash = "sha256:130328f552dcfac0b1cec75c12e3f005619dc5f874f0a06e8ff7263f0ee6225e"}, + {file = "pytest-7.2.2.tar.gz", hash = "sha256:c99ab0c73aceb050f68929bc93af19ab6db0558791c6a0715723abe9d0ade9d4"}, ] [package.dependencies] -atomicwrites = {version = ">=1.0", markers = "sys_platform == \"win32\""} -attrs = ">=17.4.0" +attrs = ">=19.2.0" colorama = {version = "*", markers = "sys_platform == \"win32\""} +exceptiongroup = {version = ">=1.0.0rc8", markers = "python_version < \"3.11\""} iniconfig = "*" -more-itertools = ">=4.0.0" packaging = "*" -pluggy = ">=0.12,<1.0" -py = ">=1.8.2" -toml = "*" +pluggy = ">=0.12,<2.0" +tomli = {version = ">=1.0.0", markers = "python_version < \"3.11\""} [package.extras] -checkqa-mypy = ["mypy (==0.780)"] -testing = ["argcomplete", "hypothesis (>=3.56)", "mock", "nose", "requests", "xmlschema"] +testing = ["argcomplete", "hypothesis (>=3.56)", "mock", "nose", "pygments (>=2.7.2)", "requests", "xmlschema"] [[package]] name = "pytest-cov" @@ -2973,4 +2949,4 @@ testing = ["func-timeout", "jaraco.itertools", "pytest (>=6)", "pytest-black (>= [metadata] lock-version = "2.0" python-versions = ">=3.8,<3.11" -content-hash = "53567a347be523a08cfbd7f65e1c74e6e9009b7622b685043971cd4e02af915d" +content-hash = "0304f0713d13aaa626a639a75b4def629dc9d5b53f1c47f4f3442f55036e8e62" diff --git a/pyproject.toml b/pyproject.toml index 80ac31818..1eba9aefd 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -103,6 +103,9 @@ setuptools = "^67.6.1" [tool.poetry.dev-dependencies] pytest_cov = "^3.0.0" +[tool.poetry.group.dev.dependencies] +pytest = "^7.2.2" + [build-system] build-backend = "poetry.core.masonry.api" requires = ["poetry-core>=1.0.0"] From b2d5511f721ce14bd089ebf8cd572c6f47646c1b Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 28 Mar 2023 18:25:43 -0300 Subject: [PATCH 009/265] No invalid month --- br_denatran_frota/code/download_frota.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/br_denatran_frota/code/download_frota.py b/br_denatran_frota/code/download_frota.py index d12cd9856..9484725ec 100644 --- a/br_denatran_frota/code/download_frota.py +++ b/br_denatran_frota/code/download_frota.py @@ -28,6 +28,9 @@ def download_frota( month=None, year=None, tempdir=None, dir=None): url = f"https://www.gov.br/infraestrutura/pt-br/assuntos/transito/conteudo-Senatran/frota-de-veiculos-{year}" else: raise ValueError("Utilize a função download_frota_old()") + + if month not in months.values(): + raise ValueError('Mês inválido.') if not tempdir: tempdir = tempfile.gettempdir() From 5ae0b1a91ecb8f98cacf8d15846b065c2731ed0b Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 28 Mar 2023 18:33:36 -0300 Subject: [PATCH 010/265] Tests where I want them. --- br_denatran_frota/code/test/download_frota_test.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/br_denatran_frota/code/test/download_frota_test.py b/br_denatran_frota/code/test/download_frota_test.py index f88ce1e99..d6e71e71d 100644 --- a/br_denatran_frota/code/test/download_frota_test.py +++ b/br_denatran_frota/code/test/download_frota_test.py @@ -24,7 +24,7 @@ def test_download_frota_with_invalid_year(self): download_frota(month=1, year=2010) def test_download_frota_with_invalid_month(self): - with self.assertRaises(HTTPError): + with self.assertRaises(ValueError): download_frota(month=13, year=2022, dir=self.test_dir) def test_download_frota_with_missing_directory(self): From 86bd42318dad2591b8b34dd87bd500f9337dbf3c Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 28 Mar 2023 18:44:54 -0300 Subject: [PATCH 011/265] Black reformat --- br_denatran_frota/code/download_frota.py | 35 +++++++------ poetry.lock | 64 +++++++++++++++++++++++- 2 files changed, 82 insertions(+), 17 deletions(-) diff --git a/br_denatran_frota/code/download_frota.py b/br_denatran_frota/code/download_frota.py index 9484725ec..ead3761d2 100644 --- a/br_denatran_frota/code/download_frota.py +++ b/br_denatran_frota/code/download_frota.py @@ -8,7 +8,7 @@ from collections import defaultdict -def download_frota( month=None, year=None, tempdir=None, dir=None): +def download_frota(month=None, year=None, tempdir=None, dir=None): months = { "janeiro": 1, "fevereiro": 2, @@ -28,9 +28,9 @@ def download_frota( month=None, year=None, tempdir=None, dir=None): url = f"https://www.gov.br/infraestrutura/pt-br/assuntos/transito/conteudo-Senatran/frota-de-veiculos-{year}" else: raise ValueError("Utilize a função download_frota_old()") - + if month not in months.values(): - raise ValueError('Mês inválido.') + raise ValueError("Mês inválido.") if not tempdir: tempdir = tempfile.gettempdir() @@ -78,27 +78,32 @@ def handle_compact(i): os.rename(filepath, dest_path_file) else: os.remove(filepath) - + def download_file(i): - if i['filetype'] in ['rar', 'zip']: + if i["filetype"] in ["rar", "zip"]: handle_compact(i) - elif i['filetype'] in ['xlsx', 'xls']: + elif i["filetype"] in ["xlsx", "xls"]: handle_xl(i) - + soup = BeautifulSoup(urlopen(url), "html.parser") nodes = soup.select("p > a") - - data = defaultdict(list) for node in nodes: txt = node.text - href = node.get('href') - match = re.search(r"(?i)\/([\w-]+)\/(\d{4})\/(\w+)\/([\w-]+)\.(?:xls|xlsx|rar|zip)$", href) + href = node.get("href") + match = re.search( + r"(?i)\/([\w-]+)\/(\d{4})\/(\w+)\/([\w-]+)\.(?:xls|xlsx|rar|zip)$", href + ) if match: matched_month = match.group(3) matched_year = match.group(2) if months.get(matched_month) == month and matched_year == str(year): - filetype = match.group(0).split('.')[-1].lower() - info = {'txt': txt, 'href': href, 'mes_name': matched_month, 'mes': month, 'ano': year, 'filetype': filetype} + filetype = match.group(0).split(".")[-1].lower() + info = { + "txt": txt, + "href": href, + "mes_name": matched_month, + "mes": month, + "ano": year, + "filetype": filetype, + } download_file(info) - -download_frota(year=2022, month = 12) \ No newline at end of file diff --git a/poetry.lock b/poetry.lock index 552c28da8..892fed80a 100644 --- a/poetry.lock +++ b/poetry.lock @@ -80,6 +80,42 @@ soupsieve = ">1.2" html5lib = ["html5lib"] lxml = ["lxml"] +[[package]] +name = "black" +version = "22.12.0" +description = "The uncompromising code formatter." +category = "main" +optional = false +python-versions = ">=3.7" +files = [ + {file = "black-22.12.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9eedd20838bd5d75b80c9f5487dbcb06836a43833a37846cf1d8c1cc01cef59d"}, + {file = 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"sha256:82d9fe8fee3401e02e79767016b4907820a7dc28d70d137eb397b92ef3cc5bfc"}, + {file = "black-22.12.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:101c69b23df9b44247bd88e1d7e90154336ac4992502d4197bdac35dd7ee3320"}, + {file = "black-22.12.0-cp39-cp39-win_amd64.whl", hash = "sha256:559c7a1ba9a006226f09e4916060982fd27334ae1998e7a38b3f33a37f7a2148"}, + {file = "black-22.12.0-py3-none-any.whl", hash = "sha256:436cc9167dd28040ad90d3b404aec22cedf24a6e4d7de221bec2730ec0c97bcf"}, + {file = "black-22.12.0.tar.gz", hash = "sha256:229351e5a18ca30f447bf724d007f890f97e13af070bb6ad4c0a441cd7596a2f"}, +] + +[package.dependencies] +click = ">=8.0.0" +mypy-extensions = ">=0.4.3" +pathspec = ">=0.9.0" +platformdirs = ">=2" +tomli = {version = ">=1.1.0", markers = "python_full_version < \"3.11.0a7\""} +typing-extensions = {version = ">=3.10.0.0", markers = "python_version < \"3.10\""} + +[package.extras] +colorama = ["colorama (>=0.4.3)"] +d = ["aiohttp (>=3.7.4)"] +jupyter = ["ipython (>=7.8.0)", "tokenize-rt (>=3.2.0)"] +uvloop = ["uvloop (>=0.15.2)"] + [[package]] name = "cachetools" version = "4.2.4" @@ -1607,6 +1643,18 @@ toolz = "*" [package.extras] complete = ["blosc", "numpy (>=1.9.0)", "pandas (>=0.19.0)", "pyzmq"] +[[package]] +name = "pathspec" +version = "0.11.1" +description = "Utility library for gitignore style pattern matching of file paths." +category = "main" +optional = false +python-versions = ">=3.7" +files = [ + {file = "pathspec-0.11.1-py3-none-any.whl", hash = "sha256:d8af70af76652554bd134c22b3e8a1cc46ed7d91edcdd721ef1a0c51a84a5293"}, + {file = "pathspec-0.11.1.tar.gz", hash = "sha256:2798de800fa92780e33acca925945e9a19a133b715067cf165b8866c15a31687"}, +] + [[package]] name = "pendulum" version = "2.1.2" @@ -2617,7 +2665,7 @@ files = [ name = "tomli" version = "2.0.1" description = "A lil' TOML parser" -category = "dev" +category = "main" optional = false python-versions = ">=3.7" files = [ @@ -2737,6 +2785,18 @@ dev = ["coveralls (>=2.1.0)", "tox (>=3.14.0)"] socks = ["requests[socks] (>=2.11.1,<3)"] test = ["vcrpy (>=1.10.3)"] +[[package]] +name = "typing-extensions" +version = "4.5.0" +description = "Backported and Experimental Type Hints for Python 3.7+" +category = "main" +optional = false +python-versions = ">=3.7" +files = [ + {file = "typing_extensions-4.5.0-py3-none-any.whl", hash = "sha256:fb33085c39dd998ac16d1431ebc293a8b3eedd00fd4a32de0ff79002c19511b4"}, + {file = "typing_extensions-4.5.0.tar.gz", hash = "sha256:5cb5f4a79139d699607b3ef622a1dedafa84e115ab0024e0d9c044a9479ca7cb"}, +] + [[package]] name = "unidecode" version = "1.3.4" @@ -2949,4 +3009,4 @@ testing = ["func-timeout", "jaraco.itertools", "pytest (>=6)", "pytest-black (>= [metadata] lock-version = "2.0" python-versions = ">=3.8,<3.11" -content-hash = "0304f0713d13aaa626a639a75b4def629dc9d5b53f1c47f4f3442f55036e8e62" +content-hash = "e2ddd4fc39e83bcf7162fa18653c18a75e8f3b7117f990d6c540bca848d06edb" From ac5aeda36e799bcb0006f0868e4f90c27e16d481 Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 28 Mar 2023 20:04:57 -0300 Subject: [PATCH 012/265] Get only frota data (for now) --- br_denatran_frota/code/download_frota.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/br_denatran_frota/code/download_frota.py b/br_denatran_frota/code/download_frota.py index ead3761d2..10a355079 100644 --- a/br_denatran_frota/code/download_frota.py +++ b/br_denatran_frota/code/download_frota.py @@ -86,7 +86,7 @@ def download_file(i): handle_xl(i) soup = BeautifulSoup(urlopen(url), "html.parser") - nodes = soup.select("p > a") + nodes = soup.select("p:contains('Frota por ') > a") for node in nodes: txt = node.text href = node.get("href") From eb4d8338685d0a1773c1529452964c5aeb1324d6 Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 28 Mar 2023 20:21:13 -0300 Subject: [PATCH 013/265] Begin encapsulation + documentation --- br_denatran_frota/code/download_frota.py | 39 ++++++++++++++++-------- 1 file changed, 26 insertions(+), 13 deletions(-) diff --git a/br_denatran_frota/code/download_frota.py b/br_denatran_frota/code/download_frota.py index 10a355079..91196b825 100644 --- a/br_denatran_frota/code/download_frota.py +++ b/br_denatran_frota/code/download_frota.py @@ -8,7 +8,28 @@ from collections import defaultdict -def download_frota(month=None, year=None, tempdir=None, dir=None): +def make_filename(i: dict, ext: bool = True) -> str: + """Cria o nome do arquivo usando o dicionário enviado. + + Args: + i (dict): Dicionário com todas as informações do arquivo. + ext (bool, optional): Especifica se o nome de arquivo gerado precisa do tipo de arquivo no fim. Defaults to True. + + Returns: + str: O nome completo do arquivo. + """ + txt = i["txt"] + mes = i["mes"] + ano = i["ano"] + filetype = i["filetype"] + filename = re.sub("\\s+", "_", txt, flags=re.UNICODE).lower() + filename = f"{filename}_{mes}-{ano}" + if ext: + filename += f".{filetype}" + return filename + + +def download_frota(month: int = None, year: int = None, tempdir=None, dir=None): months = { "janeiro": 1, "fevereiro": 2, @@ -27,7 +48,7 @@ def download_frota(month=None, year=None, tempdir=None, dir=None): if year > 2012: url = f"https://www.gov.br/infraestrutura/pt-br/assuntos/transito/conteudo-Senatran/frota-de-veiculos-{year}" else: - raise ValueError("Utilize a função download_frota_old()") + raise ValueError("Para anos anteriores eu não implementei a função ainda.") if month not in months.values(): raise ValueError("Mês inválido.") @@ -37,17 +58,6 @@ def download_frota(month=None, year=None, tempdir=None, dir=None): if not dir: dir = os.getcwd() - def make_filename(i, ext=True): - txt = i["txt"] - mes = i["mes"] - ano = i["ano"] - filetype = i["filetype"] - filename = re.sub("\\s+", "_", txt, flags=re.UNICODE).lower() - filename = f"{filename}_{mes}-{ano}" - if ext: - filename += f".{filetype}" - return filename - def handle_xl(i): dest_path_file = os.path.join(dir, f"{i['mes']}-{i['ano']}.{i['filetype']}") if not os.path.isfile(dest_path_file): @@ -107,3 +117,6 @@ def download_file(i): "filetype": filetype, } download_file(info) + + +download_frota(year=2022, month=2) From d7f5445534765fedf45b6f3e5eb457112be9c58c Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 28 Mar 2023 20:36:55 -0300 Subject: [PATCH 014/265] Better and cleaner code --- br_denatran_frota/code/download_frota.py | 87 ++++++++++--------- .../code/test/download_frota_test.py | 14 +-- 2 files changed, 53 insertions(+), 48 deletions(-) diff --git a/br_denatran_frota/code/download_frota.py b/br_denatran_frota/code/download_frota.py index 91196b825..e68379470 100644 --- a/br_denatran_frota/code/download_frota.py +++ b/br_denatran_frota/code/download_frota.py @@ -5,7 +5,41 @@ from zipfile import ZipFile from rarfile import RarFile from bs4 import BeautifulSoup -from collections import defaultdict + + +def handle_xl(i: dict): + tempdir = i["tempdir"] + dest_path_file = os.path.join(tempdir, make_filename(i)) + if not os.path.isfile(dest_path_file): + urlretrieve(i["href"], dest_path_file) + + +def handle_compact(i: dict): + tempdir = i["tempdir"] + path_file_zip = os.path.join(tempdir, make_filename(i)) + dir_file = os.path.join(tempdir, make_filename(i, ext=False)) + + if not os.path.isfile(path_file_zip): + urlretrieve(i["href"], path_file_zip) + + if i["filetype"] == "rar": + with RarFile(path_file_zip) as rar_file: + rar_file.extractall(dir_file) + else: + with ZipFile(path_file_zip) as zip_file: + zip_file.extractall(dir_file) + + for filename in os.listdir(dir_file): + filepath = os.path.join(dir_file, filename) + if os.path.isfile(filepath): + if filename.endswith((".xlsx", ".xls")): + dest_path_file = os.path.join( + dir_name, f"{i['mes']}-{i['ano']}.{filename.split('.')[-1]}" + ) + if not os.path.isfile(dest_path_file): + os.rename(filepath, dest_path_file) + else: + os.remove(filepath) def make_filename(i: dict, ext: bool = True) -> str: @@ -29,7 +63,14 @@ def make_filename(i: dict, ext: bool = True) -> str: return filename -def download_frota(month: int = None, year: int = None, tempdir=None, dir=None): +def download_file(i): + if i["filetype"] in ["rar", "zip"]: + handle_compact(i) + elif i["filetype"] in ["xlsx", "xls"]: + handle_xl(i) + + +def download_frota(month: int = None, year: int = None, tempdir=None, dir_name=None): months = { "janeiro": 1, "fevereiro": 2, @@ -55,45 +96,8 @@ def download_frota(month: int = None, year: int = None, tempdir=None, dir=None): if not tempdir: tempdir = tempfile.gettempdir() - if not dir: - dir = os.getcwd() - - def handle_xl(i): - dest_path_file = os.path.join(dir, f"{i['mes']}-{i['ano']}.{i['filetype']}") - if not os.path.isfile(dest_path_file): - urlretrieve(i["href"], dest_path_file) - - def handle_compact(i): - path_file_zip = os.path.join(tempdir, make_filename(i)) - dir_file = os.path.join(tempdir, make_filename(i, ext=False)) - - if not os.path.isfile(path_file_zip): - urlretrieve(i["href"], path_file_zip) - - if i["filetype"] == "rar": - with RarFile(path_file_zip) as rar_file: - rar_file.extractall(dir_file) - else: - with ZipFile(path_file_zip) as zip_file: - zip_file.extractall(dir_file) - - for filename in os.listdir(dir_file): - filepath = os.path.join(dir_file, filename) - if os.path.isfile(filepath): - if filename.endswith((".xlsx", ".xls")): - dest_path_file = os.path.join( - dir, f"{i['mes']}-{i['ano']}.{filename.split('.')[-1]}" - ) - if not os.path.isfile(dest_path_file): - os.rename(filepath, dest_path_file) - else: - os.remove(filepath) - - def download_file(i): - if i["filetype"] in ["rar", "zip"]: - handle_compact(i) - elif i["filetype"] in ["xlsx", "xls"]: - handle_xl(i) + if not dir_name: + dir_name = os.getcwd() soup = BeautifulSoup(urlopen(url), "html.parser") nodes = soup.select("p:contains('Frota por ') > a") @@ -115,6 +119,7 @@ def download_file(i): "mes": month, "ano": year, "filetype": filetype, + "tempdir": tempdir, } download_file(info) diff --git a/br_denatran_frota/code/test/download_frota_test.py b/br_denatran_frota/code/test/download_frota_test.py index d6e71e71d..1a6dddc39 100644 --- a/br_denatran_frota/code/test/download_frota_test.py +++ b/br_denatran_frota/code/test/download_frota_test.py @@ -7,7 +7,6 @@ class TestDownloadFrota(unittest.TestCase): - def setUp(self): self.test_dir = tempfile.mkdtemp() @@ -15,8 +14,8 @@ def tearDown(self): os.rmdir(self.test_dir) def test_download_frota_with_valid_args(self): - with patch('urllib.request.urlretrieve') as mock_urlretrieve: - download_frota(month=2, year=2022, dir=self.test_dir) + with patch("urllib.request.urlretrieve") as mock_urlretrieve: + download_frota(month=2, year=2022, dir_name=self.test_dir) mock_urlretrieve.assert_called_once() def test_download_frota_with_invalid_year(self): @@ -25,15 +24,16 @@ def test_download_frota_with_invalid_year(self): def test_download_frota_with_invalid_month(self): with self.assertRaises(ValueError): - download_frota(month=13, year=2022, dir=self.test_dir) + download_frota(month=13, year=2022, dir_name=self.test_dir) def test_download_frota_with_missing_directory(self): with self.assertRaises(FileNotFoundError): - download_frota(month=1, year=2022, dir='invalid_directory') + download_frota(month=1, year=2022, dir_name="invalid_directory") def test_download_frota_with_missing_temp_directory(self): with self.assertRaises(FileNotFoundError): - download_frota(month=1, year=2022, tempdir='invalid_directory') + download_frota(month=1, year=2022, tempdir="invalid_directory") + -if __name__ == '__main__': +if __name__ == "__main__": unittest.main() From 9cd6d486192fb5a840f40110682656f5bf62e412 Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 28 Mar 2023 20:45:24 -0300 Subject: [PATCH 015/265] More cleanup. Compact is not useful as of now --- br_denatran_frota/code/download_frota.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/br_denatran_frota/code/download_frota.py b/br_denatran_frota/code/download_frota.py index e68379470..265b2f551 100644 --- a/br_denatran_frota/code/download_frota.py +++ b/br_denatran_frota/code/download_frota.py @@ -33,9 +33,7 @@ def handle_compact(i: dict): filepath = os.path.join(dir_file, filename) if os.path.isfile(filepath): if filename.endswith((".xlsx", ".xls")): - dest_path_file = os.path.join( - dir_name, f"{i['mes']}-{i['ano']}.{filename.split('.')[-1]}" - ) + dest_path_file = os.path.join(tempdir, make_filename(i)) if not os.path.isfile(dest_path_file): os.rename(filepath, dest_path_file) else: @@ -100,10 +98,12 @@ def download_frota(month: int = None, year: int = None, tempdir=None, dir_name=N dir_name = os.getcwd() soup = BeautifulSoup(urlopen(url), "html.parser") + # Só queremos os dados de frota nacional. nodes = soup.select("p:contains('Frota por ') > a") for node in nodes: txt = node.text href = node.get("href") + # Pega a parte relevante do arquivo em questão. match = re.search( r"(?i)\/([\w-]+)\/(\d{4})\/(\w+)\/([\w-]+)\.(?:xls|xlsx|rar|zip)$", href ) From 46f3c2c03a126d78676f224e16ddb4f480e824ac Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 28 Mar 2023 21:06:26 -0300 Subject: [PATCH 016/265] Clean and good python code. --- br_denatran_frota/code/download_frota.py | 34 +++++++++++++++++------- 1 file changed, 25 insertions(+), 9 deletions(-) diff --git a/br_denatran_frota/code/download_frota.py b/br_denatran_frota/code/download_frota.py index 265b2f551..6919ac70c 100644 --- a/br_denatran_frota/code/download_frota.py +++ b/br_denatran_frota/code/download_frota.py @@ -7,9 +7,17 @@ from bs4 import BeautifulSoup -def handle_xl(i: dict): - tempdir = i["tempdir"] - dest_path_file = os.path.join(tempdir, make_filename(i)) +def handle_xl(i: dict) -> None: + """Efetivamente baixa e lida com arquivos excel. + + Args: + i (dict): Dicionário com as informações do arquivo a ser baixado. + """ + dir_name = os.getcwd() + # TODO: Isso aqui NÃO ESTÁ muito limpo ou genérico, e não sei onde deveriam ficar os arquivos por hora. + dest_path_file = os.path.join( + dir_name, "br_denatran_frota", "files", make_filename(i) + ) if not os.path.isfile(dest_path_file): urlretrieve(i["href"], dest_path_file) @@ -62,13 +70,23 @@ def make_filename(i: dict, ext: bool = True) -> str: def download_file(i): - if i["filetype"] in ["rar", "zip"]: - handle_compact(i) - elif i["filetype"] in ["xlsx", "xls"]: + if i["filetype"] in ["xlsx", "xls"]: handle_xl(i) + else: + raise ValueError("A função handle_compact tá bem esquisita por hora.") -def download_frota(month: int = None, year: int = None, tempdir=None, dir_name=None): +def download_frota(month: int, year: int): + """Função principal para baixar os dados de frota por município e tipo e também por UF e tipo. + + Args: + month (int): Mês desejado. + year (int): Ano desejado. + + Raises: + ValueError: Dá erro caso o ano desejado seja anterior ao que a função consegue no momento. + ValueError: Dá erro caso o mês desejado não seja um mês válido. + """ months = { "janeiro": 1, "fevereiro": 2, @@ -94,8 +112,6 @@ def download_frota(month: int = None, year: int = None, tempdir=None, dir_name=N if not tempdir: tempdir = tempfile.gettempdir() - if not dir_name: - dir_name = os.getcwd() soup = BeautifulSoup(urlopen(url), "html.parser") # Só queremos os dados de frota nacional. From 2bba044474ec973f9f61ad101c3e6858802292e4 Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 28 Mar 2023 21:08:36 -0300 Subject: [PATCH 017/265] More cleanup after the cleanup --- br_denatran_frota/code/download_frota.py | 4 ---- br_denatran_frota/code/test/download_frota_test.py | 12 ++---------- 2 files changed, 2 insertions(+), 14 deletions(-) diff --git a/br_denatran_frota/code/download_frota.py b/br_denatran_frota/code/download_frota.py index 6919ac70c..e4dbff033 100644 --- a/br_denatran_frota/code/download_frota.py +++ b/br_denatran_frota/code/download_frota.py @@ -110,9 +110,6 @@ def download_frota(month: int, year: int): if month not in months.values(): raise ValueError("Mês inválido.") - if not tempdir: - tempdir = tempfile.gettempdir() - soup = BeautifulSoup(urlopen(url), "html.parser") # Só queremos os dados de frota nacional. nodes = soup.select("p:contains('Frota por ') > a") @@ -135,7 +132,6 @@ def download_frota(month: int, year: int): "mes": month, "ano": year, "filetype": filetype, - "tempdir": tempdir, } download_file(info) diff --git a/br_denatran_frota/code/test/download_frota_test.py b/br_denatran_frota/code/test/download_frota_test.py index 1a6dddc39..6c258a2f9 100644 --- a/br_denatran_frota/code/test/download_frota_test.py +++ b/br_denatran_frota/code/test/download_frota_test.py @@ -15,7 +15,7 @@ def tearDown(self): def test_download_frota_with_valid_args(self): with patch("urllib.request.urlretrieve") as mock_urlretrieve: - download_frota(month=2, year=2022, dir_name=self.test_dir) + download_frota(month=2, year=2022) mock_urlretrieve.assert_called_once() def test_download_frota_with_invalid_year(self): @@ -24,15 +24,7 @@ def test_download_frota_with_invalid_year(self): def test_download_frota_with_invalid_month(self): with self.assertRaises(ValueError): - download_frota(month=13, year=2022, dir_name=self.test_dir) - - def test_download_frota_with_missing_directory(self): - with self.assertRaises(FileNotFoundError): - download_frota(month=1, year=2022, dir_name="invalid_directory") - - def test_download_frota_with_missing_temp_directory(self): - with self.assertRaises(FileNotFoundError): - download_frota(month=1, year=2022, tempdir="invalid_directory") + download_frota(month=13, year=2022) if __name__ == "__main__": From 5bb9ce6fd8985754123e92bfebb3d1fb758e2474 Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 28 Mar 2023 21:10:30 -0300 Subject: [PATCH 018/265] Remove line for testing --- br_denatran_frota/code/download_frota.py | 3 --- 1 file changed, 3 deletions(-) diff --git a/br_denatran_frota/code/download_frota.py b/br_denatran_frota/code/download_frota.py index e4dbff033..7596b899e 100644 --- a/br_denatran_frota/code/download_frota.py +++ b/br_denatran_frota/code/download_frota.py @@ -134,6 +134,3 @@ def download_frota(month: int, year: int): "filetype": filetype, } download_file(info) - - -download_frota(year=2022, month=2) From b520f2dc0793fe2a0dabd789122bc3d3aa96305a Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 28 Mar 2023 21:41:06 -0300 Subject: [PATCH 019/265] Working (badly) tests --- br_denatran_frota/code/test/download_frota_test.py | 14 +++++++++++--- 1 file changed, 11 insertions(+), 3 deletions(-) diff --git a/br_denatran_frota/code/test/download_frota_test.py b/br_denatran_frota/code/test/download_frota_test.py index 6c258a2f9..93ca1b9e0 100644 --- a/br_denatran_frota/code/test/download_frota_test.py +++ b/br_denatran_frota/code/test/download_frota_test.py @@ -14,9 +14,17 @@ def tearDown(self): os.rmdir(self.test_dir) def test_download_frota_with_valid_args(self): - with patch("urllib.request.urlretrieve") as mock_urlretrieve: - download_frota(month=2, year=2022) - mock_urlretrieve.assert_called_once() + # TODO: Since there is no teardown, this test doesn't have the same effect running twice. + # It could always download the file twice in download_frota OR we implement cleanup? + # Or we generalize with tempd irs. This might just be overkill anyway. + download_frota(month=2, year=2022) + expected_file_path = os.path.join( + os.getcwd(), + "br_denatran_frota", + "files", + "frota_por_município_e_tipo_2-2022.xls", + ) + self.assertTrue(os.path.isfile(expected_file_path)) def test_download_frota_with_invalid_year(self): with self.assertRaises(ValueError): From c0eaac008cfbe1de992324b68cfc007f8d6e0faf Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 29 Mar 2023 17:24:47 -0300 Subject: [PATCH 020/265] Improving code quality --- br_denatran_frota/code/download_frota.py | 3 +-- br_denatran_frota/code/test/download_frota_test.py | 10 +++++----- 2 files changed, 6 insertions(+), 7 deletions(-) diff --git a/br_denatran_frota/code/download_frota.py b/br_denatran_frota/code/download_frota.py index 7596b899e..a9e77d478 100644 --- a/br_denatran_frota/code/download_frota.py +++ b/br_denatran_frota/code/download_frota.py @@ -18,8 +18,7 @@ def handle_xl(i: dict) -> None: dest_path_file = os.path.join( dir_name, "br_denatran_frota", "files", make_filename(i) ) - if not os.path.isfile(dest_path_file): - urlretrieve(i["href"], dest_path_file) + urlretrieve(i["href"], dest_path_file) def handle_compact(i: dict): diff --git a/br_denatran_frota/code/test/download_frota_test.py b/br_denatran_frota/code/test/download_frota_test.py index 93ca1b9e0..27a83bd8c 100644 --- a/br_denatran_frota/code/test/download_frota_test.py +++ b/br_denatran_frota/code/test/download_frota_test.py @@ -14,15 +14,15 @@ def tearDown(self): os.rmdir(self.test_dir) def test_download_frota_with_valid_args(self): - # TODO: Since there is no teardown, this test doesn't have the same effect running twice. - # It could always download the file twice in download_frota OR we implement cleanup? - # Or we generalize with tempd irs. This might just be overkill anyway. - download_frota(month=2, year=2022) + # TODO: This is always assuming a structure of having a files dir under the denatran directory... + month = 2 + year = 2022 + download_frota(month, year) expected_file_path = os.path.join( os.getcwd(), "br_denatran_frota", "files", - "frota_por_município_e_tipo_2-2022.xls", + f"frota_por_município_e_tipo_{month}-{year}.xls", ) self.assertTrue(os.path.isfile(expected_file_path)) From 3365cc18a0f7911b2cd31a2c7c14abf3c7ddda4a Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 29 Mar 2023 17:34:52 -0300 Subject: [PATCH 021/265] Start translating pre-2012 data --- br_denatran_frota/code/download_frota_old.py | 104 ++++++++++++++++++ .../code/test/download_frota_old_test.py | 30 +++++ 2 files changed, 134 insertions(+) create mode 100644 br_denatran_frota/code/download_frota_old.py create mode 100644 br_denatran_frota/code/test/download_frota_old_test.py diff --git a/br_denatran_frota/code/download_frota_old.py b/br_denatran_frota/code/download_frota_old.py new file mode 100644 index 000000000..184d7707d --- /dev/null +++ b/br_denatran_frota/code/download_frota_old.py @@ -0,0 +1,104 @@ +import os +import re +import requests +from zipfile import ZipFile +import shutil + + +def download_frota_old(key=None, prefix=None, year=None, tempdir=None, dir=None): + def create_directory(path): + if not os.path.exists(path): + os.makedirs(path) + + def extract_files_from_zip(zip_file, extract_path): + with ZipFile(zip_file, "r") as zip: + zip.extractall(extract_path) + + if year > 2012: + raise ValueError("Utilize download_frota()") + + mi_url = f"https://www.gov.br/infraestrutura/pt-br/assuntos/transito/arquivos-denatran/estatisticas/renavam/{year}/frota{'_' if year > 2008 else ''}{year}.zip" + + create_directory(tempdir) + create_directory(dir) + + dir_temp = os.path.join(tempdir, f"frota__{year}") + path_file = os.path.join(dir_temp, ".zip") + + if not os.path.exists(path_file): + try: + response = requests.get(mi_url) + with open(path_file, "wb") as f: + f.write(response.content) + except Exception as e: + if os.path.exists(path_file): + os.remove(path_file) + + extract_files_from_zip(path_file, dir_temp) + + months = { + "jan": 1, + "fev": 2, + "mar": 3, + "abr": 4, + "mai": 5, + "jun": 6, + "jul": 7, + "ago": 8, + "set": 9, + "out": 10, + "nov": 11, + "dez": 12, + } + + for root, dirs, files in os.walk(dir_temp): + for name in files: + if name.endswith(".zip"): + extract_files_from_zip( + os.path.join(root, name), os.path.dirname(os.path.join(root, name)) + ) + + for root, dirs, files in os.walk(dir_temp): + for name in files: + file_path = os.path.join(root, name) + + get_by = { + "regiao": "(frota tipo uf)|(frota uf)|(frota regiao uf)|(frota regiao tipo uf)", + "municipio": "(frota munic)|(frota mun)", + } + + new_name = ( + os.path.basename(file_path) + .lower() + .replace("regiões", "regiao") + .replace("_", " ") + .replace("-", " ") + .replace(".xlsx", "") + .replace(".xls", "") + .replace("internet", "") + .strip() + ) + new_name = re.sub(r"^(\\d\\_|\\d)+", "", new_name) + + # Match jan|fev|... or number of month (two digits) + get_month = re.search( + rf"({'|'.join(months.keys())})|\d{{2}}(?=\d{{4}})", + new_name, + re.IGNORECASE, + ) + if get_month: + month_i = int(get_month.group(0)) + if get_month.group(1): + month_i = months[get_month.group(1)] + + file_ext = re.search(r"\.[a-zA-Z0-9]+$", new_name).group(0) + + if ( + key + and prefix + and re.search(get_by[key], new_name, re.IGNORECASE) + and name.endswith(("xls", "xlsx")) + ): + shutil.copy( + file_path, os.path.join(dir, f"{prefix}_{month_i}-{year}{file_ext}") + ) diff --git a/br_denatran_frota/code/test/download_frota_old_test.py b/br_denatran_frota/code/test/download_frota_old_test.py new file mode 100644 index 000000000..affee1619 --- /dev/null +++ b/br_denatran_frota/code/test/download_frota_old_test.py @@ -0,0 +1,30 @@ +import os +import shutil +import tempfile +import unittest + +from download_frota_old import download_frota_old + + +class TestDownloadFrotaOld(unittest.TestCase): + def setUp(self): + self.temp_dir = tempfile.mkdtemp() + self.dir = os.getcwd() + + def tearDown(self): + shutil.rmtree(self.temp_dir) + os.chdir(self.dir) + + def test_download_frota_old(self): + download_frota_old(year=2009, tempdir=self.temp_dir, dir=self.dir) + self.assertTrue(os.path.exists(os.path.join(self.dir, "frota_12-2009.xlsx"))) + self.assertTrue(os.path.exists(os.path.join(self.dir, "frota_1-2009.xlsx"))) + self.assertTrue(os.path.exists(os.path.join(self.dir, "frota_2-2009.xlsx"))) + + def test_download_frota_old_year_above_2012(self): + with self.assertRaises(ValueError): + download_frota_old(year=2013, tempdir=self.temp_dir, dir=self.dir) + + +if __name__ == "__main__": + unittest.main() From 988f35de59c0075f2795d65fb3b2fb41f9fa127a Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 29 Mar 2023 18:21:40 -0300 Subject: [PATCH 022/265] Break down into individual functions: beg --- br_denatran_frota/code/download_frota_old.py | 17 ++++++++++------- 1 file changed, 10 insertions(+), 7 deletions(-) diff --git a/br_denatran_frota/code/download_frota_old.py b/br_denatran_frota/code/download_frota_old.py index 184d7707d..ed5c15d88 100644 --- a/br_denatran_frota/code/download_frota_old.py +++ b/br_denatran_frota/code/download_frota_old.py @@ -5,14 +5,17 @@ import shutil -def download_frota_old(key=None, prefix=None, year=None, tempdir=None, dir=None): - def create_directory(path): - if not os.path.exists(path): - os.makedirs(path) +def create_directory(path): + if not os.path.exists(path): + os.makedirs(path) + + +def extract_files_from_zip(zip_file, extract_path): + with ZipFile(zip_file, "r") as zip: + zip.extractall(extract_path) - def extract_files_from_zip(zip_file, extract_path): - with ZipFile(zip_file, "r") as zip: - zip.extractall(extract_path) + +def download_frota_old(key=None, prefix=None, year=None, tempdir=None, dir=None): if year > 2012: raise ValueError("Utilize download_frota()") From 7fc3888b29e46862dc1bc628491ccc25aee3b7f9 Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 2 Apr 2023 02:09:16 -0300 Subject: [PATCH 023/265] Wrong url fixed, download not well done yet --- br_denatran_frota/code/download_frota_old.py | 33 ++++++++++---------- 1 file changed, 16 insertions(+), 17 deletions(-) diff --git a/br_denatran_frota/code/download_frota_old.py b/br_denatran_frota/code/download_frota_old.py index ed5c15d88..1ce4fe19c 100644 --- a/br_denatran_frota/code/download_frota_old.py +++ b/br_denatran_frota/code/download_frota_old.py @@ -4,6 +4,21 @@ from zipfile import ZipFile import shutil +months = { + "jan": 1, + "fev": 2, + "mar": 3, + "abr": 4, + "mai": 5, + "jun": 6, + "jul": 7, + "ago": 8, + "set": 9, + "out": 10, + "nov": 11, + "dez": 12, +} + def create_directory(path): if not os.path.exists(path): @@ -20,8 +35,7 @@ def download_frota_old(key=None, prefix=None, year=None, tempdir=None, dir=None) if year > 2012: raise ValueError("Utilize download_frota()") - mi_url = f"https://www.gov.br/infraestrutura/pt-br/assuntos/transito/arquivos-denatran/estatisticas/renavam/{year}/frota{'_' if year > 2008 else ''}{year}.zip" - + mi_url = f"https://www.gov.br/infraestrutura/pt-br/assuntos/transito/arquivos-senatran/estatisticas/renavam/{year}/frota{'_' if year > 2008 else ''}{year}.zip" create_directory(tempdir) create_directory(dir) @@ -39,21 +53,6 @@ def download_frota_old(key=None, prefix=None, year=None, tempdir=None, dir=None) extract_files_from_zip(path_file, dir_temp) - months = { - "jan": 1, - "fev": 2, - "mar": 3, - "abr": 4, - "mai": 5, - "jun": 6, - "jul": 7, - "ago": 8, - "set": 9, - "out": 10, - "nov": 11, - "dez": 12, - } - for root, dirs, files in os.walk(dir_temp): for name in files: if name.endswith(".zip"): From 97d1fbe9a33f19448e19ec7bdfe9d5e27332d40e Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 4 Apr 2023 20:30:08 -0300 Subject: [PATCH 024/265] Significant improvements to post 2012 data --- br_denatran_frota/code/download_frota.py | 126 ++++++++++++------ .../code/test/download_frota_test.py | 6 - 2 files changed, 82 insertions(+), 50 deletions(-) diff --git a/br_denatran_frota/code/download_frota.py b/br_denatran_frota/code/download_frota.py index a9e77d478..891c6c739 100644 --- a/br_denatran_frota/code/download_frota.py +++ b/br_denatran_frota/code/download_frota.py @@ -1,23 +1,37 @@ import os import re -import tempfile +import glob from urllib.request import urlopen, urlretrieve from zipfile import ZipFile from rarfile import RarFile from bs4 import BeautifulSoup +MONTHS = { + "janeiro": 1, + "fevereiro": 2, + "marco": 3, + "abril": 4, + "maio": 5, + "junho": 6, + "julho": 7, + "agosto": 8, + "setembro": 9, + "outubro": 10, + "novembro": 11, + "dezembro": 12, +} + +DATASET = "br_denatran_frota" + + def handle_xl(i: dict) -> None: - """Efetivamente baixa e lida com arquivos excel. + """Actually downloads and deals with Excel files. Args: - i (dict): Dicionário com as informações do arquivo a ser baixado. + i (dict): Dictionary with all the desired downloadable file's info. """ - dir_name = os.getcwd() - # TODO: Isso aqui NÃO ESTÁ muito limpo ou genérico, e não sei onde deveriam ficar os arquivos por hora. - dest_path_file = os.path.join( - dir_name, "br_denatran_frota", "files", make_filename(i) - ) + dest_path_file = make_filename(i) urlretrieve(i["href"], dest_path_file) @@ -48,14 +62,14 @@ def handle_compact(i: dict): def make_filename(i: dict, ext: bool = True) -> str: - """Cria o nome do arquivo usando o dicionário enviado. + """Creates the filename using the sent dictionary. Args: - i (dict): Dicionário com todas as informações do arquivo. - ext (bool, optional): Especifica se o nome de arquivo gerado precisa do tipo de arquivo no fim. Defaults to True. + i (dict): Dictionary with all the file's info. + ext (bool, optional): Specifies if the generated file name needs the filetype at the end. Defaults to True. Returns: - str: O nome completo do arquivo. + str: The full filename. """ txt = i["txt"] mes = i["mes"] @@ -75,40 +89,14 @@ def download_file(i): raise ValueError("A função handle_compact tá bem esquisita por hora.") -def download_frota(month: int, year: int): - """Função principal para baixar os dados de frota por município e tipo e também por UF e tipo. +def download_post_2012(year: int, month: int): + """_summary_ Args: - month (int): Mês desejado. - year (int): Ano desejado. - - Raises: - ValueError: Dá erro caso o ano desejado seja anterior ao que a função consegue no momento. - ValueError: Dá erro caso o mês desejado não seja um mês válido. + year (int): _description_ + month (int): _description_ """ - months = { - "janeiro": 1, - "fevereiro": 2, - "marco": 3, - "abril": 4, - "maio": 5, - "junho": 6, - "julho": 7, - "agosto": 8, - "setembro": 9, - "outubro": 10, - "novembro": 11, - "dezembro": 12, - } - - if year > 2012: - url = f"https://www.gov.br/infraestrutura/pt-br/assuntos/transito/conteudo-Senatran/frota-de-veiculos-{year}" - else: - raise ValueError("Para anos anteriores eu não implementei a função ainda.") - - if month not in months.values(): - raise ValueError("Mês inválido.") - + url = f"https://www.gov.br/infraestrutura/pt-br/assuntos/transito/conteudo-Senatran/frota-de-veiculos-{year}" soup = BeautifulSoup(urlopen(url), "html.parser") # Só queremos os dados de frota nacional. nodes = soup.select("p:contains('Frota por ') > a") @@ -122,7 +110,7 @@ def download_frota(month: int, year: int): if match: matched_month = match.group(3) matched_year = match.group(2) - if months.get(matched_month) == month and matched_year == str(year): + if MONTHS.get(matched_month) == month and matched_year == str(year): filetype = match.group(0).split(".")[-1].lower() info = { "txt": txt, @@ -133,3 +121,53 @@ def download_frota(month: int, year: int): "filetype": filetype, } download_file(info) + + +def make_dir_when_not_exists(dir_name: str): + """Auxiliary function to create a subdirectory when it is not present. + + Args: + dir_name (str): Name of the subdirectory to be created. + """ + if not os.path.exists(dir_name): + os.mkdir(dir_name) + + +def download_frota(month: int, year: int): + """Função principal para baixar os dados de frota por município e tipo e também por UF e tipo. + + Args: + month (int): Mês desejado. + year (int): Ano desejado. + + Raises: + ValueError: Dá erro caso o mês desejado não seja um mês válido. + """ + + if month not in MONTHS.values(): + raise ValueError("Mês inválido.") + + dir_list = glob.glob(f"**/{DATASET}", recursive=True) + if dir_list: + # I always want to be in the actual folder for this dataset: + os.chdir(dir_list[0]) + + # I always need a files directory inside my dataset folder. + make_dir_when_not_exists("files") + year_dir_name = f"{year}" + desired_dir_name = os.path.join("files", year_dir_name) + + # Cria pasta para aquele ano de arquivos caso seja necessário. + make_dir_when_not_exists(desired_dir_name) + os.chdir(desired_dir_name) + if year > 2012: + download_post_2012(year, month) + else: + url = f"https://www.gov.br/infraestrutura/pt-br/assuntos/transito/arquivos-senatran/estatisticas/renavam/{year}/frota{'_' if year > 2008 else ''}{year}.zip" + + generic_zip_filename = f"geral_{year}.zip" + urlretrieve(url, generic_zip_filename) + with ZipFile(generic_zip_filename) as zip_file: + zip_file.extractall() + + print(2) diff --git a/br_denatran_frota/code/test/download_frota_test.py b/br_denatran_frota/code/test/download_frota_test.py index 27a83bd8c..9495132b9 100644 --- a/br_denatran_frota/code/test/download_frota_test.py +++ b/br_denatran_frota/code/test/download_frota_test.py @@ -20,16 +20,10 @@ def test_download_frota_with_valid_args(self): download_frota(month, year) expected_file_path = os.path.join( os.getcwd(), - "br_denatran_frota", - "files", f"frota_por_município_e_tipo_{month}-{year}.xls", ) self.assertTrue(os.path.isfile(expected_file_path)) - def test_download_frota_with_invalid_year(self): - with self.assertRaises(ValueError): - download_frota(month=1, year=2010) - def test_download_frota_with_invalid_month(self): with self.assertRaises(ValueError): download_frota(month=13, year=2022) From 2340f2bd22e0037cc6d84d106a23cb9c848906a3 Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 5 Apr 2023 05:41:54 -0300 Subject: [PATCH 025/265] Add coverage --- poetry.lock | 950 +++++++++++++++++++++++++------------------------ pyproject.toml | 1 + 2 files changed, 481 insertions(+), 470 deletions(-) diff --git a/poetry.lock b/poetry.lock index 892fed80a..6c8e85754 100644 --- a/poetry.lock +++ b/poetry.lock @@ -14,21 +14,22 @@ files = [ [[package]] name = "attrs" -version = "21.4.0" +version = "22.2.0" description = "Classes Without Boilerplate" category = "dev" optional = false -python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" +python-versions = ">=3.6" files = [ - {file = "attrs-21.4.0-py2.py3-none-any.whl", hash = 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-from download_frota_old import download_frota_old - - -class TestDownloadFrotaOld(unittest.TestCase): - def setUp(self): - self.temp_dir = tempfile.mkdtemp() - self.dir = os.getcwd() - - def tearDown(self): - shutil.rmtree(self.temp_dir) - os.chdir(self.dir) - - def test_download_frota_old(self): - download_frota_old(year=2009, tempdir=self.temp_dir, dir=self.dir) - self.assertTrue(os.path.exists(os.path.join(self.dir, "frota_12-2009.xlsx"))) - self.assertTrue(os.path.exists(os.path.join(self.dir, "frota_1-2009.xlsx"))) - self.assertTrue(os.path.exists(os.path.join(self.dir, "frota_2-2009.xlsx"))) - - def test_download_frota_old_year_above_2012(self): - with self.assertRaises(ValueError): - download_frota_old(year=2013, tempdir=self.temp_dir, dir=self.dir) - - -if __name__ == "__main__": - unittest.main() From e7bfcb06075231b075aa9d1a63a045b67734ad12 Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 5 Apr 2023 05:44:42 -0300 Subject: [PATCH 027/265] No need for a separate file now --- br_denatran_frota/code/download_frota_old.py | 106 ------------------- 1 file changed, 106 deletions(-) delete mode 100644 br_denatran_frota/code/download_frota_old.py diff --git a/br_denatran_frota/code/download_frota_old.py b/br_denatran_frota/code/download_frota_old.py deleted file mode 100644 index 1ce4fe19c..000000000 --- a/br_denatran_frota/code/download_frota_old.py +++ /dev/null @@ -1,106 +0,0 @@ -import os -import re -import requests -from zipfile import ZipFile -import shutil - -months = { - "jan": 1, - "fev": 2, - "mar": 3, - "abr": 4, - "mai": 5, - "jun": 6, - "jul": 7, - "ago": 8, - "set": 9, - "out": 10, - "nov": 11, - "dez": 12, -} - - -def create_directory(path): - if not os.path.exists(path): - os.makedirs(path) - - -def extract_files_from_zip(zip_file, extract_path): - with ZipFile(zip_file, "r") as zip: - zip.extractall(extract_path) - - -def download_frota_old(key=None, prefix=None, year=None, tempdir=None, dir=None): - - if year > 2012: - raise ValueError("Utilize download_frota()") - - mi_url = f"https://www.gov.br/infraestrutura/pt-br/assuntos/transito/arquivos-senatran/estatisticas/renavam/{year}/frota{'_' if year > 2008 else ''}{year}.zip" - create_directory(tempdir) - create_directory(dir) - - dir_temp = os.path.join(tempdir, f"frota__{year}") - path_file = os.path.join(dir_temp, ".zip") - - if not os.path.exists(path_file): - try: - response = requests.get(mi_url) - with open(path_file, "wb") as f: - f.write(response.content) - except Exception as e: - if os.path.exists(path_file): - os.remove(path_file) - - extract_files_from_zip(path_file, dir_temp) - - for root, dirs, files in os.walk(dir_temp): - for name in files: - if name.endswith(".zip"): - extract_files_from_zip( - os.path.join(root, name), os.path.dirname(os.path.join(root, name)) - ) - - for root, dirs, files in os.walk(dir_temp): - for name in files: - file_path = os.path.join(root, name) - - get_by = { - "regiao": "(frota tipo uf)|(frota uf)|(frota regiao uf)|(frota regiao tipo uf)", - "municipio": "(frota munic)|(frota mun)", - } - - new_name = ( - os.path.basename(file_path) - .lower() - .replace("regiões", "regiao") - .replace("_", " ") - .replace("-", " ") - .replace(".xlsx", "") - .replace(".xls", "") - .replace("internet", "") - .strip() - ) - new_name = re.sub(r"^(\\d\\_|\\d)+", "", new_name) - - # Match jan|fev|... or number of month (two digits) - get_month = re.search( - rf"({'|'.join(months.keys())})|\d{{2}}(?=\d{{4}})", - new_name, - re.IGNORECASE, - ) - if get_month: - month_i = int(get_month.group(0)) - if get_month.group(1): - month_i = months[get_month.group(1)] - - file_ext = re.search(r"\.[a-zA-Z0-9]+$", new_name).group(0) - - if ( - key - and prefix - and re.search(get_by[key], new_name, re.IGNORECASE) - and name.endswith(("xls", "xlsx")) - ): - shutil.copy( - file_path, os.path.join(dir, f"{prefix}_{month_i}-{year}{file_ext}") - ) From 46ae51973f2af6ef35fc25e03f0bb7c05dc6d9f0 Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 5 Apr 2023 05:45:09 -0300 Subject: [PATCH 028/265] Cleanup + new tests --- br_denatran_frota/code/download_frota.py | 32 +------- .../code/test/download_frota_test.py | 82 +++++++++++++++---- 2 files changed, 69 insertions(+), 45 deletions(-) diff --git a/br_denatran_frota/code/download_frota.py b/br_denatran_frota/code/download_frota.py index 891c6c739..f152264d3 100644 --- a/br_denatran_frota/code/download_frota.py +++ b/br_denatran_frota/code/download_frota.py @@ -35,32 +35,6 @@ def handle_xl(i: dict) -> None: urlretrieve(i["href"], dest_path_file) -def handle_compact(i: dict): - tempdir = i["tempdir"] - path_file_zip = os.path.join(tempdir, make_filename(i)) - dir_file = os.path.join(tempdir, make_filename(i, ext=False)) - - if not os.path.isfile(path_file_zip): - urlretrieve(i["href"], path_file_zip) - - if i["filetype"] == "rar": - with RarFile(path_file_zip) as rar_file: - rar_file.extractall(dir_file) - else: - with ZipFile(path_file_zip) as zip_file: - zip_file.extractall(dir_file) - - for filename in os.listdir(dir_file): - filepath = os.path.join(dir_file, filename) - if os.path.isfile(filepath): - if filename.endswith((".xlsx", ".xls")): - dest_path_file = os.path.join(tempdir, make_filename(i)) - if not os.path.isfile(dest_path_file): - os.rename(filepath, dest_path_file) - else: - os.remove(filepath) - - def make_filename(i: dict, ext: bool = True) -> str: """Creates the filename using the sent dictionary. @@ -141,7 +115,7 @@ def download_frota(month: int, year: int): year (int): Ano desejado. Raises: - ValueError: Dá erro caso o mês desejado não seja um mês válido. + ValueError: Errors if the month is not a valid one. """ if month not in MONTHS.values(): @@ -157,7 +131,7 @@ def download_frota(month: int, year: int): year_dir_name = f"{year}" desired_dir_name = os.path.join("files", year_dir_name) - # Cria pasta para aquele ano de arquivos caso seja necessário. + # Create dir for that specific year should it be necessary. make_dir_when_not_exists(desired_dir_name) os.chdir(desired_dir_name) if year > 2012: @@ -169,5 +143,3 @@ def download_frota(month: int, year: int): urlretrieve(url, generic_zip_filename) with ZipFile(generic_zip_filename) as zip_file: zip_file.extractall() - - print(2) diff --git a/br_denatran_frota/code/test/download_frota_test.py b/br_denatran_frota/code/test/download_frota_test.py index 9495132b9..9226c83dc 100644 --- a/br_denatran_frota/code/test/download_frota_test.py +++ b/br_denatran_frota/code/test/download_frota_test.py @@ -1,32 +1,84 @@ import os +import shutil import tempfile import unittest -from unittest.mock import patch -from urllib.error import HTTPError -from download_frota import * +from download_frota import ( + DATASET, + MONTHS, + make_filename, + make_dir_when_not_exists, + download_frota, + download_post_2012, +) -class TestDownloadFrota(unittest.TestCase): + +class TestMakeFilename(unittest.TestCase): def setUp(self): - self.test_dir = tempfile.mkdtemp() + self.temp_dir = tempfile.mkdtemp() def tearDown(self): - os.rmdir(self.test_dir) + shutil.rmtree(self.temp_dir) + + def test_make_filename(self): + month = 2 + year = 2013 + i = { + "txt": "frota-de-veiculos-por-municipio-tipo-e-combustivel", + "mes": month, + "ano": year, + "filetype": "xlsx", + } + filename = make_filename(i) + self.assertEqual( + filename, + f"frota-de-veiculos-por-municipio-tipo-e-combustivel_{month}-{year}.xlsx", + ) - def test_download_frota_with_valid_args(self): - # TODO: This is always assuming a structure of having a files dir under the denatran directory... + def test_make_filename_without_ext(self): month = 2 - year = 2022 - download_frota(month, year) - expected_file_path = os.path.join( - os.getcwd(), - f"frota_por_município_e_tipo_{month}-{year}.xls", + year = 2013 + i = { + "txt": "frota-de-veiculos-por-municipio-tipo-e-combustivel", + "mes": 2, + "ano": 2013, + "filetype": "xlsx", + } + filename = make_filename(i, ext=False) + self.assertEqual( + filename, + f"frota-de-veiculos-por-municipio-tipo-e-combustivel_{month}-{year}", ) - self.assertTrue(os.path.isfile(expected_file_path)) + + +class TestMakeDirWhenNotExists(unittest.TestCase): + def test_make_dir_when_not_exists(self): + new_dir = os.path.join(self.temp_dir, "new_dir") + self.assertFalse(os.path.exists(new_dir)) + make_dir_when_not_exists(new_dir) + self.assertTrue(os.path.exists(new_dir)) + + def test_download_frota_with_valid_month(self): + download_frota(MONTHS["fevereiro"], 2013) + expected_files = { + "frota_de_veiculos_por_municipio_tipo_e_combustivel_2-2013.xlsx", + "frota_de_veiculos_por_uf_e_tipo_2-2013.xlsx", + } + files = set(os.listdir(os.path.join(self.temp_dir, DATASET, "files", "2013"))) + self.assertEqual(files, expected_files) def test_download_frota_with_invalid_month(self): with self.assertRaises(ValueError): - download_frota(month=13, year=2022) + download_frota(13, 2013) + + def test_download_post_2012(self): + download_post_2012(2018, MONTHS["fevereiro"]) + expected_files = { + "Frota por UF e tipo_2-2018.xlsx", + "Frota por Município e tipo e combustível_2-2018.xlsx", + } + files = set(os.listdir(os.path.join(self.temp_dir, DATASET, "files", "2018"))) + self.assertEqual(files, expected_files) if __name__ == "__main__": From 4ae29a6457f74baad78beb305445b0d55108dfba Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 5 Apr 2023 06:44:44 -0300 Subject: [PATCH 029/265] 2018 is literally a different design and this is terrible --- br_denatran_frota/code/download_frota.py | 13 +++---- .../code/test/download_frota_test.py | 34 +++++++++++++++---- 2 files changed, 34 insertions(+), 13 deletions(-) diff --git a/br_denatran_frota/code/download_frota.py b/br_denatran_frota/code/download_frota.py index f152264d3..b16452882 100644 --- a/br_denatran_frota/code/download_frota.py +++ b/br_denatran_frota/code/download_frota.py @@ -63,7 +63,7 @@ def download_file(i): raise ValueError("A função handle_compact tá bem esquisita por hora.") -def download_post_2012(year: int, month: int): +def download_post_2012(month: int, year: int): """_summary_ Args: @@ -73,7 +73,7 @@ def download_post_2012(year: int, month: int): url = f"https://www.gov.br/infraestrutura/pt-br/assuntos/transito/conteudo-Senatran/frota-de-veiculos-{year}" soup = BeautifulSoup(urlopen(url), "html.parser") # Só queremos os dados de frota nacional. - nodes = soup.select("p:contains('Frota por ') > a") + nodes = soup.select("p:contains('rota por ') > a") for node in nodes: txt = node.text href = node.get("href") @@ -107,7 +107,7 @@ def make_dir_when_not_exists(dir_name: str): os.mkdir(dir_name) -def download_frota(month: int, year: int): +def download_frota(month: int, year: int, temp_dir: None): """Função principal para baixar os dados de frota por município e tipo e também por UF e tipo. Args: @@ -125,17 +125,18 @@ def download_frota(month: int, year: int): if dir_list: # I always want to be in the actual folder for this dataset: os.chdir(dir_list[0]) - + if temp_dir: + os.chdir(temp_dir) # I always need a files directory inside my dataset folder. make_dir_when_not_exists("files") year_dir_name = f"{year}" - desired_dir_name = os.path.join("files", year_dir_name) + desired_dir_name = os.path.join(os.getcwd(), temp_dir, "files", year_dir_name) # Create dir for that specific year should it be necessary. make_dir_when_not_exists(desired_dir_name) os.chdir(desired_dir_name) if year > 2012: - download_post_2012(year, month) + download_post_2012(month, year) else: url = f"https://www.gov.br/infraestrutura/pt-br/assuntos/transito/arquivos-senatran/estatisticas/renavam/{year}/frota{'_' if year > 2008 else ''}{year}.zip" diff --git a/br_denatran_frota/code/test/download_frota_test.py b/br_denatran_frota/code/test/download_frota_test.py index 9226c83dc..291c09590 100644 --- a/br_denatran_frota/code/test/download_frota_test.py +++ b/br_denatran_frota/code/test/download_frota_test.py @@ -2,6 +2,7 @@ import shutil import tempfile import unittest +import glob from download_frota import ( DATASET, @@ -12,14 +13,13 @@ download_post_2012, ) +dir_list = glob.glob(f"**/{DATASET}", recursive=True) +if dir_list: + # I always want to be in the actual folder for this dataset: + os.chdir(dir_list[0]) -class TestMakeFilename(unittest.TestCase): - def setUp(self): - self.temp_dir = tempfile.mkdtemp() - - def tearDown(self): - shutil.rmtree(self.temp_dir) +class TestMakeFilename(unittest.TestCase): def test_make_filename(self): month = 2 year = 2013 @@ -52,12 +52,32 @@ def test_make_filename_without_ext(self): class TestMakeDirWhenNotExists(unittest.TestCase): + def setUp(self): + self.temp_dir = tempfile.mkdtemp() + + def tearDown(self): + shutil.rmtree(self.temp_dir) + def test_make_dir_when_not_exists(self): new_dir = os.path.join(self.temp_dir, "new_dir") self.assertFalse(os.path.exists(new_dir)) make_dir_when_not_exists(new_dir) self.assertTrue(os.path.exists(new_dir)) + +class TestDownloadFrota(unittest.TestCase): + def setUp(self): + # Create a simple temporary directory for files, as opposed to the real one? + # Problema aqui é que a minha estrutura sempre assume que BR DENATRAN FROTA é um repo, e ai vai criando conforme for files, ano, etc. + # Idealmente, o teste nesse caso só teria o tear down pro ano testado SÓ QUE isso é mei burro né + # Pq? Pq oras, se vc rodou 2012, aí testou 2012, vc ia perder tudo q fez pré teste. Seu teste apagar sua execução é meio esquisito. + # OK, então qual que é a maneira + self.temp_dir = tempfile.mkdtemp(dir=os.getcwd()) + + def tearDown(self): + shutil.rmtree(self.temp_dir) + + @unittest.skip("demonstrating skipping") def test_download_frota_with_valid_month(self): download_frota(MONTHS["fevereiro"], 2013) expected_files = { @@ -72,7 +92,7 @@ def test_download_frota_with_invalid_month(self): download_frota(13, 2013) def test_download_post_2012(self): - download_post_2012(2018, MONTHS["fevereiro"]) + download_frota(MONTHS["fevereiro"], 2018, self.temp_dir) expected_files = { "Frota por UF e tipo_2-2018.xlsx", "Frota por Município e tipo e combustível_2-2018.xlsx", From f1cc15be5daf0d2b9ff2b39226b8c29304382b76 Mon Sep 17 00:00:00 2001 From: Tamir Date: Sat, 8 Apr 2023 21:14:54 -0300 Subject: [PATCH 030/265] 404 but works and god knows why --- br_denatran_frota/code/download_frota.py | 19 +++++++++++++++---- .../code/test/download_frota_test.py | 7 +++++-- 2 files changed, 20 insertions(+), 6 deletions(-) diff --git a/br_denatran_frota/code/download_frota.py b/br_denatran_frota/code/download_frota.py index b16452882..a4a914e3f 100644 --- a/br_denatran_frota/code/download_frota.py +++ b/br_denatran_frota/code/download_frota.py @@ -5,7 +5,7 @@ from zipfile import ZipFile from rarfile import RarFile from bs4 import BeautifulSoup - +import requests MONTHS = { "janeiro": 1, @@ -25,6 +25,17 @@ DATASET = "br_denatran_frota" +def download_file(url, filename): + # Send a GET request to the URL + response = requests.get(url) + + # Save the contents of the response to a file + with open(filename, "wb") as f: + f.write(response.content) + + print(f"Download of {filename} complete") + + def handle_xl(i: dict) -> None: """Actually downloads and deals with Excel files. @@ -32,7 +43,7 @@ def handle_xl(i: dict) -> None: i (dict): Dictionary with all the desired downloadable file's info. """ dest_path_file = make_filename(i) - urlretrieve(i["href"], dest_path_file) + download_file(i["href"], dest_path_file) def make_filename(i: dict, ext: bool = True) -> str: @@ -56,7 +67,7 @@ def make_filename(i: dict, ext: bool = True) -> str: return filename -def download_file(i): +def call_downloader(i): if i["filetype"] in ["xlsx", "xls"]: handle_xl(i) else: @@ -94,7 +105,7 @@ def download_post_2012(month: int, year: int): "ano": year, "filetype": filetype, } - download_file(info) + call_downloader(info) def make_dir_when_not_exists(dir_name: str): diff --git a/br_denatran_frota/code/test/download_frota_test.py b/br_denatran_frota/code/test/download_frota_test.py index 291c09590..27718b538 100644 --- a/br_denatran_frota/code/test/download_frota_test.py +++ b/br_denatran_frota/code/test/download_frota_test.py @@ -92,12 +92,15 @@ def test_download_frota_with_invalid_month(self): download_frota(13, 2013) def test_download_post_2012(self): - download_frota(MONTHS["fevereiro"], 2018, self.temp_dir) + year = 2019 + download_frota(MONTHS["fevereiro"], year, self.temp_dir) expected_files = { "Frota por UF e tipo_2-2018.xlsx", "Frota por Município e tipo e combustível_2-2018.xlsx", } - files = set(os.listdir(os.path.join(self.temp_dir, DATASET, "files", "2018"))) + files = set( + os.listdir(os.path.join(self.temp_dir, DATASET, "files", f"{year}")) + ) self.assertEqual(files, expected_files) From b6b50bc85dfbb89acc53de1e27c73b3bef592877 Mon Sep 17 00:00:00 2001 From: Tamir Date: Sat, 8 Apr 2023 23:36:30 -0300 Subject: [PATCH 031/265] Fix tests and parametrize them --- br_denatran_frota/code/download_frota.py | 2 +- .../code/test/download_frota_test.py | 29 ++-- poetry.lock | 127 ++++++++++-------- pyproject.toml | 2 +- 4 files changed, 91 insertions(+), 69 deletions(-) diff --git a/br_denatran_frota/code/download_frota.py b/br_denatran_frota/code/download_frota.py index a4a914e3f..144aa0a16 100644 --- a/br_denatran_frota/code/download_frota.py +++ b/br_denatran_frota/code/download_frota.py @@ -118,7 +118,7 @@ def make_dir_when_not_exists(dir_name: str): os.mkdir(dir_name) -def download_frota(month: int, year: int, temp_dir: None): +def download_frota(month: int, year: int, temp_dir: str = None): """Função principal para baixar os dados de frota por município e tipo e também por UF e tipo. Args: diff --git a/br_denatran_frota/code/test/download_frota_test.py b/br_denatran_frota/code/test/download_frota_test.py index 27718b538..b7b971667 100644 --- a/br_denatran_frota/code/test/download_frota_test.py +++ b/br_denatran_frota/code/test/download_frota_test.py @@ -3,6 +3,7 @@ import tempfile import unittest import glob +from parameterized import parameterized from download_frota import ( DATASET, @@ -13,6 +14,14 @@ download_post_2012, ) + +def custom_name_func(testcase_func, param_num, param): + return "%s_%s" % ( + testcase_func.__name__, + parameterized.to_safe_name("_".join(str(x) for x in param.args)), + ) + + dir_list = glob.glob(f"**/{DATASET}", recursive=True) if dir_list: # I always want to be in the actual folder for this dataset: @@ -67,11 +76,6 @@ def test_make_dir_when_not_exists(self): class TestDownloadFrota(unittest.TestCase): def setUp(self): - # Create a simple temporary directory for files, as opposed to the real one? - # Problema aqui é que a minha estrutura sempre assume que BR DENATRAN FROTA é um repo, e ai vai criando conforme for files, ano, etc. - # Idealmente, o teste nesse caso só teria o tear down pro ano testado SÓ QUE isso é mei burro né - # Pq? Pq oras, se vc rodou 2012, aí testou 2012, vc ia perder tudo q fez pré teste. Seu teste apagar sua execução é meio esquisito. - # OK, então qual que é a maneira self.temp_dir = tempfile.mkdtemp(dir=os.getcwd()) def tearDown(self): @@ -91,15 +95,18 @@ def test_download_frota_with_invalid_month(self): with self.assertRaises(ValueError): download_frota(13, 2013) - def test_download_post_2012(self): - year = 2019 - download_frota(MONTHS["fevereiro"], year, self.temp_dir) + @parameterized.expand( + [(month, year) for year in range(2013, 2023) for month in range(1, 13)], + name_func=custom_name_func, + ) + def test_download_post_2012(self, month, year): + download_frota(month, year, self.temp_dir) expected_files = { - "Frota por UF e tipo_2-2018.xlsx", - "Frota por Município e tipo e combustível_2-2018.xlsx", + f"frota_por_uf_e_tipo_de_veículo_{month}-{year}.xls", + f"frota_por_município_e_tipo_{month}-{year}.xls", } files = set( - os.listdir(os.path.join(self.temp_dir, DATASET, "files", f"{year}")) + os.listdir(os.path.join(DATASET, self.temp_dir, "files", 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[[package]] name = "pytest-cov" -version = "4.0.0" +version = "3.0.0" description = "Pytest plugin for measuring coverage." category = "dev" optional = false python-versions = ">=3.6" files = [ - {file = "pytest-cov-4.0.0.tar.gz", hash = "sha256:996b79efde6433cdbd0088872dbc5fb3ed7fe1578b68cdbba634f14bb8dd0470"}, - {file = "pytest_cov-4.0.0-py3-none-any.whl", hash = "sha256:2feb1b751d66a8bd934e5edfa2e961d11309dc37b73b0eabe73b5945fee20f6b"}, + {file = "pytest-cov-3.0.0.tar.gz", hash = "sha256:e7f0f5b1617d2210a2cabc266dfe2f4c75a8d32fb89eafb7ad9d06f6d076d470"}, + {file = "pytest_cov-3.0.0-py3-none-any.whl", hash = "sha256:578d5d15ac4a25e5f961c938b85a05b09fdaae9deef3bb6de9a6e766622ca7a6"}, ] [package.dependencies] @@ -3019,4 +3034,4 @@ testing = ["big-O", "flake8 (<5)", "jaraco.functools", "jaraco.itertools", "more [metadata] lock-version = "2.0" python-versions = ">=3.8,<3.11" -content-hash = "b66b159eb704ec9ed5c49fbec70a4f8bed1c3eae80635aafb95c09f7b2c0455b" +content-hash = "a13e853a09285d3d58160ae08be07da2f7da18e0af92cf95cf46c90578e2fdb7" diff --git a/pyproject.toml b/pyproject.toml index b76cdee1f..0aefe089f 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -105,7 +105,7 @@ pytest_cov = "^3.0.0" [tool.poetry.group.dev.dependencies] pytest = "^7.2.2" -pytest-cov = "^4.0.0" +parameterized = "^0.9.0" [build-system] build-backend = "poetry.core.masonry.api" From 09d17b619ec4dcfa2a7fdfe3b37748c95ef229f8 Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 9 Apr 2023 22:24:56 -0300 Subject: [PATCH 032/265] Working simple tests, moving on --- br_denatran_frota/code/test/download_frota_test.py | 11 ++++++----- 1 file changed, 6 insertions(+), 5 deletions(-) diff --git a/br_denatran_frota/code/test/download_frota_test.py b/br_denatran_frota/code/test/download_frota_test.py index b7b971667..d718fb4b5 100644 --- a/br_denatran_frota/code/test/download_frota_test.py +++ b/br_denatran_frota/code/test/download_frota_test.py @@ -76,10 +76,11 @@ def test_make_dir_when_not_exists(self): class TestDownloadFrota(unittest.TestCase): def setUp(self): - self.temp_dir = tempfile.mkdtemp(dir=os.getcwd()) + self.temp_dir = tempfile.TemporaryDirectory() + print("im heir") def tearDown(self): - shutil.rmtree(self.temp_dir) + shutil.rmtree(self.temp_dir.name) @unittest.skip("demonstrating skipping") def test_download_frota_with_valid_month(self): @@ -96,17 +97,17 @@ def test_download_frota_with_invalid_month(self): download_frota(13, 2013) @parameterized.expand( - [(month, year) for year in range(2013, 2023) for month in range(1, 13)], + [(month, year) for year in range(2022, 2023) for month in range(1, 13)], name_func=custom_name_func, ) def test_download_post_2012(self, month, year): - download_frota(month, year, self.temp_dir) + download_frota(month, year, self.temp_dir.name) expected_files = { f"frota_por_uf_e_tipo_de_veículo_{month}-{year}.xls", f"frota_por_município_e_tipo_{month}-{year}.xls", } files = set( - os.listdir(os.path.join(DATASET, self.temp_dir, "files", f"{year}")) + os.listdir(os.path.join(DATASET, self.temp_dir.name, "files", f"{year}")) ) self.assertEqual(files, expected_files) From a0c631597f46a75ee568347acdc7002deb6b9c82 Mon Sep 17 00:00:00 2001 From: Tamir Date: Mon, 10 Apr 2023 21:02:14 -0300 Subject: [PATCH 033/265] The tests work!! --- .../code/test/download_frota_test.py | 20 +++++-------------- pytest.ini | 9 --------- 2 files changed, 5 insertions(+), 24 deletions(-) delete mode 100644 pytest.ini diff --git a/br_denatran_frota/code/test/download_frota_test.py b/br_denatran_frota/code/test/download_frota_test.py index d718fb4b5..272725349 100644 --- a/br_denatran_frota/code/test/download_frota_test.py +++ b/br_denatran_frota/code/test/download_frota_test.py @@ -77,21 +77,10 @@ def test_make_dir_when_not_exists(self): class TestDownloadFrota(unittest.TestCase): def setUp(self): self.temp_dir = tempfile.TemporaryDirectory() - print("im heir") def tearDown(self): shutil.rmtree(self.temp_dir.name) - @unittest.skip("demonstrating skipping") - def test_download_frota_with_valid_month(self): - download_frota(MONTHS["fevereiro"], 2013) - expected_files = { - "frota_de_veiculos_por_municipio_tipo_e_combustivel_2-2013.xlsx", - "frota_de_veiculos_por_uf_e_tipo_2-2013.xlsx", - } - files = set(os.listdir(os.path.join(self.temp_dir, DATASET, "files", "2013"))) - self.assertEqual(files, expected_files) - def test_download_frota_with_invalid_month(self): with self.assertRaises(ValueError): download_frota(13, 2013) @@ -103,12 +92,13 @@ def test_download_frota_with_invalid_month(self): def test_download_post_2012(self, month, year): download_frota(month, year, self.temp_dir.name) expected_files = { - f"frota_por_uf_e_tipo_de_veículo_{month}-{year}.xls", - f"frota_por_município_e_tipo_{month}-{year}.xls", + f"frota_por_uf_e_tipo_de_veículo_{month}-{year}", + f"frota_por_município_e_tipo_{month}-{year}", } - files = set( - os.listdir(os.path.join(DATASET, self.temp_dir.name, "files", f"{year}")) + list_of_files = os.listdir( + os.path.join(DATASET, self.temp_dir.name, "files", f"{year}") ) + files = set(os.path.splitext(file)[0] for file in list_of_files) self.assertEqual(files, expected_files) diff --git a/pytest.ini b/pytest.ini deleted file mode 100644 index 173ec65c1..000000000 --- a/pytest.ini +++ /dev/null @@ -1,9 +0,0 @@ -[pytest] -testpaths = - tests -norecursedirs=dist build .tox scripts -addopts = - --doctest-modules - --cov=pipelines - -r a - -v From f105cd29f47e624f442256dbc0b7fb9b1825c1e7 Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 12 Apr 2023 03:11:44 -0300 Subject: [PATCH 034/265] hold the thought --- br_denatran_frota/code/download_frota.py | 11 ++++++++++- 1 file changed, 10 insertions(+), 1 deletion(-) diff --git a/br_denatran_frota/code/download_frota.py b/br_denatran_frota/code/download_frota.py index 144aa0a16..03f894692 100644 --- a/br_denatran_frota/code/download_frota.py +++ b/br_denatran_frota/code/download_frota.py @@ -36,6 +36,11 @@ def download_file(url, filename): print(f"Download of {filename} complete") +def extract_zip(dest_path_file): + with ZipFile(dest_path_file, "r") as z: + z.extractall(os.getcwd()) + + def handle_xl(i: dict) -> None: """Actually downloads and deals with Excel files. @@ -67,11 +72,15 @@ def make_filename(i: dict, ext: bool = True) -> str: return filename +def handle_compact(i): + print(2) + + def call_downloader(i): if i["filetype"] in ["xlsx", "xls"]: handle_xl(i) else: - raise ValueError("A função handle_compact tá bem esquisita por hora.") + handle_compact(i) def download_post_2012(month: int, year: int): From 92714e97c15ed82d5ad698b357443b3c1696dffd Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 16 Apr 2023 19:28:31 -0300 Subject: [PATCH 035/265] Tests handle directory change now --- br_denatran_frota/code/download_frota.py | 13 +++++++------ 1 file changed, 7 insertions(+), 6 deletions(-) diff --git a/br_denatran_frota/code/download_frota.py b/br_denatran_frota/code/download_frota.py index 03f894692..bcf092dea 100644 --- a/br_denatran_frota/code/download_frota.py +++ b/br_denatran_frota/code/download_frota.py @@ -23,12 +23,16 @@ } DATASET = "br_denatran_frota" +headers = { + "User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/39.0.2171.95 Safari/537.36" +} def download_file(url, filename): # Send a GET request to the URL - response = requests.get(url) + new_url = url.replace("arquivos-denatran", "arquivos-senatran") + response = requests.get(new_url, headers=headers) # Save the contents of the response to a file with open(filename, "wb") as f: f.write(response.content) @@ -77,10 +81,7 @@ def handle_compact(i): def call_downloader(i): - if i["filetype"] in ["xlsx", "xls"]: - handle_xl(i) - else: - handle_compact(i) + handle_xl(i) def download_post_2012(month: int, year: int): @@ -127,7 +128,7 @@ def make_dir_when_not_exists(dir_name: str): os.mkdir(dir_name) -def download_frota(month: int, year: int, temp_dir: str = None): +def download_frota(month: int, year: int, temp_dir: str = ""): """Função principal para baixar os dados de frota por município e tipo e também por UF e tipo. Args: From cc3d84bb83d3933ab73693378c0169f7a11f9d78 Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 16 Apr 2023 19:28:53 -0300 Subject: [PATCH 036/265] And now we clean the broken URLs --- br_denatran_frota/code/test/download_frota_test.py | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/br_denatran_frota/code/test/download_frota_test.py b/br_denatran_frota/code/test/download_frota_test.py index 272725349..7991c3c57 100644 --- a/br_denatran_frota/code/test/download_frota_test.py +++ b/br_denatran_frota/code/test/download_frota_test.py @@ -76,9 +76,12 @@ def test_make_dir_when_not_exists(self): class TestDownloadFrota(unittest.TestCase): def setUp(self): - self.temp_dir = tempfile.TemporaryDirectory() + file_dir = os.path.dirname(os.path.abspath(__file__)) + os.chdir(file_dir) + self.temp_dir = tempfile.TemporaryDirectory(dir=file_dir) def tearDown(self): + print("Deleting temporary directory") shutil.rmtree(self.temp_dir.name) def test_download_frota_with_invalid_month(self): @@ -86,7 +89,7 @@ def test_download_frota_with_invalid_month(self): download_frota(13, 2013) @parameterized.expand( - [(month, year) for year in range(2022, 2023) for month in range(1, 13)], + [(month, year) for year in range(2021, 2022) for month in range(1, 4)], name_func=custom_name_func, ) def test_download_post_2012(self, month, year): From 673eb97e134521a9ec97451178f6258c17e8afca Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 18 Apr 2023 01:00:34 -0300 Subject: [PATCH 037/265] =?UTF-8?q?Agora=20j=C3=A1=20tratamos=20o=20zip=20?= =?UTF-8?q?direitinho?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- br_denatran_frota/code/download_frota.py | 9 +++++++-- br_denatran_frota/code/test/download_frota_test.py | 2 +- 2 files changed, 8 insertions(+), 3 deletions(-) diff --git a/br_denatran_frota/code/download_frota.py b/br_denatran_frota/code/download_frota.py index bcf092dea..28952d0f6 100644 --- a/br_denatran_frota/code/download_frota.py +++ b/br_denatran_frota/code/download_frota.py @@ -42,7 +42,7 @@ def download_file(url, filename): def extract_zip(dest_path_file): with ZipFile(dest_path_file, "r") as z: - z.extractall(os.getcwd()) + z.extractall() def handle_xl(i: dict) -> None: @@ -81,7 +81,12 @@ def handle_compact(i): def call_downloader(i): - handle_xl(i) + filename = make_filename(i) + if i["filetype"] in ["xlsx", "xls"]: + download_file(i["href"], filename) + elif i["filetype"] == "zip": + download_file(i["href"], filename) + extract_zip(filename) def download_post_2012(month: int, year: int): diff --git a/br_denatran_frota/code/test/download_frota_test.py b/br_denatran_frota/code/test/download_frota_test.py index 7991c3c57..9972afb5b 100644 --- a/br_denatran_frota/code/test/download_frota_test.py +++ b/br_denatran_frota/code/test/download_frota_test.py @@ -89,7 +89,7 @@ def test_download_frota_with_invalid_month(self): download_frota(13, 2013) @parameterized.expand( - [(month, year) for year in range(2021, 2022) for month in range(1, 4)], + [(month, year) for year in range(2013, 2014) for month in range(1, 4)], name_func=custom_name_func, ) def test_download_post_2012(self, month, year): From 48fc127b3e0b92ac377022473c8f39e7186e7963 Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 19 Apr 2023 04:09:36 -0300 Subject: [PATCH 038/265] Add packages (Polars and Excel readers) --- poetry.lock | 699 ++++++++++++++++++++++++++++++++++++++++++++++++- pyproject.toml | 4 + 2 files changed, 702 insertions(+), 1 deletion(-) diff --git a/poetry.lock b/poetry.lock index 33664c3d4..271795492 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,5 +1,35 @@ # This file is automatically @generated by Poetry 1.4.1 and should not be changed by hand. +[[package]] +name = "appnope" +version = "0.1.3" +description = "Disable App Nap on macOS >= 10.9" +category = "dev" +optional = false +python-versions = "*" +files = [ + {file = "appnope-0.1.3-py2.py3-none-any.whl", hash = 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"sha256:fb33085c39dd998ac16d1431ebc293a8b3eedd00fd4a32de0ff79002c19511b4"}, + {file = "typing_extensions-4.5.0.tar.gz", hash = "sha256:5cb5f4a79139d699607b3ef622a1dedafa84e115ab0024e0d9c044a9479ca7cb"}, +] + [[package]] name = "unidecode" version = "1.3.6" @@ -2958,6 +3614,18 @@ platformdirs = ">=2.4,<4" docs = ["furo (>=2022.12.7)", "proselint (>=0.13)", "sphinx (>=6.1.3)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=22.12)"] test = ["covdefaults (>=2.2.2)", "coverage (>=7.1)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=23)", "pytest (>=7.2.1)", "pytest-env (>=0.8.1)", "pytest-freezegun (>=0.4.2)", "pytest-mock (>=3.10)", "pytest-randomly (>=3.12)", "pytest-timeout (>=2.1)"] +[[package]] +name = "wcwidth" +version = "0.2.6" +description = "Measures the displayed width of unicode strings in a terminal" +category = "dev" +optional = false +python-versions = "*" +files = [ + {file = "wcwidth-0.2.6-py2.py3-none-any.whl", hash = "sha256:795b138f6875577cd91bba52baf9e445cd5118fd32723b460e30a0af30ea230e"}, + {file = "wcwidth-0.2.6.tar.gz", hash = "sha256:a5220780a404dbe3353789870978e472cfe477761f06ee55077256e509b156d0"}, +] + [[package]] name = "websocket-client" version = "1.2.1" @@ -3000,6 +3668,35 @@ files = [ [package.extras] dev = ["black (>=19.3b0)", "pytest (>=4.6.2)"] +[[package]] +name = "xlrd" +version = "2.0.1" +description = "Library for developers to extract data from Microsoft Excel (tm) .xls spreadsheet files" +category = "main" +optional = false +python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*" +files = [ + {file = "xlrd-2.0.1-py2.py3-none-any.whl", hash = "sha256:6a33ee89877bd9abc1158129f6e94be74e2679636b8a205b43b85206c3f0bbdd"}, + {file = "xlrd-2.0.1.tar.gz", hash = "sha256:f72f148f54442c6b056bf931dbc34f986fd0c3b0b6b5a58d013c9aef274d0c88"}, +] + +[package.extras] +build = ["twine", "wheel"] +docs = ["sphinx"] +test = ["pytest", "pytest-cov"] + +[[package]] +name = "xlsx2csv" +version = "0.8.1" +description = "xlsx to csv converter" +category = "main" +optional = false +python-versions = "*" +files = [ + {file = "xlsx2csv-0.8.1-py3-none-any.whl", hash = "sha256:6c36c0295d64f231570479e514d6163ce135af3c431a1705b073230bedaef9f2"}, + {file = "xlsx2csv-0.8.1.tar.gz", hash = "sha256:7ecd6d2bc2426f2e432f4fdac12211e1976d3cbb65f9033e1eda65edda2045e3"}, +] + [[package]] name = "zict" version = "2.0.0" @@ -3034,4 +3731,4 @@ testing = ["big-O", "flake8 (<5)", "jaraco.functools", "jaraco.itertools", "more [metadata] lock-version = "2.0" python-versions = ">=3.8,<3.11" -content-hash = "a13e853a09285d3d58160ae08be07da2f7da18e0af92cf95cf46c90578e2fdb7" +content-hash = "a06307115a26fddb569266cf3c030d7aad2fe2318ab9ce079581ffbc48e861bb" diff --git a/pyproject.toml b/pyproject.toml index 0aefe089f..b1ea4270f 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -99,6 +99,9 @@ oauth2client = "^4.1.3" redis-pal = "^1.0.0" rarfile = "^4.0" setuptools = "^67.6.1" +polars = "^0.17.5" +xlsx2csv = "^0.8.1" +xlrd = "^2.0.1" [tool.poetry.dev-dependencies] pytest_cov = "^3.0.0" @@ -106,6 +109,7 @@ pytest_cov = "^3.0.0" [tool.poetry.group.dev.dependencies] pytest = "^7.2.2" parameterized = "^0.9.0" +ipykernel = "^6.22.0" [build-system] build-backend = "poetry.core.masonry.api" From b7b2db4a9fc51dd027b6a29fa3e60109e854f8af Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 19 Apr 2023 04:10:10 -0300 Subject: [PATCH 039/265] Create utility functions for processing files --- br_denatran_frota/code/utils.py | 60 +++++++++++++++++++++++++++++++++ 1 file changed, 60 insertions(+) create mode 100644 br_denatran_frota/code/utils.py diff --git a/br_denatran_frota/code/utils.py b/br_denatran_frota/code/utils.py new file mode 100644 index 000000000..572cfd331 --- /dev/null +++ b/br_denatran_frota/code/utils.py @@ -0,0 +1,60 @@ +import pandas as pd +import re + +DICT_UFS = { + "AC": "Acre", + "AL": "Alagoas", + "AP": "Amapá", + "AM": "Amazonas", + "BA": "Bahia", + "CE": "Ceará", + "DF": "Distrito Federal", + "ES": "Espírito Santo", + "GO": "Goiás", + "MA": "Maranhão", + "MT": "Mato Grosso", + "MS": "Mato Grosso do Sul", + "MG": "Minas Gerais", + "PA": "Pará", + "PB": "Paraíba", + "PR": "Paraná", + "PE": "Pernambuco", + "PI": "Piauí", + "RJ": "Rio de Janeiro", + "RN": "Rio Grande do Norte", + "RS": "Rio Grande do Sul", + "RO": "Rondônia", + "RR": "Roraima", + "SC": "Santa Catarina", + "SP": "São Paulo", + "SE": "Sergipe", + "TO": "Tocantins", +} + + +def guess_header(df: pd.DataFrame, max_header_guess: int = 4) -> int: + header_guess = 0 + while header_guess < max_header_guess: + # Iffy logic, but essentially: if all rows of the column are strings, then this is a good candidate for a header. + if all(df.iloc[header_guess].apply(lambda x: isinstance(x, str))): + return header_guess + + header_guess += 1 + return 0 # If nothing is ever found until the max, let's just assume it's the first row as per usual. + + +def change_df_header(df: pd.DataFrame, header_row: int) -> pd.DataFrame: + new_header = df.iloc[header_row] + new_df = df[(header_row + 1) :].reset_index(drop=True) + new_df.rename(columns=new_header, inplace=True) + return new_df + + +def get_year_month_from_filename(filename: str) -> tuple[int, int]: + match = re.search(r"(\w+)_(\d{1,2})-(\d{4})\.(xls|xlsx)$", filename) + if match: + month = match.group(2) + year = match.group(3) + return month, year + else: + raise ValueError("No match found") From 47c6c976fae4ba1f79192b54fa7a25005b147dfa Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 19 Apr 2023 04:10:40 -0300 Subject: [PATCH 040/265] Notebook to demonstrate data cleaning --- br_denatran_frota/code/test_drive.ipynb | 229 ++++++++++++++++++++++++ 1 file changed, 229 insertions(+) create mode 100644 br_denatran_frota/code/test_drive.ipynb diff --git a/br_denatran_frota/code/test_drive.ipynb b/br_denatran_frota/code/test_drive.ipynb new file mode 100644 index 000000000..c2ff1c992 --- /dev/null +++ b/br_denatran_frota/code/test_drive.ipynb @@ -0,0 +1,229 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "import polars as pl\n", + "import pandas as pd \n", + "import os\n", + "import re\n", + "import glob\n", + "from urllib.request import urlopen, urlretrieve\n", + "from zipfile import ZipFile\n", + "from rarfile import RarFile\n", + "from bs4 import BeautifulSoup\n", + "import requests" + ] + }, + { + "cell_type": "code", + "execution_count": 87, + "metadata": {}, + "outputs": [], + "source": [ + "file = '../files/2022/frota_por_uf_e_tipo_de_veículo_2-2022.xls'\n", + "filename = os.path.split(file)[1]" + ] + }, + { + "cell_type": "code", + "execution_count": 101, + "metadata": {}, + "outputs": [], + "source": [ + "df = pd.read_excel(file)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 104, + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "def guess_header(df: pd.DataFrame, max_header_guess: int = 4) -> int:\n", + " header_guess = 0\n", + " while header_guess < max_header_guess:\n", + " # Iffy logic, but essentially: if all rows of the column are strings, then this is a good candidate for a header.\n", + " if all(df.iloc[header_guess].apply(lambda x: isinstance(x, str))):\n", + " return header_guess\n", + " \n", + " header_guess += 1\n", + " return 0 # If nothing is ever found until the max, let's just assume it's the first row as per usual. \n", + "\n", + "def change_df_header(df: pd.DataFrame, header_row: int) -> pd.DataFrame:\n", + " new_header = df.iloc[header_row]\n", + " new_df = df[(header_row+1):].reset_index(drop=True)\n", + " new_df.rename(columns=new_header, inplace=True)\n", + " return new_df\n", + "\n", + "def get_year_month_from_filename(filename: str) -> tuple[int, int]:\n", + " match = re.search(r\"(\\w+)_(\\d{1,2})-(\\d{4})\\.(xls|xlsx)$\"\n", + "\n", + ", filename)\n", + "\n", + " if match:\n", + " month = match.group(2)\n", + " year = match.group(3)\n", + " return month, year\n", + " else:\n", + " raise ValueError(\"No match found\")" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "metadata": {}, + "outputs": [], + "source": [ + "DICT_UFS = {\n", + " \"AC\": \"Acre\",\n", + " \"AL\": \"Alagoas\",\n", + " \"AP\": \"Amapá\",\n", + " \"AM\": \"Amazonas\",\n", + " \"BA\": \"Bahia\",\n", + " \"CE\": \"Ceará\",\n", + " \"DF\": \"Distrito Federal\",\n", + " \"ES\": \"Espírito Santo\",\n", + " \"GO\": \"Goiás\",\n", + " \"MA\": \"Maranhão\",\n", + " \"MT\": \"Mato Grosso\",\n", + " \"MS\": \"Mato Grosso do Sul\",\n", + " \"MG\": \"Minas Gerais\",\n", + " \"PA\": \"Pará\",\n", + " \"PB\": \"Paraíba\",\n", + " \"PR\": \"Paraná\",\n", + " \"PE\": \"Pernambuco\",\n", + " \"PI\": \"Piauí\",\n", + " \"RJ\": \"Rio de Janeiro\",\n", + " \"RN\": \"Rio Grande do Norte\",\n", + " \"RS\": \"Rio Grande do Sul\",\n", + " \"RO\": \"Rondônia\",\n", + " \"RR\": \"Roraima\",\n", + " \"SC\": \"Santa Catarina\",\n", + " \"SP\": \"São Paulo\",\n", + " \"SE\": \"Sergipe\",\n", + " \"TO\": \"Tocantins\",\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [], + "source": [ + "new_df = change_df_header(df, guess_header(df))" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Tratamento ad hoc necessário\n" + ] + }, + { + "cell_type": "code", + "execution_count": 120, + "metadata": {}, + "outputs": [], + "source": [ + "new_df.rename(columns={ new_df.columns[0]: \"sigla_uf\" }, inplace= True) # Rename for ease of use.\n", + "new_df.sigla_uf = new_df.sigla_uf.str.strip() # Remove whitespace.\n", + "clean_df = new_df[new_df.sigla_uf.isin(DICT_UFS.values())].reset_index(drop = True) # Now we get all the actual RELEVANT uf data.\n", + "month, year = get_year_month_from_filename(filename)" + ] + }, + { + "cell_type": "code", + "execution_count": 126, + "metadata": {}, + "outputs": [], + "source": [ + "clean_pl_df = pl.from_pandas(clean_df).lazy()\n", + "# Add year and month\n", + "clean_pl_df = clean_pl_df.with_columns(pl.lit(year, dtype = pl.Int64).alias('ano'), pl.lit(month, dtype = pl.Int64).alias('mes'))" + ] + }, + { + "cell_type": "code", + "execution_count": 127, + "metadata": {}, + "outputs": [], + "source": [ + "long_pl_df = clean_pl_df.melt(id_vars = ['ano', 'mes', 'sigla_uf'], variable_name= 'tipo_veiculo', value_name= 'quantidade') # Long format." + ] + }, + { + "cell_type": "code", + "execution_count": 129, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "shape: (594, 5)
anomessigla_uftipo_veiculoquantidade
i64i64strstri64
20222"Acre""TOTAL"321989
20222"Amapá""TOTAL"225303
20222"Amazonas""TOTAL"1020046
20222"Pará""TOTAL"2367668
20222"Rondônia""TOTAL"1118903
20222"Roraima""TOTAL"252315
20222"Tocantins""TOTAL"796159
20222"Alagoas""TOTAL"988002
20222"Bahia""TOTAL"4720073
20222"Ceará""TOTAL"3529429
20222"Maranhão""TOTAL"1950201
20222"Paraíba""TOTAL"1477707
……………
20222"Sergipe""UTILITÁRIO"7459
20222"Espírito Santo…"UTILITÁRIO"29102
20222"Minas Gerais""UTILITÁRIO"116020
20222"Rio de Janeiro…"UTILITÁRIO"88531
20222"São Paulo""UTILITÁRIO"410642
20222"Paraná""UTILITÁRIO"93204
20222"Rio Grande do …"UTILITÁRIO"93702
20222"Santa Catarina…"UTILITÁRIO"105113
20222"Distrito Feder…"UTILITÁRIO"39414
20222"Goiás""UTILITÁRIO"43899
20222"Mato Grosso""UTILITÁRIO"24451
20222"Mato Grosso do…"UTILITÁRIO"19279
" + ], + "text/plain": [ + "shape: (594, 5)\n", + "┌──────┬─────┬────────────────────┬──────────────┬────────────┐\n", + "│ ano ┆ mes ┆ sigla_uf ┆ tipo_veiculo ┆ quantidade │\n", + "│ --- ┆ --- ┆ --- ┆ --- ┆ --- │\n", + "│ i64 ┆ i64 ┆ str ┆ str ┆ i64 │\n", + "╞══════╪═════╪════════════════════╪══════════════╪════════════╡\n", + "│ 2022 ┆ 2 ┆ Acre ┆ TOTAL ┆ 321989 │\n", + "│ 2022 ┆ 2 ┆ Amapá ┆ TOTAL ┆ 225303 │\n", + "│ 2022 ┆ 2 ┆ Amazonas ┆ TOTAL ┆ 1020046 │\n", + "│ 2022 ┆ 2 ┆ Pará ┆ TOTAL ┆ 2367668 │\n", + "│ … ┆ … ┆ … ┆ … ┆ … │\n", + "│ 2022 ┆ 2 ┆ Distrito Federal ┆ UTILITÁRIO ┆ 39414 │\n", + "│ 2022 ┆ 2 ┆ Goiás ┆ UTILITÁRIO ┆ 43899 │\n", + "│ 2022 ┆ 2 ┆ Mato Grosso ┆ UTILITÁRIO ┆ 24451 │\n", + "│ 2022 ┆ 2 ┆ Mato Grosso do Sul ┆ UTILITÁRIO ┆ 19279 │\n", + "└──────┴─────┴────────────────────┴──────────────┴────────────┘" + ] + }, + "execution_count": 129, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "long_pl_df.collect()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "pipelines-Fyk5jlG0-py3.10", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.6" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} From a854ccdc0d5bcb6dfd43d163fd4a13a74e5025f0 Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 19 Apr 2023 04:23:53 -0300 Subject: [PATCH 041/265] Cleaning works for uf tipo --- br_denatran_frota/code/test_drive.ipynb | 202 ++++++++++-------------- 1 file changed, 86 insertions(+), 116 deletions(-) diff --git a/br_denatran_frota/code/test_drive.ipynb b/br_denatran_frota/code/test_drive.ipynb index c2ff1c992..576cd333a 100644 --- a/br_denatran_frota/code/test_drive.ipynb +++ b/br_denatran_frota/code/test_drive.ipynb @@ -15,70 +15,7 @@ "from zipfile import ZipFile\n", "from rarfile import RarFile\n", "from bs4 import BeautifulSoup\n", - "import requests" - ] - }, - { - "cell_type": "code", - "execution_count": 87, - "metadata": {}, - "outputs": [], - "source": [ - "file = '../files/2022/frota_por_uf_e_tipo_de_veículo_2-2022.xls'\n", - "filename = os.path.split(file)[1]" - ] - }, - { - "cell_type": "code", - "execution_count": 101, - "metadata": {}, - "outputs": [], - "source": [ - "df = pd.read_excel(file)\n" - ] - }, - { - "cell_type": "code", - "execution_count": 104, - "metadata": {}, - "outputs": [], - "source": [ - "\n", - "def guess_header(df: pd.DataFrame, max_header_guess: int = 4) -> int:\n", - " header_guess = 0\n", - " while header_guess < max_header_guess:\n", - " # Iffy logic, but essentially: if all rows of the column are strings, then this is a good candidate for a header.\n", - " if all(df.iloc[header_guess].apply(lambda x: isinstance(x, str))):\n", - " return header_guess\n", - " \n", - " header_guess += 1\n", - " return 0 # If nothing is ever found until the max, let's just assume it's the first row as per usual. \n", - "\n", - "def change_df_header(df: pd.DataFrame, header_row: int) -> pd.DataFrame:\n", - " new_header = df.iloc[header_row]\n", - " new_df = df[(header_row+1):].reset_index(drop=True)\n", - " new_df.rename(columns=new_header, inplace=True)\n", - " return new_df\n", - "\n", - "def get_year_month_from_filename(filename: str) -> tuple[int, int]:\n", - " match = re.search(r\"(\\w+)_(\\d{1,2})-(\\d{4})\\.(xls|xlsx)$\"\n", - "\n", - ", filename)\n", - "\n", - " if match:\n", - " month = match.group(2)\n", - " year = match.group(3)\n", - " return month, year\n", - " else:\n", - " raise ValueError(\"No match found\")" - ] - }, - { - "cell_type": "code", - "execution_count": 57, - "metadata": {}, - "outputs": [], - "source": [ + "import requests\n", "DICT_UFS = {\n", " \"AC\": \"Acre\",\n", " \"AL\": \"Alagoas\",\n", @@ -112,56 +49,7 @@ }, { "cell_type": "code", - "execution_count": 52, - "metadata": {}, - "outputs": [], - "source": [ - "new_df = change_df_header(df, guess_header(df))" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Tratamento ad hoc necessário\n" - ] - }, - { - "cell_type": "code", - "execution_count": 120, - "metadata": {}, - "outputs": [], - "source": [ - "new_df.rename(columns={ new_df.columns[0]: \"sigla_uf\" }, inplace= True) # Rename for ease of use.\n", - "new_df.sigla_uf = new_df.sigla_uf.str.strip() # Remove whitespace.\n", - "clean_df = new_df[new_df.sigla_uf.isin(DICT_UFS.values())].reset_index(drop = True) # Now we get all the actual RELEVANT uf data.\n", - "month, year = get_year_month_from_filename(filename)" - ] - }, - { - "cell_type": "code", - "execution_count": 126, - "metadata": {}, - "outputs": [], - "source": [ - "clean_pl_df = pl.from_pandas(clean_df).lazy()\n", - "# Add year and month\n", - "clean_pl_df = clean_pl_df.with_columns(pl.lit(year, dtype = pl.Int64).alias('ano'), pl.lit(month, dtype = pl.Int64).alias('mes'))" - ] - }, - { - "cell_type": "code", - "execution_count": 127, - "metadata": {}, - "outputs": [], - "source": [ - "long_pl_df = clean_pl_df.melt(id_vars = ['ano', 'mes', 'sigla_uf'], variable_name= 'tipo_veiculo', value_name= 'quantidade') # Long format." - ] - }, - { - "cell_type": "code", - "execution_count": 129, + "execution_count": 13, "metadata": {}, "outputs": [ { @@ -194,14 +82,96 @@ "└──────┴─────┴────────────────────┴──────────────┴────────────┘" ] }, - "execution_count": 129, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "long_pl_df.collect()" + "\n", + "def guess_header(df: pd.DataFrame, max_header_guess: int = 4) -> int:\n", + " header_guess = 0\n", + " while header_guess < max_header_guess:\n", + " # Iffy logic, but essentially: if all rows of the column are strings, then this is a good candidate for a header.\n", + " if all(df.iloc[header_guess].apply(lambda x: isinstance(x, str))):\n", + " return header_guess\n", + " \n", + " header_guess += 1\n", + " return 0 # If nothing is ever found until the max, let's just assume it's the first row as per usual. \n", + "\n", + "def change_df_header(df: pd.DataFrame, header_row: int) -> pd.DataFrame:\n", + " new_header = df.iloc[header_row]\n", + " new_df = df[(header_row+1):].reset_index(drop=True)\n", + " new_df.rename(columns=new_header, inplace=True)\n", + " return new_df\n", + "\n", + "def get_year_month_from_filename(filename: str) -> tuple[int, int]:\n", + " match = re.search(r\"(\\w+)_(\\d{1,2})-(\\d{4})\\.(xls|xlsx)$\"\n", + "\n", + ", filename)\n", + "\n", + " if match:\n", + " month = match.group(2)\n", + " year = match.group(3)\n", + " return month, year\n", + " else:\n", + " raise ValueError(\"No match found\")\n", + "def treat_uf_tipo(file):\n", + " filename = os.path.split(file)[1]\n", + " df = pd.read_excel(file)\n", + " new_df = change_df_header(df, guess_header(df))\n", + " # This is ad hoc for UF_tipo.\n", + " new_df.rename(columns={ new_df.columns[0]: \"sigla_uf\" }, inplace= True) # Rename for ease of use.\n", + " new_df.sigla_uf = new_df.sigla_uf.str.strip() # Remove whitespace.\n", + " clean_df = new_df[new_df.sigla_uf.isin(DICT_UFS.values())].reset_index(drop = True) # Now we get all the actual RELEVANT uf data.\n", + " month, year = get_year_month_from_filename(filename)\n", + " clean_pl_df = pl.from_pandas(clean_df).lazy()\n", + "# Add year and month\n", + " clean_pl_df = clean_pl_df.with_columns(pl.lit(year, dtype = pl.Int64).alias('ano'), pl.lit(month, dtype = pl.Int64).alias('mes'))\n", + " clean_pl_df = clean_pl_df.melt(id_vars = ['ano', 'mes', 'sigla_uf'], variable_name= 'tipo_veiculo', value_name= 'quantidade') # Long format.\n", + " return clean_pl_df.collect()\n", + "treat_uf_tipo('../files/2022/frota_por_uf_e_tipo_de_veículo_2-2022.xls')" ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "shape: (0, 5)
anomessigla_uftipo_veiculoquantidade
i64i64strstrstr
" + ], + "text/plain": [ + "shape: (0, 5)\n", + "┌─────┬─────┬──────────┬──────────────┬────────────┐\n", + "│ ano ┆ mes ┆ sigla_uf ┆ tipo_veiculo ┆ quantidade │\n", + "│ --- ┆ --- ┆ --- ┆ --- ┆ --- │\n", + "│ i64 ┆ i64 ┆ str ┆ str ┆ str │\n", + "╞═════╪═════╪══════════╪══════════════╪════════════╡\n", + "└─────┴─────┴──────────┴──────────────┴────────────┘" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [] } ], "metadata": { From f74c3e0b72bdc8247525a57fa32e926dead659d7 Mon Sep 17 00:00:00 2001 From: Tamir Date: Thu, 20 Apr 2023 03:59:26 -0300 Subject: [PATCH 042/265] Start file for UF Tipo treatment --- br_denatran_frota/code/frota_uf_tipo.py | 62 +++++++++++++++++++++++++ 1 file changed, 62 insertions(+) create mode 100644 br_denatran_frota/code/frota_uf_tipo.py diff --git a/br_denatran_frota/code/frota_uf_tipo.py b/br_denatran_frota/code/frota_uf_tipo.py new file mode 100644 index 000000000..3884c9349 --- /dev/null +++ b/br_denatran_frota/code/frota_uf_tipo.py @@ -0,0 +1,62 @@ +import polars as pl +import pandas as pd +import os +from utils import guess_header, change_df_header, get_year_month_from_filename + + +DICT_UFS = { + "AC": "Acre", + "AL": "Alagoas", + "AP": "Amapá", + "AM": "Amazonas", + "BA": "Bahia", + "CE": "Ceará", + "DF": "Distrito Federal", + "ES": "Espírito Santo", + "GO": "Goiás", + "MA": "Maranhão", + "MT": "Mato Grosso", + "MS": "Mato Grosso do Sul", + "MG": "Minas Gerais", + "PA": "Pará", + "PB": "Paraíba", + "PR": "Paraná", + "PE": "Pernambuco", + "PI": "Piauí", + "RJ": "Rio de Janeiro", + "RN": "Rio Grande do Norte", + "RS": "Rio Grande do Sul", + "RO": "Rondônia", + "RR": "Roraima", + "SC": "Santa Catarina", + "SP": "São Paulo", + "SE": "Sergipe", + "TO": "Tocantins", +} + + +def treat_uf_tipo(file) -> pl.DataFrame: + filename = os.path.split(file)[1] + df = pd.read_excel(file) + new_df = change_df_header(df, guess_header(df)) + # This is ad hoc for UF_tipo. + new_df.rename( + columns={new_df.columns[0]: "sigla_uf"}, inplace=True + ) # Rename for ease of use. + new_df.sigla_uf = new_df.sigla_uf.str.strip() # Remove whitespace. + clean_df = new_df[new_df.sigla_uf.isin(DICT_UFS.values())].reset_index( + drop=True + ) # Now we get all the actual RELEVANT uf data. + month, year = get_year_month_from_filename(filename) + clean_pl_df = pl.from_pandas(clean_df).lazy() + # Add year and month + clean_pl_df = clean_pl_df.with_columns( + pl.lit(year, dtype=pl.Int64).alias("ano"), + pl.lit(month, dtype=pl.Int64).alias("mes"), + ) + clean_pl_df = clean_pl_df.melt( + id_vars=["ano", "mes", "sigla_uf"], + variable_name="tipo_veiculo", + value_name="quantidade", + ) # Long format. + return clean_pl_df.collect() From 42b07d6257f6e027623827ea96f3ea9b0167ae82 Mon Sep 17 00:00:00 2001 From: Tamir Date: Thu, 20 Apr 2023 04:41:30 -0300 Subject: [PATCH 043/265] Better handling of directory changes --- br_denatran_frota/code/download_frota.py | 26 ++++++++++++++++-------- 1 file changed, 18 insertions(+), 8 deletions(-) diff --git a/br_denatran_frota/code/download_frota.py b/br_denatran_frota/code/download_frota.py index 28952d0f6..52ce439e6 100644 --- a/br_denatran_frota/code/download_frota.py +++ b/br_denatran_frota/code/download_frota.py @@ -75,8 +75,6 @@ def make_filename(i: dict, ext: bool = True) -> str: filename += f".{filetype}" return filename - -def handle_compact(i): print(2) @@ -143,24 +141,29 @@ def download_frota(month: int, year: int, temp_dir: str = ""): Raises: ValueError: Errors if the month is not a valid one. """ - if month not in MONTHS.values(): raise ValueError("Mês inválido.") dir_list = glob.glob(f"**/{DATASET}", recursive=True) + # Get the directory where this Python file is located + initial_dir = os.path.dirname(os.path.abspath(__file__)) + + # Construct the path to the "files" directory relative to this directory + files_dir = os.path.join(initial_dir, "..", "files") if dir_list: - # I always want to be in the actual folder for this dataset: + # I always want to be in the actual folder for this dataset, because I might start in the pipelines full repo: os.chdir(dir_list[0]) if temp_dir: os.chdir(temp_dir) # I always need a files directory inside my dataset folder. - make_dir_when_not_exists("files") + make_dir_when_not_exists(files_dir) + # I should always switch to the files dir now and save stuff inside it. + os.chdir(files_dir) year_dir_name = f"{year}" - desired_dir_name = os.path.join(os.getcwd(), temp_dir, "files", year_dir_name) # Create dir for that specific year should it be necessary. - make_dir_when_not_exists(desired_dir_name) - os.chdir(desired_dir_name) + make_dir_when_not_exists(year_dir_name) + os.chdir(year_dir_name) if year > 2012: download_post_2012(month, year) else: @@ -170,3 +173,10 @@ def download_frota(month: int, year: int, temp_dir: str = ""): urlretrieve(url, generic_zip_filename) with ZipFile(generic_zip_filename) as zip_file: zip_file.extractall() + os.chdir(initial_dir) + + +year = 2022 +if __name__ == "__main__": + for month in range(1, 6): + download_frota(month, year) From 155d75ad43bd4d9f17827a009648267dae337bf1 Mon Sep 17 00:00:00 2001 From: Tamir Date: Thu, 20 Apr 2023 04:55:35 -0300 Subject: [PATCH 044/265] Reorganize testing into two distinct types --- .../test/download_frota_integration_tests.py | 46 +++++++++++++++++++ ...a_test.py => download_frota_unit_tests.py} | 33 ------------- 2 files changed, 46 insertions(+), 33 deletions(-) create mode 100644 br_denatran_frota/code/test/download_frota_integration_tests.py rename br_denatran_frota/code/test/{download_frota_test.py => download_frota_unit_tests.py} (62%) diff --git a/br_denatran_frota/code/test/download_frota_integration_tests.py b/br_denatran_frota/code/test/download_frota_integration_tests.py new file mode 100644 index 000000000..6dab06b1e --- /dev/null +++ b/br_denatran_frota/code/test/download_frota_integration_tests.py @@ -0,0 +1,46 @@ +import os +import shutil +import tempfile +import unittest +import glob +from parameterized import parameterized +from download_frota import ( + DATASET, + MONTHS, + download_frota, +) + + +class TestDownloadFrota(unittest.TestCase): + def setUp(self): + file_dir = os.path.dirname(os.path.abspath(__file__)) + os.chdir(file_dir) + self.temp_dir = tempfile.TemporaryDirectory(dir=file_dir) + + def tearDown(self): + print("Deleting temporary directory") + shutil.rmtree(self.temp_dir.name) + + def test_download_frota_with_invalid_month(self): + with self.assertRaises(ValueError): + download_frota(13, 2013) + + @parameterized.expand( + [(month, year) for year in range(2021, 2023) for month in range(1, 12)], + name_func=custom_name_func, + ) + def test_download_post_2012(self, month, year): + download_frota(month, year, self.temp_dir.name) + expected_files = { + f"frota_por_uf_e_tipo_de_veículo_{month}-{year}", + f"frota_por_município_e_tipo_{month}-{year}", + } + list_of_files = os.listdir( + os.path.join(DATASET, self.temp_dir.name, "files", f"{year}") + ) + files = set(os.path.splitext(file)[0] for file in list_of_files) + self.assertEqual(files, expected_files) + + +if __name__ == "__main__": + unittest.main() diff --git a/br_denatran_frota/code/test/download_frota_test.py b/br_denatran_frota/code/test/download_frota_unit_tests.py similarity index 62% rename from br_denatran_frota/code/test/download_frota_test.py rename to br_denatran_frota/code/test/download_frota_unit_tests.py index 9972afb5b..cc212f612 100644 --- a/br_denatran_frota/code/test/download_frota_test.py +++ b/br_denatran_frota/code/test/download_frota_unit_tests.py @@ -10,8 +10,6 @@ MONTHS, make_filename, make_dir_when_not_exists, - download_frota, - download_post_2012, ) @@ -74,36 +72,5 @@ def test_make_dir_when_not_exists(self): self.assertTrue(os.path.exists(new_dir)) -class TestDownloadFrota(unittest.TestCase): - def setUp(self): - file_dir = os.path.dirname(os.path.abspath(__file__)) - os.chdir(file_dir) - self.temp_dir = tempfile.TemporaryDirectory(dir=file_dir) - - def tearDown(self): - print("Deleting temporary directory") - shutil.rmtree(self.temp_dir.name) - - def test_download_frota_with_invalid_month(self): - with self.assertRaises(ValueError): - download_frota(13, 2013) - - @parameterized.expand( - [(month, year) for year in range(2013, 2014) for month in range(1, 4)], - name_func=custom_name_func, - ) - def test_download_post_2012(self, month, year): - download_frota(month, year, self.temp_dir.name) - expected_files = { - f"frota_por_uf_e_tipo_de_veículo_{month}-{year}", - f"frota_por_município_e_tipo_{month}-{year}", - } - list_of_files = os.listdir( - os.path.join(DATASET, self.temp_dir.name, "files", f"{year}") - ) - files = set(os.path.splitext(file)[0] for file in list_of_files) - self.assertEqual(files, expected_files) - - if __name__ == "__main__": unittest.main() From 66afce1d6efcb16bd376e6b74de5d14d143630ff Mon Sep 17 00:00:00 2001 From: Tamir Date: Thu, 20 Apr 2023 05:24:54 -0300 Subject: [PATCH 045/265] More test rearranging --- .../code/test/download_frota_integration_tests.py | 13 ++++++++----- .../code/test/download_frota_unit_tests.py | 14 +++++++------- 2 files changed, 15 insertions(+), 12 deletions(-) diff --git a/br_denatran_frota/code/test/download_frota_integration_tests.py b/br_denatran_frota/code/test/download_frota_integration_tests.py index 6dab06b1e..331b35be8 100644 --- a/br_denatran_frota/code/test/download_frota_integration_tests.py +++ b/br_denatran_frota/code/test/download_frota_integration_tests.py @@ -11,7 +11,14 @@ ) -class TestDownloadFrota(unittest.TestCase): +def custom_name_func(testcase_func, param_num, param): + return "%s_%s" % ( + testcase_func.__name__, + parameterized.to_safe_name("_".join(str(x) for x in param.args)), + ) + + +class TestAllPossibleYears(unittest.TestCase): def setUp(self): file_dir = os.path.dirname(os.path.abspath(__file__)) os.chdir(file_dir) @@ -21,10 +28,6 @@ def tearDown(self): print("Deleting temporary directory") shutil.rmtree(self.temp_dir.name) - def test_download_frota_with_invalid_month(self): - with self.assertRaises(ValueError): - download_frota(13, 2013) - @parameterized.expand( [(month, year) for year in range(2021, 2023) for month in range(1, 12)], name_func=custom_name_func, diff --git a/br_denatran_frota/code/test/download_frota_unit_tests.py b/br_denatran_frota/code/test/download_frota_unit_tests.py index cc212f612..a128bf894 100644 --- a/br_denatran_frota/code/test/download_frota_unit_tests.py +++ b/br_denatran_frota/code/test/download_frota_unit_tests.py @@ -10,16 +10,10 @@ MONTHS, make_filename, make_dir_when_not_exists, + download_frota, ) -def custom_name_func(testcase_func, param_num, param): - return "%s_%s" % ( - testcase_func.__name__, - parameterized.to_safe_name("_".join(str(x) for x in param.args)), - ) - - dir_list = glob.glob(f"**/{DATASET}", recursive=True) if dir_list: # I always want to be in the actual folder for this dataset: @@ -72,5 +66,11 @@ def test_make_dir_when_not_exists(self): self.assertTrue(os.path.exists(new_dir)) +class TestDownloadFrota(unittest.TestCase): + def test_download_frota_with_invalid_month(self): + with self.assertRaises(ValueError): + download_frota(13, 2013) + + if __name__ == "__main__": unittest.main() From 5aab93c98c120fe23531f1f1d0dd4be886cc232e Mon Sep 17 00:00:00 2001 From: Tamir Date: Thu, 20 Apr 2023 07:28:33 -0300 Subject: [PATCH 046/265] Revert bugged discovery --- .../test/download_frota_integration_tests.py | 49 ------------------- ...a_unit_tests.py => download_frota_test.py} | 25 ++++++++++ 2 files changed, 25 insertions(+), 49 deletions(-) delete mode 100644 br_denatran_frota/code/test/download_frota_integration_tests.py rename br_denatran_frota/code/test/{download_frota_unit_tests.py => download_frota_test.py} (67%) diff --git a/br_denatran_frota/code/test/download_frota_integration_tests.py b/br_denatran_frota/code/test/download_frota_integration_tests.py deleted file mode 100644 index 331b35be8..000000000 --- a/br_denatran_frota/code/test/download_frota_integration_tests.py +++ /dev/null @@ -1,49 +0,0 @@ -import os -import shutil -import tempfile -import unittest -import glob -from parameterized import parameterized -from download_frota import ( - DATASET, - MONTHS, - download_frota, -) - - -def custom_name_func(testcase_func, param_num, param): - return "%s_%s" % ( - testcase_func.__name__, - parameterized.to_safe_name("_".join(str(x) for x in param.args)), - ) - - -class TestAllPossibleYears(unittest.TestCase): - def setUp(self): - file_dir = os.path.dirname(os.path.abspath(__file__)) - os.chdir(file_dir) - self.temp_dir = tempfile.TemporaryDirectory(dir=file_dir) - - def tearDown(self): - print("Deleting temporary directory") - shutil.rmtree(self.temp_dir.name) - - @parameterized.expand( - [(month, year) for year in range(2021, 2023) for month in range(1, 12)], - name_func=custom_name_func, - ) - def test_download_post_2012(self, month, year): - download_frota(month, year, self.temp_dir.name) - expected_files = { - f"frota_por_uf_e_tipo_de_veículo_{month}-{year}", - f"frota_por_município_e_tipo_{month}-{year}", - } - list_of_files = os.listdir( - os.path.join(DATASET, self.temp_dir.name, "files", f"{year}") - ) - files = set(os.path.splitext(file)[0] for file in list_of_files) - self.assertEqual(files, expected_files) - - -if __name__ == "__main__": - unittest.main() diff --git a/br_denatran_frota/code/test/download_frota_unit_tests.py b/br_denatran_frota/code/test/download_frota_test.py similarity index 67% rename from br_denatran_frota/code/test/download_frota_unit_tests.py rename to br_denatran_frota/code/test/download_frota_test.py index a128bf894..49fc203a6 100644 --- a/br_denatran_frota/code/test/download_frota_unit_tests.py +++ b/br_denatran_frota/code/test/download_frota_test.py @@ -67,10 +67,35 @@ def test_make_dir_when_not_exists(self): class TestDownloadFrota(unittest.TestCase): + def setUp(self): + file_dir = os.path.dirname(os.path.abspath(__file__)) + os.chdir(file_dir) + self.temp_dir = tempfile.TemporaryDirectory(dir=file_dir) + + def tearDown(self): + print("Deleting temporary directory") + shutil.rmtree(self.temp_dir.name) + def test_download_frota_with_invalid_month(self): with self.assertRaises(ValueError): download_frota(13, 2013) + @parameterized.expand( + [(month, year) for year in range(2013, 2014) for month in range(1, 4)], + name_func=custom_name_func, + ) + def test_download_post_2012(self, month, year): + download_frota(month, year, self.temp_dir.name) + expected_files = { + f"frota_por_uf_e_tipo_de_veículo_{month}-{year}", + f"frota_por_município_e_tipo_{month}-{year}", + } + list_of_files = os.listdir( + os.path.join(DATASET, self.temp_dir.name, "files", f"{year}") + ) + files = set(os.path.splitext(file)[0] for file in list_of_files) + self.assertEqual(files, expected_files) + if __name__ == "__main__": unittest.main() From 427ae9700de3e132da2fb5b2440cd8056105cde9 Mon Sep 17 00:00:00 2001 From: Tamir Date: Thu, 20 Apr 2023 07:32:41 -0300 Subject: [PATCH 047/265] Revert "Revert bugged discovery" This reverts commit 5aab93c98c120fe23531f1f1d0dd4be886cc232e. --- .../test/download_frota_integration_tests.py | 49 +++++++++++++++++++ ...a_test.py => download_frota_unit_tests.py} | 25 ---------- 2 files changed, 49 insertions(+), 25 deletions(-) create mode 100644 br_denatran_frota/code/test/download_frota_integration_tests.py rename br_denatran_frota/code/test/{download_frota_test.py => download_frota_unit_tests.py} (67%) diff --git a/br_denatran_frota/code/test/download_frota_integration_tests.py b/br_denatran_frota/code/test/download_frota_integration_tests.py new file mode 100644 index 000000000..331b35be8 --- /dev/null +++ b/br_denatran_frota/code/test/download_frota_integration_tests.py @@ -0,0 +1,49 @@ +import os +import shutil +import tempfile +import unittest +import glob +from parameterized import parameterized +from download_frota import ( + DATASET, + MONTHS, + download_frota, +) + + +def custom_name_func(testcase_func, param_num, param): + return "%s_%s" % ( + testcase_func.__name__, + parameterized.to_safe_name("_".join(str(x) for x in param.args)), + ) + + +class TestAllPossibleYears(unittest.TestCase): + def setUp(self): + file_dir = os.path.dirname(os.path.abspath(__file__)) + os.chdir(file_dir) + self.temp_dir = tempfile.TemporaryDirectory(dir=file_dir) + + def tearDown(self): + print("Deleting temporary directory") + shutil.rmtree(self.temp_dir.name) + + @parameterized.expand( + [(month, year) for year in range(2021, 2023) for month in range(1, 12)], + name_func=custom_name_func, + ) + def test_download_post_2012(self, month, year): + download_frota(month, year, self.temp_dir.name) + expected_files = { + f"frota_por_uf_e_tipo_de_veículo_{month}-{year}", + f"frota_por_município_e_tipo_{month}-{year}", + } + list_of_files = os.listdir( + os.path.join(DATASET, self.temp_dir.name, "files", f"{year}") + ) + files = set(os.path.splitext(file)[0] for file in list_of_files) + self.assertEqual(files, expected_files) + + +if __name__ == "__main__": + unittest.main() diff --git a/br_denatran_frota/code/test/download_frota_test.py b/br_denatran_frota/code/test/download_frota_unit_tests.py similarity index 67% rename from br_denatran_frota/code/test/download_frota_test.py rename to br_denatran_frota/code/test/download_frota_unit_tests.py index 49fc203a6..a128bf894 100644 --- a/br_denatran_frota/code/test/download_frota_test.py +++ b/br_denatran_frota/code/test/download_frota_unit_tests.py @@ -67,35 +67,10 @@ def test_make_dir_when_not_exists(self): class TestDownloadFrota(unittest.TestCase): - def setUp(self): - file_dir = os.path.dirname(os.path.abspath(__file__)) - os.chdir(file_dir) - self.temp_dir = tempfile.TemporaryDirectory(dir=file_dir) - - def tearDown(self): - print("Deleting temporary directory") - shutil.rmtree(self.temp_dir.name) - def test_download_frota_with_invalid_month(self): with self.assertRaises(ValueError): download_frota(13, 2013) - @parameterized.expand( - [(month, year) for year in range(2013, 2014) for month in range(1, 4)], - name_func=custom_name_func, - ) - def test_download_post_2012(self, month, year): - download_frota(month, year, self.temp_dir.name) - expected_files = { - f"frota_por_uf_e_tipo_de_veículo_{month}-{year}", - f"frota_por_município_e_tipo_{month}-{year}", - } - list_of_files = os.listdir( - os.path.join(DATASET, self.temp_dir.name, "files", f"{year}") - ) - files = set(os.path.splitext(file)[0] for file in list_of_files) - self.assertEqual(files, expected_files) - if __name__ == "__main__": unittest.main() From 73c8cadb8de1c058dab11aa643f46d09c232e95a Mon Sep 17 00:00:00 2001 From: Tamir Date: Thu, 20 Apr 2023 07:35:14 -0300 Subject: [PATCH 048/265] Discovery works --- ...ta_integration_tests.py => download_frota_integration_test.py} | 0 .../{download_frota_unit_tests.py => download_frota_unit_test.py} | 0 2 files changed, 0 insertions(+), 0 deletions(-) rename br_denatran_frota/code/test/{download_frota_integration_tests.py => download_frota_integration_test.py} (100%) rename br_denatran_frota/code/test/{download_frota_unit_tests.py => download_frota_unit_test.py} (100%) diff --git a/br_denatran_frota/code/test/download_frota_integration_tests.py b/br_denatran_frota/code/test/download_frota_integration_test.py similarity index 100% rename from br_denatran_frota/code/test/download_frota_integration_tests.py rename to br_denatran_frota/code/test/download_frota_integration_test.py diff --git a/br_denatran_frota/code/test/download_frota_unit_tests.py b/br_denatran_frota/code/test/download_frota_unit_test.py similarity index 100% rename from br_denatran_frota/code/test/download_frota_unit_tests.py rename to br_denatran_frota/code/test/download_frota_unit_test.py From 6df4a898d4d6a4685b6b8657e6fbed2b7186f73e Mon Sep 17 00:00:00 2001 From: Tamir Date: Fri, 21 Apr 2023 03:36:15 -0300 Subject: [PATCH 049/265] Pre commit enforcing py 3.9 --- .pre-commit-config.yaml | 1 - 1 file changed, 1 deletion(-) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 834971b77..354a09d96 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -12,7 +12,6 @@ repos: rev: 22.12.0 hooks: - id: black - language_version: python3.9 exclude: 'pipelines\/\{\{cookiecutter\.project_name\}\}.*' - repo: https://github.com/PyCQA/flake8 rev: 6.0.0 From 1d43c57adaf020904de79e33a6fa6953078f5bd9 Mon Sep 17 00:00:00 2001 From: Tamir Date: Fri, 21 Apr 2023 03:36:56 -0300 Subject: [PATCH 050/265] Add function to verify denatran total --- br_denatran_frota/code/utils.py | 17 +++++++++++++++++ 1 file changed, 17 insertions(+) diff --git a/br_denatran_frota/code/utils.py b/br_denatran_frota/code/utils.py index 572cfd331..40b73d2d9 100644 --- a/br_denatran_frota/code/utils.py +++ b/br_denatran_frota/code/utils.py @@ -1,4 +1,6 @@ +# -*- coding: utf-8 -*- import pandas as pd +import polars as pl import re DICT_UFS = { @@ -58,3 +60,18 @@ def get_year_month_from_filename(filename: str) -> tuple[int, int]: return month, year else: raise ValueError("No match found") + + +def verify_total(df: pl.DataFrame): + columns_for_total = df.select(pl.exclude("TOTAL")).select(pl.exclude([pl.Utf8])) + calculated_total = columns_for_total.select( + pl.fold( + acc=pl.lit(0), function=lambda acc, x: acc + x, exprs=pl.col("*") + ).alias("calculated_total") + )["calculated_total"] + + mask = df["TOTAL"] == calculated_total + if pl.sum(~mask) != 0: + raise ValueError( + "A coluna de TOTAL da base original tem inconsistências e não soma tudo das demais colunas." + ) From 30ca4cd610b05c97e6201b54aae2057d14356a74 Mon Sep 17 00:00:00 2001 From: Tamir Date: Fri, 21 Apr 2023 03:45:10 -0300 Subject: [PATCH 051/265] Wide to long now checks and removes total --- br_denatran_frota/code/frota_uf_tipo.py | 10 +++++++++- 1 file changed, 9 insertions(+), 1 deletion(-) diff --git a/br_denatran_frota/code/frota_uf_tipo.py b/br_denatran_frota/code/frota_uf_tipo.py index 3884c9349..213f52cc9 100644 --- a/br_denatran_frota/code/frota_uf_tipo.py +++ b/br_denatran_frota/code/frota_uf_tipo.py @@ -1,7 +1,13 @@ +# -*- coding: utf-8 -*- import polars as pl import pandas as pd import os -from utils import guess_header, change_df_header, get_year_month_from_filename +from utils import ( + guess_header, + change_df_header, + get_year_month_from_filename, + verify_total, +) DICT_UFS = { @@ -49,11 +55,13 @@ def treat_uf_tipo(file) -> pl.DataFrame: ) # Now we get all the actual RELEVANT uf data. month, year = get_year_month_from_filename(filename) clean_pl_df = pl.from_pandas(clean_df).lazy() + verify_total(clean_pl_df.collect()) # Add year and month clean_pl_df = clean_pl_df.with_columns( pl.lit(year, dtype=pl.Int64).alias("ano"), pl.lit(month, dtype=pl.Int64).alias("mes"), ) + clean_pl_df = clean_pl_df.select(pl.exclude("TOTAL")) clean_pl_df = clean_pl_df.melt( id_vars=["ano", "mes", "sigla_uf"], variable_name="tipo_veiculo", From 830ad07f1cf5b06973624e694d5126ba10b4eae2 Mon Sep 17 00:00:00 2001 From: Tamir Date: Fri, 21 Apr 2023 18:44:51 -0300 Subject: [PATCH 052/265] Adds packages for manage.py to work --- poetry.lock | 114 ++++++++++++++++++++++++++++++++++++++++++++++++- pyproject.toml | 3 ++ 2 files changed, 116 insertions(+), 1 deletion(-) diff --git a/poetry.lock b/poetry.lock index 271795492..ea7af3f74 100644 --- a/poetry.lock +++ b/poetry.lock @@ -12,6 +12,21 @@ files = [ {file = "appnope-0.1.3.tar.gz", hash = "sha256:02bd91c4de869fbb1e1c50aafc4098827a7a54ab2f39d9dcba6c9547ed920e24"}, ] +[[package]] +name = "arrow" +version = "1.2.3" +description = "Better dates & times for Python" +category = "main" +optional = false +python-versions = ">=3.6" +files = [ + {file = "arrow-1.2.3-py3-none-any.whl", hash = "sha256:5a49ab92e3b7b71d96cd6bfcc4df14efefc9dfa96ea19045815914a6ab6b1fe2"}, + {file = "arrow-1.2.3.tar.gz", hash = "sha256:3934b30ca1b9f292376d9db15b19446088d12ec58629bc3f0da28fd55fb633a1"}, +] + +[package.dependencies] +python-dateutil = ">=2.7.0" + [[package]] name = "asttokens" version = "2.2.1" @@ -123,6 +138,21 @@ soupsieve = ">1.2" html5lib = ["html5lib"] lxml = ["lxml"] +[[package]] +name = "binaryornot" +version = "0.4.4" +description = "Ultra-lightweight pure Python package to check if a file is binary or text." +category = "main" +optional = false +python-versions = "*" +files = [ + {file = "binaryornot-0.4.4-py2.py3-none-any.whl", hash = "sha256:b8b71173c917bddcd2c16070412e369c3ed7f0528926f70cac18a6c97fd563e4"}, + {file = "binaryornot-0.4.4.tar.gz", hash = "sha256:359501dfc9d40632edc9fac890e19542db1a287bbcfa58175b66658392018061"}, +] + +[package.dependencies] +chardet = ">=3.0.2" + [[package]] name = "cachetools" version = "4.2.4" @@ -236,6 +266,18 @@ files = [ {file = "cfgv-3.3.1.tar.gz", hash = "sha256:f5a830efb9ce7a445376bb66ec94c638a9787422f96264c98edc6bdeed8ab736"}, ] +[[package]] +name = "chardet" +version = "5.1.0" +description = "Universal encoding detector for Python 3" +category = "main" +optional = false +python-versions = ">=3.7" +files = [ + {file = "chardet-5.1.0-py3-none-any.whl", hash = "sha256:362777fb014af596ad31334fde1e8c327dfdb076e1960d1694662d46a6917ab9"}, + {file = "chardet-5.1.0.tar.gz", hash = "sha256:0d62712b956bc154f85fb0a266e2a3c5913c2967e00348701b32411d6def31e5"}, +] + [[package]] name = "charset-normalizer" version = "2.0.8" @@ -403,6 +445,27 @@ mypy = ["contourpy[bokeh]", "docutils-stubs", "mypy (==0.991)", "types-Pillow"] test = ["Pillow", "matplotlib", "pytest"] test-no-images = ["pytest"] +[[package]] +name = "cookiecutter" +version = "2.1.1" +description = "A command-line utility that creates projects from project templates, e.g. creating a Python package project from a Python package project template." +category = "main" +optional = false +python-versions = ">=3.7" +files = [ + {file = "cookiecutter-2.1.1-py2.py3-none-any.whl", hash = "sha256:9f3ab027cec4f70916e28f03470bdb41e637a3ad354b4d65c765d93aad160022"}, + {file = "cookiecutter-2.1.1.tar.gz", hash = "sha256:f3982be8d9c53dac1261864013fdec7f83afd2e42ede6f6dd069c5e149c540d5"}, +] + +[package.dependencies] +binaryornot = ">=0.4.4" +click = ">=7.0,<9.0.0" +Jinja2 = ">=2.7,<4.0.0" +jinja2-time = ">=0.2.0" +python-slugify = ">=4.0.0" +pyyaml = ">=5.3.1" +requests = ">=2.23.0" + [[package]] name = "coverage" version = "7.2.3" @@ -1456,6 +1519,22 @@ MarkupSafe = ">=2.0" [package.extras] i18n = ["Babel (>=2.7)"] +[[package]] +name = "jinja2-time" +version = "0.2.0" +description = "Jinja2 Extension for Dates and Times" +category = "main" +optional = false +python-versions = "*" +files = [ + {file = "jinja2-time-0.2.0.tar.gz", hash = "sha256:d14eaa4d315e7688daa4969f616f226614350c48730bfa1692d2caebd8c90d40"}, + {file = "jinja2_time-0.2.0-py2.py3-none-any.whl", hash = "sha256:d3eab6605e3ec8b7a0863df09cc1d23714908fa61aa6986a845c20ba488b4efa"}, +] + +[package.dependencies] +arrow = "*" +jinja2 = "*" + [[package]] name = "jupyter-client" version = "7.3.4" @@ -2871,6 +2950,18 @@ text-unidecode = ">=1.3" [package.extras] unidecode = ["Unidecode (>=1.1.1)"] +[[package]] +name = "python-string-utils" +version = "1.0.0" +description = "Utility functions for strings validation and manipulation." +category = "main" +optional = false +python-versions = ">=3.5" +files = [ + {file = "python-string-utils-1.0.0.tar.gz", hash = "sha256:dcf9060b03f07647c0a603408dc8b03f807f3b54a05c6e19eb14460256fac0cb"}, + {file = "python_string_utils-1.0.0-py3-none-any.whl", hash = "sha256:f1a88700baf99db1a9b6953f44181ad9ca56623c81e257e6009707e2e7851fa4"}, +] + [[package]] name = "pytz" version = "2021.3" @@ -3540,6 +3631,27 @@ dev = ["coveralls (>=2.1.0)", "tox (>=3.14.0)"] socks = ["requests[socks] (>=2.11.1,<3)"] test = ["vcrpy (>=1.10.3)"] +[[package]] +name = "typer" +version = "0.7.0" +description = "Typer, build great CLIs. Easy to code. Based on Python type hints." +category = "main" +optional = false +python-versions = ">=3.6" +files = [ + {file = "typer-0.7.0-py3-none-any.whl", hash = "sha256:b5e704f4e48ec263de1c0b3a2387cd405a13767d2f907f44c1a08cbad96f606d"}, + {file = "typer-0.7.0.tar.gz", hash = "sha256:ff797846578a9f2a201b53442aedeb543319466870fbe1c701eab66dd7681165"}, +] + +[package.dependencies] +click = ">=7.1.1,<9.0.0" + +[package.extras] +all = ["colorama (>=0.4.3,<0.5.0)", "rich (>=10.11.0,<13.0.0)", "shellingham (>=1.3.0,<2.0.0)"] +dev = ["autoflake (>=1.3.1,<2.0.0)", "flake8 (>=3.8.3,<4.0.0)", "pre-commit (>=2.17.0,<3.0.0)"] +doc = ["cairosvg (>=2.5.2,<3.0.0)", "mdx-include (>=1.4.1,<2.0.0)", "mkdocs (>=1.1.2,<2.0.0)", "mkdocs-material (>=8.1.4,<9.0.0)", "pillow (>=9.3.0,<10.0.0)"] +test = ["black (>=22.3.0,<23.0.0)", "coverage (>=6.2,<7.0)", "isort (>=5.0.6,<6.0.0)", "mypy (==0.910)", "pytest (>=4.4.0,<8.0.0)", "pytest-cov (>=2.10.0,<5.0.0)", "pytest-sugar (>=0.9.4,<0.10.0)", "pytest-xdist (>=1.32.0,<4.0.0)", "rich (>=10.11.0,<13.0.0)", "shellingham (>=1.3.0,<2.0.0)"] + [[package]] name = "typing-extensions" version = "4.5.0" @@ -3731,4 +3843,4 @@ testing = ["big-O", "flake8 (<5)", "jaraco.functools", "jaraco.itertools", "more [metadata] lock-version = "2.0" python-versions = ">=3.8,<3.11" -content-hash = "a06307115a26fddb569266cf3c030d7aad2fe2318ab9ce079581ffbc48e861bb" +content-hash = "a3e71799a5863e871ed54be65449b470cc7a73f6aafea6cb4a192ed70ccc580f" diff --git a/pyproject.toml b/pyproject.toml index b1ea4270f..65a8f5a47 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -102,6 +102,9 @@ setuptools = "^67.6.1" polars = "^0.17.5" xlsx2csv = "^0.8.1" xlrd = "^2.0.1" +typer = "^0.7.0" +cookiecutter = "^2.1.1" +python-string-utils = "^1.0.0" [tool.poetry.dev-dependencies] pytest_cov = "^3.0.0" From 7e6303df2986741dde1f2b78f4c1b4bfaea58ba7 Mon Sep 17 00:00:00 2001 From: Tamir Date: Fri, 21 Apr 2023 18:45:33 -0300 Subject: [PATCH 053/265] Create pipeline folder structure --- pipelines/datasets/__init__.py | 1 + .../datasets/br_denatran_frota/__init__.py | 0 .../datasets/br_denatran_frota/constants.py | 42 +++++++++ pipelines/datasets/br_denatran_frota/flows.py | 81 +++++++++++++++++ .../datasets/br_denatran_frota/schedules.py | 88 +++++++++++++++++++ pipelines/datasets/br_denatran_frota/tasks.py | 60 +++++++++++++ pipelines/datasets/br_denatran_frota/utils.py | 31 +++++++ 7 files changed, 303 insertions(+) create mode 100644 pipelines/datasets/br_denatran_frota/__init__.py create mode 100644 pipelines/datasets/br_denatran_frota/constants.py create mode 100644 pipelines/datasets/br_denatran_frota/flows.py create mode 100644 pipelines/datasets/br_denatran_frota/schedules.py create mode 100644 pipelines/datasets/br_denatran_frota/tasks.py create mode 100644 pipelines/datasets/br_denatran_frota/utils.py diff --git a/pipelines/datasets/__init__.py b/pipelines/datasets/__init__.py index cb3fe714e..47a8fe679 100644 --- a/pipelines/datasets/__init__.py +++ b/pipelines/datasets/__init__.py @@ -24,3 +24,4 @@ from pipelines.datasets.br_me_caged.flows import * from pipelines.datasets.br_ibge_pnadc.flows import * from pipelines.datasets.cross_update.flows import * +from pipelines.datasets.br_denatran_frota.flows import * diff --git a/pipelines/datasets/br_denatran_frota/__init__.py b/pipelines/datasets/br_denatran_frota/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/pipelines/datasets/br_denatran_frota/constants.py b/pipelines/datasets/br_denatran_frota/constants.py new file mode 100644 index 000000000..a323827db --- /dev/null +++ b/pipelines/datasets/br_denatran_frota/constants.py @@ -0,0 +1,42 @@ +# -*- coding: utf-8 -*- +""" +Constant values for the datasets projects +""" + + +############################################################################### +# +# Esse é um arquivo onde podem ser declaratas constantes que serão usadas +# pelo projeto br_denatran_frota. +# +# Por ser um arquivo opcional, pode ser removido sem prejuízo ao funcionamento +# do projeto, caos não esteja em uso. +# +# Para declarar constantes, basta fazer conforme o exemplo abaixo: +# +# ``` +# class constants(Enum): +# """ +# Constant values for the br_denatran_frota project +# """ +# FOO = "bar" +# ``` +# +# Para usá-las, basta fazer conforme o exemplo abaixo: +# +# ```py +# from pipelines.datasets.br_denatran_frota.constants import constants +# print(constants.FOO.value) +# ``` +# +############################################################################### + +from enum import Enum + + +class constants(Enum): # pylint: disable=c0103 + """ + Constant values for the br_denatran_frota project + """ + + FOO = "bar" diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py new file mode 100644 index 000000000..0d45deb50 --- /dev/null +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -0,0 +1,81 @@ +# -*- coding: utf-8 -*- +""" +Flows for br_denatran_frota +""" + +############################################################################### +# +# Aqui é onde devem ser definidos os flows do projeto. +# Cada flow representa uma sequência de passos que serão executados +# em ordem. +# +# Mais informações sobre flows podem ser encontradas na documentação do +# Prefect: https://docs.prefect.io/core/concepts/flows.html +# +# De modo a manter consistência na codebase, todo o código escrito passará +# pelo pylint. Todos os warnings e erros devem ser corrigidos. +# +# Existem diversas maneiras de declarar flows. No entanto, a maneira mais +# conveniente e recomendada pela documentação é usar a API funcional. +# Em essência, isso implica simplesmente na chamada de funções, passando +# os parâmetros necessários para a execução em cada uma delas. +# +# Também, após a definição de um flow, para o adequado funcionamento, é +# mandatório configurar alguns parâmetros dele, os quais são: +# - storage: onde esse flow está armazenado. No caso, o storage é o +# próprio módulo Python que contém o flow. Sendo assim, deve-se +# configurar o storage como o pipelines.datasets +# - run_config: para o caso de execução em cluster Kubernetes, que é +# provavelmente o caso, é necessário configurar o run_config com a +# imagem Docker que será usada para executar o flow. Assim sendo, +# basta usar constants.DOCKER_IMAGE.value, que é automaticamente +# gerado. +# - schedule (opcional): para o caso de execução em intervalos regulares, +# deve-se utilizar algum dos schedules definidos em schedules.py +# +# Um exemplo de flow, considerando todos os pontos acima, é o seguinte: +# +# ----------------------------------------------------------------------------- +# from prefect import task +# from prefect import Flow +# from prefect.run_configs import KubernetesRun +# from prefect.storage import GCS +# from pipelines.constants import constants +# from my_tasks import my_task, another_task +# from my_schedules import some_schedule +# +# with Flow("my_flow") as flow: +# a = my_task(param1=1, param2=2) +# b = another_task(a, param3=3) +# +# flow.storage = GCS(constants.GCS_FLOWS_BUCKET.value) +# flow.run_config = KubernetesRun(image=constants.DOCKER_IMAGE.value) +# flow.schedule = some_schedule +# ----------------------------------------------------------------------------- +# +# Abaixo segue um código para exemplificação, que pode ser removido. +# +############################################################################### + + +from prefect.run_configs import KubernetesRun +from prefect.storage import GCS +from pipelines.constants import constants +from pipelines.datasets.br_denatran_frota.tasks import say_hello + +# from pipelines.datasets.br_denatran_frota.schedules import every_two_weeks +from pipelines.utils.decorators import Flow + +with Flow( + name="my_flow", + code_owners=[ + "discord-username", + ], +) as datasets_br_denatran_frota_flow: + say_hello() + +datasets_br_denatran_frota_flow.storage = GCS(constants.GCS_FLOWS_BUCKET.value) +datasets_br_denatran_frota_flow.run_config = KubernetesRun( + image=constants.DOCKER_IMAGE.value +) +# flow.schedule = every_two_weeks diff --git a/pipelines/datasets/br_denatran_frota/schedules.py b/pipelines/datasets/br_denatran_frota/schedules.py new file mode 100644 index 000000000..8967b8c93 --- /dev/null +++ b/pipelines/datasets/br_denatran_frota/schedules.py @@ -0,0 +1,88 @@ +# -*- coding: utf-8 -*- +""" +Schedules for br_denatran_frota +""" + +############################################################################### +# +# Aqui é onde devem ser definidos os schedules para os flows do projeto. +# Cada schedule indica o intervalo de tempo entre as execuções. +# Um schedule pode ser definido para um ou mais flows. +# Mais informações sobre schedules podem ser encontradas na documentação do +# Prefect: https://docs.prefect.io/core/concepts/schedules.html +# +# De modo a manter consistência na codebase, todo o código escrito passará +# pelo pylint. Todos os warnings e erros devem ser corrigidos. +# +# Os schedules devem ser definidos de acordo com a sintaxe do Prefect, como, +# por exemplo, o seguinte (para executar a cada 1 minuto): +# +# ----------------------------------------------------------------------------- +# from datetime import timedelta, datetime +# from prefect.schedules import Schedule +# from prefect.schedules.clocks import IntervalClock +# from pipelines.constants import constants +# +# minute_schedule = Schedule( +# clocks=[ +# IntervalClock( +# interval=timedelta(minutes=1), +# start_date=datetime(2021, 1, 1), +# labels=[ +# constants.DATASETS_AGENT_LABEL.value, +# ] +# ), +# ] +# ) +# ----------------------------------------------------------------------------- +# +# Vale notar que o parâmetro `labels` é obrigatório e deve ser uma lista com +# apenas um elemento, correspondendo ao label do agente que será executado. +# O label do agente é definido em `constants.py` e deve ter o formato +# `DATASETS_AGENT_LABEL`. +# +# Outro exemplo, para executar todos os dias à meia noite, segue abaixo: +# +# ----------------------------------------------------------------------------- +# from prefect import task +# from datetime import timedelta +# import pendulum +# from prefect.schedules import Schedule +# from prefect.schedules.clocks import IntervalClock +# from pipelines.constants import constants +# +# every_day_at_midnight = Schedule( +# clocks=[ +# IntervalClock( +# interval=timedelta(days=1), +# start_date=pendulum.datetime( +# 2021, 1, 1, 0, 0, 0, tz="America/Sao_Paulo"), +# labels=[ +# constants.K8S_AGENT_LABEL.value, +# ] +# ) +# ] +# ) +# ----------------------------------------------------------------------------- +# +# Abaixo segue um código para exemplificação, que pode ser removido. +# +############################################################################### + + +from datetime import timedelta, datetime +from prefect.schedules import Schedule +from prefect.schedules.clocks import IntervalClock +from pipelines.constants import constants + +every_two_weeks = Schedule( + clocks=[ + IntervalClock( + interval=timedelta(weeks=2), + start_date=datetime(2021, 1, 1), + labels=[ + constants.DATASETS_AGENT_LABEL.value, + ], + ), + ] +) diff --git a/pipelines/datasets/br_denatran_frota/tasks.py b/pipelines/datasets/br_denatran_frota/tasks.py new file mode 100644 index 000000000..8ec526846 --- /dev/null +++ b/pipelines/datasets/br_denatran_frota/tasks.py @@ -0,0 +1,60 @@ +# -*- coding: utf-8 -*- +""" +Tasks for br_denatran_frota +""" + +############################################################################### +# +# Aqui é onde devem ser definidas as tasks para os flows do projeto. +# Cada task representa um passo da pipeline. Não é estritamente necessário +# tratar todas as exceções que podem ocorrer durante a execução de uma task, +# mas é recomendável, ainda que não vá implicar em uma quebra no sistema. +# Mais informações sobre tasks podem ser encontradas na documentação do +# Prefect: https://docs.prefect.io/core/concepts/tasks.html +# +# De modo a manter consistência na codebase, todo o código escrito passará +# pelo pylint. Todos os warnings e erros devem ser corrigidos. +# +# As tasks devem ser definidas como funções comuns ao Python, com o decorador +# @task acima. É recomendado inserir type hints para as variáveis. +# +# Um exemplo de task é o seguinte: +# +# ----------------------------------------------------------------------------- +# from prefect import task +# +# @task +# def my_task(param1: str, param2: int) -> str: +# """ +# My task description. +# """ +# return f'{param1} {param2}' +# ----------------------------------------------------------------------------- +# +# Você também pode usar pacotes Python arbitrários, como numpy, pandas, etc. +# +# ----------------------------------------------------------------------------- +# from prefect import task +# import numpy as np +# +# @task +# def my_task(a: np.ndarray, b: np.ndarray) -> str: +# """ +# My task description. +# """ +# return np.add(a, b) +# ----------------------------------------------------------------------------- +# +# Abaixo segue um código para exemplificação, que pode ser removido. +# +############################################################################### + +from prefect import task + + +@task # noqa +def say_hello(name: str = "World") -> str: + """ + Greeting task. + """ + return f"Hello, {name}!" diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py new file mode 100644 index 000000000..45810ab91 --- /dev/null +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -0,0 +1,31 @@ +# -*- coding: utf-8 -*- +""" +General purpose functions for the br_denatran_frota project +""" + +############################################################################### +# +# Esse é um arquivo onde podem ser declaratas funções que serão usadas +# pelo projeto br_denatran_frota. +# +# Por ser um arquivo opcional, pode ser removido sem prejuízo ao funcionamento +# do projeto, caos não esteja em uso. +# +# Para declarar funções, basta fazer em código Python comum, como abaixo: +# +# ``` +# def foo(): +# """ +# Function foo +# """ +# print("foo") +# ``` +# +# Para usá-las, basta fazer conforme o exemplo abaixo: +# +# ```py +# from pipelines.datasets.br_denatran_frota.utils import foo +# foo() +# ``` +# +############################################################################### From 7779e0ad99bfe0122d2efbc41cc7af0613df1cf8 Mon Sep 17 00:00:00 2001 From: Tamir Date: Sat, 22 Apr 2023 18:39:12 -0300 Subject: [PATCH 054/265] Just for stashing --- br_denatran_frota/code/test_drive.ipynb | 321 ++++++++++++------ ...ta_por_munic\303\255pio_e_tipo_2-2022.xls" | Bin 0 -> 1183744 bytes ...or_uf_e_tipo_de_ve\303\255culo_2-2022.xls" | Bin 0 -> 33792 bytes 3 files changed, 218 insertions(+), 103 deletions(-) create mode 100644 "br_denatran_frota/files/2022/frota_por_munic\303\255pio_e_tipo_2-2022.xls" create mode 100644 "br_denatran_frota/files/2022/frota_por_uf_e_tipo_de_ve\303\255culo_2-2022.xls" diff --git a/br_denatran_frota/code/test_drive.ipynb b/br_denatran_frota/code/test_drive.ipynb index 576cd333a..7bb9411db 100644 --- a/br_denatran_frota/code/test_drive.ipynb +++ b/br_denatran_frota/code/test_drive.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 8, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -15,7 +15,8 @@ "from zipfile import ZipFile\n", "from rarfile import RarFile\n", "from bs4 import BeautifulSoup\n", - "import requests\n", + "import difflib\n", + "from utils import guess_header, change_df_header, get_year_month_from_filename, treat_uf_tipo\n", "DICT_UFS = {\n", " \"AC\": \"Acre\",\n", " \"AL\": \"Alagoas\",\n", @@ -49,129 +50,243 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "#treat_uf_tipo('../files/2022/frota_por_uf_e_tipo_de_veículo_2-2022.xls')" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "from download_frota import download_frota" + ] + }, + { + "cell_type": "code", + "execution_count": 9, "metadata": {}, "outputs": [ { - "data": { - "text/html": [ - "
\n", - "shape: (594, 5)
anomessigla_uftipo_veiculoquantidade
i64i64strstri64
20222"Acre""TOTAL"321989
20222"Amapá""TOTAL"225303
20222"Amazonas""TOTAL"1020046
20222"Pará""TOTAL"2367668
20222"Rondônia""TOTAL"1118903
20222"Roraima""TOTAL"252315
20222"Tocantins""TOTAL"796159
20222"Alagoas""TOTAL"988002
20222"Bahia""TOTAL"4720073
20222"Ceará""TOTAL"3529429
20222"Maranhão""TOTAL"1950201
20222"Paraíba""TOTAL"1477707
……………
20222"Sergipe""UTILITÁRIO"7459
20222"Espírito Santo…"UTILITÁRIO"29102
20222"Minas Gerais""UTILITÁRIO"116020
20222"Rio de Janeiro…"UTILITÁRIO"88531
20222"São Paulo""UTILITÁRIO"410642
20222"Paraná""UTILITÁRIO"93204
20222"Rio Grande do …"UTILITÁRIO"93702
20222"Santa Catarina…"UTILITÁRIO"105113
20222"Distrito Feder…"UTILITÁRIO"39414
20222"Goiás""UTILITÁRIO"43899
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" - ], - "text/plain": [ - "shape: (594, 5)\n", - "┌──────┬─────┬────────────────────┬──────────────┬────────────┐\n", - "│ ano ┆ mes ┆ sigla_uf ┆ tipo_veiculo ┆ quantidade │\n", - "│ --- ┆ --- ┆ --- ┆ --- ┆ --- │\n", - "│ i64 ┆ i64 ┆ str ┆ str ┆ i64 │\n", - "╞══════╪═════╪════════════════════╪══════════════╪════════════╡\n", - "│ 2022 ┆ 2 ┆ Acre ┆ TOTAL ┆ 321989 │\n", - "│ 2022 ┆ 2 ┆ Amapá ┆ TOTAL ┆ 225303 │\n", - "│ 2022 ┆ 2 ┆ Amazonas ┆ TOTAL ┆ 1020046 │\n", - "│ 2022 ┆ 2 ┆ Pará ┆ TOTAL ┆ 2367668 │\n", - "│ … ┆ … ┆ … ┆ … ┆ … │\n", - "│ 2022 ┆ 2 ┆ Distrito Federal ┆ UTILITÁRIO ┆ 39414 │\n", - "│ 2022 ┆ 2 ┆ Goiás ┆ UTILITÁRIO ┆ 43899 │\n", - "│ 2022 ┆ 2 ┆ Mato Grosso ┆ UTILITÁRIO ┆ 24451 │\n", - "│ 2022 ┆ 2 ┆ Mato Grosso do Sul ┆ UTILITÁRIO ┆ 19279 │\n", - "└──────┴─────┴────────────────────┴──────────────┴────────────┘" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" + "name": "stdout", + "output_type": "stream", + "text": [ + "Download of frota_por_uf_e_tipo_de_veículo_2-2022.xls complete\n", + "Download of frota_por_município_e_tipo_2-2022.xls complete\n" + ] } ], "source": [ + "download_frota(2, 2022)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/tamir/.cache/pypoetry/virtualenvs/pipelines-Fyk5jlG0-py3.10/lib/python3.10/site-packages/requests/__init__.py:102: RequestsDependencyWarning: urllib3 (1.26.7) or chardet (5.1.0)/charset_normalizer (2.0.8) doesn't match a supported version!\n", + " warnings.warn(\"urllib3 ({}) or chardet ({})/charset_normalizer ({}) doesn't match a supported \"\n", + "Downloading: 100%|██████████| 5570/5570 [00:00<00:00, 10744.58rows/s]\n" + ] + } + ], + "source": [ + "import basedosdados as bd \n", + "municipios_query = \"\"\"SELECT nome, id_municipio, sigla_uf FROM `basedosdados.br_bd_diretorios_brasil.municipio`\n", + "\"\"\"\n", + "bd_municipios = bd.read_sql(municipios_query, 'tamir-pipelines')\n", + "bd_municipios = pl.from_pandas(bd_municipios)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "file = '../files/2022/frota_por_município_e_tipo_2-2022.xls'\n", + "filename = os.path.split(file)[1]\n", + "df = pd.read_excel(file)\n", + "new_df = change_df_header(df, guess_header(df))\n", + "new_df.rename(columns={ new_df.columns[0]: \"sigla_uf\" , new_df.columns[1]: 'nome_denatran'}, inplace= True) # Rename for ease of use.\n", + "new_df.sigla_uf = new_df.sigla_uf.str.strip() # Remove whitespace.\n", + "new_df = pl.from_pandas(new_df)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "uf = 'RN'" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "# for uf in DICT_UFS:\n", + "denatran_uf = new_df.filter(pl.col('sigla_uf') == uf)\n", + "ibge_uf = bd_municipios.filter(pl.col('sigla_uf') == uf)\n", + "ibge_uf = ibge_uf.with_columns(pl.col('nome').str.to_lowercase())" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'denatran_uf' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[1], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m denatran_uf\n", + "\u001b[0;31mNameError\u001b[0m: name 'denatran_uf' is not defined" + ] + } + ], + "source": [ + "denatran_uf" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "def get_city_name_ibge(denatran_name: str):\n", + " matches = difflib.get_close_matches(denatran_name.lower(), ibge_uf['nome'].str.to_lowercase(), n = 1)\n", + " if matches:\n", + " return matches[0]\n", + " else:\n", + " return '' # I don't want this to error out directly, because then I can get all municipalities.\n", + "x = denatran_uf['nome_denatran'].apply(get_city_name_ibge)\n", + "denatran_uf = denatran_uf.with_columns(x.alias('suggested_nome_ibge'))" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "def match_ibge(denatran_uf: pl.DataFrame, ibge_uf: pl.DataFrame):\n", + " joined_df = denatran_uf.join(ibge_uf, left_on=['suggested_nome_ibge', 'sigla_uf'], right_on=['nome', 'sigla_uf'], how='left')\n", + " mismatched_rows = joined_df.filter(pl.col('id_municipio').is_null())\n", "\n", - "def guess_header(df: pd.DataFrame, max_header_guess: int = 4) -> int:\n", - " header_guess = 0\n", - " while header_guess < max_header_guess:\n", - " # Iffy logic, but essentially: if all rows of the column are strings, then this is a good candidate for a header.\n", - " if all(df.iloc[header_guess].apply(lambda x: isinstance(x, str))):\n", - " return header_guess\n", - " \n", - " header_guess += 1\n", - " return 0 # If nothing is ever found until the max, let's just assume it's the first row as per usual. \n", - "\n", - "def change_df_header(df: pd.DataFrame, header_row: int) -> pd.DataFrame:\n", - " new_header = df.iloc[header_row]\n", - " new_df = df[(header_row+1):].reset_index(drop=True)\n", - " new_df.rename(columns=new_header, inplace=True)\n", - " return new_df\n", - "\n", - "def get_year_month_from_filename(filename: str) -> tuple[int, int]:\n", - " match = re.search(r\"(\\w+)_(\\d{1,2})-(\\d{4})\\.(xls|xlsx)$\"\n", - "\n", - ", filename)\n", + " if len(mismatched_rows) > 0:\n", + " error_message = \"Os seguintes municípios falharam: \\n\"\n", + " for row in mismatched_rows.rows(named = True):\n", + " error_message += f\"{row['nome_denatran']} ({row['sigla_uf']})\\n\"\n", + " raise ValueError(error_message)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "ename": "ValueError", + "evalue": "Os seguintes municípios falharam: \nASSU (RN)\n", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[9], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m match_ibge(denatran_uf, ibge_uf)\n", + "Cell \u001b[0;32mIn[8], line 9\u001b[0m, in \u001b[0;36mmatch_ibge\u001b[0;34m(denatran_uf, ibge_uf)\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[39mfor\u001b[39;00m row \u001b[39min\u001b[39;00m mismatched_rows\u001b[39m.\u001b[39mrows(named \u001b[39m=\u001b[39m \u001b[39mTrue\u001b[39;00m):\n\u001b[1;32m 8\u001b[0m error_message \u001b[39m+\u001b[39m\u001b[39m=\u001b[39m \u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39m{\u001b[39;00mrow[\u001b[39m'\u001b[39m\u001b[39mnome_denatran\u001b[39m\u001b[39m'\u001b[39m]\u001b[39m}\u001b[39;00m\u001b[39m (\u001b[39m\u001b[39m{\u001b[39;00mrow[\u001b[39m'\u001b[39m\u001b[39msigla_uf\u001b[39m\u001b[39m'\u001b[39m]\u001b[39m}\u001b[39;00m\u001b[39m)\u001b[39m\u001b[39m\\n\u001b[39;00m\u001b[39m\"\u001b[39m\n\u001b[0;32m----> 9\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mValueError\u001b[39;00m(error_message)\n", + "\u001b[0;31mValueError\u001b[0m: Os seguintes municípios falharam: \nASSU (RN)\n" + ] + } + ], + "source": [ + "match_ibge(denatran_uf, ibge_uf)" + ] + }, + { + "cell_type": "code", + "execution_count": 232, + "metadata": {}, + "outputs": [], + "source": [ + "joined_df = denatran_uf.join(ibge_uf, left_on=['suggested_nome_ibge', 'sigla_uf'], right_on=['nome', 'sigla_uf'], how='left')\n", "\n", - " if match:\n", - " month = match.group(2)\n", - " year = match.group(3)\n", - " return month, year\n", - " else:\n", - " raise ValueError(\"No match found\")\n", - "def treat_uf_tipo(file):\n", - " filename = os.path.split(file)[1]\n", - " df = pd.read_excel(file)\n", - " new_df = change_df_header(df, guess_header(df))\n", - " # This is ad hoc for UF_tipo.\n", - " new_df.rename(columns={ new_df.columns[0]: \"sigla_uf\" }, inplace= True) # Rename for ease of use.\n", - " new_df.sigla_uf = new_df.sigla_uf.str.strip() # Remove whitespace.\n", - " clean_df = new_df[new_df.sigla_uf.isin(DICT_UFS.values())].reset_index(drop = True) # Now we get all the actual RELEVANT uf data.\n", - " month, year = get_year_month_from_filename(filename)\n", - " clean_pl_df = pl.from_pandas(clean_df).lazy()\n", - "# Add year and month\n", - " clean_pl_df = clean_pl_df.with_columns(pl.lit(year, dtype = pl.Int64).alias('ano'), pl.lit(month, dtype = pl.Int64).alias('mes'))\n", - " clean_pl_df = clean_pl_df.melt(id_vars = ['ano', 'mes', 'sigla_uf'], variable_name= 'tipo_veiculo', value_name= 'quantidade') # Long format.\n", - " return clean_pl_df.collect()\n", - "treat_uf_tipo('../files/2022/frota_por_uf_e_tipo_de_veículo_2-2022.xls')" + "mismatched = joined_df.filter(pl.col('id_municipio').is_null())" ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 146, "metadata": {}, "outputs": [], - "source": [] + "source": [ + "def verify_total(df: pl.DataFrame):\n", + " columns_for_total = df.select( pl.exclude(\"TOTAL\")).select(pl.exclude([pl.Utf8]))\n", + " calculated_total = columns_for_total.select( pl.fold( acc=pl.lit(0), function=lambda acc, x: acc + x, exprs=pl.col(\"*\")\n", + " ).alias(\"calculated_total\"))['calculated_total']\n", + "\n", + " mask = df['TOTAL'] == calculated_total\n", + " if pl.sum(~mask) != 0:\n", + " raise ValueError('A coluna de TOTAL da base original tem inconsistências e não soma tudo das demais colunas.')\n", + " # Verifies that we can do drop total and do LONG. \n", + "verify_total(new_df)" + ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "metadata": {}, "outputs": [ { - "data": { - "text/html": [ - "
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anomessigla_uftipo_veiculoquantidade
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" - ], - "text/plain": [ - "shape: (0, 5)\n", - "┌─────┬─────┬──────────┬──────────────┬────────────┐\n", - "│ ano ┆ mes ┆ sigla_uf ┆ tipo_veiculo ┆ quantidade │\n", - "│ --- ┆ --- ┆ --- ┆ --- ┆ --- │\n", - "│ i64 ┆ i64 ┆ str ┆ str ┆ str │\n", - "╞═════╪═════╪══════════╪══════════════╪════════════╡\n", - "└─────┴─────┴──────────┴──────────────┴────────────┘" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" + "ename": "TypeError", + "evalue": "DataFrame.apply() got an unexpected keyword argument 'predicate'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[12], line 12\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[39m# set id_municipio to 1 when nome_denatran is 'B' and sigla_uf is 'MG'\u001b[39;00m\n\u001b[1;32m 11\u001b[0m mask1 \u001b[39m=\u001b[39m (df[\u001b[39m'\u001b[39m\u001b[39mnome_denatran\u001b[39m\u001b[39m'\u001b[39m] \u001b[39m==\u001b[39m \u001b[39m'\u001b[39m\u001b[39mB\u001b[39m\u001b[39m'\u001b[39m) \u001b[39m&\u001b[39m (df[\u001b[39m'\u001b[39m\u001b[39msigla_uf\u001b[39m\u001b[39m'\u001b[39m] \u001b[39m==\u001b[39m \u001b[39m'\u001b[39m\u001b[39mMG\u001b[39m\u001b[39m'\u001b[39m)\n\u001b[0;32m---> 12\u001b[0m df[\u001b[39m'\u001b[39m\u001b[39mid_municipio\u001b[39m\u001b[39m'\u001b[39m] \u001b[39m=\u001b[39m df\u001b[39m.\u001b[39;49mapply(\u001b[39mlambda\u001b[39;49;00m x: \u001b[39m1\u001b[39;49m \u001b[39mif\u001b[39;49;00m mask1[x] \u001b[39melse\u001b[39;49;00m x[\u001b[39m'\u001b[39;49m\u001b[39mid_municipio\u001b[39;49m\u001b[39m'\u001b[39;49m], predicate\u001b[39m=\u001b[39;49mmask1)\n\u001b[1;32m 14\u001b[0m \u001b[39m# set id_municipio to 23 when nome_denatran is 'C' and sigla_uf is 'RJ'\u001b[39;00m\n\u001b[1;32m 15\u001b[0m mask2 \u001b[39m=\u001b[39m (df[\u001b[39m'\u001b[39m\u001b[39mnome_denatran\u001b[39m\u001b[39m'\u001b[39m] \u001b[39m==\u001b[39m \u001b[39m'\u001b[39m\u001b[39mC\u001b[39m\u001b[39m'\u001b[39m) \u001b[39m&\u001b[39m (df[\u001b[39m'\u001b[39m\u001b[39msigla_uf\u001b[39m\u001b[39m'\u001b[39m] \u001b[39m==\u001b[39m \u001b[39m'\u001b[39m\u001b[39mRJ\u001b[39m\u001b[39m'\u001b[39m)\n", + "\u001b[0;31mTypeError\u001b[0m: DataFrame.apply() got an unexpected keyword argument 'predicate'" + ] } ], - "source": [] + "source": [ + "import polars as pl\n", + "\n", + "# create a sample polars data frame\n", + "df = pl.DataFrame({\n", + " 'nome_denatran': ['A', 'B', 'C', 'D'],\n", + " 'sigla_uf': ['SP', 'MG', 'RJ', 'ES'],\n", + " 'id_municipio': [0, 0, 0, 0]\n", + "})\n", + "\n", + "# set id_municipio to 1 when nome_denatran is 'B' and sigla_uf is 'MG'\n", + "mask1 = (df['nome_denatran'] == 'B') & (df['sigla_uf'] == 'MG')\n", + "df['id_municipio'] = df.apply(lambda x: 1 if mask1[x] else x['id_municipio'], predicate=mask1)\n", + "\n", + "# set id_municipio to 23 when nome_denatran is 'C' and sigla_uf is 'RJ'\n", + "mask2 = (df['nome_denatran'] == 'C') & (df['sigla_uf'] == 'RJ')\n", + "df['id_municipio'] = df.apply(lambda x: 23 if mask2[x] else x['id_municipio'], predicate=mask2)\n", + "\n", + "# print the updated data frame\n", + "print(df)\n" + ] } ], "metadata": { diff --git "a/br_denatran_frota/files/2022/frota_por_munic\303\255pio_e_tipo_2-2022.xls" "b/br_denatran_frota/files/2022/frota_por_munic\303\255pio_e_tipo_2-2022.xls" new file mode 100644 index 0000000000000000000000000000000000000000..fd37025cd0a73890779470bcf62c330fdf17bd2c GIT binary patch literal 1183744 zcmeFad%R`oS=YI%ySlrQaO>O%34~1&NCGKLxOT z){xGG4&sa%!pt}quNVYJz`J-w5X3=8G;zlJ#M_LHi1C7=h=^R&(Q(9@@Avn-Ywf*H zovM_d8Rw7rOed?(TJL(-dwJgH{yguy|H@x}`0xF;?|JzTkIwz~rK9^t|L)fFMh|Y4 zzli%w{qv`cM)yCjp8wsgTete+ui)k%aJ`F)|B&nH`$nT5<@$y9k48Vn^@}c#MnBH= z?gvJrpWu2A9sDHMdmkE&ewyojS4N|M&P9{||9}54K;UQT<3ZMur5Uj-BbFp<&Qgq6 zh7qqu&*ypp*C%j&BG)HzeKHp)FnXBlglIv|&h;5w zujKknt})kValMM`)m*RP`fRSx;d(9C>$qOe^|@T1$MpuTt6ZPY^>eu1$n_?!N4Os4 zdNbD-aJ_}=3%S0C>*sQPG1ptU-p2JMTwlud7}wjmI<7sgeXawp3D+Ul5!W@YDc3RA zmvNnNopQ~%=3Hl7U(U7QT5_$p)?C-Q-obT)>v67|TtAQNom@Yk>p$Xpg6kJ>J<0Wz zT&}~r`1=&s(_CN0^$WS4;rc~fznJUYTwl%g9lBzf6DdCxIV!3pK*OX*9W;4wDc@rj+yy;`1`(m!HawR@1_1FL8r4PRM$pbln zGU~>CZ%@5noqu1Ie?N(TFO9xG-~3QY-UO%mbJV}}_1{>~x%9xL4ydJCX-`+eo;WAuAv6ln16LznggiD#fzq4Fj; 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z3hJRTI@xg1F7{n^(??%8mS_CxTAMiWga=;F18z40?SlF95v&MUj7!{d{Bk?+Y6L!7 zxDBBX!d3)sneRm4mfS7`+T7cy%-fv|geEt>7Sh(>oxIH3>~2?h-a^Lvqr=Dw)vff@ z;}a&{MxR!?s@~lshnv45W$4Kr&spp&IHP#8A>8p#3>t+?R*)FC(NQu>EXze}qK{-1=!kV7q+?Y}17ZZ0{NbZd*|=)WdZM)XV({ zMm-Q0{GJM;a!isEY4VEqI}*$&4`qq`@{#C+EV7`QIgG2DTrHla<*s%~oR$8MmjxP3 z24#*6+)+qs0Y!7}82oBMj{KsGsiQQ!=RZ|?n<7tR<4k#ILH6L}n&ob{Z}Lp>@hRJX zsE8ed{~8TgaMXcch;0=Pd^F{pZ_R{%h1=*AdqRNYr==$adsyb%^6w$p9vAy}=KsGO C<*<+d literal 0 HcmV?d00001 From bdcfe4871bd9acd5d428b7be1db484a70deff819 Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 23 Apr 2023 05:02:17 -0300 Subject: [PATCH 055/265] Create constants file --- br_denatran_frota/code/constants.py | 34 +++++++++++++++++++++++++++++ 1 file changed, 34 insertions(+) create mode 100644 br_denatran_frota/code/constants.py diff --git a/br_denatran_frota/code/constants.py b/br_denatran_frota/code/constants.py new file mode 100644 index 000000000..bd50c4bab --- /dev/null +++ b/br_denatran_frota/code/constants.py @@ -0,0 +1,34 @@ +# -*- coding: utf-8 -*- +DICT_UFS = { + "AC": "Acre", + "AL": "Alagoas", + "AP": "Amapá", + "AM": "Amazonas", + "BA": "Bahia", + "CE": "Ceará", + "DF": "Distrito Federal", + "ES": "Espírito Santo", + "GO": "Goiás", + "MA": "Maranhão", + "MT": "Mato Grosso", + "MS": "Mato Grosso do Sul", + "MG": "Minas Gerais", + "PA": "Pará", + "PB": "Paraíba", + "PR": "Paraná", + "PE": "Pernambuco", + "PI": "Piauí", + "RJ": "Rio de Janeiro", + "RN": "Rio Grande do Norte", + "RS": "Rio Grande do Sul", + "RO": "Rondônia", + "RR": "Roraima", + "SC": "Santa Catarina", + "SP": "São Paulo", + "SE": "Sergipe", + "TO": "Tocantins", +} + +REGRAS = { + ("RN", "ASSU"): "açu", +} From 44e39b4005ffbd3a4a3fefd6ce90a311d66aa898 Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 23 Apr 2023 05:05:04 -0300 Subject: [PATCH 056/265] Add more utility functions --- br_denatran_frota/code/utils.py | 68 ++++++++++++++++++--------------- 1 file changed, 37 insertions(+), 31 deletions(-) diff --git a/br_denatran_frota/code/utils.py b/br_denatran_frota/code/utils.py index 40b73d2d9..e51cf3586 100644 --- a/br_denatran_frota/code/utils.py +++ b/br_denatran_frota/code/utils.py @@ -1,37 +1,9 @@ # -*- coding: utf-8 -*- import pandas as pd import polars as pl +import difflib import re - -DICT_UFS = { - "AC": "Acre", - "AL": "Alagoas", - "AP": "Amapá", - "AM": "Amazonas", - "BA": "Bahia", - "CE": "Ceará", - "DF": "Distrito Federal", - "ES": "Espírito Santo", - "GO": "Goiás", - "MA": "Maranhão", - "MT": "Mato Grosso", - "MS": "Mato Grosso do Sul", - "MG": "Minas Gerais", - "PA": "Pará", - "PB": "Paraíba", - "PR": "Paraná", - "PE": "Pernambuco", - "PI": "Piauí", - "RJ": "Rio de Janeiro", - "RN": "Rio Grande do Norte", - "RS": "Rio Grande do Sul", - "RO": "Rondônia", - "RR": "Roraima", - "SC": "Santa Catarina", - "SP": "São Paulo", - "SE": "Sergipe", - "TO": "Tocantins", -} +from constants import DICT_UFS, REGRAS def guess_header(df: pd.DataFrame, max_header_guess: int = 4) -> int: @@ -62,7 +34,7 @@ def get_year_month_from_filename(filename: str) -> tuple[int, int]: raise ValueError("No match found") -def verify_total(df: pl.DataFrame): +def verify_total(df: pl.DataFrame) -> None: columns_for_total = df.select(pl.exclude("TOTAL")).select(pl.exclude([pl.Utf8])) calculated_total = columns_for_total.select( pl.fold( @@ -75,3 +47,37 @@ def verify_total(df: pl.DataFrame): raise ValueError( "A coluna de TOTAL da base original tem inconsistências e não soma tudo das demais colunas." ) + + +def fix_suggested_nome_ibge(row) -> str: + key = (row[0], row[1]) + if key in REGRAS: + return REGRAS[key] + else: + return row[-1] + + +def match_ibge(denatran_uf: pl.DataFrame, ibge_uf: pl.DataFrame) -> None: + joined_df = denatran_uf.join( + ibge_uf, + left_on=["suggested_nome_ibge", "sigla_uf"], + right_on=["nome", "sigla_uf"], + how="left", + ) + mismatched_rows = joined_df.filter(pl.col("id_municipio").is_null()) + + if len(mismatched_rows) > 0: + error_message = "Os seguintes municípios falharam: \n" + for row in mismatched_rows.rows(named=True): + error_message += f"{row['nome_denatran']} ({row['sigla_uf']})\n" + raise ValueError(error_message) + + +def get_city_name_ibge(denatran_name: str, ibge_uf: pl.DataFrame) -> str: + matches = difflib.get_close_matches( + denatran_name.lower(), ibge_uf["nome"].str.to_lowercase(), n=1 + ) + if matches: + return matches[0] + else: + return "" # I don't want this to error out directly, because then I can get all municipalities. From 031d4de0c7086f0f5802235bab934601bfca77e2 Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 23 Apr 2023 05:11:43 -0300 Subject: [PATCH 057/265] Migrate code to proper folder --- .../datasets/br_denatran_frota/constants.py | 34 +++++++- pipelines/datasets/br_denatran_frota/utils.py | 86 +++++++++++++++++++ 2 files changed, 119 insertions(+), 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/constants.py b/pipelines/datasets/br_denatran_frota/constants.py index a323827db..977dd7eec 100644 --- a/pipelines/datasets/br_denatran_frota/constants.py +++ b/pipelines/datasets/br_denatran_frota/constants.py @@ -39,4 +39,36 @@ class constants(Enum): # pylint: disable=c0103 Constant values for the br_denatran_frota project """ - FOO = "bar" + DICT_UFS = { + "AC": "Acre", + "AL": "Alagoas", + "AP": "Amapá", + "AM": "Amazonas", + "BA": "Bahia", + "CE": "Ceará", + "DF": "Distrito Federal", + "ES": "Espírito Santo", + "GO": "Goiás", + "MA": "Maranhão", + "MT": "Mato Grosso", + "MS": "Mato Grosso do Sul", + "MG": "Minas Gerais", + "PA": "Pará", + "PB": "Paraíba", + "PR": "Paraná", + "PE": "Pernambuco", + "PI": "Piauí", + "RJ": "Rio de Janeiro", + "RN": "Rio Grande do Norte", + "RS": "Rio Grande do Sul", + "RO": "Rondônia", + "RR": "Roraima", + "SC": "Santa Catarina", + "SP": "São Paulo", + "SE": "Sergipe", + "TO": "Tocantins", + } + + REGRAS = { + ("RN", "ASSU"): "açu", + } diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index 45810ab91..b00798d26 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -29,3 +29,89 @@ # ``` # ############################################################################### +# -*- coding: utf-8 -*- +import pandas as pd +import polars as pl +import difflib +import re +from pipelines.datasets.br_denatran_frota.constants import constants + +DICT_UFS = constants.DICT_UFS.value +REGRAS = constants.REGRAS.value + + +def guess_header(df: pd.DataFrame, max_header_guess: int = 4) -> int: + header_guess = 0 + while header_guess < max_header_guess: + # Iffy logic, but essentially: if all rows of the column are strings, then this is a good candidate for a header. + if all(df.iloc[header_guess].apply(lambda x: isinstance(x, str))): + return header_guess + + header_guess += 1 + return 0 # If nothing is ever found until the max, let's just assume it's the first row as per usual. + + +def change_df_header(df: pd.DataFrame, header_row: int) -> pd.DataFrame: + new_header = df.iloc[header_row] + new_df = df[(header_row + 1) :].reset_index(drop=True) + new_df.rename(columns=new_header, inplace=True) + return new_df + + +def get_year_month_from_filename(filename: str) -> tuple[int, int]: + match = re.search(r"(\w+)_(\d{1,2})-(\d{4})\.(xls|xlsx)$", filename) + if match: + month = match.group(2) + year = match.group(3) + return month, year + else: + raise ValueError("No match found") + + +def verify_total(df: pl.DataFrame) -> None: + columns_for_total = df.select(pl.exclude("TOTAL")).select(pl.exclude([pl.Utf8])) + calculated_total = columns_for_total.select( + pl.fold( + acc=pl.lit(0), function=lambda acc, x: acc + x, exprs=pl.col("*") + ).alias("calculated_total") + )["calculated_total"] + + mask = df["TOTAL"] == calculated_total + if pl.sum(~mask) != 0: + raise ValueError( + "A coluna de TOTAL da base original tem inconsistências e não soma tudo das demais colunas." + ) + + +def fix_suggested_nome_ibge(row) -> str: + key = (row[0], row[1]) + if key in REGRAS: + return REGRAS[key] + else: + return row[-1] + + +def match_ibge(denatran_uf: pl.DataFrame, ibge_uf: pl.DataFrame) -> None: + joined_df = denatran_uf.join( + ibge_uf, + left_on=["suggested_nome_ibge", "sigla_uf"], + right_on=["nome", "sigla_uf"], + how="left", + ) + mismatched_rows = joined_df.filter(pl.col("id_municipio").is_null()) + + if len(mismatched_rows) > 0: + error_message = "Os seguintes municípios falharam: \n" + for row in mismatched_rows.rows(named=True): + error_message += f"{row['nome_denatran']} ({row['sigla_uf']})\n" + raise ValueError(error_message) + + +def get_city_name_ibge(denatran_name: str, ibge_uf: pl.DataFrame) -> str: + matches = difflib.get_close_matches( + denatran_name.lower(), ibge_uf["nome"].str.to_lowercase(), n=1 + ) + if matches: + return matches[0] + else: + return "" # I don't want this to error out directly, because then I can get all municipalities. From 635c61f6d37eddc882e0c3e6f1684f4e80f10cac Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 23 Apr 2023 05:26:55 -0300 Subject: [PATCH 058/265] More constants --- .../datasets/br_denatran_frota/constants.py | 17 +++++++++++++++++ 1 file changed, 17 insertions(+) diff --git a/pipelines/datasets/br_denatran_frota/constants.py b/pipelines/datasets/br_denatran_frota/constants.py index 977dd7eec..74eda5115 100644 --- a/pipelines/datasets/br_denatran_frota/constants.py +++ b/pipelines/datasets/br_denatran_frota/constants.py @@ -72,3 +72,20 @@ class constants(Enum): # pylint: disable=c0103 REGRAS = { ("RN", "ASSU"): "açu", } + + MONTHS = { + "janeiro": 1, + "fevereiro": 2, + "marco": 3, + "abril": 4, + "maio": 5, + "junho": 6, + "julho": 7, + "agosto": 8, + "setembro": 9, + "outubro": 10, + "novembro": 11, + "dezembro": 12, + } + + DATASET = "br_denatran_frota" From 8e089a729768bbaa7463fdc91a26738a1f7b2645 Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 23 Apr 2023 06:20:25 -0300 Subject: [PATCH 059/265] Rename substituions ruleset --- pipelines/datasets/br_denatran_frota/constants.py | 2 +- pipelines/datasets/br_denatran_frota/utils.py | 6 +++--- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/constants.py b/pipelines/datasets/br_denatran_frota/constants.py index 74eda5115..06a19a0ae 100644 --- a/pipelines/datasets/br_denatran_frota/constants.py +++ b/pipelines/datasets/br_denatran_frota/constants.py @@ -69,7 +69,7 @@ class constants(Enum): # pylint: disable=c0103 "TO": "Tocantins", } - REGRAS = { + SUBSTITUTIONS = { ("RN", "ASSU"): "açu", } diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index b00798d26..f2ae280eb 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -37,7 +37,7 @@ from pipelines.datasets.br_denatran_frota.constants import constants DICT_UFS = constants.DICT_UFS.value -REGRAS = constants.REGRAS.value +SUBSTITUTIONS = constants.SUBSTITUTIONS.value def guess_header(df: pd.DataFrame, max_header_guess: int = 4) -> int: @@ -85,8 +85,8 @@ def verify_total(df: pl.DataFrame) -> None: def fix_suggested_nome_ibge(row) -> str: key = (row[0], row[1]) - if key in REGRAS: - return REGRAS[key] + if key in SUBSTITUTIONS: + return SUBSTITUTIONS[key] else: return row[-1] From 2fe17fe3a7a30c7576b9d9f8dc920921f9ef85cf Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 23 Apr 2023 06:25:47 -0300 Subject: [PATCH 060/265] Cleanup --- br_denatran_frota/code/frota_uf_tipo.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/br_denatran_frota/code/frota_uf_tipo.py b/br_denatran_frota/code/frota_uf_tipo.py index 213f52cc9..aad75545e 100644 --- a/br_denatran_frota/code/frota_uf_tipo.py +++ b/br_denatran_frota/code/frota_uf_tipo.py @@ -2,7 +2,7 @@ import polars as pl import pandas as pd import os -from utils import ( +from br_denatran_frota.code.butils import ( guess_header, change_df_header, get_year_month_from_filename, From a25ce639cbe4f737fb54ce93037dfbab632bbdc1 Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 23 Apr 2023 06:26:06 -0300 Subject: [PATCH 061/265] Cleanup crew --- .../code/{utils.py => butils.py} | 0 br_denatran_frota/code/download_frota.py | 3 +- br_denatran_frota/code/test_drive.ipynb | 443 +++++++++++++----- 3 files changed, 335 insertions(+), 111 deletions(-) rename br_denatran_frota/code/{utils.py => butils.py} (100%) diff --git a/br_denatran_frota/code/utils.py b/br_denatran_frota/code/butils.py similarity index 100% rename from br_denatran_frota/code/utils.py rename to br_denatran_frota/code/butils.py diff --git a/br_denatran_frota/code/download_frota.py b/br_denatran_frota/code/download_frota.py index 52ce439e6..097a78d96 100644 --- a/br_denatran_frota/code/download_frota.py +++ b/br_denatran_frota/code/download_frota.py @@ -1,3 +1,4 @@ +# -*- coding: utf-8 -*- import os import re import glob @@ -75,8 +76,6 @@ def make_filename(i: dict, ext: bool = True) -> str: filename += f".{filetype}" return filename - print(2) - def call_downloader(i): filename = make_filename(i) diff --git a/br_denatran_frota/code/test_drive.ipynb b/br_denatran_frota/code/test_drive.ipynb index 7bb9411db..fed5fa695 100644 --- a/br_denatran_frota/code/test_drive.ipynb +++ b/br_denatran_frota/code/test_drive.ipynb @@ -2,9 +2,21 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "ename": "ImportError", + "evalue": "cannot import name 'get_city_name_ibge' from 'utils' (/home/tamir/basedosdados/pipelines/br_denatran_frota/code/utils.py)", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mImportError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[2], line 11\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mbs4\u001b[39;00m \u001b[39mimport\u001b[39;00m BeautifulSoup\n\u001b[1;32m 10\u001b[0m \u001b[39mimport\u001b[39;00m \u001b[39mdifflib\u001b[39;00m\n\u001b[0;32m---> 11\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mutils\u001b[39;00m \u001b[39mimport\u001b[39;00m guess_header, change_df_header, get_year_month_from_filename, verify_total, get_city_name_ibge, match_ibge\n\u001b[1;32m 12\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mconstants\u001b[39;00m \u001b[39mimport\u001b[39;00m DICT_UFS, REGRAS\n", + "\u001b[0;31mImportError\u001b[0m: cannot import name 'get_city_name_ibge' from 'utils' (/home/tamir/basedosdados/pipelines/br_denatran_frota/code/utils.py)" + ] + } + ], "source": [ "import polars as pl\n", "import pandas as pd \n", @@ -16,41 +28,13 @@ "from rarfile import RarFile\n", "from bs4 import BeautifulSoup\n", "import difflib\n", - "from utils import guess_header, change_df_header, get_year_month_from_filename, treat_uf_tipo\n", - "DICT_UFS = {\n", - " \"AC\": \"Acre\",\n", - " \"AL\": \"Alagoas\",\n", - " \"AP\": \"Amapá\",\n", - " \"AM\": \"Amazonas\",\n", - " \"BA\": \"Bahia\",\n", - " \"CE\": \"Ceará\",\n", - " \"DF\": \"Distrito Federal\",\n", - " \"ES\": \"Espírito Santo\",\n", - " \"GO\": \"Goiás\",\n", - " \"MA\": \"Maranhão\",\n", - " \"MT\": \"Mato Grosso\",\n", - " \"MS\": \"Mato Grosso do Sul\",\n", - " \"MG\": \"Minas Gerais\",\n", - " \"PA\": \"Pará\",\n", - " \"PB\": \"Paraíba\",\n", - " \"PR\": \"Paraná\",\n", - " \"PE\": \"Pernambuco\",\n", - " \"PI\": \"Piauí\",\n", - " \"RJ\": \"Rio de Janeiro\",\n", - " \"RN\": \"Rio Grande do Norte\",\n", - " \"RS\": \"Rio Grande do Sul\",\n", - " \"RO\": \"Rondônia\",\n", - " \"RR\": \"Roraima\",\n", - " \"SC\": \"Santa Catarina\",\n", - " \"SP\": \"São Paulo\",\n", - " \"SE\": \"Sergipe\",\n", - " \"TO\": \"Tocantins\",\n", - "}" + "from br_denatran_frota.utils import guess_header, change_df_header, get_year_month_from_filename, verify_total, get_city_name_ibge, match_ibge\n", + "from constants import DICT_UFS, REGRAS" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -60,7 +44,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -69,7 +53,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "metadata": {}, "outputs": [ { @@ -87,16 +71,14 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "/home/tamir/.cache/pypoetry/virtualenvs/pipelines-Fyk5jlG0-py3.10/lib/python3.10/site-packages/requests/__init__.py:102: RequestsDependencyWarning: urllib3 (1.26.7) or chardet (5.1.0)/charset_normalizer (2.0.8) doesn't match a supported version!\n", - " warnings.warn(\"urllib3 ({}) or chardet ({})/charset_normalizer ({}) doesn't match a supported \"\n", - "Downloading: 100%|██████████| 5570/5570 [00:00<00:00, 10744.58rows/s]\n" + "Downloading: 100%|██████████| 5570/5570 [00:00<00:00, 12793.96rows/s]\n" ] } ], @@ -110,7 +92,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -125,7 +107,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -134,7 +116,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -146,19 +128,44 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": {}, "outputs": [ { - "ename": "NameError", - "evalue": "name 'denatran_uf' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[1], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m denatran_uf\n", - "\u001b[0;31mNameError\u001b[0m: name 'denatran_uf' is not defined" - ] + "data": { + "text/html": [ + "

\n", + "shape: (167, 24)
sigla_ufnome_denatranTOTALAUTOMOVELBONDECAMINHAOCAMINHAO TRATORCAMINHONETECAMIONETACHASSI PLATAFCICLOMOTORMICRO-ONIBUSMOTOCICLETAMOTONETAONIBUSQUADRICICLOREBOQUESEMI-REBOQUESIDE-CAROUTROSTRATOR ESTEITRATOR RODASTRICICLOUTILITARIO
strstri64i64i64i64i64i64i64i64i64i64i64i64i64i64i64i64i64i64i64i64i64i64
"RN""ACARI"40351394012272799107313168428616031801500412
"RN""AFONSO BEZERRA…186773003711533002108076517061040004
"RN""AGUA NOVA"10572600160429028613942031020005
"RN""ALEXANDRIA"612222240146195506202502686216180483402500141
"RN""ALMINO AFONSO"16214650241951504984313530104060007
"RN""ALTO DO RODRIG…541118980266740873115222196367340451302803134
"RN""ANGICOS"41891400013954247201821184715320040901400126
"RN""ANTONIO MARTIN…20165500460122200213111512150600500011
"RN""APODI"177714506051259105112303615480722683630714608400185
"RN""AREIA BRANCA"9801321202024154412802414731911827770629205200778
"RN""ARES"3098124309131854405913111781490138430400028
"RN""ASSU"266678400096057166832201416751062524061270219970970012186
………………………………………………………………
"RN""TIBAU"18296930537150190601260812940017502101014
"RN""TIBAU DO SUL"4676191107104921970124541375198280501109000156
"RN""TIMBAUBA DOS B…69721201206013069324357062030008
"RN""TOUROS"83152463018658861230134393945303630381707013102
"RN""TRIUNFO POTIGU…89823702208611047497243050010001
"RN""UMARIZAL"3879107308116275270727193533480292401700125
"RN""UPANEMA"4127114901151228527059132011378160171102200012
"RN""VARZEA"123047002106226053582338095040002
"RN""VENHA-VER"8502700170789007443127020000005
"RN""VERA CRUZ"39891238021143714905111967592601360100127
"RN""VICOSA"515162081276001285162011040001
"RN""VILA FLOR"847298010237150182433192012010007
" + ], + "text/plain": [ + "shape: (167, 24)\n", + "┌──────────┬────────────┬───────┬───────────┬───┬────────────┬────────────┬──────────┬────────────┐\n", + "│ sigla_uf ┆ nome_denat ┆ TOTAL ┆ AUTOMOVEL ┆ … ┆ TRATOR ┆ TRATOR ┆ TRICICLO ┆ UTILITARIO │\n", + "│ --- ┆ ran ┆ --- ┆ --- ┆ ┆ ESTEI ┆ RODAS ┆ --- ┆ --- │\n", + "│ str ┆ --- ┆ i64 ┆ i64 ┆ ┆ --- ┆ --- ┆ i64 ┆ i64 │\n", + "│ ┆ str ┆ ┆ ┆ ┆ i64 ┆ i64 ┆ ┆ │\n", + "╞══════════╪════════════╪═══════╪═══════════╪═══╪════════════╪════════════╪══════════╪════════════╡\n", + "│ RN ┆ ACARI ┆ 4035 ┆ 1394 ┆ … ┆ 0 ┆ 0 ┆ 4 ┆ 12 │\n", + "│ RN ┆ AFONSO ┆ 1867 ┆ 730 ┆ … ┆ 0 ┆ 0 ┆ 0 ┆ 4 │\n", + "│ ┆ BEZERRA ┆ ┆ ┆ ┆ ┆ ┆ ┆ │\n", + "│ RN ┆ AGUA NOVA ┆ 1057 ┆ 260 ┆ … ┆ 0 ┆ 0 ┆ 0 ┆ 5 │\n", + "│ RN ┆ ALEXANDRIA ┆ 6122 ┆ 2224 ┆ … ┆ 0 ┆ 0 ┆ 1 ┆ 41 │\n", + "│ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … │\n", + "│ RN ┆ VENHA-VER ┆ 850 ┆ 270 ┆ … ┆ 0 ┆ 0 ┆ 0 ┆ 5 │\n", + "│ RN ┆ VERA CRUZ ┆ 3989 ┆ 1238 ┆ … ┆ 0 ┆ 0 ┆ 1 ┆ 27 │\n", + "│ RN ┆ VICOSA ┆ 515 ┆ 162 ┆ … ┆ 0 ┆ 0 ┆ 0 ┆ 1 │\n", + "│ RN ┆ VILA FLOR ┆ 847 ┆ 298 ┆ … ┆ 0 ┆ 0 ┆ 0 ┆ 7 │\n", + "└──────────┴────────────┴───────┴───────────┴───┴────────────┴────────────┴──────────┴────────────┘" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ @@ -167,40 +174,25 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ - "def get_city_name_ibge(denatran_name: str):\n", - " matches = difflib.get_close_matches(denatran_name.lower(), ibge_uf['nome'].str.to_lowercase(), n = 1)\n", - " if matches:\n", - " return matches[0]\n", - " else:\n", - " return '' # I don't want this to error out directly, because then I can get all municipalities.\n", + "\n", "x = denatran_uf['nome_denatran'].apply(get_city_name_ibge)\n", "denatran_uf = denatran_uf.with_columns(x.alias('suggested_nome_ibge'))" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "metadata": {}, "outputs": [], - "source": [ - "def match_ibge(denatran_uf: pl.DataFrame, ibge_uf: pl.DataFrame):\n", - " joined_df = denatran_uf.join(ibge_uf, left_on=['suggested_nome_ibge', 'sigla_uf'], right_on=['nome', 'sigla_uf'], how='left')\n", - " mismatched_rows = joined_df.filter(pl.col('id_municipio').is_null())\n", - "\n", - " if len(mismatched_rows) > 0:\n", - " error_message = \"Os seguintes municípios falharam: \\n\"\n", - " for row in mismatched_rows.rows(named = True):\n", - " error_message += f\"{row['nome_denatran']} ({row['sigla_uf']})\\n\"\n", - " raise ValueError(error_message)\n" - ] + "source": [] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "metadata": {}, "outputs": [ { @@ -210,8 +202,8 @@ "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[9], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m match_ibge(denatran_uf, ibge_uf)\n", - "Cell \u001b[0;32mIn[8], line 9\u001b[0m, in \u001b[0;36mmatch_ibge\u001b[0;34m(denatran_uf, ibge_uf)\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[39mfor\u001b[39;00m row \u001b[39min\u001b[39;00m mismatched_rows\u001b[39m.\u001b[39mrows(named \u001b[39m=\u001b[39m \u001b[39mTrue\u001b[39;00m):\n\u001b[1;32m 8\u001b[0m error_message \u001b[39m+\u001b[39m\u001b[39m=\u001b[39m \u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39m{\u001b[39;00mrow[\u001b[39m'\u001b[39m\u001b[39mnome_denatran\u001b[39m\u001b[39m'\u001b[39m]\u001b[39m}\u001b[39;00m\u001b[39m (\u001b[39m\u001b[39m{\u001b[39;00mrow[\u001b[39m'\u001b[39m\u001b[39msigla_uf\u001b[39m\u001b[39m'\u001b[39m]\u001b[39m}\u001b[39;00m\u001b[39m)\u001b[39m\u001b[39m\\n\u001b[39;00m\u001b[39m\"\u001b[39m\n\u001b[0;32m----> 9\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mValueError\u001b[39;00m(error_message)\n", + "Cell \u001b[0;32mIn[26], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m match_ibge(denatran_uf, ibge_uf)\n", + "Cell \u001b[0;32mIn[25], line 9\u001b[0m, in \u001b[0;36mmatch_ibge\u001b[0;34m(denatran_uf, ibge_uf)\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[39mfor\u001b[39;00m row \u001b[39min\u001b[39;00m mismatched_rows\u001b[39m.\u001b[39mrows(named \u001b[39m=\u001b[39m \u001b[39mTrue\u001b[39;00m):\n\u001b[1;32m 8\u001b[0m error_message \u001b[39m+\u001b[39m\u001b[39m=\u001b[39m \u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39m{\u001b[39;00mrow[\u001b[39m'\u001b[39m\u001b[39mnome_denatran\u001b[39m\u001b[39m'\u001b[39m]\u001b[39m}\u001b[39;00m\u001b[39m (\u001b[39m\u001b[39m{\u001b[39;00mrow[\u001b[39m'\u001b[39m\u001b[39msigla_uf\u001b[39m\u001b[39m'\u001b[39m]\u001b[39m}\u001b[39;00m\u001b[39m)\u001b[39m\u001b[39m\\n\u001b[39;00m\u001b[39m\"\u001b[39m\n\u001b[0;32m----> 9\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mValueError\u001b[39;00m(error_message)\n", "\u001b[0;31mValueError\u001b[0m: Os seguintes municípios falharam: \nASSU (RN)\n" ] } @@ -222,7 +214,23 @@ }, { "cell_type": "code", - "execution_count": 232, + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "nomes = ibge_uf['nome'].to_list()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -233,59 +241,276 @@ }, { "cell_type": "code", - "execution_count": 146, + "execution_count": null, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " sigla_uf nome_denatran TOTAL AUTOMOVEL BONDE CAMINHAO \\\n", + "0 RN ACARI 4035 1394 0 122 \n", + "1 RN AFONSO BEZERRA 1867 730 0 37 \n", + "2 RN AGUA NOVA 1057 260 0 16 \n", + "3 RN ALEXANDRIA 6122 2224 0 146 \n", + "4 RN ALMINO AFONSO 1621 465 0 24 \n", + ".. ... ... ... ... ... ... \n", + "162 RN VARZEA 1230 470 0 21 \n", + "163 RN VENHA-VER 850 270 0 17 \n", + "164 RN VERA CRUZ 3989 1238 0 211 \n", + "165 RN VICOSA 515 162 0 8 \n", + "166 RN VILA FLOR 847 298 0 10 \n", + "\n", + " CAMINHAO TRATOR CAMINHONETE CAMIONETA CHASSI PLATAF ... QUADRICICLO \\\n", + "0 7 279 91 0 ... 0 \n", + "1 1 153 30 0 ... 0 \n", + "2 0 42 9 0 ... 0 \n", + "3 19 550 62 0 ... 0 \n", + "4 1 95 15 0 ... 0 \n", + ".. ... ... ... ... ... ... \n", + "162 0 62 26 0 ... 0 \n", + "163 0 78 9 0 ... 0 \n", + "164 4 371 49 0 ... 0 \n", + "165 1 27 6 0 ... 0 \n", + "166 2 37 15 0 ... 0 \n", + "\n", + " REBOQUE SEMI-REBOQUE SIDE-CAR OUTROS TRATOR ESTEI TRATOR RODAS \\\n", + "0 31 8 0 15 0 0 \n", + "1 6 1 0 4 0 0 \n", + "2 3 1 0 2 0 0 \n", + "3 48 34 0 25 0 0 \n", + "4 10 4 0 6 0 0 \n", + ".. ... ... ... ... ... ... \n", + "162 9 5 0 4 0 0 \n", + "163 2 0 0 0 0 0 \n", + "164 13 6 0 1 0 0 \n", + "165 1 1 0 4 0 0 \n", + "166 1 2 0 1 0 0 \n", + "\n", + " TRICICLO UTILITARIO suggested_nome_ibge \n", + "0 4 12 acari \n", + "1 0 4 afonso bezerra \n", + "2 0 5 água nova \n", + "3 1 41 alexandria \n", + "4 0 7 almino afonso \n", + ".. ... ... ... \n", + "162 0 2 várzea \n", + "163 0 5 venha-ver \n", + "164 1 27 vera cruz \n", + "165 0 1 viçosa \n", + "166 0 7 vila flor \n", + "\n", + "[167 rows x 25 columns]\n" + ] + } + ], "source": [ - "def verify_total(df: pl.DataFrame):\n", - " columns_for_total = df.select( pl.exclude(\"TOTAL\")).select(pl.exclude([pl.Utf8]))\n", - " calculated_total = columns_for_total.select( pl.fold( acc=pl.lit(0), function=lambda acc, x: acc + x, exprs=pl.col(\"*\")\n", - " ).alias(\"calculated_total\"))['calculated_total']\n", + "import pandas as pd\n", + "zdf = denatran_uf.to_pandas()\n", "\n", - " mask = df['TOTAL'] == calculated_total\n", - " if pl.sum(~mask) != 0:\n", - " raise ValueError('A coluna de TOTAL da base original tem inconsistências e não soma tudo das demais colunas.')\n", - " # Verifies that we can do drop total and do LONG. \n", - "verify_total(new_df)" + "REGRAS = {('RN', 'ASSU'): 'açu'}\n", + "\n", + "# Define a function to apply the ruleset\n", + "def get_name_c(row):\n", + " key = (row['sigla_uf'], row['nome_denatran'])\n", + " if key in REGRAS:\n", + " return REGRAS[key]\n", + " else:\n", + " return row['suggested_nome_ibge']\n", + "\n", + "# Apply the function to the DataFrame\n", + "zdf['suggested_nome_ibge'] = zdf.apply(get_name_c, axis=1)\n", + "\n", + "# Print the modified DataFrame\n", + "print(zdf)\n" ] }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, "metadata": {}, "outputs": [ { - "ename": "TypeError", - "evalue": "DataFrame.apply() got an unexpected keyword argument 'predicate'", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[12], line 12\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[39m# set id_municipio to 1 when nome_denatran is 'B' and sigla_uf is 'MG'\u001b[39;00m\n\u001b[1;32m 11\u001b[0m mask1 \u001b[39m=\u001b[39m (df[\u001b[39m'\u001b[39m\u001b[39mnome_denatran\u001b[39m\u001b[39m'\u001b[39m] \u001b[39m==\u001b[39m \u001b[39m'\u001b[39m\u001b[39mB\u001b[39m\u001b[39m'\u001b[39m) \u001b[39m&\u001b[39m (df[\u001b[39m'\u001b[39m\u001b[39msigla_uf\u001b[39m\u001b[39m'\u001b[39m] \u001b[39m==\u001b[39m \u001b[39m'\u001b[39m\u001b[39mMG\u001b[39m\u001b[39m'\u001b[39m)\n\u001b[0;32m---> 12\u001b[0m df[\u001b[39m'\u001b[39m\u001b[39mid_municipio\u001b[39m\u001b[39m'\u001b[39m] \u001b[39m=\u001b[39m df\u001b[39m.\u001b[39;49mapply(\u001b[39mlambda\u001b[39;49;00m x: \u001b[39m1\u001b[39;49m \u001b[39mif\u001b[39;49;00m mask1[x] \u001b[39melse\u001b[39;49;00m x[\u001b[39m'\u001b[39;49m\u001b[39mid_municipio\u001b[39;49m\u001b[39m'\u001b[39;49m], predicate\u001b[39m=\u001b[39;49mmask1)\n\u001b[1;32m 14\u001b[0m \u001b[39m# set id_municipio to 23 when nome_denatran is 'C' and sigla_uf is 'RJ'\u001b[39;00m\n\u001b[1;32m 15\u001b[0m mask2 \u001b[39m=\u001b[39m (df[\u001b[39m'\u001b[39m\u001b[39mnome_denatran\u001b[39m\u001b[39m'\u001b[39m] \u001b[39m==\u001b[39m \u001b[39m'\u001b[39m\u001b[39mC\u001b[39m\u001b[39m'\u001b[39m) \u001b[39m&\u001b[39m (df[\u001b[39m'\u001b[39m\u001b[39msigla_uf\u001b[39m\u001b[39m'\u001b[39m] \u001b[39m==\u001b[39m \u001b[39m'\u001b[39m\u001b[39mRJ\u001b[39m\u001b[39m'\u001b[39m)\n", - "\u001b[0;31mTypeError\u001b[0m: DataFrame.apply() got an unexpected keyword argument 'predicate'" - ] + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " sigla_uf nome_denatran TOTAL AUTOMOVEL BONDE CAMINHAO CAMINHAO TRATOR \\\n", + "11 RN ASSU 26667 8400 0 960 57 \n", + "\n", + " CAMINHONETE CAMIONETA CHASSI PLATAF ... QUADRICICLO REBOQUE \\\n", + "11 1668 322 0 ... 0 219 \n", + "\n", + " SEMI-REBOQUE SIDE-CAR OUTROS TRATOR ESTEI TRATOR RODAS TRICICLO \\\n", + "11 97 0 97 0 0 12 \n", + "\n", + " UTILITARIO suggested_nome_ibge \n", + "11 186 açu \n", + "\n", + "[1 rows x 25 columns]" + ] + }, + "execution_count": 46, + "metadata": {}, + "output_type": "execute_result" } ], + "source": [ + "zdf.loc[zdf['nome_denatran'] == 'ASSU']" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "import polars as pl\n", "\n", - "# create a sample polars data frame\n", - "df = pl.DataFrame({\n", - " 'nome_denatran': ['A', 'B', 'C', 'D'],\n", - " 'sigla_uf': ['SP', 'MG', 'RJ', 'ES'],\n", - " 'id_municipio': [0, 0, 0, 0]\n", + "# Create example polars DataFrame\n", + "zdf = pl.DataFrame({\n", + " 'sigla_uf': ['RN', 'MG', 'RS'],\n", + " 'nome_denatran': ['ASSU', 'BELO HORIZONTE', 'PORTO ALEGRE'],\n", + " 'suggested_nome_ibge': ['Unknown', 'Unknown', 'Unknown'],\n", + " 'id': [1, 2, 3]\n", "})\n", "\n", - "# set id_municipio to 1 when nome_denatran is 'B' and sigla_uf is 'MG'\n", - "mask1 = (df['nome_denatran'] == 'B') & (df['sigla_uf'] == 'MG')\n", - "df['id_municipio'] = df.apply(lambda x: 1 if mask1[x] else x['id_municipio'], predicate=mask1)\n", + "# Define your ruleset as a dictionary\n", + "\n", + "# Define a function to apply the ruleset\n", "\n", - "# set id_municipio to 23 when nome_denatran is 'C' and sigla_uf is 'RJ'\n", - "mask2 = (df['nome_denatran'] == 'C') & (df['sigla_uf'] == 'RJ')\n", - "df['id_municipio'] = df.apply(lambda x: 23 if mask2[x] else x['id_municipio'], predicate=mask2)\n", "\n", - "# print the updated data frame\n", - "print(df)\n" + "# Apply the function to the polars DataFrame\n", + "denatran_uf = denatran_uf.with_columns(denatran_uf.apply(fix_suggested_nome_ibge)['apply'].alias('suggested_nome_ibge'))\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Defaults to True. + + Returns: + str: The full filename. + """ + txt = i["txt"] + mes = i["mes"] + ano = i["ano"] + filetype = i["filetype"] + filename = re.sub("\\s+", "_", txt, flags=re.UNICODE).lower() + filename = f"{filename}_{mes}-{ano}" + if ext: + filename += f".{filetype}" + return filename + + +def make_dir_when_not_exists(dir_name: str): + """Auxiliary function to create a subdirectory when it is not present. + + Args: + dir_name (str): Name of the subdirectory to be created. + """ + if not os.path.exists(dir_name): + os.mkdir(dir_name) From 60bdf9b43f30d7ea4e9246ba3e345ce9b48f3f1b Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 23 Apr 2023 06:48:26 -0300 Subject: [PATCH 063/265] Small refactoring --- br_denatran_frota/code/constants.py | 2 +- br_denatran_frota/code/download_frota.py | 4 ++-- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/br_denatran_frota/code/constants.py b/br_denatran_frota/code/constants.py index bd50c4bab..88ce21463 100644 --- a/br_denatran_frota/code/constants.py +++ b/br_denatran_frota/code/constants.py @@ -29,6 +29,6 @@ "TO": "Tocantins", } -REGRAS = { +SUBSTITUTIONS = { ("RN", "ASSU"): "açu", } diff --git a/br_denatran_frota/code/download_frota.py b/br_denatran_frota/code/download_frota.py index 097a78d96..6060769fc 100644 --- a/br_denatran_frota/code/download_frota.py +++ b/br_denatran_frota/code/download_frota.py @@ -24,7 +24,7 @@ } DATASET = "br_denatran_frota" -headers = { +HEADERS = { "User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/39.0.2171.95 Safari/537.36" } @@ -33,7 +33,7 @@ def download_file(url, filename): # Send a GET request to the URL new_url = url.replace("arquivos-denatran", "arquivos-senatran") - response = requests.get(new_url, headers=headers) + response = requests.get(new_url, headers=HEADERS) # Save the contents of the response to a file with open(filename, "wb") as f: f.write(response.content) From 0a07c40e3512741fd6f5d2f59e392f7ac050f765 Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 23 Apr 2023 07:33:07 -0300 Subject: [PATCH 064/265] More reorganizing --- br_denatran_frota/code/frota_uf_tipo.py | 2 +- br_denatran_frota/code/test_drive.ipynb | 259 ++---------------- .../code/{butils.py => utils.py} | 2 +- 3 files changed, 18 insertions(+), 245 deletions(-) rename br_denatran_frota/code/{butils.py => utils.py} (97%) diff --git a/br_denatran_frota/code/frota_uf_tipo.py b/br_denatran_frota/code/frota_uf_tipo.py index aad75545e..05d3aacf2 100644 --- a/br_denatran_frota/code/frota_uf_tipo.py +++ b/br_denatran_frota/code/frota_uf_tipo.py @@ -2,7 +2,7 @@ import polars as pl import pandas as pd import os -from br_denatran_frota.code.butils import ( +from br_denatran_frota.code.utils import ( guess_header, change_df_header, get_year_month_from_filename, diff --git a/br_denatran_frota/code/test_drive.ipynb b/br_denatran_frota/code/test_drive.ipynb index fed5fa695..6a367de1b 100644 --- a/br_denatran_frota/code/test_drive.ipynb +++ b/br_denatran_frota/code/test_drive.ipynb @@ -2,21 +2,9 @@ "cells": [ { "cell_type": "code", - "execution_count": 2, + "execution_count": 9, "metadata": {}, - "outputs": [ - { - "ename": "ImportError", - "evalue": "cannot import name 'get_city_name_ibge' from 'utils' (/home/tamir/basedosdados/pipelines/br_denatran_frota/code/utils.py)", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mImportError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[2], line 11\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mbs4\u001b[39;00m \u001b[39mimport\u001b[39;00m BeautifulSoup\n\u001b[1;32m 10\u001b[0m \u001b[39mimport\u001b[39;00m \u001b[39mdifflib\u001b[39;00m\n\u001b[0;32m---> 11\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mutils\u001b[39;00m \u001b[39mimport\u001b[39;00m guess_header, change_df_header, get_year_month_from_filename, verify_total, get_city_name_ibge, match_ibge\n\u001b[1;32m 12\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mconstants\u001b[39;00m \u001b[39mimport\u001b[39;00m DICT_UFS, REGRAS\n", - "\u001b[0;31mImportError\u001b[0m: cannot import name 'get_city_name_ibge' from 'utils' (/home/tamir/basedosdados/pipelines/br_denatran_frota/code/utils.py)" - ] - } - ], + "outputs": [], "source": [ "import polars as pl\n", "import pandas as pd \n", @@ -28,8 +16,8 @@ "from rarfile import RarFile\n", "from bs4 import BeautifulSoup\n", "import difflib\n", - "from br_denatran_frota.utils import guess_header, change_df_header, get_year_month_from_filename, verify_total, get_city_name_ibge, match_ibge\n", - "from constants import DICT_UFS, REGRAS" + "from br_denatran_frota.code.utils import *\n", + "from br_denatran_frota.code.constants import DICT_UFS, SUBSTITUTIONS" ] }, { @@ -71,14 +59,16 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "Downloading: 100%|██████████| 5570/5570 [00:00<00:00, 12793.96rows/s]\n" + "/home/tamir/.cache/pypoetry/virtualenvs/pipelines-Fyk5jlG0-py3.10/lib/python3.10/site-packages/requests/__init__.py:102: RequestsDependencyWarning: urllib3 (1.26.7) or chardet (5.1.0)/charset_normalizer (2.0.8) doesn't match a supported version!\n", + " warnings.warn(\"urllib3 ({}) or chardet ({})/charset_normalizer ({}) doesn't match a supported \"\n", + "Downloading: 100%|██████████| 5570/5570 [00:00<00:00, 8581.01rows/s]\n" ] } ], @@ -92,7 +82,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "metadata": {}, "outputs": [], "source": [ @@ -111,7 +101,7 @@ "metadata": {}, "outputs": [], "source": [ - "uf = 'RN'" + "new_df = new_df.with_columns(new_df.apply(fix_suggested_nome_ibge)['apply'].alias('suggested_nome_ibge'))" ] }, { @@ -126,52 +116,6 @@ "ibge_uf = ibge_uf.with_columns(pl.col('nome').str.to_lowercase())" ] }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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"RN""ANTONIO MARTIN…20165500460122200213111512150600500011
"RN""APODI"177714506051259105112303615480722683630714608400185
"RN""AREIA BRANCA"9801321202024154412802414731911827770629205200778
"RN""ARES"3098124309131854405913111781490138430400028
"RN""ASSU"266678400096057166832201416751062524061270219970970012186
………………………………………………………………
"RN""TIBAU"18296930537150190601260812940017502101014
"RN""TIBAU DO SUL"4676191107104921970124541375198280501109000156
"RN""TIMBAUBA DOS B…69721201206013069324357062030008
"RN""TOUROS"83152463018658861230134393945303630381707013102
"RN""TRIUNFO POTIGU…89823702208611047497243050010001
"RN""UMARIZAL"3879107308116275270727193533480292401700125
"RN""UPANEMA"4127114901151228527059132011378160171102200012
"RN""VARZEA"123047002106226053582338095040002
"RN""VENHA-VER"8502700170789007443127020000005
"RN""VERA CRUZ"39891238021143714905111967592601360100127
"RN""VICOSA"515162081276001285162011040001
"RN""VILA FLOR"847298010237150182433192012010007
" - ], - "text/plain": [ - "shape: (167, 24)\n", - "┌──────────┬────────────┬───────┬───────────┬───┬────────────┬────────────┬──────────┬────────────┐\n", - "│ sigla_uf ┆ nome_denat ┆ TOTAL ┆ AUTOMOVEL ┆ … ┆ TRATOR ┆ TRATOR ┆ TRICICLO ┆ UTILITARIO │\n", - "│ --- ┆ ran ┆ --- ┆ --- ┆ ┆ ESTEI ┆ RODAS ┆ --- ┆ --- │\n", - "│ str ┆ --- ┆ i64 ┆ i64 ┆ ┆ --- ┆ --- ┆ i64 ┆ i64 │\n", - "│ ┆ str ┆ ┆ ┆ ┆ i64 ┆ i64 ┆ ┆ │\n", - "╞══════════╪════════════╪═══════╪═══════════╪═══╪════════════╪════════════╪══════════╪════════════╡\n", - "│ RN ┆ ACARI ┆ 4035 ┆ 1394 ┆ … ┆ 0 ┆ 0 ┆ 4 ┆ 12 │\n", - "│ RN ┆ AFONSO ┆ 1867 ┆ 730 ┆ … ┆ 0 ┆ 0 ┆ 0 ┆ 4 │\n", - "│ ┆ BEZERRA ┆ ┆ ┆ ┆ ┆ ┆ ┆ │\n", - "│ RN ┆ AGUA NOVA ┆ 1057 ┆ 260 ┆ … ┆ 0 ┆ 0 ┆ 0 ┆ 5 │\n", - "│ RN ┆ ALEXANDRIA ┆ 6122 ┆ 2224 ┆ … ┆ 0 ┆ 0 ┆ 1 ┆ 41 │\n", - "│ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … │\n", - "│ RN ┆ VENHA-VER ┆ 850 ┆ 270 ┆ … ┆ 0 ┆ 0 ┆ 0 ┆ 5 │\n", - "│ RN ┆ VERA CRUZ ┆ 3989 ┆ 1238 ┆ … ┆ 0 ┆ 0 ┆ 1 ┆ 27 │\n", - "│ RN ┆ VICOSA ┆ 515 ┆ 162 ┆ … ┆ 0 ┆ 0 ┆ 0 ┆ 1 │\n", - "│ RN ┆ VILA FLOR ┆ 847 ┆ 298 ┆ … ┆ 0 ┆ 0 ┆ 0 ┆ 7 │\n", - "└──────────┴────────────┴───────┴───────────┴───┴────────────┴────────────┴──────────┴────────────┘" - ] - }, - "execution_count": 23, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "denatran_uf" - ] - }, { "cell_type": "code", "execution_count": null, @@ -192,19 +136,18 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, "outputs": [ { - "ename": "ValueError", - "evalue": "Os seguintes municípios falharam: \nASSU (RN)\n", + "ename": "NameError", + "evalue": "name 'denatran_uf' is not defined", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[26], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m match_ibge(denatran_uf, ibge_uf)\n", - "Cell \u001b[0;32mIn[25], line 9\u001b[0m, in \u001b[0;36mmatch_ibge\u001b[0;34m(denatran_uf, ibge_uf)\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[39mfor\u001b[39;00m row \u001b[39min\u001b[39;00m mismatched_rows\u001b[39m.\u001b[39mrows(named \u001b[39m=\u001b[39m \u001b[39mTrue\u001b[39;00m):\n\u001b[1;32m 8\u001b[0m error_message \u001b[39m+\u001b[39m\u001b[39m=\u001b[39m \u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39m{\u001b[39;00mrow[\u001b[39m'\u001b[39m\u001b[39mnome_denatran\u001b[39m\u001b[39m'\u001b[39m]\u001b[39m}\u001b[39;00m\u001b[39m (\u001b[39m\u001b[39m{\u001b[39;00mrow[\u001b[39m'\u001b[39m\u001b[39msigla_uf\u001b[39m\u001b[39m'\u001b[39m]\u001b[39m}\u001b[39;00m\u001b[39m)\u001b[39m\u001b[39m\\n\u001b[39;00m\u001b[39m\"\u001b[39m\n\u001b[0;32m----> 9\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mValueError\u001b[39;00m(error_message)\n", - "\u001b[0;31mValueError\u001b[0m: Os seguintes municípios falharam: \nASSU (RN)\n" + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[4], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m match_ibge(denatran_uf, ibge_uf)\n", + "\u001b[0;31mNameError\u001b[0m: name 'denatran_uf' is not defined" ] } ], @@ -239,92 +182,6 @@ "mismatched = joined_df.filter(pl.col('id_municipio').is_null())" ] }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " sigla_uf nome_denatran TOTAL AUTOMOVEL BONDE CAMINHAO \\\n", - "0 RN ACARI 4035 1394 0 122 \n", - "1 RN AFONSO BEZERRA 1867 730 0 37 \n", - "2 RN AGUA NOVA 1057 260 0 16 \n", - "3 RN ALEXANDRIA 6122 2224 0 146 \n", - "4 RN ALMINO AFONSO 1621 465 0 24 \n", - ".. ... ... ... ... ... ... \n", - "162 RN VARZEA 1230 470 0 21 \n", - "163 RN VENHA-VER 850 270 0 17 \n", - "164 RN VERA CRUZ 3989 1238 0 211 \n", - "165 RN VICOSA 515 162 0 8 \n", - "166 RN VILA FLOR 847 298 0 10 \n", - "\n", - " CAMINHAO TRATOR CAMINHONETE CAMIONETA CHASSI PLATAF ... QUADRICICLO \\\n", - "0 7 279 91 0 ... 0 \n", - "1 1 153 30 0 ... 0 \n", - "2 0 42 9 0 ... 0 \n", - "3 19 550 62 0 ... 0 \n", - "4 1 95 15 0 ... 0 \n", - ".. ... ... ... ... ... ... \n", - "162 0 62 26 0 ... 0 \n", - "163 0 78 9 0 ... 0 \n", - "164 4 371 49 0 ... 0 \n", - "165 1 27 6 0 ... 0 \n", - "166 2 37 15 0 ... 0 \n", - "\n", - " REBOQUE SEMI-REBOQUE SIDE-CAR OUTROS TRATOR ESTEI TRATOR RODAS \\\n", - "0 31 8 0 15 0 0 \n", - "1 6 1 0 4 0 0 \n", - "2 3 1 0 2 0 0 \n", - "3 48 34 0 25 0 0 \n", - "4 10 4 0 6 0 0 \n", - ".. ... ... ... ... ... ... \n", - "162 9 5 0 4 0 0 \n", - "163 2 0 0 0 0 0 \n", - "164 13 6 0 1 0 0 \n", - "165 1 1 0 4 0 0 \n", - "166 1 2 0 1 0 0 \n", - "\n", - " TRICICLO UTILITARIO suggested_nome_ibge \n", - "0 4 12 acari \n", - "1 0 4 afonso bezerra \n", - "2 0 5 água nova \n", - "3 1 41 alexandria \n", - "4 0 7 almino afonso \n", - ".. ... ... ... \n", - "162 0 2 várzea \n", - "163 0 5 venha-ver \n", - "164 1 27 vera cruz \n", - "165 0 1 viçosa \n", - "166 0 7 vila flor \n", - "\n", - "[167 rows x 25 columns]\n" - ] - } - ], - "source": [ - "import pandas as pd\n", - "zdf = denatran_uf.to_pandas()\n", - "\n", - "REGRAS = {('RN', 'ASSU'): 'açu'}\n", - "\n", - "# Define a function to apply the ruleset\n", - "def get_name_c(row):\n", - " key = (row['sigla_uf'], row['nome_denatran'])\n", - " if key in REGRAS:\n", - " return REGRAS[key]\n", - " else:\n", - " return row['suggested_nome_ibge']\n", - "\n", - "# Apply the function to the DataFrame\n", - "zdf['suggested_nome_ibge'] = zdf.apply(get_name_c, axis=1)\n", - "\n", - "# Print the modified DataFrame\n", - "print(zdf)\n" - ] - }, { "cell_type": "code", "execution_count": null, @@ -428,90 +285,6 @@ "source": [ "zdf.loc[zdf['nome_denatran'] == 'ASSU']" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import polars as pl\n", - "\n", - "# Create example polars DataFrame\n", - "zdf = pl.DataFrame({\n", - " 'sigla_uf': ['RN', 'MG', 'RS'],\n", - " 'nome_denatran': ['ASSU', 'BELO HORIZONTE', 'PORTO ALEGRE'],\n", - " 'suggested_nome_ibge': ['Unknown', 'Unknown', 'Unknown'],\n", - " 'id': [1, 2, 3]\n", - "})\n", - "\n", - "# Define your ruleset as a dictionary\n", - "\n", - "# Define a function to apply the ruleset\n", - "\n", - "\n", - "# Apply the function to the polars DataFrame\n", - "denatran_uf = denatran_uf.with_columns(denatran_uf.apply(fix_suggested_nome_ibge)['apply'].alias('suggested_nome_ibge'))\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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Defaults to 4. + + Returns: + int: Index of the row where the header is contained. + """ header_guess = 0 while header_guess < max_header_guess: # Iffy logic, but essentially: if all rows of the column are strings, then this is a good candidate for a header. @@ -18,6 +30,15 @@ def guess_header(df: pd.DataFrame, max_header_guess: int = 4) -> int: def change_df_header(df: pd.DataFrame, header_row: int) -> pd.DataFrame: + """Changes the dataframe's header to a row inside of it and returns the corrected df. + Ideally, to be used in conjunction with guess_header(). + Args: + df (pd.DataFrame): Dataframe whose header we want changed. + header_row (int): Index of the row where the header is located. + + Returns: + pd.DataFrame: Returns the same dataframe but with the corrected header + """ new_header = df.iloc[header_row] new_df = df[(header_row + 1) :].reset_index(drop=True) new_df.rename(columns=new_header, inplace=True) @@ -25,6 +46,17 @@ def change_df_header(df: pd.DataFrame, header_row: int) -> pd.DataFrame: def get_year_month_from_filename(filename: str) -> tuple[int, int]: + """Helper to extract month and year information from files named indicator_month-year.xls + + Args: + filename (str): Name of the file. + + Raises: + ValueError: Errors out if nothing is found, which likely means the filename is not the correct format. + + Returns: + tuple[int, int]: Month, year. + """ match = re.search(r"(\w+)_(\d{1,2})-(\d{4})\.(xls|xlsx)$", filename) if match: month = match.group(2) @@ -35,29 +67,66 @@ def get_year_month_from_filename(filename: str) -> tuple[int, int]: def verify_total(df: pl.DataFrame) -> None: + """Helper function that is meant to act as a guard to guarantee that we can pivot from wide to long. + Essentially, gets a Wide dataframe, excludes all string columns and the TOTAL column and sums it all row wise. + Then verifies if the calculated total column is the same as the TOTAL column. + If not, raises an error. + + Args: + df (pl.DataFrame): Wide format dataframe to verify. + + Raises: + ValueError: Errors out if the sum of the columns is actually different than the total. + """ columns_for_total = df.select(pl.exclude("TOTAL")).select(pl.exclude([pl.Utf8])) calculated_total = columns_for_total.select( pl.fold( acc=pl.lit(0), function=lambda acc, x: acc + x, exprs=pl.col("*") ).alias("calculated_total") )["calculated_total"] - mask = df["TOTAL"] == calculated_total if pl.sum(~mask) != 0: raise ValueError( - "A coluna de TOTAL da base original tem inconsistências e não soma tudo das demais colunas." + "A coluna de TOTAL da base original tem inconsistências e não é igual à soma das demais colunas." ) -def fix_suggested_nome_ibge(row) -> str: +def fix_suggested_nome_ibge(row: tuple[str, ...]) -> str: + """Gets a row from a dataframe and applies the SUBSTITUTIONS constant ruleset where applicable. + This fixes the dataframe to have the names of municipalities according to IBGE. + The fixes are necessary because match_ibge() will fail where the DENATRAN data has typos in city names. + + Args: + row (tuple[str, ...]): Row from the dataframe we want to apply the IBGE substitutions. + + Raises: + ValueError: Errors out if the desired parts of the row do not conform to the expected format. + + Returns: + str: Returns the suggested IBGE name, either the pre existing or the one in the ruleset for substitutions. + """ key = (row[0], row[1]) - if key in REGRAS: - return REGRAS[key] + if (not isinstance(row[0], str)) or (not isinstance(row[1], str)): + raise ValueError("This is not a valid key to be checked.") + if key in SUBSTITUTIONS: + return SUBSTITUTIONS[key] else: return row[-1] def match_ibge(denatran_uf: pl.DataFrame, ibge_uf: pl.DataFrame) -> None: + """Takes a dataframe of the Denatran data and an IBGE dataframe of municipalities. + Joins them using the IBGE name of both. The IBGE name of denatran_uf is ideally filled via get_city_name(). + This verifies if there are any municipalities in denatran_uf that have no corresponding municipality in the IBGE database. + These must be manually fixed via the constants file and the fix_suggested_nome function. + Will error out if there are municipalities that have no correspondence whatsover. + Args: + denatran_uf (pl.DataFrame): Dataframe with the DENATRAN data, filtered by state (UF). + ibge_uf (pl.DataFrame): Dataframe with the IBGE municipalities data, filtered by state (UF). + + Raises: + ValueError: Errors if there are municipalities that have not match and outputs them all with the state to enable manual fix. + """ joined_df = denatran_uf.join( ibge_uf, left_on=["suggested_nome_ibge", "sigla_uf"], @@ -65,7 +134,6 @@ def match_ibge(denatran_uf: pl.DataFrame, ibge_uf: pl.DataFrame) -> None: how="left", ) mismatched_rows = joined_df.filter(pl.col("id_municipio").is_null()) - if len(mismatched_rows) > 0: error_message = "Os seguintes municípios falharam: \n" for row in mismatched_rows.rows(named=True): @@ -74,6 +142,17 @@ def match_ibge(denatran_uf: pl.DataFrame, ibge_uf: pl.DataFrame) -> None: def get_city_name_ibge(denatran_name: str, ibge_uf: pl.DataFrame) -> str: + """Gets the closest match to the denatran name of the municipality in the IBGE dataframe of the same state. + This ibge_uf dataframe is pulled directly from Base dos Dados to ensure correctness. + Returns either the match or an empty string in case no match is found. + + + Args: + denatran_name (str): The name of the municipality according to DENATRAN data. + ibge_uf (pl.DataFrame): Dataframe with the information from municipalities for a certain state (UF). + Returns: + str: Closest match to the denatran name or an empty string if no such match is found. + """ matches = difflib.get_close_matches( denatran_name.lower(), ibge_uf["nome"].str.to_lowercase(), n=1 ) From 15cec37d4c34734b8f47f223bb0962f46dd73424 Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 23 Apr 2023 14:06:18 -0300 Subject: [PATCH 066/265] Fix documentation in utils --- br_denatran_frota/code/utils.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/br_denatran_frota/code/utils.py b/br_denatran_frota/code/utils.py index d2b561844..160b39d48 100644 --- a/br_denatran_frota/code/utils.py +++ b/br_denatran_frota/code/utils.py @@ -97,7 +97,7 @@ def fix_suggested_nome_ibge(row: tuple[str, ...]) -> str: The fixes are necessary because match_ibge() will fail where the DENATRAN data has typos in city names. Args: - row (tuple[str, ...]): Row from the dataframe we want to apply the IBGE substitutions. + row (tuple[str, ...]): Row from the full DENATRAN dataframe we want to apply the IBGE substitutions to. Raises: ValueError: Errors out if the desired parts of the row do not conform to the expected format. From 0ff97de77a3b54af8f334bbac382445fcaaa17c5 Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 23 Apr 2023 16:24:12 -0300 Subject: [PATCH 067/265] Apply better fuzzy matching for strings --- br_denatran_frota/code/utils.py | 22 +++++++++++++++------- poetry.lock | 17 ++++++++++++++++- pyproject.toml | 1 + 3 files changed, 32 insertions(+), 8 deletions(-) diff --git a/br_denatran_frota/code/utils.py b/br_denatran_frota/code/utils.py index 160b39d48..dcbf1e9db 100644 --- a/br_denatran_frota/code/utils.py +++ b/br_denatran_frota/code/utils.py @@ -1,7 +1,8 @@ # -*- coding: utf-8 -*- import pandas as pd import polars as pl -import difflib +from string_utils import asciify +from thefuzz import process import re from br_denatran_frota.code.constants import DICT_UFS, SUBSTITUTIONS @@ -106,8 +107,12 @@ def fix_suggested_nome_ibge(row: tuple[str, ...]) -> str: str: Returns the suggested IBGE name, either the pre existing or the one in the ruleset for substitutions. """ key = (row[0], row[1]) - if (not isinstance(row[0], str)) or (not isinstance(row[1], str)): - raise ValueError("This is not a valid key to be checked.") + if ( + (not isinstance(row[0], str)) + or (not isinstance(row[1], str)) + or (not isinstance(row[-1], str)) + ): + raise ValueError("This row is not in the expected format.") if key in SUBSTITUTIONS: return SUBSTITUTIONS[key] else: @@ -153,10 +158,13 @@ def get_city_name_ibge(denatran_name: str, ibge_uf: pl.DataFrame) -> str: Returns: str: Closest match to the denatran name or an empty string if no such match is found. """ - matches = difflib.get_close_matches( - denatran_name.lower(), ibge_uf["nome"].str.to_lowercase(), n=1 + matches = process.extract( + denatran_name.lower(), + ibge_uf["nome"].apply(asciify).str.to_lowercase(), + limit=1, ) - if matches: - return matches[0] + matched_name = matches[0] + if matched_name[1] >= 60: # Apply threshold + return matched_name[0] else: return "" # I don't want this to error out directly, because then I can get all municipalities. diff --git a/poetry.lock b/poetry.lock index ea7af3f74..10f586d8f 100644 --- a/poetry.lock +++ b/poetry.lock @@ -3479,6 +3479,21 @@ files = [ {file = "text_unidecode-1.3-py2.py3-none-any.whl", hash = "sha256:1311f10e8b895935241623731c2ba64f4c455287888b18189350b67134a822e8"}, ] +[[package]] +name = "thefuzz" +version = "0.19.0" +description = "Fuzzy string matching in python" +category = "main" +optional = false +python-versions = "*" +files = [ + {file = "thefuzz-0.19.0-py2.py3-none-any.whl", hash = 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0bc7fd6bd37661d98aef0a4129825cfab8b877eb Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 23 Apr 2023 16:53:46 -0300 Subject: [PATCH 069/265] Maybe difflib was better --- br_denatran_frota/code/utils.py | 22 +++++++--------------- poetry.lock | 15 --------------- pyproject.toml | 2 -- 3 files changed, 7 insertions(+), 32 deletions(-) diff --git a/br_denatran_frota/code/utils.py b/br_denatran_frota/code/utils.py index dcbf1e9db..160b39d48 100644 --- a/br_denatran_frota/code/utils.py +++ b/br_denatran_frota/code/utils.py @@ -1,8 +1,7 @@ # -*- coding: utf-8 -*- import pandas as pd import polars as pl -from string_utils import asciify -from thefuzz import process +import difflib import re from br_denatran_frota.code.constants import DICT_UFS, SUBSTITUTIONS @@ -107,12 +106,8 @@ def fix_suggested_nome_ibge(row: tuple[str, ...]) -> str: str: Returns the suggested IBGE name, either the pre existing or the one in the ruleset for substitutions. """ key = (row[0], row[1]) - if ( - (not isinstance(row[0], str)) - or (not isinstance(row[1], str)) - or (not isinstance(row[-1], str)) - ): - raise ValueError("This row is not in the expected format.") + if (not isinstance(row[0], str)) or (not isinstance(row[1], str)): + raise ValueError("This is not a valid key to be checked.") if key in SUBSTITUTIONS: return SUBSTITUTIONS[key] else: @@ -158,13 +153,10 @@ def get_city_name_ibge(denatran_name: str, ibge_uf: pl.DataFrame) -> str: Returns: str: Closest match to the denatran name or an empty string if no such match is found. """ - matches = process.extract( - denatran_name.lower(), - ibge_uf["nome"].apply(asciify).str.to_lowercase(), - limit=1, + matches = difflib.get_close_matches( + denatran_name.lower(), ibge_uf["nome"].str.to_lowercase(), n=1 ) - matched_name = matches[0] - if matched_name[1] >= 60: # Apply threshold - return matched_name[0] + if matches: + return matches[0] else: return "" # I don't want this to error out directly, because then I can get all municipalities. diff --git a/poetry.lock b/poetry.lock index 3fab28aa0..2b0aab238 100644 --- a/poetry.lock +++ b/poetry.lock @@ -3714,21 +3714,6 @@ files = [ {file = "text_unidecode-1.3-py2.py3-none-any.whl", hash = "sha256:1311f10e8b895935241623731c2ba64f4c455287888b18189350b67134a822e8"}, ] -[[package]] -name = "thefuzz" -version = "0.19.0" -description = "Fuzzy string matching in python" -category = "main" -optional = false -python-versions = "*" -files = [ - {file = "thefuzz-0.19.0-py2.py3-none-any.whl", hash = "sha256:4fcdde8e40f5ca5e8106bc7665181f9598a9c8b18b0a4d38c41a095ba6788972"}, - {file = "thefuzz-0.19.0.tar.gz", hash = "sha256:6f7126db2f2c8a54212b05e3a740e45f4291c497d75d20751728f635bb74aa3d"}, -] - -[package.extras] -speedup = ["python-levenshtein (>=0.12)"] - [[package]] name = "toml" version = "0.10.2" diff --git a/pyproject.toml b/pyproject.toml index 094792f1f..65a8f5a47 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -105,8 +105,6 @@ xlrd = "^2.0.1" typer = "^0.7.0" cookiecutter = "^2.1.1" python-string-utils = "^1.0.0" -thefuzz = "^0.19.0" -python-levenshtein = "^0.21.0" [tool.poetry.dev-dependencies] pytest_cov = "^3.0.0" From 882e8beb90d33cedb90ad82b0251b0125c538b6c Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 23 Apr 2023 17:48:09 -0300 Subject: [PATCH 070/265] All rules done afaik --- br_denatran_frota/code/constants.py | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/br_denatran_frota/code/constants.py b/br_denatran_frota/code/constants.py index 88ce21463..7e5cc7425 100644 --- a/br_denatran_frota/code/constants.py +++ b/br_denatran_frota/code/constants.py @@ -30,5 +30,9 @@ } SUBSTITUTIONS = { - ("RN", "ASSU"): "açu", + ("RN", "assu"): "acu", + ("PB", "sao domingos de pombal"): "sao domingos", + ("PB", "santarem"): "joca claudino", + ("SP", "embu"): "embu das artes", + ("TO", "sao valerio da natividade"): "sao valerio", } From a55714eebb657ea13dcb6654213692b109e7c94c Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 23 Apr 2023 17:48:51 -0300 Subject: [PATCH 071/265] Actual decent file to be tested --- .../code/frota_municipio_tipo.py | 62 +++++++++++++++++++ 1 file changed, 62 insertions(+) create mode 100644 br_denatran_frota/code/frota_municipio_tipo.py diff --git a/br_denatran_frota/code/frota_municipio_tipo.py b/br_denatran_frota/code/frota_municipio_tipo.py new file mode 100644 index 000000000..94f37eaf1 --- /dev/null +++ b/br_denatran_frota/code/frota_municipio_tipo.py @@ -0,0 +1,62 @@ +# -*- coding: utf-8 -*- +import polars as pl +import pandas as pd +from string_utils import asciify +import os +from urllib.request import urlopen, urlretrieve +from zipfile import ZipFile +from rarfile import RarFile +from bs4 import BeautifulSoup +import difflib +from br_denatran_frota.code.utils import ( + change_df_header, + fix_suggested_nome_ibge, + guess_header, + get_city_name_ibge, + match_ibge, +) +from br_denatran_frota.code.constants import DICT_UFS, SUBSTITUTIONS + +import basedosdados as bd + +municipios_query = """SELECT nome, id_municipio, sigla_uf FROM `basedosdados.br_bd_diretorios_brasil.municipio` +""" +bd_municipios = bd.read_sql(municipios_query, "tamir-pipelines") +bd_municipios = pl.from_pandas(bd_municipios) + +file = "br_denatran_frota/files/2022/frota_por_município_e_tipo_2-2022.xls" +filename = os.path.split(file)[1] +df = pd.read_excel(file) +new_df = change_df_header(df, guess_header(df)) +new_df.rename( + columns={new_df.columns[0]: "sigla_uf", new_df.columns[1]: "nome_denatran"}, + inplace=True, +) # Rename for ease of use. +new_df.sigla_uf = new_df.sigla_uf.str.strip() # Remove whitespace. +new_df = pl.from_pandas(new_df) +new_df = new_df.with_columns(pl.col("nome_denatran").apply(asciify).str.to_lowercase()) +new_df = new_df.filter(pl.col("nome_denatran") != "municipio nao informado") + + +def verify_uf(denatran_df: pl.DataFrame, ibge_df: pl.DataFrame, uf: str): + denatran_uf = denatran_df.filter(pl.col("sigla_uf") == uf) + ibge_uf = ibge_df.filter(pl.col("sigla_uf") == uf) + ibge_uf = ibge_uf.with_columns(pl.col("nome").apply(asciify).str.to_lowercase()) + municipios_na_bd = ibge_uf["nome"].to_list() + x = denatran_uf["nome_denatran"].apply(lambda x: get_city_name_ibge(x, ibge_uf)) + denatran_uf = denatran_uf.with_columns(x.alias("suggested_nome_ibge")) + denatran_uf = denatran_uf.with_columns( + denatran_uf.apply(fix_suggested_nome_ibge)["apply"].alias("suggested_nome_ibge") + ) + municipios_no_denatran = denatran_uf["suggested_nome_ibge"].to_list() + d = set(municipios_na_bd) - set(municipios_no_denatran) + z = denatran_uf.groupby("suggested_nome_ibge").count().filter(pl.col("count") > 1) + if not z.is_empty(): + print(z["suggested_nome_ibge"].to_list(), uf) + if d: + print(d, uf) + match_ibge(denatran_uf, ibge_uf) + + +for uf in DICT_UFS: + verify_uf(new_df, bd_municipios, uf) From 35d3ebc35b1162c036b2df7317009f8fa8f3e488 Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 23 Apr 2023 17:49:37 -0300 Subject: [PATCH 072/265] Imports cleanup --- br_denatran_frota/code/frota_municipio_tipo.py | 5 ----- 1 file changed, 5 deletions(-) diff --git a/br_denatran_frota/code/frota_municipio_tipo.py b/br_denatran_frota/code/frota_municipio_tipo.py index 94f37eaf1..33b13f8e0 100644 --- a/br_denatran_frota/code/frota_municipio_tipo.py +++ b/br_denatran_frota/code/frota_municipio_tipo.py @@ -3,11 +3,6 @@ import pandas as pd from string_utils import asciify import os -from urllib.request import urlopen, urlretrieve -from zipfile import ZipFile -from rarfile import RarFile -from bs4 import BeautifulSoup -import difflib from br_denatran_frota.code.utils import ( change_df_header, fix_suggested_nome_ibge, From ba51ac5ca31fd7a041c43013a6b025da6cf202fb Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 23 Apr 2023 17:54:06 -0300 Subject: [PATCH 073/265] Added guard --- br_denatran_frota/code/frota_municipio_tipo.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/br_denatran_frota/code/frota_municipio_tipo.py b/br_denatran_frota/code/frota_municipio_tipo.py index 33b13f8e0..48b0eaf0a 100644 --- a/br_denatran_frota/code/frota_municipio_tipo.py +++ b/br_denatran_frota/code/frota_municipio_tipo.py @@ -31,6 +31,8 @@ new_df = pl.from_pandas(new_df) new_df = new_df.with_columns(pl.col("nome_denatran").apply(asciify).str.to_lowercase()) new_df = new_df.filter(pl.col("nome_denatran") != "municipio nao informado") +if new_df.shape[0] != bd_municipios.shape[0]: + raise ValueError("Uh oh") def verify_uf(denatran_df: pl.DataFrame, ibge_df: pl.DataFrame, uf: str): From da00c6d309e99fd6b6dba970bc37a1c484dd805e Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 25 Apr 2023 00:33:34 -0300 Subject: [PATCH 074/265] Clean up --- .../code/frota_municipio_tipo.py | 2 ++ .../test/download_frota_integration_test.py | 3 ++- .../code/test/download_frota_unit_test.py | 3 ++- ...ta_por_munic\303\255pio_e_tipo_2-2022.xls" | Bin 1183744 -> 0 bytes ...or_uf_e_tipo_de_ve\303\255culo_2-2022.xls" | Bin 33792 -> 0 bytes 5 files changed, 6 insertions(+), 2 deletions(-) delete mode 100644 "br_denatran_frota/files/2022/frota_por_munic\303\255pio_e_tipo_2-2022.xls" delete mode 100644 "br_denatran_frota/files/2022/frota_por_uf_e_tipo_de_ve\303\255culo_2-2022.xls" diff --git a/br_denatran_frota/code/frota_municipio_tipo.py b/br_denatran_frota/code/frota_municipio_tipo.py index 48b0eaf0a..2db886fcf 100644 --- a/br_denatran_frota/code/frota_municipio_tipo.py +++ b/br_denatran_frota/code/frota_municipio_tipo.py @@ -12,6 +12,8 @@ ) from br_denatran_frota.code.constants import DICT_UFS, SUBSTITUTIONS +## TODO: Extract everything then run this? Create prefect? where to go now + import basedosdados as bd municipios_query = """SELECT nome, id_municipio, sigla_uf FROM `basedosdados.br_bd_diretorios_brasil.municipio` diff --git a/br_denatran_frota/code/test/download_frota_integration_test.py b/br_denatran_frota/code/test/download_frota_integration_test.py index 331b35be8..654a5b6e0 100644 --- a/br_denatran_frota/code/test/download_frota_integration_test.py +++ b/br_denatran_frota/code/test/download_frota_integration_test.py @@ -1,10 +1,11 @@ +# -*- coding: utf-8 -*- import os import shutil import tempfile import unittest import glob from parameterized import parameterized -from download_frota import ( +from br_denatran_frota.code.download_frota import ( DATASET, MONTHS, download_frota, diff --git a/br_denatran_frota/code/test/download_frota_unit_test.py b/br_denatran_frota/code/test/download_frota_unit_test.py index a128bf894..5442587ef 100644 --- a/br_denatran_frota/code/test/download_frota_unit_test.py +++ b/br_denatran_frota/code/test/download_frota_unit_test.py @@ -1,3 +1,4 @@ +# -*- coding: utf-8 -*- import os import shutil import tempfile @@ -5,7 +6,7 @@ import glob from parameterized import parameterized -from download_frota import ( +from br_denatran_frota.code.download_frota import ( DATASET, MONTHS, make_filename, diff --git "a/br_denatran_frota/files/2022/frota_por_munic\303\255pio_e_tipo_2-2022.xls" "b/br_denatran_frota/files/2022/frota_por_munic\303\255pio_e_tipo_2-2022.xls" deleted file mode 100644 index fd37025cd0a73890779470bcf62c330fdf17bd2c..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 1183744 zcmeFad%R`oS=YI%ySlrQaO>O%34~1&NCGKLxOT z){xGG4&sa%!pt}quNVYJz`J-w5X3=8G;zlJ#M_LHi1C7=h=^R&(Q(9@@Avn-Ywf*H zovM_d8Rw7rOed?(TJL(-dwJgH{yguy|H@x}`0xF;?|JzTkIwz~rK9^t|L)fFMh|Y4 zzli%w{qv`cM)yCjp8wsgTete+ui)k%aJ`F)|B&nH`$nT5<@$y9k48Vn^@}c#MnBH= z?gvJrpWu2A9sDHMdmkE&ewyojS4N|M&P9{||9}54K;UQT<3ZMur5Uj-BbFp<&Qgq6 zh7qqu&*ypp*C%j&BG)HzeKHp)FnXBlglIv|&h;5w zujKknt})kValMM`)m*RP`fRSx;d(9C>$qOe^|@T1$MpuTt6ZPY^>eu1$n_?!N4Os4 zdNbD-aJ_}=3%S0C>*sQPG1ptU-p2JMTwlud7}wjmI<7sgeXawp3D+Ul5!W@YDc3RA zmvNnNopQ~%=3Hl7U(U7QT5_$p)?C-Q-obT)>v67|TtAQNom@Yk>p$Xpg6kJ>J<0Wz zT&}~r`1=&s(_CN0^$WS4;rc~fznJUYTwl%g9lBzf6DdCxIV!3pK*OX*9W;4wDc@rj+yy;`1`(m!HawR@1_1FL8r4PRM$pbln zGU~>CZ%@5noqu1Ie?N(TFO9xG-~3QY-UO%mbJV}}_1{>~x%9xL4ydJCX-`+eo;WAuAv6ln16LznggiD#fzq4Fj; zxiy~maceyMacW$GclUF@xR*=xa`zhY|BpA)Fa5YRUi@)uyzS%ExP)x^cq4uO$7$m} z*RmtoT(#GX9#XB?s`mMBJl7Tlue|(vhWwh_>fPRADt{^32Rg(PZA712BYfiO zFvd;Erp~LbzKR-8Tz&f!S6_Mg4d^gvGf!OI)O_dGz2!Ug57BeF+j?X$w|82FJN-WP z*rw+$boB-0}8jwKT&QlhN-Rz5RTbHOlk7W{{h)&@m7m z8hXp<_p7-MUH5Gaz4xE@YcqWL*yuaeXX)-Wui9Ei->0OFzW+XD=Q{tw(H~G{-fkiz z+y1_QW*0jkd-LeKf>AxlKHsHu7DKoB@U~IEarE74@WXs}zq;s~zZYv_H2Rmfz_Q`L zkBlw9#B<93MgQXNffo{Rxhgm|K;*aQuFX%!Be|0aQMFV;_`0^{BJM+19vF@ zeRnATt~-=}+a1ck`wr#bd57}fbcga^d57{ljpt77|Dm+=g4^Kpo9|Fwuf;@tIU4vK`u!7kDE}3ADF35(DF64J?;lP(ST5)0Rd{jYbxZwov>p|*=&tPNLf7Sj&DQ6YF?w9IE}*-#q9Tc5bS5mDeC8gZm|ZbW>%heibFof{G9?x7K3eCI~Q#CvE& zINrGt(e@r1k=pLuh&cXn8~NzT-B(9~xQ9mWzB(e;Jv4In)sfWhp^>|D;lAyRQy*;=MF-_tk-u-Af~PU!C#2HFEdW zftlUQNbbHmuNoRro(5ji$C*|f9ckS0Ds*%_V{XQJQVh5-GB3eJ2dh$Kl3v~ zBM-qct^D<0|Mj=V?Y}D*ls#{&jOzLC`4^OZ;L7h=%bvh#tE-C^0c zfAEFF2eJjP?GG;94(u;VwO-vl|G|CEe~ZC1V4p`hJfm&JF6y;4a_h0irS8zk7vD=G zgYwWCIS=8t(nvx0!jXL7%KF@ryp0bo-&x%kC(h4*8zzXepu;!a_d?>}SlExe@w3NQ z$A95HPe1uJPrd0wS58MCk`J~2E?s`*txv@1_D15{V`A9j(O*cM@k!#gPw5GyuS>+& zAG-Y1(;xdsKYi-~?=?Zdl+V`su$za^ck{^Y-Ms29-4uDHn+KkH`e#1&w=VAHh3C6@ z^!9E(=PunyfNeGpKK1mE|McIvxSJQ9@8-?7ck{V->E_LwZXSB-=^y#K|McQ+UVOfr zFSxy%&%aAIQf`~gm8YKmp?~(zFYe|g=ev2!?cF?bmu{r@*3I*tdirO7>~CJ&%}ed( z&3DJN&!n3--vg$7^yH6x^hYl4=2Opia{;Ek`YzpUW7CJ{>Tqp+|8$*@8$wb`@Fk!vyEvVJ^AQIe(2(EUVgrt3oz~H+@+gsO#A4` z_y3)Ld~r9gIN!|$nD*#hy4l9GkDmP7zy5s}ck}6X^On0~+L&(Mau1mH$fMuq zoA1)iHl{uD=)d{!uf3?7E2CGz_(prre)Wg0{M=ocdFkc1?k6|v+2lMGb9?~RNi$XX z=)JaV!=+Ckg$(my|A*iGmG6J|vmd(hOLrT)@1?gM!u9vVByyN+^KP0|PgEM(km_LH zsJ3kyeUMByU#fmxqVo3Bm7S;O?L2+ceJ>}#{1OK9WAA?dyPq7t>#6ber{4F>)6ab6 zlRx?o7}__V8``JddI>}OF$U$po`PV#)r@6k8@*gF$a(CDow$T-~>8c;L zD(Qp6unuRrr1K>6gmp8OEX(~dTC-^*@&%DE9=XN>P@ zpna0@Kgo#hM{_Cg4j}D;sPX&Y=$r2Q1R}ny+MqUdyB%Hr3|8$`|zU_}aesQC(-!uxdIN#{& z&o#QuAjsc)*KfbL(a+s93Trsu=+$$LZnFat9l!I>T-@mAZ5o9UoNx3^=NjE6{?X`P zeaqp+jlRJ~C+~UgeL=JHH2Y#2?b8x_q}tG|)^(3yn&AI8Y4-By>IX01`p}i}E($(y znNCiVu~Jw)0&OpkKL3LcQTKJ{>OMrq^rr5Ztj{+lhsWAE)>LU(y@&0F!3UA&0_|hvF>H;u5b51Vk78rnp@1Ozc z`J@Kp;95TU6Ed>*?>2VdOZa3-??2I4)&{$_C4&5M2fHlTfTEsyP}EZoih2?hZ~owe zfa2Qj03LYo)~7Lmr^v80|5PLwEWHHyYG(Ov@_>E!6t?0nM!kq^XJWXkr@rpFXB9Ht z*FN(#VAlR_7x%s3)+dpg{1oZH&(V0_bVr)-Gc+lt-8V35q+JiVm!jJd&Z^cYU-#a3 zBfg${=4nxb^T(2NSw_FXJw$We)Avp6f=5+Sca#^VcVNGIN{^G5c5h>?ee&KB`mr%Jw%cW-D zmzLkU)iQGB3(rC0MYpxAWVs!(_#K{4+C22Lf^EF}HkeX8I=;fXkyV`QZJ~#cOs)_`v57ha#_=ua9Q zPOeWDlj&mq#3OHf^3yMkE?xdq zmZbmYW#rd=7Qt#WKU&!*>cJZQX|%>qC4Q|;9=&4g_30bm{H8a}-}1y0PdxoTmg0%` zKKs5W-v9Iy&pq?rXZi5{;lo#q#=Gr4ly>7c9sS8mSGd?D@lQT!^y6$x_~g;(rxx}! 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z3hJRTI@xg1F7{n^(??%8mS_CxTAMiWga=;F18z40?SlF95v&MUj7!{d{Bk?+Y6L!7 zxDBBX!d3)sneRm4mfS7`+T7cy%-fv|geEt>7Sh(>oxIH3>~2?h-a^Lvqr=Dw)vff@ z;}a&{MxR!?s@~lshnv45W$4Kr&spp&IHP#8A>8p#3>t+?R*)FC(NQu>EXze}qK{-1=!kV7q+?Y}17ZZ0{NbZd*|=)WdZM)XV({ zMm-Q0{GJM;a!isEY4VEqI}*$&4`qq`@{#C+EV7`QIgG2DTrHla<*s%~oR$8MmjxP3 z24#*6+)+qs0Y!7}82oBMj{KsGsiQQ!=RZ|?n<7tR<4k#ILH6L}n&ob{Z}Lp>@hRJX zsE8ed{~8TgaMXcch;0=Pd^F{pZ_R{%h1=*AdqRNYr==$adsyb%^6w$p9vAy}=KsGO C<*<+d From baceabcd177543e48a7d3ebeabd4e0d496c88e2e Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 25 Apr 2023 02:34:39 -0300 Subject: [PATCH 075/265] Reorganizing --- br_denatran_frota/code/constants.py | 22 +++ br_denatran_frota/code/download_frota.py | 127 +----------------- .../code/test/download_frota_unit_test.py | 8 +- br_denatran_frota/code/utils.py | 114 +++++++++++++++- 4 files changed, 140 insertions(+), 131 deletions(-) diff --git a/br_denatran_frota/code/constants.py b/br_denatran_frota/code/constants.py index 7e5cc7425..ce21f239e 100644 --- a/br_denatran_frota/code/constants.py +++ b/br_denatran_frota/code/constants.py @@ -1,4 +1,26 @@ # -*- coding: utf-8 -*- + +MONTHS = { + "janeiro": 1, + "fevereiro": 2, + "marco": 3, + "abril": 4, + "maio": 5, + "junho": 6, + "julho": 7, + "agosto": 8, + "setembro": 9, + "outubro": 10, + "novembro": 11, + "dezembro": 12, +} + +DATASET = "br_denatran_frota" + +HEADERS = { + "User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/39.0.2171.95 Safari/537.36" +} + DICT_UFS = { "AC": "Acre", "AL": "Alagoas", diff --git a/br_denatran_frota/code/download_frota.py b/br_denatran_frota/code/download_frota.py index 6060769fc..7306d08c6 100644 --- a/br_denatran_frota/code/download_frota.py +++ b/br_denatran_frota/code/download_frota.py @@ -1,133 +1,10 @@ # -*- coding: utf-8 -*- import os -import re import glob from urllib.request import urlopen, urlretrieve from zipfile import ZipFile -from rarfile import RarFile -from bs4 import BeautifulSoup -import requests - -MONTHS = { - "janeiro": 1, - "fevereiro": 2, - "marco": 3, - "abril": 4, - "maio": 5, - "junho": 6, - "julho": 7, - "agosto": 8, - "setembro": 9, - "outubro": 10, - "novembro": 11, - "dezembro": 12, -} - -DATASET = "br_denatran_frota" -HEADERS = { - "User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/39.0.2171.95 Safari/537.36" -} - - -def download_file(url, filename): - # Send a GET request to the URL - - new_url = url.replace("arquivos-denatran", "arquivos-senatran") - response = requests.get(new_url, headers=HEADERS) - # Save the contents of the response to a file - with open(filename, "wb") as f: - f.write(response.content) - - print(f"Download of {filename} complete") - - -def extract_zip(dest_path_file): - with ZipFile(dest_path_file, "r") as z: - z.extractall() - - -def handle_xl(i: dict) -> None: - """Actually downloads and deals with Excel files. - - Args: - i (dict): Dictionary with all the desired downloadable file's info. - """ - dest_path_file = make_filename(i) - download_file(i["href"], dest_path_file) - - -def make_filename(i: dict, ext: bool = True) -> str: - """Creates the filename using the sent dictionary. - - Args: - i (dict): Dictionary with all the file's info. - ext (bool, optional): Specifies if the generated file name needs the filetype at the end. Defaults to True. - - Returns: - str: The full filename. - """ - txt = i["txt"] - mes = i["mes"] - ano = i["ano"] - filetype = i["filetype"] - filename = re.sub("\\s+", "_", txt, flags=re.UNICODE).lower() - filename = f"{filename}_{mes}-{ano}" - if ext: - filename += f".{filetype}" - return filename - - -def call_downloader(i): - filename = make_filename(i) - if i["filetype"] in ["xlsx", "xls"]: - download_file(i["href"], filename) - elif i["filetype"] == "zip": - download_file(i["href"], filename) - extract_zip(filename) - - -def download_post_2012(month: int, year: int): - """_summary_ - - Args: - year (int): _description_ - month (int): _description_ - """ - url = f"https://www.gov.br/infraestrutura/pt-br/assuntos/transito/conteudo-Senatran/frota-de-veiculos-{year}" - soup = BeautifulSoup(urlopen(url), "html.parser") - # Só queremos os dados de frota nacional. - nodes = soup.select("p:contains('rota por ') > a") - for node in nodes: - txt = node.text - href = node.get("href") - # Pega a parte relevante do arquivo em questão. - match = re.search( - r"(?i)\/([\w-]+)\/(\d{4})\/(\w+)\/([\w-]+)\.(?:xls|xlsx|rar|zip)$", href - ) - if match: - matched_month = match.group(3) - matched_year = match.group(2) - if MONTHS.get(matched_month) == month and matched_year == str(year): - filetype = match.group(0).split(".")[-1].lower() - info = { - "txt": txt, - "href": href, - "mes_name": matched_month, - "mes": month, - "ano": year, - "filetype": filetype, - } - call_downloader(info) - - -def make_dir_when_not_exists(dir_name: str): - """Auxiliary function to create a subdirectory when it is not present. - - Args: - dir_name (str): Name of the subdirectory to be created. - """ - if not os.path.exists(dir_name): - os.mkdir(dir_name) +from br_denatran_frota.code.constants import MONTHS, DATASET +from br_denatran_frota.code.utils import make_dir_when_not_exists, download_post_2012 def download_frota(month: int, year: int, temp_dir: str = ""): diff --git a/br_denatran_frota/code/test/download_frota_unit_test.py b/br_denatran_frota/code/test/download_frota_unit_test.py index 5442587ef..65007d9d5 100644 --- a/br_denatran_frota/code/test/download_frota_unit_test.py +++ b/br_denatran_frota/code/test/download_frota_unit_test.py @@ -6,14 +6,12 @@ import glob from parameterized import parameterized -from br_denatran_frota.code.download_frota import ( - DATASET, - MONTHS, +from br_denatran_frota.code.utils import ( make_filename, make_dir_when_not_exists, - download_frota, ) - +from br_denatran_frota.code.constants import DATASET +from br_denatran_frota.code.download_frota import download_frota dir_list = glob.glob(f"**/{DATASET}", recursive=True) if dir_list: diff --git a/br_denatran_frota/code/utils.py b/br_denatran_frota/code/utils.py index 160b39d48..8aa9bebec 100644 --- a/br_denatran_frota/code/utils.py +++ b/br_denatran_frota/code/utils.py @@ -3,7 +3,18 @@ import polars as pl import difflib import re -from br_denatran_frota.code.constants import DICT_UFS, SUBSTITUTIONS +import os +from zipfile import ZipFile +from br_denatran_frota.code.constants import ( + DICT_UFS, + SUBSTITUTIONS, + HEADERS, + DATASET, + MONTHS, +) +import requests +from urllib.request import urlopen, urlretrieve +from bs4 import BeautifulSoup def guess_header(df: pd.DataFrame, max_header_guess: int = 4) -> int: @@ -160,3 +171,104 @@ def get_city_name_ibge(denatran_name: str, ibge_uf: pl.DataFrame) -> str: return matches[0] else: return "" # I don't want this to error out directly, because then I can get all municipalities. + + +def download_file(url, filename): + # Send a GET request to the URL + + new_url = url.replace("arquivos-denatran", "arquivos-senatran") + response = requests.get(new_url, headers=HEADERS) + # Save the contents of the response to a file + with open(filename, "wb") as f: + f.write(response.content) + + print(f"Download of {filename} complete") + + +def extract_zip(dest_path_file): + with ZipFile(dest_path_file, "r") as z: + z.extractall() + + +def handle_xl(i: dict) -> None: + """Actually downloads and deals with Excel files. + + Args: + i (dict): Dictionary with all the desired downloadable file's info. + """ + dest_path_file = make_filename(i) + download_file(i["href"], dest_path_file) + + +def make_filename(i: dict, ext: bool = True) -> str: + """Creates the filename using the sent dictionary. + + Args: + i (dict): Dictionary with all the file's info. + ext (bool, optional): Specifies if the generated file name needs the filetype at the end. Defaults to True. + + Returns: + str: The full filename. + """ + txt = i["txt"] + mes = i["mes"] + ano = i["ano"] + filetype = i["filetype"] + filename = re.sub("\\s+", "_", txt, flags=re.UNICODE).lower() + filename = f"{filename}_{mes}-{ano}" + if ext: + filename += f".{filetype}" + return filename + + +def call_downloader(i): + filename = make_filename(i) + if i["filetype"] in ["xlsx", "xls"]: + download_file(i["href"], filename) + elif i["filetype"] == "zip": + download_file(i["href"], filename) + extract_zip(filename) + + +def download_post_2012(month: int, year: int): + """_summary_ + + Args: + year (int): _description_ + month (int): _description_ + """ + url = f"https://www.gov.br/infraestrutura/pt-br/assuntos/transito/conteudo-Senatran/frota-de-veiculos-{year}" + soup = BeautifulSoup(urlopen(url), "html.parser") + # Só queremos os dados de frota nacional. + nodes = soup.select("p:contains('rota por ') > a") + for node in nodes: + txt = node.text + href = node.get("href") + # Pega a parte relevante do arquivo em questão. + match = re.search( + r"(?i)\/([\w-]+)\/(\d{4})\/(\w+)\/([\w-]+)\.(?:xls|xlsx|rar|zip)$", href + ) + if match: + matched_month = match.group(3) + matched_year = match.group(2) + if MONTHS.get(matched_month) == month and matched_year == str(year): + filetype = match.group(0).split(".")[-1].lower() + info = { + "txt": txt, + "href": href, + "mes_name": matched_month, + "mes": month, + "ano": year, + "filetype": filetype, + } + call_downloader(info) + + +def make_dir_when_not_exists(dir_name: str): + """Auxiliary function to create a subdirectory when it is not present. + + Args: + dir_name (str): Name of the subdirectory to be created. + """ + if not os.path.exists(dir_name): + os.mkdir(dir_name) From 293364bf4dc61ab8e8eb7a9404fa97db2eb1c048 Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 26 Apr 2023 01:50:35 -0300 Subject: [PATCH 076/265] Testing more stuff --- br_denatran_frota/code/download_frota.py | 6 --- .../test/download_frota_integration_test.py | 1 + .../code/test/download_frota_unit_test.py | 47 +++++++++++++++++++ br_denatran_frota/code/utils.py | 1 + 4 files changed, 49 insertions(+), 6 deletions(-) diff --git a/br_denatran_frota/code/download_frota.py b/br_denatran_frota/code/download_frota.py index 7306d08c6..4c6bb56da 100644 --- a/br_denatran_frota/code/download_frota.py +++ b/br_denatran_frota/code/download_frota.py @@ -50,9 +50,3 @@ def download_frota(month: int, year: int, temp_dir: str = ""): with ZipFile(generic_zip_filename) as zip_file: zip_file.extractall() os.chdir(initial_dir) - - -year = 2022 -if __name__ == "__main__": - for month in range(1, 6): - download_frota(month, year) diff --git a/br_denatran_frota/code/test/download_frota_integration_test.py b/br_denatran_frota/code/test/download_frota_integration_test.py index 654a5b6e0..d110cef91 100644 --- a/br_denatran_frota/code/test/download_frota_integration_test.py +++ b/br_denatran_frota/code/test/download_frota_integration_test.py @@ -29,6 +29,7 @@ def tearDown(self): print("Deleting temporary directory") shutil.rmtree(self.temp_dir.name) + @unittest.skip("take it easy") @parameterized.expand( [(month, year) for year in range(2021, 2023) for month in range(1, 12)], name_func=custom_name_func, diff --git a/br_denatran_frota/code/test/download_frota_unit_test.py b/br_denatran_frota/code/test/download_frota_unit_test.py index 65007d9d5..0ddfba6c2 100644 --- a/br_denatran_frota/code/test/download_frota_unit_test.py +++ b/br_denatran_frota/code/test/download_frota_unit_test.py @@ -4,6 +4,7 @@ import tempfile import unittest import glob +import pandas as pd from parameterized import parameterized from br_denatran_frota.code.utils import ( @@ -12,6 +13,7 @@ ) from br_denatran_frota.code.constants import DATASET from br_denatran_frota.code.download_frota import download_frota +from br_denatran_frota.code.utils import guess_header dir_list = glob.glob(f"**/{DATASET}", recursive=True) if dir_list: @@ -71,5 +73,50 @@ def test_download_frota_with_invalid_month(self): download_frota(13, 2013) +class TestGuessHeader(unittest.TestCase): + def test_correct_header_guess(self): + # Test case 1: Correct header guess + df = pd.DataFrame( + { + "A": ["Name", "Alice", "Bob"], + "B": ["Age", 30, 40], + "C": ["Country", "USA", "Canada"], + } + ) + self.assertEqual(guess_header(df), 0) # Header is in the first row + + def test_no_header_found(self): + # Test case 2: No header found + df = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6], "C": [7, 8, 9]}) + self.assertEqual( + guess_header(df), 0 + ) # Header is assumed to be in the first row + + def test_header_found_beyond_max_header_guess(self): + # Test case 3: Header found beyond max_header_guess + df = pd.DataFrame( + {"A": [1, 2, 3], "B": [4, 5, 6], "C": ["Name", "Alice", "Bob"]} + ) + self.assertEqual( + guess_header(df, max_header_guess=2), 0 + ) # Header is assumed to be in the first row + + def test_empty_dataframe(self): + # Test case 4: Empty dataframe + df = pd.DataFrame() + self.assertEqual( + guess_header(df), 0 + ) # Header is assumed to be in the first row + + def test_all_columns_are_strings_not_in_header_row(self): + # Test case 5: All columns are strings but not in header row + df = pd.DataFrame( + {"A": ["1", "2", "3"], "B": ["4", "5", "6"], "C": ["7", "8", "9"]} + ) + self.assertEqual( + guess_header(df), 0 + ) # Header is assumed to be in the first row + + if __name__ == "__main__": unittest.main() diff --git a/br_denatran_frota/code/utils.py b/br_denatran_frota/code/utils.py index 8aa9bebec..b6fcf2cf7 100644 --- a/br_denatran_frota/code/utils.py +++ b/br_denatran_frota/code/utils.py @@ -50,6 +50,7 @@ def change_df_header(df: pd.DataFrame, header_row: int) -> pd.DataFrame: Returns: pd.DataFrame: Returns the same dataframe but with the corrected header """ + print(2) new_header = df.iloc[header_row] new_df = df[(header_row + 1) :].reset_index(drop=True) new_df.rename(columns=new_header, inplace=True) From dda7427c8872715698c6b9c25a9ec8b72ef5a2cc Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 26 Apr 2023 03:13:01 -0300 Subject: [PATCH 077/265] Coverage back --- poetry.lock | 259 +++---------------------------------------------- pyproject.toml | 4 +- 2 files changed, 13 insertions(+), 250 deletions(-) diff --git a/poetry.lock b/poetry.lock index 2b0aab238..5409f7a5b 100644 --- a/poetry.lock +++ b/poetry.lock @@ -61,7 +61,7 @@ files = [ name = "attrs" version = "22.2.0" description = "Classes Without Boilerplate" -category = "dev" +category = "main" optional = false python-versions = ">=3.6" files = [ @@ -470,7 +470,7 @@ requests = ">=2.23.0" name = "coverage" version = "7.2.3" description = "Code coverage measurement for Python" -category = "dev" +category = "main" optional = false python-versions = ">=3.7" files = [ @@ -763,7 +763,7 @@ files = [ name = "exceptiongroup" version = "1.1.1" description = 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-[tool.poetry.dev-dependencies] -pytest_cov = "^3.0.0" +pytest-cov = "^4.0.0" [tool.poetry.group.dev.dependencies] pytest = "^7.2.2" From 19d276fd5076ef73f5f61b1cbfcf6193f50167ae Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 26 Apr 2023 03:13:15 -0300 Subject: [PATCH 078/265] Increasing coverage and cleanup of guess header --- br_denatran_frota/code/utils.py | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/br_denatran_frota/code/utils.py b/br_denatran_frota/code/utils.py index b6fcf2cf7..9c961c375 100644 --- a/br_denatran_frota/code/utils.py +++ b/br_denatran_frota/code/utils.py @@ -21,17 +21,19 @@ def guess_header(df: pd.DataFrame, max_header_guess: int = 4) -> int: """Function to deal with problematic dataframes coming from Excel/CSV files. Tries to guess which row is the header by examining the first few rows (max given by max_header_guess). Assumes that the header is the first row where all of the columns are strings. - This will NOT work for a strings only dataframe. + This will NOT properly work for a strings only dataframe and will always guess the first row for it. Args: df (pd.DataFrame): Dataframe whose header we don't know. - max_header_guess (int, optional): Number of initial rows we want to check . Defaults to 4. + max_header_guess (int, optional): Number of initial rows we want to check. Defaults to 4. Returns: int: Index of the row where the header is contained. """ header_guess = 0 while header_guess < max_header_guess: + if len(df) - 1 < header_guess: + break # Iffy logic, but essentially: if all rows of the column are strings, then this is a good candidate for a header. if all(df.iloc[header_guess].apply(lambda x: isinstance(x, str))): return header_guess @@ -50,7 +52,6 @@ def change_df_header(df: pd.DataFrame, header_row: int) -> pd.DataFrame: Returns: pd.DataFrame: Returns the same dataframe but with the corrected header """ - print(2) new_header = df.iloc[header_row] new_df = df[(header_row + 1) :].reset_index(drop=True) new_df.rename(columns=new_header, inplace=True) From 9faed06c05a7e8448fc80e8aba26b09acd34aa65 Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 26 Apr 2023 03:13:26 -0300 Subject: [PATCH 079/265] Reduce exposure --- br_denatran_frota/code/test/download_frota_integration_test.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/br_denatran_frota/code/test/download_frota_integration_test.py b/br_denatran_frota/code/test/download_frota_integration_test.py index d110cef91..68fc426cf 100644 --- a/br_denatran_frota/code/test/download_frota_integration_test.py +++ b/br_denatran_frota/code/test/download_frota_integration_test.py @@ -31,7 +31,7 @@ def tearDown(self): @unittest.skip("take it easy") @parameterized.expand( - [(month, year) for year in range(2021, 2023) for month in range(1, 12)], + [(month, year) for year in range(2021, 2022) for month in range(1, 3)], name_func=custom_name_func, ) def test_download_post_2012(self, month, year): From 514f156f669f3d3c2d40c6b30223ef6c711d7f78 Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 26 Apr 2023 03:37:40 -0300 Subject: [PATCH 080/265] More testing --- .../code/test/download_frota_unit_test.py | 18 +++++++++++++++++- 1 file changed, 17 insertions(+), 1 deletion(-) diff --git a/br_denatran_frota/code/test/download_frota_unit_test.py b/br_denatran_frota/code/test/download_frota_unit_test.py index 0ddfba6c2..a43275729 100644 --- a/br_denatran_frota/code/test/download_frota_unit_test.py +++ b/br_denatran_frota/code/test/download_frota_unit_test.py @@ -13,7 +13,7 @@ ) from br_denatran_frota.code.constants import DATASET from br_denatran_frota.code.download_frota import download_frota -from br_denatran_frota.code.utils import guess_header +from br_denatran_frota.code.utils import guess_header, get_year_month_from_filename dir_list = glob.glob(f"**/{DATASET}", recursive=True) if dir_list: @@ -118,5 +118,21 @@ def test_all_columns_are_strings_not_in_header_row(self): ) # Header is assumed to be in the first row +class TestFilenameExtraction(unittest.TestCase): + def test_correct_file(self): + filename = "indicator_2-2022.xlsx" + self.assertEqual(get_year_month_from_filename(filename), ("2", "2022")) + + def test_not_excel_file(self): + filename = "indicator_2-2022" + with self.assertRaises(ValueError): + get_year_month_from_filename(filename) + + def test_excel_but_incorrect_format(self): + filename = "random_2_20.xlsx" + with self.assertRaises(ValueError): + get_year_month_from_filename(filename) + + if __name__ == "__main__": unittest.main() From 02cd15a08c54552178dcb7f5cd76e0943890bca8 Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 26 Apr 2023 03:37:52 -0300 Subject: [PATCH 081/265] Erroring when appropriate for municipio_tipo --- .../code/frota_municipio_tipo.py | 56 +++++++++++-------- 1 file changed, 33 insertions(+), 23 deletions(-) diff --git a/br_denatran_frota/code/frota_municipio_tipo.py b/br_denatran_frota/code/frota_municipio_tipo.py index 2db886fcf..a400a88af 100644 --- a/br_denatran_frota/code/frota_municipio_tipo.py +++ b/br_denatran_frota/code/frota_municipio_tipo.py @@ -9,6 +9,7 @@ guess_header, get_city_name_ibge, match_ibge, + verify_total, ) from br_denatran_frota.code.constants import DICT_UFS, SUBSTITUTIONS @@ -16,12 +17,39 @@ import basedosdados as bd + +def verify_uf(denatran_df: pl.DataFrame, ibge_df: pl.DataFrame, uf: str): + denatran_uf = denatran_df.filter(pl.col("sigla_uf") == uf) + ibge_uf = ibge_df.filter(pl.col("sigla_uf") == uf) + ibge_uf = ibge_uf.with_columns(pl.col("nome").apply(asciify).str.to_lowercase()) + municipios_na_bd = ibge_uf["nome"].to_list() + x = denatran_uf["nome_denatran"].apply(lambda x: get_city_name_ibge(x, ibge_uf)) + denatran_uf = denatran_uf.with_columns(x.alias("suggested_nome_ibge")) + denatran_uf = denatran_uf.with_columns( + denatran_uf.apply(fix_suggested_nome_ibge)["apply"].alias("suggested_nome_ibge") + ) + municipios_no_denatran = denatran_uf["suggested_nome_ibge"].to_list() + d = set(municipios_no_denatran) - set(municipios_na_bd) + municipios_duplicados = ( + denatran_uf.groupby("suggested_nome_ibge").count().filter(pl.col("count") > 1) + ) + if not municipios_duplicados.is_empty(): + raise ValueError( + f"Existem municípios com mesmo nome do IBGE em {uf}! São eles {municipios_duplicados['suggested_nome_ibge'].to_list()}" + ) + if d: + # This here is probably impossible and shouldn't happen due to the matching coming from the BD data. + # The set difference might occur the other way around, but still, better safe. + raise ValueError(f"Existem municípios em {uf} que não estão na BD.") + match_ibge(denatran_uf, ibge_uf) + + municipios_query = """SELECT nome, id_municipio, sigla_uf FROM `basedosdados.br_bd_diretorios_brasil.municipio` """ bd_municipios = bd.read_sql(municipios_query, "tamir-pipelines") bd_municipios = pl.from_pandas(bd_municipios) -file = "br_denatran_frota/files/2022/frota_por_município_e_tipo_2-2022.xls" +file = "br_denatran_frota/files/2022/frota_por_município_e_tipo_2-2022.xls" # Hardcode problem filename = os.path.split(file)[1] df = pd.read_excel(file) new_df = change_df_header(df, guess_header(df)) @@ -33,29 +61,11 @@ new_df = pl.from_pandas(new_df) new_df = new_df.with_columns(pl.col("nome_denatran").apply(asciify).str.to_lowercase()) new_df = new_df.filter(pl.col("nome_denatran") != "municipio nao informado") -if new_df.shape[0] != bd_municipios.shape[0]: - raise ValueError("Uh oh") - - -def verify_uf(denatran_df: pl.DataFrame, ibge_df: pl.DataFrame, uf: str): - denatran_uf = denatran_df.filter(pl.col("sigla_uf") == uf) - ibge_uf = ibge_df.filter(pl.col("sigla_uf") == uf) - ibge_uf = ibge_uf.with_columns(pl.col("nome").apply(asciify).str.to_lowercase()) - municipios_na_bd = ibge_uf["nome"].to_list() - x = denatran_uf["nome_denatran"].apply(lambda x: get_city_name_ibge(x, ibge_uf)) - denatran_uf = denatran_uf.with_columns(x.alias("suggested_nome_ibge")) - denatran_uf = denatran_uf.with_columns( - denatran_uf.apply(fix_suggested_nome_ibge)["apply"].alias("suggested_nome_ibge") +if new_df.shape[0] > bd_municipios.shape[0]: + raise ValueError( + f"Atenção: a base do Denatran tem {new_df.shape[0]} linhas e isso é mais municípios do que a BD com {bd_municipios.shape[0]}" ) - municipios_no_denatran = denatran_uf["suggested_nome_ibge"].to_list() - d = set(municipios_na_bd) - set(municipios_no_denatran) - z = denatran_uf.groupby("suggested_nome_ibge").count().filter(pl.col("count") > 1) - if not z.is_empty(): - print(z["suggested_nome_ibge"].to_list(), uf) - if d: - print(d, uf) - match_ibge(denatran_uf, ibge_uf) - +verify_total(new_df) for uf in DICT_UFS: verify_uf(new_df, bd_municipios, uf) From 5fb737fe0e94e4ea98886db0b9ee9a9ee80c6f40 Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 26 Apr 2023 03:39:27 -0300 Subject: [PATCH 082/265] This is useless --- br_denatran_frota/code/test/download_frota_integration_test.py | 1 - 1 file changed, 1 deletion(-) diff --git a/br_denatran_frota/code/test/download_frota_integration_test.py b/br_denatran_frota/code/test/download_frota_integration_test.py index 68fc426cf..649035b43 100644 --- a/br_denatran_frota/code/test/download_frota_integration_test.py +++ b/br_denatran_frota/code/test/download_frota_integration_test.py @@ -29,7 +29,6 @@ def tearDown(self): print("Deleting temporary directory") shutil.rmtree(self.temp_dir.name) - @unittest.skip("take it easy") @parameterized.expand( [(month, year) for year in range(2021, 2022) for month in range(1, 3)], name_func=custom_name_func, From 4d2f644662a65dc9ff6a6a4aa103aef715f1c257 Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 26 Apr 2023 04:30:05 -0300 Subject: [PATCH 083/265] Directories are again working!!!! --- br_denatran_frota/code/download_frota.py | 8 ++++---- .../code/test/download_frota_integration_test.py | 8 ++++---- 2 files changed, 8 insertions(+), 8 deletions(-) diff --git a/br_denatran_frota/code/download_frota.py b/br_denatran_frota/code/download_frota.py index 4c6bb56da..ff4b771f3 100644 --- a/br_denatran_frota/code/download_frota.py +++ b/br_denatran_frota/code/download_frota.py @@ -23,14 +23,14 @@ def download_frota(month: int, year: int, temp_dir: str = ""): dir_list = glob.glob(f"**/{DATASET}", recursive=True) # Get the directory where this Python file is located initial_dir = os.path.dirname(os.path.abspath(__file__)) - + if temp_dir: + os.chdir(temp_dir) # Construct the path to the "files" directory relative to this directory - files_dir = os.path.join(initial_dir, "..", "files") + files_dir = os.path.join(os.getcwd(), "files") if dir_list: # I always want to be in the actual folder for this dataset, because I might start in the pipelines full repo: os.chdir(dir_list[0]) - if temp_dir: - os.chdir(temp_dir) + # I always need a files directory inside my dataset folder. make_dir_when_not_exists(files_dir) # I should always switch to the files dir now and save stuff inside it. diff --git a/br_denatran_frota/code/test/download_frota_integration_test.py b/br_denatran_frota/code/test/download_frota_integration_test.py index 649035b43..844cd2cc0 100644 --- a/br_denatran_frota/code/test/download_frota_integration_test.py +++ b/br_denatran_frota/code/test/download_frota_integration_test.py @@ -4,6 +4,7 @@ import tempfile import unittest import glob +import contextlib from parameterized import parameterized from br_denatran_frota.code.download_frota import ( DATASET, @@ -23,7 +24,8 @@ class TestAllPossibleYears(unittest.TestCase): def setUp(self): file_dir = os.path.dirname(os.path.abspath(__file__)) os.chdir(file_dir) - self.temp_dir = tempfile.TemporaryDirectory(dir=file_dir) + dataset_dir = os.path.join(file_dir, "..", "..") + self.temp_dir = tempfile.TemporaryDirectory(dir=dataset_dir) def tearDown(self): print("Deleting temporary directory") @@ -39,9 +41,7 @@ def test_download_post_2012(self, month, year): f"frota_por_uf_e_tipo_de_veículo_{month}-{year}", f"frota_por_município_e_tipo_{month}-{year}", } - list_of_files = os.listdir( - os.path.join(DATASET, self.temp_dir.name, "files", f"{year}") - ) + list_of_files = os.listdir(os.path.join(self.temp_dir.name, "files", f"{year}")) files = set(os.path.splitext(file)[0] for file in list_of_files) self.assertEqual(files, expected_files) From 5896ac96d04137f60db232997a50c21e60c84563 Mon Sep 17 00:00:00 2001 From: Tamir Date: Sat, 29 Apr 2023 02:37:08 -0300 Subject: [PATCH 084/265] All constants --- .../datasets/br_denatran_frota/constants.py | 49 +++++++++++-------- 1 file changed, 28 insertions(+), 21 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/constants.py b/pipelines/datasets/br_denatran_frota/constants.py index 0e14e5a3e..5491b46cb 100644 --- a/pipelines/datasets/br_denatran_frota/constants.py +++ b/pipelines/datasets/br_denatran_frota/constants.py @@ -39,6 +39,29 @@ class constants(Enum): # pylint: disable=c0103 Constant values for the br_denatran_frota project """ + # -*- coding: utf-8 -*- + + MONTHS = { + "janeiro": 1, + "fevereiro": 2, + "marco": 3, + "abril": 4, + "maio": 5, + "junho": 6, + "julho": 7, + "agosto": 8, + "setembro": 9, + "outubro": 10, + "novembro": 11, + "dezembro": 12, + } + + DATASET = "br_denatran_frota" + + HEADERS = { + "User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/39.0.2171.95 Safari/537.36" + } + DICT_UFS = { "AC": "Acre", "AL": "Alagoas", @@ -70,25 +93,9 @@ class constants(Enum): # pylint: disable=c0103 } SUBSTITUTIONS = { - ("RN", "ASSU"): "açu", - } - - MONTHS = { - "janeiro": 1, - "fevereiro": 2, - "marco": 3, - "abril": 4, - "maio": 5, - "junho": 6, - "julho": 7, - "agosto": 8, - "setembro": 9, - "outubro": 10, - "novembro": 11, - "dezembro": 12, - } - - DATASET = "br_denatran_frota" - HEADERS = { - "User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/39.0.2171.95 Safari/537.36" + ("RN", "assu"): "acu", + ("PB", "sao domingos de pombal"): "sao domingos", + ("PB", "santarem"): "joca claudino", + ("SP", "embu"): "embu das artes", + ("TO", "sao valerio da natividade"): "sao valerio", } From a42845c78f4a8494827acaa4390fb20d68468edb Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Sat, 29 Apr 2023 05:51:16 +0000 Subject: [PATCH 085/265] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- br_denatran_frota/README.md | 2 +- br_denatran_frota/code/download_frota.R | 14 +-- br_denatran_frota/code/download_frota_old.R | 38 +++--- br_denatran_frota/code/frota_municipio_tipo.R | 10 +- br_denatran_frota/code/frota_uf_tipo.R | 6 +- br_denatran_frota/code/setup.py | 11 +- br_denatran_frota/code/utils.R | 54 ++++----- br_denatran_frota/dataset_config.yaml | 6 +- br_denatran_frota/municipio_tipo/publish.sql | 2 +- .../municipio_tipo/table_config.yaml | 108 +++++++++--------- br_denatran_frota/uf_tipo/publish.sql | 2 +- br_denatran_frota/uf_tipo/table_config.yaml | 108 +++++++++--------- pipelines/datasets/__init__.py | 1 - pipelines/datasets/delete_flows/tasks.py | 2 +- 14 files changed, 182 insertions(+), 182 deletions(-) diff --git a/br_denatran_frota/README.md b/br_denatran_frota/README.md index feaeb233b..d8415e1fd 100644 --- a/br_denatran_frota/README.md +++ b/br_denatran_frota/README.md @@ -14,7 +14,7 @@ Dependências: - [unrar](https://www.rarlab.com/rar_add.htm) para extrair os arquivos `.rar` via cli. -Ubuntu e Debian: +Ubuntu e Debian: ```sh sudo apt-get install unrar ``` \ No newline at end of file diff --git a/br_denatran_frota/code/download_frota.R b/br_denatran_frota/code/download_frota.R index b9ce2930c..e797298ae 100644 --- a/br_denatran_frota/code/download_frota.R +++ b/br_denatran_frota/code/download_frota.R @@ -8,7 +8,7 @@ library(dplyr) library(purrr) download_frota <- function(key = NULL, prefix = NULL, month, year, tempdir = tempdir(), dir = getwd()) { - + months <- c( "janeiro" = 1, "fevereiro" = 2, @@ -40,8 +40,8 @@ download_frota <- function(key = NULL, prefix = NULL, month, year, tempdir = tem } make_filename <- function(i, ext = TRUE) { - stringi::stri_trans_general(i$txt, id = "Latin-ASCII; lower") %>% - stringr::str_replace_all("\\s+", "_") %>% + stringi::stri_trans_general(i$txt, id = "Latin-ASCII; lower") %>% + stringr::str_replace_all("\\s+", "_") %>% paste0(., "_", i$mes, "-", i$ano, ifelse(ext, paste0(".", i$filetype), as.character(""))) } @@ -54,7 +54,7 @@ download_frota <- function(key = NULL, prefix = NULL, month, year, tempdir = tem ) } } - + handle_compact <- function(i) { path_file_zip <- paste0(tempdir, "/", make_filename(i)) dir_file <- paste0(tempdir, "/", make_filename(i, ext = F)) @@ -70,7 +70,7 @@ download_frota <- function(key = NULL, prefix = NULL, month, year, tempdir = tem } else { archive::archive_extract(path_file_zip, dir = dir_file) } - + # Remove rar, zip files. Keep only xls or xlsx list.files(dir_file, full.names = T, pattern = "rar|zip") %>% purrr::walk(~file.remove(.x)) @@ -115,8 +115,8 @@ download_frota <- function(key = NULL, prefix = NULL, month, year, tempdir = tem dplyr::filter( stringr::str_detect(txt, regex(key, ignore_case = TRUE)), mes %in% month - ) %>% - purrr::transpose() %>% + ) %>% + purrr::transpose() %>% purrr::walk(~download_file(.x)) } diff --git a/br_denatran_frota/code/download_frota_old.R b/br_denatran_frota/code/download_frota_old.R index 61d645616..fa3b4b45f 100644 --- a/br_denatran_frota/code/download_frota_old.R +++ b/br_denatran_frota/code/download_frota_old.R @@ -3,17 +3,17 @@ library(stringr) library(stringi) download_frota_old <- function(key = NULL, prefix = NULL, year, tempdir = tempdir(), dir = getwd()) { - + if (year > 2012) { stop("Utilize download_frota()") } mi_url <- paste0( - "https://www.gov.br/infraestrutura/pt-br/assuntos/transito/arquivos-denatran/estatisticas/renavam/", - year, + "https://www.gov.br/infraestrutura/pt-br/assuntos/transito/arquivos-denatran/estatisticas/renavam/", + year, "/frota", - ifelse(year > 2008, "_", ""), - year, + ifelse(year > 2008, "_", ""), + year, ".zip" ) @@ -37,13 +37,13 @@ download_frota_old <- function(key = NULL, prefix = NULL, year, tempdir = tempdi ) utils::unzip( - path_file, + path_file, exdir = paste0(tempdir, "/", "frota__", year) ) } - + months <- c( - "jan" = 1, + "jan" = 1, "fev" = 2, "mar" = 3, "abr" = 4, @@ -53,18 +53,18 @@ download_frota_old <- function(key = NULL, prefix = NULL, year, tempdir = tempdi "ago" = 8, "set" = 9, "out" = 10, - "nov" = 11, + "nov" = 11, "dez" = 12 ) - list.files(path = dir_temp, full.names = T, recursive = T) %>% + list.files(path = dir_temp, full.names = T, recursive = T) %>% purrr::walk(function(i) { if (stringr::str_ends(i, ".zip")) { utils::unzip(i, exdir = paste0(dirname(i), "/")) } }) - list.files(path = dir_temp, full.names = T, recursive = T) %>% + list.files(path = dir_temp, full.names = T, recursive = T) %>% purrr::walk(function(i) { get_by <- list( @@ -72,22 +72,22 @@ download_frota_old <- function(key = NULL, prefix = NULL, year, tempdir = tempdi municipio = "(frota munic)|(frota mun)" ) - new_name <- basename(i) %>% - stringi::stri_trans_general(id = "Latin-ASCII; lower") %>% - stringr::str_replace("regi�es", "regiao") %>% - stringr::str_replace_all("\\s+", "_") %>% - stringr::str_replace_all("_|-", " ") %>% - stringr::str_replace("^(\\d\\_|\\d)+", "") %>% + new_name <- basename(i) %>% + stringi::stri_trans_general(id = "Latin-ASCII; lower") %>% + stringr::str_replace("regi�es", "regiao") %>% + stringr::str_replace_all("\\s+", "_") %>% + stringr::str_replace_all("_|-", " ") %>% + stringr::str_replace("^(\\d\\_|\\d)+", "") %>% stringr::str_replace_all("internet|^\\s", "") # Match jan|fev|... or number of month (two digits) get_month <- stringr::str_match( - new_name, + new_name, regex(paste0(stringr::str_c(names(months), collapse = "|"), "|\\d{2}(?=\\d{4})"), ignore_case = T) ) month_i <- ifelse( - stringr::str_count(get_month) == 2, + stringr::str_count(get_month) == 2, as.numeric(get_month), months[get_month] ) diff --git a/br_denatran_frota/code/frota_municipio_tipo.R b/br_denatran_frota/code/frota_municipio_tipo.R index 4f935e17b..837c9a22e 100644 --- a/br_denatran_frota/code/frota_municipio_tipo.R +++ b/br_denatran_frota/code/frota_municipio_tipo.R @@ -31,7 +31,7 @@ PREFIX_FROTA_MUN <- "frota_mun_tipo" 2014:2020 %>% purrr::walk( ~download_frota( - key = "Frota por Munic", + key = "Frota por Munic", prefix = PREFIX_FROTA_MUN, month = 1:12, year = .x, @@ -42,7 +42,7 @@ PREFIX_FROTA_MUN <- "frota_mun_tipo" 2021 %>% purrr::walk( ~download_frota( - key = "Frota por Munic", + key = "Frota por Munic", prefix = PREFIX_FROTA_MUN, month = 1:3, year = .x, @@ -125,13 +125,13 @@ df_municipios %>% ) -> frota_municipios_dist -frota_municipios_dist %>% +frota_municipios_dist %>% filter(is.na(id_municipio)) %>% group_by(municipio_original, sigla_uf) %>% summarise() -frota_municipios_dist %>% +frota_municipios_dist %>% dplyr::filter(!is.na(id_municipio)) %>% - dplyr::select(!municipio_original) %>% + dplyr::select(!municipio_original) %>% readr::write_rds(file = "output/municipio_tipo.rds") %T>% readr::write_csv(file = "output/municipio_tipo.csv") \ No newline at end of file diff --git a/br_denatran_frota/code/frota_uf_tipo.R b/br_denatran_frota/code/frota_uf_tipo.R index b92aede98..d46624c48 100644 --- a/br_denatran_frota/code/frota_uf_tipo.R +++ b/br_denatran_frota/code/frota_uf_tipo.R @@ -32,7 +32,7 @@ PREFIX_FROTA_REG <- "frota_regiao_tipo" # Download da frota por regiao e tipo em 2013 ## Demais meses de agosto a key é "Frota por Tipo" -2013 %>% +2013 %>% purrr::walk(~download_frota( key = "Frota por tipo", prefix = PREFIX_FROTA_REG, @@ -91,7 +91,7 @@ list.files(PATH_DOWNLOAD_REG, full.names = T) %>% # Cada tibble deve ter 25 colunas e 27 linhas frota_regiao %>% purrr::map_lgl(~ncol(.x) == 25 & nrow(.x) == 27) %>% all(T) -frota_regiao %>% - purrr::map_dfr(~tidyr::unnest(.)) %>% +frota_regiao %>% + purrr::map_dfr(~tidyr::unnest(.)) %>% readr::write_csv(file = "output/uf_tipo.csv") %T>% readr::write_rds(file = "output/uf_tipo.rds") \ No newline at end of file diff --git a/br_denatran_frota/code/setup.py b/br_denatran_frota/code/setup.py index 4a1e6d3ad..6cd60597a 100644 --- a/br_denatran_frota/code/setup.py +++ b/br_denatran_frota/code/setup.py @@ -1,11 +1,12 @@ +# -*- coding: utf-8 -*- from setuptools import setup setup( - name='download_frota', - version='1.0', - py_modules=['download_frota'], + name="download_frota", + version="1.0", + py_modules=["download_frota"], install_requires=[ - 'beautifulsoup4', - 'rarfile', + "beautifulsoup4", + "rarfile", ], ) diff --git a/br_denatran_frota/code/utils.R b/br_denatran_frota/code/utils.R index 93e136d0d..e26c381ec 100644 --- a/br_denatran_frota/code/utils.R +++ b/br_denatran_frota/code/utils.R @@ -6,7 +6,7 @@ find_sheet <- function(x, date) { } ) - sheet_names <- read_sheet %>% + sheet_names <- read_sheet %>% stringr::str_subset(., "^(?!.*Glossário).*$") if (length(sheet_names) == 1) { @@ -15,8 +15,8 @@ find_sheet <- function(x, date) { month_name <- lubridate::month(date, label = T) query_sheet <- stringr::str_subset( - sheet_names, - regex(paste0("\\d{2}(?=\\d{4}$)", "|", month_name), ignore_case = T) + sheet_names, + regex(paste0("\\d{2}(?=\\d{4}$)", "|", month_name), ignore_case = T) ) if (length(query_sheet) == 0) { @@ -44,7 +44,7 @@ row_of_header <- function(x, key_of_header) { if (length(result) == 0) { return(0) } - + if (length(result) > 1) { result[2] } else { @@ -68,8 +68,8 @@ read_old_xls <- function(x, date) { while (start_row <= 5) { result <- try( xlsx::read.xlsx2( - x, - sheetName = sheet_name, + x, + sheetName = sheet_name, startRow = start_row, endRow = 10 ), @@ -81,15 +81,15 @@ read_old_xls <- function(x, date) { } start_row <- start_row + 1 } - xlsx::read.xlsx2(x, sheetName = sheet_name, startRow = start_row) %>% + xlsx::read.xlsx2(x, sheetName = sheet_name, startRow = start_row) %>% tibble::as_tibble() } read_xl <- function(x, type) { - date <- stringr::str_match(x, "\\d{1,2}-\\d{4}") %>% - paste0("01-", .) %>% + date <- stringr::str_match(x, "\\d{1,2}-\\d{4}") %>% + paste0("01-", .) %>% lubridate::dmy() - + read <- function(pl) { tryCatch( readxl::read_excel(pl, sheet = find_sheet(pl, date)), @@ -97,11 +97,11 @@ read_xl <- function(x, type) { ) } - read(x) %>% - set_header(., key_of_header = type) %>% - janitor::clean_names() %>% - dplyr::rename_with(.fn = function(x) stringr::str_replace(x, pattern = "_|\\.|-", replacement = "")) %>% - dplyr::select(!starts_with("na")) %>% + read(x) %>% + set_header(., key_of_header = type) %>% + janitor::clean_names() %>% + dplyr::rename_with(.fn = function(x) stringr::str_replace(x, pattern = "_|\\.|-", replacement = "")) %>% + dplyr::select(!starts_with("na")) %>% dplyr::mutate( ano = lubridate::year(date), mes = lubridate::month(date) @@ -120,30 +120,30 @@ download_utils_files <- function() { download_utils_files() -ibge_ids <- readxl::read_excel("input/ibge_cods/RELATORIO_DTB_BRASIL_DISTRITO.xls") %>% +ibge_ids <- readxl::read_excel("input/ibge_cods/RELATORIO_DTB_BRASIL_DISTRITO.xls") %>% janitor::clean_names() -ufs <- ibge_ids %>% - dplyr::group_by(nome_uf, uf) %>% - dplyr::summarise() %>% - dplyr::ungroup() %>% - dplyr::mutate(uf = as.numeric(uf)) %>% +ufs <- ibge_ids %>% + dplyr::group_by(nome_uf, uf) %>% + dplyr::summarise() %>% + dplyr::ungroup() %>% + dplyr::mutate(uf = as.numeric(uf)) %>% dplyr::rename(id_uf = uf) -municipios <- ibge_ids %>% +municipios <- ibge_ids %>% dplyr::group_by( uf, nome_uf, - codigo_municipio_completo, + codigo_municipio_completo, nome_municipio - ) %>% - dplyr::summarise() %>% + ) %>% + dplyr::summarise() %>% dplyr::mutate( name_upper = stringi::stri_trans_general(nome_municipio, id = "Latin-ASCII; upper"), codigo_municipio_completo = as.numeric(codigo_municipio_completo), uf = as.numeric(uf) - ) %>% - dplyr::ungroup() %>% + ) %>% + dplyr::ungroup() %>% dplyr::rename( id_uf = uf, uf = nome_uf, diff --git a/br_denatran_frota/dataset_config.yaml b/br_denatran_frota/dataset_config.yaml index d8db54254..9a43e3b43 100644 --- a/br_denatran_frota/dataset_config.yaml +++ b/br_denatran_frota/dataset_config.yaml @@ -17,7 +17,7 @@ organization: Departamento Nacional de Trânsito # REQUIRED # Qual departamento/grupo/pessoa mantém os dados originais? author: name: Departamento Nacional de Trânsito - email: + email: # Onde encontrar os dados originais e mais informações? website: @@ -35,7 +35,7 @@ groups: # - sem acentos # - não repita nomes de grupos (ex. educacao, saude, meio ambiente, economia, etc.) tags: - - veiculo + - veiculo - trafego # Em quais línguas a base (ou a fonte original) está disponível? @@ -65,5 +65,5 @@ brazilian_IP: não # Essa base está sob qual licença? # A licença MIT se aplica a bases públicas. # Caso não seja pública, ver opções aqui: https://help.data.world/hc/en-us/articles/115006114287-Common-license-types-for-datasets -license: +license: name: MIT # REQUIRED diff --git a/br_denatran_frota/municipio_tipo/publish.sql b/br_denatran_frota/municipio_tipo/publish.sql index f4e74c045..4b7acaffd 100644 --- a/br_denatran_frota/municipio_tipo/publish.sql +++ b/br_denatran_frota/municipio_tipo/publish.sql @@ -20,7 +20,7 @@ TIPOS: */ CREATE VIEW basedosdados-312117.br_denatran_frota.municipio_tipo AS -SELECT +SELECT SAFE_CAST(sigla_uf AS STRING) sigla_uf, SAFE_CAST(id_municipio AS STRING) id_municipio, SAFE_CAST(ano AS INT64) ano, diff --git a/br_denatran_frota/municipio_tipo/table_config.yaml b/br_denatran_frota/municipio_tipo/table_config.yaml index 2ab4752e2..28af5cb70 100644 --- a/br_denatran_frota/municipio_tipo/table_config.yaml +++ b/br_denatran_frota/municipio_tipo/table_config.yaml @@ -35,12 +35,12 @@ treated_by: email: pdesacastro@gmail.com # Se houve passos de tratamento, limpeza e manipulação de dados, descreva-os aqui. -treatment_description: | +treatment_description: | Padronização das colunas. Nova coluna, id_municipio. Remoção das linhas "MUNICIPIO NAO INFORMADO". # Com qual frequência a base é atualizada? # Opções: hora | dia | semana | mes | 1 ano | 2 anos | 5 anos | 10 anos | unico | recorrente -data_update_frequency: mes # REQUIRED +data_update_frequency: mes # REQUIRED # Nível da observação (qual é a granularidade de cada linha na tabela) # Escolha todas as opções necessárias. @@ -110,158 +110,158 @@ partitions: # REQUIRED # Para esses, defina is_in_staging como False. # Além disso, você deve adicionar as colunas de partição aqui e definir is_partition como True. columns: # REQUIRED - - - + + - name: sigla_uf description: Sigla da Unidade da Federação original da base is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: id_municipio description: ID Município - IBGE 7 Dígitos is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: ano description: Ano is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: mes description: Mês is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: automovel description: Automóvel is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: bonde description: Bonde is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: caminhao description: Caminhão is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: caminhaotrator description: Caminhão Trator is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: caminhonete description: Caminhonete is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: camioneta description: Camioneta is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: chassiplataforma description: Chassi Plataforma is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: ciclomotor description: Ciclo Motor is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: microonibus description: Microônibus is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: motocicleta description: Motocicleta is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: motoneta description: Motoneta is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: onibus description: Ônibus is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: quadriciclo description: Quadriciclo is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: reboque description: Reboque is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: semireboque description: Semi-reboque is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: sidecar description: Side-car is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: outros description: Argumento que não se enquadra em nenhuma definição estabelecida is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: tratoresteira description: Trator esteira is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: tratorrodas description: Trator rodas is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: triciclo description: Triciclo is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: utilitario description: Utilitário is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: total description: Total is_in_staging: True # Bool [True, False], whether the column is in the staging table diff --git a/br_denatran_frota/uf_tipo/publish.sql b/br_denatran_frota/uf_tipo/publish.sql index 016ef11b3..0725b27d8 100644 --- a/br_denatran_frota/uf_tipo/publish.sql +++ b/br_denatran_frota/uf_tipo/publish.sql @@ -20,7 +20,7 @@ TIPOS: */ CREATE VIEW basedosdados-312117.br_denatran_frota.uf_tipo AS -SELECT +SELECT SAFE_CAST(sigla_uf AS STRING) sigla_uf, SAFE_CAST(ano AS INT64) ano, SAFE_CAST(mes AS INT64) mes, diff --git a/br_denatran_frota/uf_tipo/table_config.yaml b/br_denatran_frota/uf_tipo/table_config.yaml index 08424b33c..66cb8f5bc 100644 --- a/br_denatran_frota/uf_tipo/table_config.yaml +++ b/br_denatran_frota/uf_tipo/table_config.yaml @@ -36,12 +36,12 @@ treated_by: email: pdesacastro@gmail.com # Se houve passos de tratamento, limpeza e manipulação de dados, descreva-os aqui. -treatment_description: | +treatment_description: | Padronização dos nomes das colunas. Remoção das linhas do total dos estados. # Com qual frequência a base é atualizada? # Opções: hora | dia | semana | mes | 1 ano | 2 anos | 5 anos | 10 anos | unico | recorrente -data_update_frequency: mes # REQUIRED +data_update_frequency: mes # REQUIRED # Nível da observação (qual é a granularidade de cada linha na tabela) # Escolha todas as opções necessárias. @@ -111,152 +111,152 @@ partitions: # REQUIRED # Para esses, defina is_in_staging como False. # Além disso, você deve adicionar as colunas de partição aqui e definir is_partition como True. columns: # REQUIRED - - - + + - name: sigla_uf description: Sigla da Unidade da Federação is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: ano - description: Ano + description: Ano is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: mes - description: Mês + description: Mês is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: automovel description: Automóvel is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: bonde description: Bonde is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: caminhao description: Caminhão is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: caminhaotrator description: Caminhão Trator is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: caminhonete description: Caminhonete is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: camioneta description: Camioneta is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: chassiplataforma description: Chassi Plataforma is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: ciclomotor description: Ciclo Motor is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: microonibus description: Microônibus is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: motocicleta description: Motocicleta is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: motoneta description: Motoneta is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: onibus description: Ônibus is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: quadriciclo description: Quadriciclo is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: reboque description: Reboque is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: semireboque description: Semi-reboque is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: sidecar description: Side-car is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: outros description: Argumento que não se enquadra em nenhuma definição estabelecida is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: tratoresteira description: Trator esteira is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: tratorrodas description: Trator rodas is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: triciclo description: Triciclo is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: utilitario description: Utilitário is_in_staging: True # Bool [True, False], whether the column is in the staging table is_partition: False # Bool [True, False], whether the column is a partition. - - - + + - name: total description: Total is_in_staging: True # Bool [True, False], whether the column is in the staging table diff --git a/pipelines/datasets/__init__.py b/pipelines/datasets/__init__.py index 6f0a8d204..5f2fbe94b 100644 --- a/pipelines/datasets/__init__.py +++ b/pipelines/datasets/__init__.py @@ -29,4 +29,3 @@ from pipelines.datasets.cross_update.flows import * from pipelines.datasets.br_denatran_frota.flows import * from pipelines.datasets.br_anatel_banda_larga_fixa.flows import * - diff --git a/pipelines/datasets/delete_flows/tasks.py b/pipelines/datasets/delete_flows/tasks.py index bc2f818b5..8aa52ba75 100644 --- a/pipelines/datasets/delete_flows/tasks.py +++ b/pipelines/datasets/delete_flows/tasks.py @@ -85,4 +85,4 @@ def delete_flow_run(flow_run_dict: Dict[str, str], client: Client = None) -> Non log(type(response["data"]["delete_flow_run"])) log(response["data"]) if not success: - pass \ No newline at end of file + pass From 70d7d64c502b8f8b8d6a0b8b4941fd9b47a89c26 Mon Sep 17 00:00:00 2001 From: Tamir Date: Sat, 29 Apr 2023 03:34:44 -0300 Subject: [PATCH 086/265] Add utils function to correct folder --- pipelines/datasets/br_denatran_frota/utils.py | 135 +++++++++++++++++- 1 file changed, 131 insertions(+), 4 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index a620f9eb9..272984bbb 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -38,15 +38,32 @@ from zipfile import ZipFile import requests from pipelines.datasets.br_denatran_frota.constants import constants +from bs4 import BeautifulSoup +from urllib.request import urlopen DICT_UFS = constants.DICT_UFS.value SUBSTITUTIONS = constants.SUBSTITUTIONS.value HEADERS = constants.HEADERS.value +MONTHS = constants.MONTHS.value def guess_header(df: pd.DataFrame, max_header_guess: int = 4) -> int: + """Function to deal with problematic dataframes coming from Excel/CSV files. + Tries to guess which row is the header by examining the first few rows (max given by max_header_guess). + Assumes that the header is the first row where all of the columns are strings. + This will NOT properly work for a strings only dataframe and will always guess the first row for it. + + Args: + df (pd.DataFrame): Dataframe whose header we don't know. + max_header_guess (int, optional): Number of initial rows we want to check. Defaults to 4. + + Returns: + int: Index of the row where the header is contained. + """ header_guess = 0 while header_guess < max_header_guess: + if len(df) - 1 < header_guess: + break # Iffy logic, but essentially: if all rows of the column are strings, then this is a good candidate for a header. if all(df.iloc[header_guess].apply(lambda x: isinstance(x, str))): return header_guess @@ -56,6 +73,15 @@ def guess_header(df: pd.DataFrame, max_header_guess: int = 4) -> int: def change_df_header(df: pd.DataFrame, header_row: int) -> pd.DataFrame: + """Changes the dataframe's header to a row inside of it and returns the corrected df. + Ideally, to be used in conjunction with guess_header(). + Args: + df (pd.DataFrame): Dataframe whose header we want changed. + header_row (int): Index of the row where the header is located. + + Returns: + pd.DataFrame: Returns the same dataframe but with the corrected header + """ new_header = df.iloc[header_row] new_df = df[(header_row + 1) :].reset_index(drop=True) new_df.rename(columns=new_header, inplace=True) @@ -63,6 +89,17 @@ def change_df_header(df: pd.DataFrame, header_row: int) -> pd.DataFrame: def get_year_month_from_filename(filename: str) -> tuple[int, int]: + """Helper to extract month and year information from files named indicator_month-year.xls + + Args: + filename (str): Name of the file. + + Raises: + ValueError: Errors out if nothing is found, which likely means the filename is not the correct format. + + Returns: + tuple[int, int]: Month, year. + """ match = re.search(r"(\w+)_(\d{1,2})-(\d{4})\.(xls|xlsx)$", filename) if match: month = match.group(2) @@ -73,22 +110,47 @@ def get_year_month_from_filename(filename: str) -> tuple[int, int]: def verify_total(df: pl.DataFrame) -> None: + """Helper function that is meant to act as a guard to guarantee that we can pivot from wide to long. + Essentially, gets a Wide dataframe, excludes all string columns and the TOTAL column and sums it all row wise. + Then verifies if the calculated total column is the same as the TOTAL column. + If not, raises an error. + + Args: + df (pl.DataFrame): Wide format dataframe to verify. + + Raises: + ValueError: Errors out if the sum of the columns is actually different than the total. + """ columns_for_total = df.select(pl.exclude("TOTAL")).select(pl.exclude([pl.Utf8])) calculated_total = columns_for_total.select( pl.fold( acc=pl.lit(0), function=lambda acc, x: acc + x, exprs=pl.col("*") ).alias("calculated_total") )["calculated_total"] - mask = df["TOTAL"] == calculated_total if pl.sum(~mask) != 0: raise ValueError( - "A coluna de TOTAL da base original tem inconsistências e não soma tudo das demais colunas." + "A coluna de TOTAL da base original tem inconsistências e não é igual à soma das demais colunas." ) -def fix_suggested_nome_ibge(row) -> str: +def fix_suggested_nome_ibge(row: tuple[str, ...]) -> str: + """Gets a row from a dataframe and applies the SUBSTITUTIONS constant ruleset where applicable. + This fixes the dataframe to have the names of municipalities according to IBGE. + The fixes are necessary because match_ibge() will fail where the DENATRAN data has typos in city names. + + Args: + row (tuple[str, ...]): Row from the full DENATRAN dataframe we want to apply the IBGE substitutions to. + + Raises: + ValueError: Errors out if the desired parts of the row do not conform to the expected format. + + Returns: + str: Returns the suggested IBGE name, either the pre existing or the one in the ruleset for substitutions. + """ key = (row[0], row[1]) + if (not isinstance(row[0], str)) or (not isinstance(row[1], str)): + raise ValueError("This is not a valid key to be checked.") if key in SUBSTITUTIONS: return SUBSTITUTIONS[key] else: @@ -96,6 +158,18 @@ def fix_suggested_nome_ibge(row) -> str: def match_ibge(denatran_uf: pl.DataFrame, ibge_uf: pl.DataFrame) -> None: + """Takes a dataframe of the Denatran data and an IBGE dataframe of municipalities. + Joins them using the IBGE name of both. The IBGE name of denatran_uf is ideally filled via get_city_name(). + This verifies if there are any municipalities in denatran_uf that have no corresponding municipality in the IBGE database. + These must be manually fixed via the constants file and the fix_suggested_nome function. + Will error out if there are municipalities that have no correspondence whatsover. + Args: + denatran_uf (pl.DataFrame): Dataframe with the DENATRAN data, filtered by state (UF). + ibge_uf (pl.DataFrame): Dataframe with the IBGE municipalities data, filtered by state (UF). + + Raises: + ValueError: Errors if there are municipalities that have not match and outputs them all with the state to enable manual fix. + """ joined_df = denatran_uf.join( ibge_uf, left_on=["suggested_nome_ibge", "sigla_uf"], @@ -103,7 +177,6 @@ def match_ibge(denatran_uf: pl.DataFrame, ibge_uf: pl.DataFrame) -> None: how="left", ) mismatched_rows = joined_df.filter(pl.col("id_municipio").is_null()) - if len(mismatched_rows) > 0: error_message = "Os seguintes municípios falharam: \n" for row in mismatched_rows.rows(named=True): @@ -112,6 +185,17 @@ def match_ibge(denatran_uf: pl.DataFrame, ibge_uf: pl.DataFrame) -> None: def get_city_name_ibge(denatran_name: str, ibge_uf: pl.DataFrame) -> str: + """Gets the closest match to the denatran name of the municipality in the IBGE dataframe of the same state. + This ibge_uf dataframe is pulled directly from Base dos Dados to ensure correctness. + Returns either the match or an empty string in case no match is found. + + + Args: + denatran_name (str): The name of the municipality according to DENATRAN data. + ibge_uf (pl.DataFrame): Dataframe with the information from municipalities for a certain state (UF). + Returns: + str: Closest match to the denatran name or an empty string if no such match is found. + """ matches = difflib.get_close_matches( denatran_name.lower(), ibge_uf["nome"].str.to_lowercase(), n=1 ) @@ -169,6 +253,49 @@ def make_filename(i: dict, ext: bool = True) -> str: return filename +def call_downloader(i): + filename = make_filename(i) + if i["filetype"] in ["xlsx", "xls"]: + download_file(i["href"], filename) + elif i["filetype"] == "zip": + download_file(i["href"], filename) + extract_zip(filename) + + +def download_post_2012(month: int, year: int): + """_summary_ + + Args: + year (int): _description_ + month (int): _description_ + """ + url = f"https://www.gov.br/infraestrutura/pt-br/assuntos/transito/conteudo-Senatran/frota-de-veiculos-{year}" + soup = BeautifulSoup(urlopen(url), "html.parser") + # Só queremos os dados de frota nacional. + nodes = soup.select("p:contains('rota por ') > a") + for node in nodes: + txt = node.text + href = node.get("href") + # Pega a parte relevante do arquivo em questão. + match = re.search( + r"(?i)\/([\w-]+)\/(\d{4})\/(\w+)\/([\w-]+)\.(?:xls|xlsx|rar|zip)$", href + ) + if match: + matched_month = match.group(3) + matched_year = match.group(2) + if MONTHS.get(matched_month) == month and matched_year == str(year): + filetype = match.group(0).split(".")[-1].lower() + info = { + "txt": txt, + "href": href, + "mes_name": matched_month, + "mes": month, + "ano": year, + "filetype": filetype, + } + call_downloader(info) + + def make_dir_when_not_exists(dir_name: str): """Auxiliary function to create a subdirectory when it is not present. 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insertions(+), 0 deletions(-) rename br_denatran_frota/code/test/download_frota_unit_test.py => pipelines/datasets/br_denatran_frota/functions_test.py (100%) diff --git a/br_denatran_frota/code/test/download_frota_unit_test.py b/pipelines/datasets/br_denatran_frota/functions_test.py similarity index 100% rename from br_denatran_frota/code/test/download_frota_unit_test.py rename to pipelines/datasets/br_denatran_frota/functions_test.py From f56900a4e0dc816d497c11a4dd64cdbfcda8585d Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 2 May 2023 07:39:26 -0300 Subject: [PATCH 089/265] Correct importing --- pipelines/datasets/br_denatran_frota/functions_test.py | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/functions_test.py b/pipelines/datasets/br_denatran_frota/functions_test.py index a43275729..88428f5f5 100644 --- a/pipelines/datasets/br_denatran_frota/functions_test.py +++ b/pipelines/datasets/br_denatran_frota/functions_test.py @@ -7,14 +7,17 @@ import pandas as pd from parameterized import parameterized -from br_denatran_frota.code.utils import ( +from pipelines.datasets.br_denatran_frota.utils import ( make_filename, make_dir_when_not_exists, ) -from br_denatran_frota.code.constants import DATASET +from pipelines.datasets.br_denatran_frota.constants import constants from br_denatran_frota.code.download_frota import download_frota from br_denatran_frota.code.utils import guess_header, get_year_month_from_filename + +DATASET = constants.DATASET.value + dir_list = glob.glob(f"**/{DATASET}", recursive=True) if dir_list: # I always want to be in the actual folder for this dataset: From 2624e483c1463611eea6a8d3c05a6ee186b78845 Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 2 May 2023 08:14:02 -0300 Subject: [PATCH 090/265] Fix import yet again --- pipelines/datasets/br_denatran_frota/functions_test.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/functions_test.py b/pipelines/datasets/br_denatran_frota/functions_test.py index 88428f5f5..634c76104 100644 --- a/pipelines/datasets/br_denatran_frota/functions_test.py +++ b/pipelines/datasets/br_denatran_frota/functions_test.py @@ -10,10 +10,11 @@ from pipelines.datasets.br_denatran_frota.utils import ( make_filename, make_dir_when_not_exists, + guess_header, + get_year_month_from_filename, ) from pipelines.datasets.br_denatran_frota.constants import constants from br_denatran_frota.code.download_frota import download_frota -from br_denatran_frota.code.utils import guess_header, get_year_month_from_filename DATASET = constants.DATASET.value From 1283baf510db7d5ec2a2c088dd9aa3bf16ae9a53 Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 2 May 2023 08:33:44 -0300 Subject: [PATCH 091/265] Add todo list for myself and ignore it. --- .gitignore | 1 + 1 file changed, 1 insertion(+) diff --git a/.gitignore b/.gitignore index b2973e34b..aa41b1ff4 100644 --- a/.gitignore +++ b/.gitignore @@ -141,3 +141,4 @@ dmypy.json notebooks/ /tests/ poetry.lock +pipelines/datasets/br_denatran_frota/todo_list.txt From 4a37eeac59b92cc541df2d2257a9a3c8aeca1953 Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 2 May 2023 16:43:38 -0300 Subject: [PATCH 092/265] First task --- pipelines/datasets/br_denatran_frota/tasks.py | 57 +++++++++++++++++-- 1 file changed, 53 insertions(+), 4 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/tasks.py b/pipelines/datasets/br_denatran_frota/tasks.py index 8ec526846..6c5052942 100644 --- a/pipelines/datasets/br_denatran_frota/tasks.py +++ b/pipelines/datasets/br_denatran_frota/tasks.py @@ -50,11 +50,60 @@ ############################################################################### from prefect import task +import glob +import os +from pipelines.datasets.br_denatran_frota.constants import constants +from pipelines.datasets.br_denatran_frota.utils import ( + make_dir_when_not_exists, + download_post_2012, +) + + +MONTHS = constants.MONTHS.value +DATASET = constants.DATASET.value @task # noqa -def say_hello(name: str = "World") -> str: - """ - Greeting task. +def crawl(month: int, year: int, temp_dir: str = ""): + """Função principal para baixar os dados de frota por município e tipo e também por UF e tipo. + + Args: + month (int): Mês desejado. + year (int): Ano desejado. + + Raises: + ValueError: Errors if the month is not a valid one. """ - return f"Hello, {name}!" + if month not in MONTHS.values(): + raise ValueError("Mês inválido.") + + dir_list = glob.glob(f"**/{DATASET}", recursive=True) + # Get the directory where this Python file is located + initial_dir = os.path.dirname(os.path.abspath(__file__)) + if temp_dir: + os.chdir(temp_dir) + # Construct the path to the "files" directory relative to this directory + files_dir = os.path.join(os.getcwd(), "files") + if dir_list: + # I always want to be in the actual folder for this dataset, because I might start in the pipelines full repo: + os.chdir(dir_list[0]) + + # I always need a files directory inside my dataset folder. + make_dir_when_not_exists(files_dir) + # I should always switch to the files dir now and save stuff inside it. + os.chdir(files_dir) + year_dir_name = f"{year}" + + # Create dir for that specific year should it be necessary. + make_dir_when_not_exists(year_dir_name) + os.chdir(year_dir_name) + if year > 2012: + download_post_2012(month, year) + # else: + # url = f"https://www.gov.br/infraestrutura/pt-br/assuntos/transito/arquivos-senatran/estatisticas/renavam/{year}/frota{'_' if year > 2008 else ''}{year}.zip" + + # generic_zip_filename = f"geral_{year}.zip" + # urlretrieve(url, generic_zip_filename) + # with ZipFile(generic_zip_filename) as zip_file: + # zip_file.extractall() + os.chdir(initial_dir) From 2be72b086ad07fbc05b1ec724d30957bb677734b Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 2 May 2023 18:29:09 -0300 Subject: [PATCH 093/265] Extra arguments for task --- pipelines/datasets/br_denatran_frota/tasks.py | 42 ++++++++++++++++++- 1 file changed, 40 insertions(+), 2 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/tasks.py b/pipelines/datasets/br_denatran_frota/tasks.py index 6c5052942..266d7ad5e 100644 --- a/pipelines/datasets/br_denatran_frota/tasks.py +++ b/pipelines/datasets/br_denatran_frota/tasks.py @@ -56,14 +56,22 @@ from pipelines.datasets.br_denatran_frota.utils import ( make_dir_when_not_exists, download_post_2012, + verify_total, + change_df_header, + guess_header, + get_year_month_from_filename, ) - +import pandas as pd +import polars as pl MONTHS = constants.MONTHS.value DATASET = constants.DATASET.value +DICT_UFS = constants.DICT_UFS.value -@task # noqa +@task( + name="crawler", description="Extrai os arquivos do Denatran para ano e mês." +) # noqa def crawl(month: int, year: int, temp_dir: str = ""): """Função principal para baixar os dados de frota por município e tipo e também por UF e tipo. @@ -107,3 +115,33 @@ def crawl(month: int, year: int, temp_dir: str = ""): # with ZipFile(generic_zip_filename) as zip_file: # zip_file.extractall() os.chdir(initial_dir) + + +@task(name="treatment of uf data", description="Trata os dados do Denatran para UF") +def treat_uf_tipo(file) -> pl.DataFrame: + filename = os.path.split(file)[1] + df = pd.read_excel(file) + new_df = change_df_header(df, guess_header(df)) + # This is ad hoc for UF_tipo. + new_df.rename( + columns={new_df.columns[0]: "sigla_uf"}, inplace=True + ) # Rename for ease of use. + new_df.sigla_uf = new_df.sigla_uf.str.strip() # Remove whitespace. + clean_df = new_df[new_df.sigla_uf.isin(DICT_UFS.values())].reset_index( + drop=True + ) # Now we get all the actual RELEVANT uf data. + month, year = get_year_month_from_filename(filename) + clean_pl_df = pl.from_pandas(clean_df).lazy() + verify_total(clean_pl_df.collect()) + # Add year and month + clean_pl_df = clean_pl_df.with_columns( + pl.lit(year, dtype=pl.Int64).alias("ano"), + pl.lit(month, dtype=pl.Int64).alias("mes"), + ) + clean_pl_df = clean_pl_df.select(pl.exclude("TOTAL")) + clean_pl_df = clean_pl_df.melt( + id_vars=["ano", "mes", "sigla_uf"], + variable_name="tipo_veiculo", + value_name="quantidade", + ) # Long format. + return clean_pl_df.collect() From 0e62488ff2185dcd4732af19ad8002cd353ea661 Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 3 May 2023 07:02:12 -0300 Subject: [PATCH 094/265] Dirty test clean up + flow start --- pipelines/datasets/br_denatran_frota/flows.py | 50 +++++++++++++++---- .../br_denatran_frota/functions_test.py | 10 ---- pipelines/datasets/br_denatran_frota/tasks.py | 6 +-- 3 files changed, 41 insertions(+), 25 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index 0d45deb50..4fa1e6422 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -57,25 +57,53 @@ # ############################################################################### - +from datetime import datetime, timedelta from prefect.run_configs import KubernetesRun from prefect.storage import GCS +from prefect import Parameter, case +from prefect.tasks.prefect import ( + create_flow_run, + wait_for_flow_run, +) + from pipelines.constants import constants -from pipelines.datasets.br_denatran_frota.tasks import say_hello +from pipelines.utils.constants import constants as utils_constants -# from pipelines.datasets.br_denatran_frota.schedules import every_two_weeks from pipelines.utils.decorators import Flow +from pipelines.utils.execute_dbt_model.constants import constants as dump_db_constants +from pipelines.utils.tasks import ( + create_table_and_upload_to_gcs, + rename_current_flow_run_dataset_table, + get_current_flow_labels, +) +from pipelines.datasets.br_denatran_frota.tasks import crawl, treat_uf_tipo + +# from pipelines.datasets.br_denatran_frota.schedules import every_two_weeks with Flow( - name="my_flow", + name="br_denatran_frota.uf_tipo", code_owners=[ - "discord-username", + "Tamir", ], -) as datasets_br_denatran_frota_flow: - say_hello() +) as br_denatran_frota_uf_tipo: + dataset_id = Parameter("dataset_id", default="br_denatran_frota", required=True) + table_id = Parameter("table_id", default="uf_tipo", required=True) -datasets_br_denatran_frota_flow.storage = GCS(constants.GCS_FLOWS_BUCKET.value) -datasets_br_denatran_frota_flow.run_config = KubernetesRun( - image=constants.DOCKER_IMAGE.value -) + # Materialization mode + materialization_mode = Parameter( + "materialization_mode", default="dev", required=False + ) + + materialize_after_dump = Parameter( + "materialize after dump", default=False, required=False + ) + + dbt_alias = Parameter("dbt_alias", default=True, required=False) + + rename_flow_run = rename_current_flow_run_dataset_table( + prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id + ) + +br_denatran_frota_uf_tipo.storage = GCS(constants.GCS_FLOWS_BUCKET.value) +br_denatran_frota_uf_tipo.run_config = KubernetesRun(image=constants.DOCKER_IMAGE.value) # flow.schedule = every_two_weeks diff --git a/pipelines/datasets/br_denatran_frota/functions_test.py b/pipelines/datasets/br_denatran_frota/functions_test.py index 634c76104..e637c2bb5 100644 --- a/pipelines/datasets/br_denatran_frota/functions_test.py +++ b/pipelines/datasets/br_denatran_frota/functions_test.py @@ -3,9 +3,7 @@ import shutil import tempfile import unittest -import glob import pandas as pd -from parameterized import parameterized from pipelines.datasets.br_denatran_frota.utils import ( make_filename, @@ -17,14 +15,6 @@ from br_denatran_frota.code.download_frota import download_frota -DATASET = constants.DATASET.value - -dir_list = glob.glob(f"**/{DATASET}", recursive=True) -if dir_list: - # I always want to be in the actual folder for this dataset: - os.chdir(dir_list[0]) - - class TestMakeFilename(unittest.TestCase): def test_make_filename(self): month = 2 diff --git a/pipelines/datasets/br_denatran_frota/tasks.py b/pipelines/datasets/br_denatran_frota/tasks.py index 266d7ad5e..7c3678d08 100644 --- a/pipelines/datasets/br_denatran_frota/tasks.py +++ b/pipelines/datasets/br_denatran_frota/tasks.py @@ -69,9 +69,7 @@ DICT_UFS = constants.DICT_UFS.value -@task( - name="crawler", description="Extrai os arquivos do Denatran para ano e mês." -) # noqa +@task() # noqa def crawl(month: int, year: int, temp_dir: str = ""): """Função principal para baixar os dados de frota por município e tipo e também por UF e tipo. @@ -117,7 +115,7 @@ def crawl(month: int, year: int, temp_dir: str = ""): os.chdir(initial_dir) -@task(name="treatment of uf data", description="Trata os dados do Denatran para UF") +@task() def treat_uf_tipo(file) -> pl.DataFrame: filename = os.path.split(file)[1] df = pd.read_excel(file) From 0e495bca5967f86e8352fe19621b5539f335119e Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 3 May 2023 07:16:45 -0300 Subject: [PATCH 095/265] Tests are the bomb --- .../br_denatran_frota/functions_test.py | 4 +- .../datasets/br_denatran_frota/tasks_test.py | 48 +++++++++++++++++++ 2 files changed, 50 insertions(+), 2 deletions(-) create mode 100644 pipelines/datasets/br_denatran_frota/tasks_test.py diff --git a/pipelines/datasets/br_denatran_frota/functions_test.py b/pipelines/datasets/br_denatran_frota/functions_test.py index e637c2bb5..e537606b6 100644 --- a/pipelines/datasets/br_denatran_frota/functions_test.py +++ b/pipelines/datasets/br_denatran_frota/functions_test.py @@ -12,7 +12,7 @@ get_year_month_from_filename, ) from pipelines.datasets.br_denatran_frota.constants import constants -from br_denatran_frota.code.download_frota import download_frota +from pipelines.datasets.br_denatran_frota.tasks import crawl class TestMakeFilename(unittest.TestCase): @@ -64,7 +64,7 @@ def test_make_dir_when_not_exists(self): class TestDownloadFrota(unittest.TestCase): def test_download_frota_with_invalid_month(self): with self.assertRaises(ValueError): - download_frota(13, 2013) + crawl(13, 2013) class TestGuessHeader(unittest.TestCase): diff --git a/pipelines/datasets/br_denatran_frota/tasks_test.py b/pipelines/datasets/br_denatran_frota/tasks_test.py new file mode 100644 index 000000000..c26551fb6 --- /dev/null +++ b/pipelines/datasets/br_denatran_frota/tasks_test.py @@ -0,0 +1,48 @@ +# -*- coding: utf-8 -*- +import os +import shutil +import tempfile +import unittest + +from parameterized import parameterized +from br_denatran_frota.code.download_frota import ( + DATASET, + MONTHS, + download_frota, +) + + +def custom_name_func(testcase_func, param_num, param): + return "%s_%s" % ( + testcase_func.__name__, + parameterized.to_safe_name("_".join(str(x) for x in param.args)), + ) + + +class TestAllPossibleYears(unittest.TestCase): + def setUp(self): + file_dir = os.path.dirname(os.path.abspath(__file__)) + os.chdir(file_dir) + self.temp_dir = tempfile.TemporaryDirectory(dir=file_dir) + + def tearDown(self): + print("Deleting temporary directory") + shutil.rmtree(self.temp_dir.name) + + @parameterized.expand( + [(month, year) for year in range(2021, 2022) for month in range(1, 3)], + name_func=custom_name_func, + ) + def test_download_post_2012(self, month, year): + download_frota(month, year, self.temp_dir.name) + expected_files = { + f"frota_por_uf_e_tipo_de_veículo_{month}-{year}", + f"frota_por_município_e_tipo_{month}-{year}", + } + list_of_files = os.listdir(os.path.join(self.temp_dir.name, "files", f"{year}")) + files = set(os.path.splitext(file)[0] for file in list_of_files) + self.assertEqual(files, expected_files) + + +if __name__ == "__main__": + unittest.main() From 7d0ff674cecad95492212266ac914fa3c3a53424 Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 3 May 2023 07:18:45 -0300 Subject: [PATCH 096/265] Clean up task tests --- pipelines/datasets/br_denatran_frota/tasks_test.py | 8 ++------ 1 file changed, 2 insertions(+), 6 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/tasks_test.py b/pipelines/datasets/br_denatran_frota/tasks_test.py index c26551fb6..a8caafd69 100644 --- a/pipelines/datasets/br_denatran_frota/tasks_test.py +++ b/pipelines/datasets/br_denatran_frota/tasks_test.py @@ -5,11 +5,7 @@ import unittest from parameterized import parameterized -from br_denatran_frota.code.download_frota import ( - DATASET, - MONTHS, - download_frota, -) +from pipelines.datasets.br_denatran_frota.tasks import crawl def custom_name_func(testcase_func, param_num, param): @@ -34,7 +30,7 @@ def tearDown(self): name_func=custom_name_func, ) def test_download_post_2012(self, month, year): - download_frota(month, year, self.temp_dir.name) + crawl.run(month, year, self.temp_dir.name) expected_files = { f"frota_por_uf_e_tipo_de_veículo_{month}-{year}", f"frota_por_município_e_tipo_{month}-{year}", From f69fadbffbd9f3a4aa4a961e5b68b0bb87f51180 Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 3 May 2023 07:22:01 -0300 Subject: [PATCH 097/265] Works as is --- pipelines/datasets/br_denatran_frota/tasks_test.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/tasks_test.py b/pipelines/datasets/br_denatran_frota/tasks_test.py index a8caafd69..ef2d4bb41 100644 --- a/pipelines/datasets/br_denatran_frota/tasks_test.py +++ b/pipelines/datasets/br_denatran_frota/tasks_test.py @@ -19,7 +19,7 @@ class TestAllPossibleYears(unittest.TestCase): def setUp(self): file_dir = os.path.dirname(os.path.abspath(__file__)) os.chdir(file_dir) - self.temp_dir = tempfile.TemporaryDirectory(dir=file_dir) + self.temp_dir = tempfile.TemporaryDirectory(dir=os.getcwd()) def tearDown(self): print("Deleting temporary directory") From f49382492e70b3e86467ded8c6f39f2889222786 Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 3 May 2023 08:55:44 -0300 Subject: [PATCH 098/265] Better encapsulation, all tests pass --- pipelines/datasets/br_denatran_frota/tasks.py | 29 +++++-------------- .../datasets/br_denatran_frota/tasks_test.py | 7 +++-- pipelines/datasets/br_denatran_frota/utils.py | 22 +++++--------- 3 files changed, 19 insertions(+), 39 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/tasks.py b/pipelines/datasets/br_denatran_frota/tasks.py index 7c3678d08..28314ad60 100644 --- a/pipelines/datasets/br_denatran_frota/tasks.py +++ b/pipelines/datasets/br_denatran_frota/tasks.py @@ -55,11 +55,12 @@ from pipelines.datasets.br_denatran_frota.constants import constants from pipelines.datasets.br_denatran_frota.utils import ( make_dir_when_not_exists, - download_post_2012, + extract_links_post_2012, verify_total, change_df_header, guess_header, get_year_month_from_filename, + call_downloader, ) import pandas as pd import polars as pl @@ -82,29 +83,14 @@ def crawl(month: int, year: int, temp_dir: str = ""): """ if month not in MONTHS.values(): raise ValueError("Mês inválido.") - - dir_list = glob.glob(f"**/{DATASET}", recursive=True) - # Get the directory where this Python file is located - initial_dir = os.path.dirname(os.path.abspath(__file__)) - if temp_dir: - os.chdir(temp_dir) - # Construct the path to the "files" directory relative to this directory - files_dir = os.path.join(os.getcwd(), "files") - if dir_list: - # I always want to be in the actual folder for this dataset, because I might start in the pipelines full repo: - os.chdir(dir_list[0]) - - # I always need a files directory inside my dataset folder. + files_dir = os.path.join(temp_dir, "files") make_dir_when_not_exists(files_dir) - # I should always switch to the files dir now and save stuff inside it. - os.chdir(files_dir) - year_dir_name = f"{year}" - - # Create dir for that specific year should it be necessary. + year_dir_name = os.path.join(files_dir, f"{year}") make_dir_when_not_exists(year_dir_name) - os.chdir(year_dir_name) if year > 2012: - download_post_2012(month, year) + files_to_download = extract_links_post_2012(month, year, year_dir_name) + for file_dict in files_to_download: + call_downloader(file_dict) # else: # url = f"https://www.gov.br/infraestrutura/pt-br/assuntos/transito/arquivos-senatran/estatisticas/renavam/{year}/frota{'_' if year > 2008 else ''}{year}.zip" @@ -112,7 +98,6 @@ def crawl(month: int, year: int, temp_dir: str = ""): # urlretrieve(url, generic_zip_filename) # with ZipFile(generic_zip_filename) as zip_file: # zip_file.extractall() - os.chdir(initial_dir) @task() diff --git a/pipelines/datasets/br_denatran_frota/tasks_test.py b/pipelines/datasets/br_denatran_frota/tasks_test.py index ef2d4bb41..212820ec5 100644 --- a/pipelines/datasets/br_denatran_frota/tasks_test.py +++ b/pipelines/datasets/br_denatran_frota/tasks_test.py @@ -6,6 +6,9 @@ from parameterized import parameterized from pipelines.datasets.br_denatran_frota.tasks import crawl +from pipelines.datasets.br_denatran_frota.constants import constants + +DATASET = constants.DATASET.value def custom_name_func(testcase_func, param_num, param): @@ -17,9 +20,7 @@ def custom_name_func(testcase_func, param_num, param): class TestAllPossibleYears(unittest.TestCase): def setUp(self): - file_dir = os.path.dirname(os.path.abspath(__file__)) - os.chdir(file_dir) - self.temp_dir = tempfile.TemporaryDirectory(dir=os.getcwd()) + self.temp_dir = tempfile.TemporaryDirectory(dir=os.path.join(f"{DATASET}")) def tearDown(self): print("Deleting temporary directory") diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index 272984bbb..5c4447190 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -222,16 +222,6 @@ def extract_zip(dest_path_file): z.extractall() -def handle_xl(i: dict) -> None: - """Actually downloads and deals with Excel files. - - Args: - i (dict): Dictionary with all the desired downloadable file's info. - """ - dest_path_file = make_filename(i) - download_file(i["href"], dest_path_file) - - def make_filename(i: dict, ext: bool = True) -> str: """Creates the filename using the sent dictionary. @@ -245,15 +235,16 @@ def make_filename(i: dict, ext: bool = True) -> str: txt = i["txt"] mes = i["mes"] ano = i["ano"] + directory = i["destination_dir"] filetype = i["filetype"] filename = re.sub("\\s+", "_", txt, flags=re.UNICODE).lower() - filename = f"{filename}_{mes}-{ano}" + filename = f"{directory}/{filename}_{mes}-{ano}" if ext: filename += f".{filetype}" return filename -def call_downloader(i): +def call_downloader(i: dict): filename = make_filename(i) if i["filetype"] in ["xlsx", "xls"]: download_file(i["href"], filename) @@ -262,7 +253,7 @@ def call_downloader(i): extract_zip(filename) -def download_post_2012(month: int, year: int): +def extract_links_post_2012(month: int, year: int, directory: str) -> list[dict]: """_summary_ Args: @@ -273,6 +264,7 @@ def download_post_2012(month: int, year: int): soup = BeautifulSoup(urlopen(url), "html.parser") # Só queremos os dados de frota nacional. nodes = soup.select("p:contains('rota por ') > a") + valid_links = [] for node in nodes: txt = node.text href = node.get("href") @@ -292,8 +284,10 @@ def download_post_2012(month: int, year: int): "mes": month, "ano": year, "filetype": filetype, + "destination_dir": directory, } - call_downloader(info) + valid_links.append(info) + return valid_links def make_dir_when_not_exists(dir_name: str): From e6a7c0088089e313564a95a07aaf32d2e3f41155 Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 3 May 2023 09:29:23 -0300 Subject: [PATCH 099/265] flows goes --- pipelines/datasets/br_denatran_frota/flows.py | 5 +++-- pipelines/datasets/br_denatran_frota/run.py | 4 ++++ 2 files changed, 7 insertions(+), 2 deletions(-) create mode 100644 pipelines/datasets/br_denatran_frota/run.py diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index 4fa1e6422..5648d753b 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -86,8 +86,8 @@ "Tamir", ], ) as br_denatran_frota_uf_tipo: - dataset_id = Parameter("dataset_id", default="br_denatran_frota", required=True) - table_id = Parameter("table_id", default="uf_tipo", required=True) + dataset_id = Parameter("dataset_id", default="br_denatran_frota") + table_id = Parameter("table_id", default="uf_tipo") # Materialization mode materialization_mode = Parameter( @@ -103,6 +103,7 @@ rename_flow_run = rename_current_flow_run_dataset_table( prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id ) + crawl(month=2, year=2021) # Download the desired files. br_denatran_frota_uf_tipo.storage = GCS(constants.GCS_FLOWS_BUCKET.value) br_denatran_frota_uf_tipo.run_config = KubernetesRun(image=constants.DOCKER_IMAGE.value) diff --git a/pipelines/datasets/br_denatran_frota/run.py b/pipelines/datasets/br_denatran_frota/run.py new file mode 100644 index 000000000..a0ead7920 --- /dev/null +++ b/pipelines/datasets/br_denatran_frota/run.py @@ -0,0 +1,4 @@ +# -*- coding: utf-8 -*- +from flows import br_denatran_frota_uf_tipo + +br_denatran_frota_uf_tipo.run() From 2e986b8e40f4c927736dc516f3878bbe5a62d0dc Mon Sep 17 00:00:00 2001 From: Tamir Date: Thu, 4 May 2023 23:39:11 -0300 Subject: [PATCH 100/265] Changes in header guess uses other flow for test --- .../datasets/br_denatran_frota/constants.py | 2 + pipelines/datasets/br_denatran_frota/flows.py | 54 +++++++++++-------- pipelines/datasets/br_denatran_frota/tasks.py | 3 +- pipelines/datasets/br_denatran_frota/utils.py | 9 ++-- 4 files changed, 42 insertions(+), 26 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/constants.py b/pipelines/datasets/br_denatran_frota/constants.py index 5491b46cb..9316af09f 100644 --- a/pipelines/datasets/br_denatran_frota/constants.py +++ b/pipelines/datasets/br_denatran_frota/constants.py @@ -99,3 +99,5 @@ class constants(Enum): # pylint: disable=c0103 ("SP", "embu"): "embu das artes", ("TO", "sao valerio da natividade"): "sao valerio", } + + DOWNLOAD_PATH = f"pipelines/datasets/{DATASET}/tmp/input" diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index 5648d753b..783214312 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -60,16 +60,16 @@ from datetime import datetime, timedelta from prefect.run_configs import KubernetesRun from prefect.storage import GCS -from prefect import Parameter, case +from prefect import Parameter, case, Flow from prefect.tasks.prefect import ( create_flow_run, wait_for_flow_run, ) -from pipelines.constants import constants +from pipelines.constants import constants as pipelines_constants from pipelines.utils.constants import constants as utils_constants -from pipelines.utils.decorators import Flow +# from pipelines.utils.decorators import Flow from pipelines.utils.execute_dbt_model.constants import constants as dump_db_constants from pipelines.utils.tasks import ( create_table_and_upload_to_gcs, @@ -77,34 +77,44 @@ get_current_flow_labels, ) from pipelines.datasets.br_denatran_frota.tasks import crawl, treat_uf_tipo +from pipelines.datasets.br_denatran_frota.constants import constants +download_path = constants.DOWNLOAD_PATH.value # from pipelines.datasets.br_denatran_frota.schedules import every_two_weeks with Flow( name="br_denatran_frota.uf_tipo", - code_owners=[ - "Tamir", - ], + # code_owners=[ + # "Tamir", + # ], ) as br_denatran_frota_uf_tipo: - dataset_id = Parameter("dataset_id", default="br_denatran_frota") - table_id = Parameter("table_id", default="uf_tipo") + # dataset_id = Parameter("dataset_id", default="br_denatran_frota") + # table_id = Parameter("table_id", default="uf_tipo") - # Materialization mode - materialization_mode = Parameter( - "materialization_mode", default="dev", required=False - ) + # # Materialization mode + # materialization_mode = Parameter( + # "materialization_mode", default="dev", required=False + # ) - materialize_after_dump = Parameter( - "materialize after dump", default=False, required=False - ) + # materialize_after_dump = Parameter( + # "materialize after dump", default=False, required=False + # ) - dbt_alias = Parameter("dbt_alias", default=True, required=False) + # dbt_alias = Parameter("dbt_alias", default=True, required=False) - rename_flow_run = rename_current_flow_run_dataset_table( - prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id - ) - crawl(month=2, year=2021) # Download the desired files. + # rename_flow_run = rename_current_flow_run_dataset_table( + # prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id + # ) + crawled = crawl( + month=2, year=2021, temp_dir=download_path + ) # Download the desired files. + uf_tipo_file = "/home/tamir/basedosdados/pipelines/pipelines/datasets/br_denatran_frota/tmp/input/files/2021/frota_por_uf_e_tipo_de_veículo_2-2021.xls" + df = treat_uf_tipo(file=uf_tipo_file, upstream_tasks=[crawled]) -br_denatran_frota_uf_tipo.storage = GCS(constants.GCS_FLOWS_BUCKET.value) -br_denatran_frota_uf_tipo.run_config = KubernetesRun(image=constants.DOCKER_IMAGE.value) + print("foi?") + +br_denatran_frota_uf_tipo.storage = GCS(pipelines_constants.GCS_FLOWS_BUCKET.value) +br_denatran_frota_uf_tipo.run_config = KubernetesRun( + image=pipelines_constants.DOCKER_IMAGE.value +) # flow.schedule = every_two_weeks diff --git a/pipelines/datasets/br_denatran_frota/tasks.py b/pipelines/datasets/br_denatran_frota/tasks.py index 28314ad60..07a4b5ae8 100644 --- a/pipelines/datasets/br_denatran_frota/tasks.py +++ b/pipelines/datasets/br_denatran_frota/tasks.py @@ -127,4 +127,5 @@ def treat_uf_tipo(file) -> pl.DataFrame: variable_name="tipo_veiculo", value_name="quantidade", ) # Long format. - return clean_pl_df.collect() + clean_pl_df = clean_pl_df.collect() + return clean_pl_df.write_csv(file=f"{filename}.csv", has_header=True) diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index 5c4447190..d8185c671 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -61,15 +61,18 @@ def guess_header(df: pd.DataFrame, max_header_guess: int = 4) -> int: int: Index of the row where the header is contained. """ header_guess = 0 + possible_guess_list = [header_guess] while header_guess < max_header_guess: if len(df) - 1 < header_guess: break # Iffy logic, but essentially: if all rows of the column are strings, then this is a good candidate for a header. if all(df.iloc[header_guess].apply(lambda x: isinstance(x, str))): - return header_guess + possible_guess_list.append(header_guess) header_guess += 1 - return 0 # If nothing is ever found until the max, let's just assume it's the first row as per usual. + return max( + possible_guess_list + ) # If nothing is ever found until the max, let's just assume it's the first row as per usual. def change_df_header(df: pd.DataFrame, header_row: int) -> pd.DataFrame: @@ -297,4 +300,4 @@ def make_dir_when_not_exists(dir_name: str): dir_name (str): Name of the subdirectory to be created. """ if not os.path.exists(dir_name): - os.mkdir(dir_name) + os.makedirs(dir_name) From f0a3a687b99b7efd87932c8b71c7282e17bda7a6 Mon Sep 17 00:00:00 2001 From: Tamir Date: Fri, 5 May 2023 00:45:36 -0300 Subject: [PATCH 101/265] Adjustment in tests after adjusting function --- .../datasets/br_denatran_frota/functions_test.py | 12 ++++++++---- 1 file changed, 8 insertions(+), 4 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/functions_test.py b/pipelines/datasets/br_denatran_frota/functions_test.py index e537606b6..f435c762f 100644 --- a/pipelines/datasets/br_denatran_frota/functions_test.py +++ b/pipelines/datasets/br_denatran_frota/functions_test.py @@ -14,6 +14,8 @@ from pipelines.datasets.br_denatran_frota.constants import constants from pipelines.datasets.br_denatran_frota.tasks import crawl +DOWNLOAD_PATH = constants.DOWNLOAD_PATH.value + class TestMakeFilename(unittest.TestCase): def test_make_filename(self): @@ -24,11 +26,12 @@ def test_make_filename(self): "mes": month, "ano": year, "filetype": "xlsx", + "destination_dir": DOWNLOAD_PATH, } filename = make_filename(i) self.assertEqual( filename, - f"frota-de-veiculos-por-municipio-tipo-e-combustivel_{month}-{year}.xlsx", + f"{DOWNLOAD_PATH}/frota-de-veiculos-por-municipio-tipo-e-combustivel_{month}-{year}.xlsx", ) def test_make_filename_without_ext(self): @@ -39,11 +42,12 @@ def test_make_filename_without_ext(self): "mes": 2, "ano": 2013, "filetype": "xlsx", + "destination_dir": DOWNLOAD_PATH, } filename = make_filename(i, ext=False) self.assertEqual( filename, - f"frota-de-veiculos-por-municipio-tipo-e-combustivel_{month}-{year}", + f"{DOWNLOAD_PATH}/frota-de-veiculos-por-municipio-tipo-e-combustivel_{month}-{year}", ) @@ -108,8 +112,8 @@ def test_all_columns_are_strings_not_in_header_row(self): {"A": ["1", "2", "3"], "B": ["4", "5", "6"], "C": ["7", "8", "9"]} ) self.assertEqual( - guess_header(df), 0 - ) # Header is assumed to be in the first row + guess_header(df), len(df) - 1 + ) # Header is assumed to be in the last row class TestFilenameExtraction(unittest.TestCase): From 6fb15561f49f73638f96dc1b48c496f76288f37f Mon Sep 17 00:00:00 2001 From: Tamir Date: Fri, 5 May 2023 00:53:17 -0300 Subject: [PATCH 102/265] Cleaner task test --- pipelines/datasets/br_denatran_frota/tasks_test.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/tasks_test.py b/pipelines/datasets/br_denatran_frota/tasks_test.py index 212820ec5..3ba9a06e2 100644 --- a/pipelines/datasets/br_denatran_frota/tasks_test.py +++ b/pipelines/datasets/br_denatran_frota/tasks_test.py @@ -9,6 +9,7 @@ from pipelines.datasets.br_denatran_frota.constants import constants DATASET = constants.DATASET.value +DOWNLOAD_PATH = constants.DOWNLOAD_PATH.value def custom_name_func(testcase_func, param_num, param): @@ -20,7 +21,9 @@ def custom_name_func(testcase_func, param_num, param): class TestAllPossibleYears(unittest.TestCase): def setUp(self): - self.temp_dir = tempfile.TemporaryDirectory(dir=os.path.join(f"{DATASET}")) + self.temp_dir = tempfile.TemporaryDirectory( + dir=os.path.join(f"{DOWNLOAD_PATH}") + ) def tearDown(self): print("Deleting temporary directory") From f6e1f8c3a57f733ae9b70436de465acb4d8eb649 Mon Sep 17 00:00:00 2001 From: Tamir Date: Fri, 5 May 2023 01:15:51 -0300 Subject: [PATCH 103/265] Constant for the CSVs --- pipelines/datasets/br_denatran_frota/constants.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/pipelines/datasets/br_denatran_frota/constants.py b/pipelines/datasets/br_denatran_frota/constants.py index 9316af09f..298dd1959 100644 --- a/pipelines/datasets/br_denatran_frota/constants.py +++ b/pipelines/datasets/br_denatran_frota/constants.py @@ -101,3 +101,5 @@ class constants(Enum): # pylint: disable=c0103 } DOWNLOAD_PATH = f"pipelines/datasets/{DATASET}/tmp/input" + + OUTPUT_PATH = f"pipelines/datasets/{DATASET}/tmp/output" From 87aa026512c4d031426d9a1e249e6fbfea708216 Mon Sep 17 00:00:00 2001 From: Tamir Date: Fri, 5 May 2023 03:36:54 -0300 Subject: [PATCH 104/265] Debugging via workaround --- .../datasets/br_denatran_frota/handlers.py | 137 ++++++++++++++++++ pipelines/datasets/br_denatran_frota/tasks.py | 39 ++--- .../datasets/br_denatran_frota/tasks_test.py | 4 +- 3 files changed, 150 insertions(+), 30 deletions(-) create mode 100644 pipelines/datasets/br_denatran_frota/handlers.py diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py new file mode 100644 index 000000000..daedaf045 --- /dev/null +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -0,0 +1,137 @@ +# -*- coding: utf-8 -*- +""" +Tasks for br_denatran_frota +""" + +############################################################################### +# +# Aqui é onde devem ser definidas as tasks para os flows do projeto. +# Cada task representa um passo da pipeline. Não é estritamente necessário +# tratar todas as exceções que podem ocorrer durante a execução de uma task, +# mas é recomendável, ainda que não vá implicar em uma quebra no sistema. +# Mais informações sobre tasks podem ser encontradas na documentação do +# Prefect: https://docs.prefect.io/core/concepts/tasks.html +# +# De modo a manter consistência na codebase, todo o código escrito passará +# pelo pylint. Todos os warnings e erros devem ser corrigidos. +# +# As tasks devem ser definidas como funções comuns ao Python, com o decorador +# @task acima. É recomendado inserir type hints para as variáveis. +# +# Um exemplo de task é o seguinte: +# +# ----------------------------------------------------------------------------- +# from prefect import task +# +# @task +# def my_task(param1: str, param2: int) -> str: +# """ +# My task description. +# """ +# return f'{param1} {param2}' +# ----------------------------------------------------------------------------- +# +# Você também pode usar pacotes Python arbitrários, como numpy, pandas, etc. +# +# ----------------------------------------------------------------------------- +# from prefect import task +# import numpy as np +# +# @task +# def my_task(a: np.ndarray, b: np.ndarray) -> str: +# """ +# My task description. +# """ +# return np.add(a, b) +# ----------------------------------------------------------------------------- +# +# Abaixo segue um código para exemplificação, que pode ser removido. +# +############################################################################### + +from prefect import task +import glob +import os +from pipelines.datasets.br_denatran_frota.constants import constants +from pipelines.datasets.br_denatran_frota.utils import ( + make_dir_when_not_exists, + extract_links_post_2012, + verify_total, + change_df_header, + guess_header, + get_year_month_from_filename, + call_downloader, +) +import pandas as pd +import polars as pl + +MONTHS = constants.MONTHS.value +DATASET = constants.DATASET.value +DICT_UFS = constants.DICT_UFS.value +OUTPUT_PATH = constants.OUTPUT_PATH.value + + +def crawl(month: int, year: int, temp_dir: str = ""): + """Função principal para baixar os dados de frota por município e tipo e também por UF e tipo. + + Args: + month (int): Mês desejado. + year (int): Ano desejado. + + Raises: + ValueError: Errors if the month is not a valid one. + """ + if month not in MONTHS.values(): + raise ValueError("Mês inválido.") + files_dir = os.path.join(temp_dir, "files") + make_dir_when_not_exists(files_dir) + year_dir_name = os.path.join(files_dir, f"{year}") + make_dir_when_not_exists(year_dir_name) + if year > 2012: + files_to_download = extract_links_post_2012(month, year, year_dir_name) + for file_dict in files_to_download: + call_downloader(file_dict) + # else: + # url = f"https://www.gov.br/infraestrutura/pt-br/assuntos/transito/arquivos-senatran/estatisticas/renavam/{year}/frota{'_' if year > 2008 else ''}{year}.zip" + + # generic_zip_filename = f"geral_{year}.zip" + # urlretrieve(url, generic_zip_filename) + # with ZipFile(generic_zip_filename) as zip_file: + # zip_file.extractall() + + +def treat_uf_tipo(file) -> pl.DataFrame: + filename = os.path.split(file)[1] + df = pd.read_excel(file) + new_df = change_df_header(df, guess_header(df)) + # This is ad hoc for UF_tipo. + new_df.rename( + columns={new_df.columns[0]: "sigla_uf"}, inplace=True + ) # Rename for ease of use. + new_df.sigla_uf = new_df.sigla_uf.str.strip() # Remove whitespace. + clean_df = new_df[new_df.sigla_uf.isin(DICT_UFS.values())].reset_index( + drop=True + ) # Now we get all the actual RELEVANT uf data. + month, year = get_year_month_from_filename(filename) + clean_pl_df = pl.from_pandas(clean_df).lazy() + verify_total(clean_pl_df.collect()) + # Add year and month + clean_pl_df = clean_pl_df.with_columns( + pl.lit(year, dtype=pl.Int64).alias("ano"), + pl.lit(month, dtype=pl.Int64).alias("mes"), + ) + clean_pl_df = clean_pl_df.select(pl.exclude("TOTAL")) + clean_pl_df = clean_pl_df.melt( + id_vars=["ano", "mes", "sigla_uf"], + variable_name="tipo_veiculo", + value_name="quantidade", + ) # Long format. + clean_pl_df = clean_pl_df.collect() + return clean_pl_df + + +def output_file_to_csv(df: pl.DataFrame) -> None: + pass + + +# df.write_csv(file=f"{OUTPUT_PATH}/{filename}.csv", has_header=True) diff --git a/pipelines/datasets/br_denatran_frota/tasks.py b/pipelines/datasets/br_denatran_frota/tasks.py index 07a4b5ae8..15972fd46 100644 --- a/pipelines/datasets/br_denatran_frota/tasks.py +++ b/pipelines/datasets/br_denatran_frota/tasks.py @@ -64,40 +64,17 @@ ) import pandas as pd import polars as pl +from pipelines.datasets.br_denatran_frota.handlers import crawl MONTHS = constants.MONTHS.value DATASET = constants.DATASET.value DICT_UFS = constants.DICT_UFS.value +OUTPUT_PATH = constants.OUTPUT_PATH.value @task() # noqa -def crawl(month: int, year: int, temp_dir: str = ""): - """Função principal para baixar os dados de frota por município e tipo e também por UF e tipo. - - Args: - month (int): Mês desejado. - year (int): Ano desejado. - - Raises: - ValueError: Errors if the month is not a valid one. - """ - if month not in MONTHS.values(): - raise ValueError("Mês inválido.") - files_dir = os.path.join(temp_dir, "files") - make_dir_when_not_exists(files_dir) - year_dir_name = os.path.join(files_dir, f"{year}") - make_dir_when_not_exists(year_dir_name) - if year > 2012: - files_to_download = extract_links_post_2012(month, year, year_dir_name) - for file_dict in files_to_download: - call_downloader(file_dict) - # else: - # url = f"https://www.gov.br/infraestrutura/pt-br/assuntos/transito/arquivos-senatran/estatisticas/renavam/{year}/frota{'_' if year > 2008 else ''}{year}.zip" - - # generic_zip_filename = f"geral_{year}.zip" - # urlretrieve(url, generic_zip_filename) - # with ZipFile(generic_zip_filename) as zip_file: - # zip_file.extractall() +def crawler(month: int, year: int, temp_dir: str = ""): + crawl(month, year, temp_dir) @task() @@ -128,4 +105,10 @@ def treat_uf_tipo(file) -> pl.DataFrame: value_name="quantidade", ) # Long format. clean_pl_df = clean_pl_df.collect() - return clean_pl_df.write_csv(file=f"{filename}.csv", has_header=True) + return clean_pl_df + + +@task() +def output_file_to_csv(df: pl.DataFrame) -> None: + pass + # df.write_csv(file=f"{OUTPUT_PATH}/{filename}.csv", has_header=True) diff --git a/pipelines/datasets/br_denatran_frota/tasks_test.py b/pipelines/datasets/br_denatran_frota/tasks_test.py index 3ba9a06e2..aba59aeab 100644 --- a/pipelines/datasets/br_denatran_frota/tasks_test.py +++ b/pipelines/datasets/br_denatran_frota/tasks_test.py @@ -5,7 +5,7 @@ import unittest from parameterized import parameterized -from pipelines.datasets.br_denatran_frota.tasks import crawl +from pipelines.datasets.br_denatran_frota.handlers import crawl from pipelines.datasets.br_denatran_frota.constants import constants DATASET = constants.DATASET.value @@ -30,7 +30,7 @@ def tearDown(self): shutil.rmtree(self.temp_dir.name) @parameterized.expand( - [(month, year) for year in range(2021, 2022) for month in range(1, 3)], + [(month, year) for year in range(2013, 2014) for month in range(1, 3)], name_func=custom_name_func, ) def test_download_post_2012(self, month, year): From d2a5eec6d41e4cff52409133457d09b998f0f473 Mon Sep 17 00:00:00 2001 From: Tamir Date: Fri, 5 May 2023 03:38:36 -0300 Subject: [PATCH 105/265] Adjustment still makes tests pass --- pipelines/datasets/br_denatran_frota/tasks_test.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/tasks_test.py b/pipelines/datasets/br_denatran_frota/tasks_test.py index aba59aeab..56453020c 100644 --- a/pipelines/datasets/br_denatran_frota/tasks_test.py +++ b/pipelines/datasets/br_denatran_frota/tasks_test.py @@ -5,7 +5,7 @@ import unittest from parameterized import parameterized -from pipelines.datasets.br_denatran_frota.handlers import crawl +from pipelines.datasets.br_denatran_frota.handlers import crawl, treat_uf_tipo from pipelines.datasets.br_denatran_frota.constants import constants DATASET = constants.DATASET.value @@ -30,11 +30,11 @@ def tearDown(self): shutil.rmtree(self.temp_dir.name) @parameterized.expand( - [(month, year) for year in range(2013, 2014) for month in range(1, 3)], + [(month, year) for year in range(2022, 2023) for month in range(1, 3)], name_func=custom_name_func, ) def test_download_post_2012(self, month, year): - crawl.run(month, year, self.temp_dir.name) + crawl(month, year, self.temp_dir.name) expected_files = { f"frota_por_uf_e_tipo_de_veículo_{month}-{year}", f"frota_por_município_e_tipo_{month}-{year}", From 63b999889912efc366ede5df0363ef916917b209 Mon Sep 17 00:00:00 2001 From: Tamir Date: Fri, 5 May 2023 03:56:00 -0300 Subject: [PATCH 106/265] No test side effects --- pipelines/datasets/br_denatran_frota/flows.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index 783214312..0c3926d12 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -76,7 +76,7 @@ rename_current_flow_run_dataset_table, get_current_flow_labels, ) -from pipelines.datasets.br_denatran_frota.tasks import crawl, treat_uf_tipo +from pipelines.datasets.br_denatran_frota.tasks import crawler, treat_uf_tipo from pipelines.datasets.br_denatran_frota.constants import constants download_path = constants.DOWNLOAD_PATH.value @@ -105,7 +105,7 @@ # rename_flow_run = rename_current_flow_run_dataset_table( # prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id # ) - crawled = crawl( + crawled = crawler( month=2, year=2021, temp_dir=download_path ) # Download the desired files. uf_tipo_file = "/home/tamir/basedosdados/pipelines/pipelines/datasets/br_denatran_frota/tmp/input/files/2021/frota_por_uf_e_tipo_de_veículo_2-2021.xls" From 9b3665b44d06a10dbf886d609649bd34e45a6c0b Mon Sep 17 00:00:00 2001 From: Tamir Date: Fri, 5 May 2023 05:33:31 -0300 Subject: [PATCH 107/265] RAR files work now --- .../datasets/br_denatran_frota/constants.py | 2 ++ .../datasets/br_denatran_frota/tasks_test.py | 8 +++--- pipelines/datasets/br_denatran_frota/utils.py | 28 ++++++++++++++++++- 3 files changed, 33 insertions(+), 5 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/constants.py b/pipelines/datasets/br_denatran_frota/constants.py index 298dd1959..80cbc5f13 100644 --- a/pipelines/datasets/br_denatran_frota/constants.py +++ b/pipelines/datasets/br_denatran_frota/constants.py @@ -103,3 +103,5 @@ class constants(Enum): # pylint: disable=c0103 DOWNLOAD_PATH = f"pipelines/datasets/{DATASET}/tmp/input" OUTPUT_PATH = f"pipelines/datasets/{DATASET}/tmp/output" + + UF_TIPO_BASIC_FILENAME = "frota_por_uf_e_tipo_de_veículo" diff --git a/pipelines/datasets/br_denatran_frota/tasks_test.py b/pipelines/datasets/br_denatran_frota/tasks_test.py index 56453020c..9655c1b95 100644 --- a/pipelines/datasets/br_denatran_frota/tasks_test.py +++ b/pipelines/datasets/br_denatran_frota/tasks_test.py @@ -30,18 +30,18 @@ def tearDown(self): shutil.rmtree(self.temp_dir.name) @parameterized.expand( - [(month, year) for year in range(2022, 2023) for month in range(1, 3)], + [(month, year) for year in range(2014, 2016) for month in range(1, 3)], name_func=custom_name_func, ) def test_download_post_2012(self, month, year): crawl(month, year, self.temp_dir.name) expected_files = { - f"frota_por_uf_e_tipo_de_veículo_{month}-{year}", - f"frota_por_município_e_tipo_{month}-{year}", + f"frota_por_uf_e_tipo_de_veiculo_{month}-{year}", + f"frota_por_municipio_e_tipo_{month}-{year}", } list_of_files = os.listdir(os.path.join(self.temp_dir.name, "files", f"{year}")) files = set(os.path.splitext(file)[0] for file in list_of_files) - self.assertEqual(files, expected_files) + self.assertTrue(expected_files.issubset(files)) if __name__ == "__main__": diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index d8185c671..976c5a7e2 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -36,7 +36,9 @@ import re import os from zipfile import ZipFile +from rarfile import RarFile import requests +from string_utils import asciify from pipelines.datasets.br_denatran_frota.constants import constants from bs4 import BeautifulSoup from urllib.request import urlopen @@ -45,6 +47,7 @@ SUBSTITUTIONS = constants.SUBSTITUTIONS.value HEADERS = constants.HEADERS.value MONTHS = constants.MONTHS.value +UF_TIPO_BASIC_FILENAME = constants.UF_TIPO_BASIC_FILENAME def guess_header(df: pd.DataFrame, max_header_guess: int = 4) -> int: @@ -225,6 +228,25 @@ def extract_zip(dest_path_file): z.extractall() +def extract_rar(dest_path_file): + with RarFile(dest_path_file, "r") as r: + files_inside_rar = [f.filename for f in r.infolist()] + rar_filename = r.filename + rar_filename_split = rar_filename.split("/") + directory = "/".join(rar_filename_split[: len(rar_filename_split) - 1]) + for file in files_inside_rar: + if re.search("UF", file, re.IGNORECASE): + new_extension = file.split(".")[-1] + new_filename = f"{r.filename.split('.')[0]}.{new_extension}" + r.extract(file, path=directory) + os.rename(f"{directory}/{file}", new_filename) + elif re.search("municipio", file, re.IGNORECASE): + new_extension = file.split(".")[-1] + new_filename = f"{r.filename.split('.')[0]}.{new_extension}" + r.extract(file, path=directory) + os.rename(f"{directory}/{file}", new_filename) + + def make_filename(i: dict, ext: bool = True) -> str: """Creates the filename using the sent dictionary. @@ -235,7 +257,7 @@ def make_filename(i: dict, ext: bool = True) -> str: Returns: str: The full filename. """ - txt = i["txt"] + txt = asciify(i["txt"]) mes = i["mes"] ano = i["ano"] directory = i["destination_dir"] @@ -254,6 +276,10 @@ def call_downloader(i: dict): elif i["filetype"] == "zip": download_file(i["href"], filename) extract_zip(filename) + elif i["filetype"] == "rar": + download_file(i["href"], filename) + extract_rar(filename) + print(2) def extract_links_post_2012(month: int, year: int, directory: str) -> list[dict]: From e3032f61df653cb17ee49055879592734f7312bb Mon Sep 17 00:00:00 2001 From: Tamir Date: Fri, 5 May 2023 05:52:28 -0300 Subject: [PATCH 108/265] Awesome trick for reusing code for zip and rar --- pipelines/datasets/br_denatran_frota/utils.py | 42 +++++++++---------- 1 file changed, 21 insertions(+), 21 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index 976c5a7e2..9756d2bae 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -228,22 +228,26 @@ def extract_zip(dest_path_file): z.extractall() -def extract_rar(dest_path_file): - with RarFile(dest_path_file, "r") as r: - files_inside_rar = [f.filename for f in r.infolist()] - rar_filename = r.filename - rar_filename_split = rar_filename.split("/") - directory = "/".join(rar_filename_split[: len(rar_filename_split) - 1]) - for file in files_inside_rar: - if re.search("UF", file, re.IGNORECASE): - new_extension = file.split(".")[-1] - new_filename = f"{r.filename.split('.')[0]}.{new_extension}" - r.extract(file, path=directory) - os.rename(f"{directory}/{file}", new_filename) - elif re.search("municipio", file, re.IGNORECASE): +def generic_extractor(dest_path_file): + extension = dest_path_file.split(".")[-1] + if extension == "rar": + extractor_function = RarFile + elif extension == "zip": + extractor_function = ZipFile + else: + raise ValueError(f"Unsupported type {extension} for compressed file.") + with extractor_function(dest_path_file, "r") as f: + files_inside_compressed = [f.filename for f in f.infolist()] + compressed_filename = f.filename + compressed_filename_split = compressed_filename.split("/") + directory = "/".join( + compressed_filename_split[: len(compressed_filename_split) - 1] + ) + for file in files_inside_compressed: + if re.search("UF|municipio", file, re.IGNORECASE): new_extension = file.split(".")[-1] - new_filename = f"{r.filename.split('.')[0]}.{new_extension}" - r.extract(file, path=directory) + new_filename = f"{f.filename.split('.')[0]}.{new_extension}" + f.extract(file, path=directory) os.rename(f"{directory}/{file}", new_filename) @@ -273,13 +277,9 @@ def call_downloader(i: dict): filename = make_filename(i) if i["filetype"] in ["xlsx", "xls"]: download_file(i["href"], filename) - elif i["filetype"] == "zip": - download_file(i["href"], filename) - extract_zip(filename) - elif i["filetype"] == "rar": + elif i["filetype"] == "zip" or i["filetype"] == "rar": download_file(i["href"], filename) - extract_rar(filename) - print(2) + generic_extractor(filename) def extract_links_post_2012(month: int, year: int, directory: str) -> list[dict]: From d3d9599f864bf917e5d9cc0915cc7dd80e5d5a13 Mon Sep 17 00:00:00 2001 From: Tamir Date: Fri, 5 May 2023 05:54:11 -0300 Subject: [PATCH 109/265] No need for specific zip function anymore --- pipelines/datasets/br_denatran_frota/utils.py | 5 ----- 1 file changed, 5 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index 9756d2bae..c51ed8ae1 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -223,11 +223,6 @@ def download_file(url, filename): print(f"Download of {filename} complete") -def extract_zip(dest_path_file): - with ZipFile(dest_path_file, "r") as z: - z.extractall() - - def generic_extractor(dest_path_file): extension = dest_path_file.split(".")[-1] if extension == "rar": From d88e64ebfae196559cb9505ff7cd92f62435e6f1 Mon Sep 17 00:00:00 2001 From: Tamir Date: Fri, 5 May 2023 06:13:04 -0300 Subject: [PATCH 110/265] Treat 2013 exception --- pipelines/datasets/br_denatran_frota/tasks_test.py | 2 +- pipelines/datasets/br_denatran_frota/utils.py | 4 ++++ 2 files changed, 5 insertions(+), 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/tasks_test.py b/pipelines/datasets/br_denatran_frota/tasks_test.py index 9655c1b95..8a6735346 100644 --- a/pipelines/datasets/br_denatran_frota/tasks_test.py +++ b/pipelines/datasets/br_denatran_frota/tasks_test.py @@ -30,7 +30,7 @@ def tearDown(self): shutil.rmtree(self.temp_dir.name) @parameterized.expand( - [(month, year) for year in range(2014, 2016) for month in range(1, 3)], + [(month, year) for year in range(2013, 2023) for month in range(1, 3)], name_func=custom_name_func, ) def test_download_post_2012(self, month, year): diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index c51ed8ae1..9eb55a9fd 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -259,6 +259,10 @@ def make_filename(i: dict, ext: bool = True) -> str: txt = asciify(i["txt"]) mes = i["mes"] ano = i["ano"] + if ano == 2013: + # Need to treat this specific difference because name is misleading. This should solve + txt = txt.replace("tipo", "uf e tipo") + txt = txt.replace("Municipio", "municipio e tipo") directory = i["destination_dir"] filetype = i["filetype"] filename = re.sub("\\s+", "_", txt, flags=re.UNICODE).lower() From 0d8cea23469c0d60a2e642e9d42d33ec28fcd292 Mon Sep 17 00:00:00 2001 From: Tamir Date: Sat, 6 May 2023 22:42:03 -0300 Subject: [PATCH 111/265] Modifications to deal with pre 2013 data --- .../datasets/br_denatran_frota/handlers.py | 21 ++++++++++++------- .../datasets/br_denatran_frota/tasks_test.py | 7 +++++++ pipelines/datasets/br_denatran_frota/utils.py | 19 ++++++++--------- 3 files changed, 29 insertions(+), 18 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index daedaf045..49ae1c0ba 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -50,7 +50,6 @@ ############################################################################### from prefect import task -import glob import os from pipelines.datasets.br_denatran_frota.constants import constants from pipelines.datasets.br_denatran_frota.utils import ( @@ -61,6 +60,7 @@ guess_header, get_year_month_from_filename, call_downloader, + generic_extractor, ) import pandas as pd import polars as pl @@ -91,13 +91,18 @@ def crawl(month: int, year: int, temp_dir: str = ""): files_to_download = extract_links_post_2012(month, year, year_dir_name) for file_dict in files_to_download: call_downloader(file_dict) - # else: - # url = f"https://www.gov.br/infraestrutura/pt-br/assuntos/transito/arquivos-senatran/estatisticas/renavam/{year}/frota{'_' if year > 2008 else ''}{year}.zip" - - # generic_zip_filename = f"geral_{year}.zip" - # urlretrieve(url, generic_zip_filename) - # with ZipFile(generic_zip_filename) as zip_file: - # zip_file.extractall() + else: + url = f"https://www.gov.br/infraestrutura/pt-br/assuntos/transito/arquivos-senatran/estatisticas/renavam/{year}/frota{'_' if year > 2008 else ''}{year}.zip" + info = { + "txt": "Dados anuais", + "href": url, + "mes_name": MONTHS.get(month), + "mes": month, + "ano": year, + "filetype": "zip", + "destination_dir": temp_dir, + } + call_downloader(info) def treat_uf_tipo(file) -> pl.DataFrame: diff --git a/pipelines/datasets/br_denatran_frota/tasks_test.py b/pipelines/datasets/br_denatran_frota/tasks_test.py index 8a6735346..311c99a58 100644 --- a/pipelines/datasets/br_denatran_frota/tasks_test.py +++ b/pipelines/datasets/br_denatran_frota/tasks_test.py @@ -43,6 +43,13 @@ def test_download_post_2012(self, month, year): files = set(os.path.splitext(file)[0] for file in list_of_files) self.assertTrue(expected_files.issubset(files)) + @parameterized.expand( + [(month, year) for year in range(2012, 2013) for month in range(1, 3)], + name_func=custom_name_func, + ) + def test_download_pre_2012(self, month, year): + crawl(month, year, self.temp_dir.name) + if __name__ == "__main__": unittest.main() diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index 9eb55a9fd..f53d328bd 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -223,7 +223,7 @@ def download_file(url, filename): print(f"Download of {filename} complete") -def generic_extractor(dest_path_file): +def generic_extractor(dest_path_file: str): extension = dest_path_file.split(".")[-1] if extension == "rar": extractor_function = RarFile @@ -232,18 +232,17 @@ def generic_extractor(dest_path_file): else: raise ValueError(f"Unsupported type {extension} for compressed file.") with extractor_function(dest_path_file, "r") as f: - files_inside_compressed = [f.filename for f in f.infolist()] compressed_filename = f.filename compressed_filename_split = compressed_filename.split("/") directory = "/".join( compressed_filename_split[: len(compressed_filename_split) - 1] ) - for file in files_inside_compressed: - if re.search("UF|municipio", file, re.IGNORECASE): - new_extension = file.split(".")[-1] + for file in f.infolist(): + if re.search("UF|municipio", file.filename, re.IGNORECASE): + new_extension = file.filename.split(".")[-1] new_filename = f"{f.filename.split('.')[0]}.{new_extension}" - f.extract(file, path=directory) - os.rename(f"{directory}/{file}", new_filename) + f.extract(file.filename, path=directory) + os.rename(f"{directory}/{file.filename}", new_filename) def make_filename(i: dict, ext: bool = True) -> str: @@ -282,11 +281,11 @@ def call_downloader(i: dict): def extract_links_post_2012(month: int, year: int, directory: str) -> list[dict]: - """_summary_ + """Extracts links of the Denatran files post 2012. Args: - year (int): _description_ - month (int): _description_ + year (int): A year starting from 2013 onwards. + month (int): A month from 1 to 12. """ url = f"https://www.gov.br/infraestrutura/pt-br/assuntos/transito/conteudo-Senatran/frota-de-veiculos-{year}" soup = BeautifulSoup(urlopen(url), "html.parser") From 20cc2b17b9352bd77a68b27238ed981fcd80e472 Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 7 May 2023 02:47:29 -0300 Subject: [PATCH 112/265] Pre-2013: crude but getting there --- .../datasets/br_denatran_frota/constants.py | 4 ++ .../datasets/br_denatran_frota/handlers.py | 53 +++++++++++++++---- .../datasets/br_denatran_frota/tasks_test.py | 14 ++--- pipelines/datasets/br_denatran_frota/utils.py | 6 ++- 4 files changed, 58 insertions(+), 19 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/constants.py b/pipelines/datasets/br_denatran_frota/constants.py index 80cbc5f13..003e1401b 100644 --- a/pipelines/datasets/br_denatran_frota/constants.py +++ b/pipelines/datasets/br_denatran_frota/constants.py @@ -105,3 +105,7 @@ class constants(Enum): # pylint: disable=c0103 OUTPUT_PATH = f"pipelines/datasets/{DATASET}/tmp/output" UF_TIPO_BASIC_FILENAME = "frota_por_uf_e_tipo_de_veículo" + + MUNIC_TIPO_BASIC_FILENAME = "frota_por_municipio_e_tipo" + + MONTHS_SHORT = {month[:3]: number for month, number in MONTHS.items()} diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 49ae1c0ba..adaec0416 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -51,6 +51,7 @@ from prefect import task import os +import re from pipelines.datasets.br_denatran_frota.constants import constants from pipelines.datasets.br_denatran_frota.utils import ( make_dir_when_not_exists, @@ -60,15 +61,19 @@ guess_header, get_year_month_from_filename, call_downloader, - generic_extractor, + download_file, ) import pandas as pd import polars as pl +from zipfile import ZipFile MONTHS = constants.MONTHS.value DATASET = constants.DATASET.value DICT_UFS = constants.DICT_UFS.value OUTPUT_PATH = constants.OUTPUT_PATH.value +MONTHS_SHORT = constants.MONTHS_SHORT.value +UF_TIPO_BASIC_FILENAME = constants.UF_TIPO_BASIC_FILENAME.value +MUNIC_TIPO_BASIC_FILENAME = constants.MUNIC_TIPO_BASIC_FILENAME.value def crawl(month: int, year: int, temp_dir: str = ""): @@ -93,16 +98,42 @@ def crawl(month: int, year: int, temp_dir: str = ""): call_downloader(file_dict) else: url = f"https://www.gov.br/infraestrutura/pt-br/assuntos/transito/arquivos-senatran/estatisticas/renavam/{year}/frota{'_' if year > 2008 else ''}{year}.zip" - info = { - "txt": "Dados anuais", - "href": url, - "mes_name": MONTHS.get(month), - "mes": month, - "ano": year, - "filetype": "zip", - "destination_dir": temp_dir, - } - call_downloader(info) + # info = { + # "txt": "Dados anuais", + # "href": url, + # "mes_name": MONTHS.get(month), + # "mes": month, + # "ano": year, + # "filetype": "zip", + # "destination_dir": temp_dir, + # } + # call_downloader(info) + # Nesse caso aqui, o que eu quero? Eu quero baixar o zip: + filename = f"{year_dir_name}/dados_anuais.zip" + download_file(url, filename) + # Aí depois eu preciso andar pelo zip: + with ZipFile(filename, "r") as f: + compressed_files = [file for file in f.infolist() if not file.is_dir()] + for file in compressed_files: + filename = file.filename.split("/")[-1] + if re.search("Tipo UF", filename, re.IGNORECASE): + match = re.search(rf"Tipo UF\.\s*(.*?)\s*\.{year}", filename) + if match: + month = match.group(1).lower() + month_value = MONTHS.get(month) or MONTHS_SHORT.get(month) + extension = filename.split(".")[-1] + new_filename = f"{year_dir_name}/{UF_TIPO_BASIC_FILENAME}_{month_value}-{year}.{extension}" + f.extract(file, path=year_dir_name) + os.rename(f"{year_dir_name}/{file.filename}", new_filename) + elif re.search("Munic", filename, re.IGNORECASE): + match = re.search(rf"Munic\.\s*(.*?)\s*\.{year}", filename) + if match: + month = match.group(1).lower() + month_value = MONTHS.get(month) or MONTHS_SHORT.get(month) + extension = filename.split(".")[-1] + new_filename = f"{year_dir_name}/{MUNIC_TIPO_BASIC_FILENAME}_{month_value}-{year}.{extension}" + f.extract(file, path=year_dir_name) + os.rename(f"{year_dir_name}/{file.filename}", new_filename) def treat_uf_tipo(file) -> pl.DataFrame: diff --git a/pipelines/datasets/br_denatran_frota/tasks_test.py b/pipelines/datasets/br_denatran_frota/tasks_test.py index 311c99a58..59815d423 100644 --- a/pipelines/datasets/br_denatran_frota/tasks_test.py +++ b/pipelines/datasets/br_denatran_frota/tasks_test.py @@ -30,7 +30,7 @@ def tearDown(self): shutil.rmtree(self.temp_dir.name) @parameterized.expand( - [(month, year) for year in range(2013, 2023) for month in range(1, 3)], + [(month, year) for year in range(2012, 2023) for month in range(1, 3)], name_func=custom_name_func, ) def test_download_post_2012(self, month, year): @@ -43,12 +43,12 @@ def test_download_post_2012(self, month, year): files = set(os.path.splitext(file)[0] for file in list_of_files) self.assertTrue(expected_files.issubset(files)) - @parameterized.expand( - [(month, year) for year in range(2012, 2013) for month in range(1, 3)], - name_func=custom_name_func, - ) - def test_download_pre_2012(self, month, year): - crawl(month, year, self.temp_dir.name) + # @parameterized.expand( + # [(month, year) for year in range(2012, 2013) for month in range(1, 3)], + # name_func=custom_name_func, + # ) + # def test_download_pre_2012(self, month, year): + # crawl(month, year, self.temp_dir.name) if __name__ == "__main__": diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index f53d328bd..33c6f7e7d 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -238,7 +238,11 @@ def generic_extractor(dest_path_file: str): compressed_filename_split[: len(compressed_filename_split) - 1] ) for file in f.infolist(): - if re.search("UF|municipio", file.filename, re.IGNORECASE): + print(file) + if ( + re.search("UF|municipio", file.filename, re.IGNORECASE) + and not file.is_dir() + ): new_extension = file.filename.split(".")[-1] new_filename = f"{f.filename.split('.')[0]}.{new_extension}" f.extract(file.filename, path=directory) From 653fcf43caa3bc6fcf4530cd0e3d2ea49d7a1c5c Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 7 May 2023 18:53:42 -0300 Subject: [PATCH 113/265] 2012 extraction works! --- pipelines/datasets/br_denatran_frota/constants.py | 2 +- pipelines/datasets/br_denatran_frota/handlers.py | 6 +++--- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/constants.py b/pipelines/datasets/br_denatran_frota/constants.py index 003e1401b..24cb62653 100644 --- a/pipelines/datasets/br_denatran_frota/constants.py +++ b/pipelines/datasets/br_denatran_frota/constants.py @@ -104,7 +104,7 @@ class constants(Enum): # pylint: disable=c0103 OUTPUT_PATH = f"pipelines/datasets/{DATASET}/tmp/output" - UF_TIPO_BASIC_FILENAME = "frota_por_uf_e_tipo_de_veículo" + UF_TIPO_BASIC_FILENAME = "frota_por_uf_e_tipo_de_veiculo" MUNIC_TIPO_BASIC_FILENAME = "frota_por_municipio_e_tipo" diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index adaec0416..b989a3aef 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -116,10 +116,10 @@ def crawl(month: int, year: int, temp_dir: str = ""): compressed_files = [file for file in f.infolist() if not file.is_dir()] for file in compressed_files: filename = file.filename.split("/")[-1] - if re.search("Tipo UF", filename, re.IGNORECASE): - match = re.search(rf"Tipo UF\.\s*(.*?)\s*\.{year}", filename) + if re.search("Tipo", filename, re.IGNORECASE): + match = re.search(r"Tipo UF\s+([^\s\d]+\s*)*([12]\d{3})", filename) if match: - month = match.group(1).lower() + month = match.group(1).lower().replace(".", "") month_value = MONTHS.get(month) or MONTHS_SHORT.get(month) extension = filename.split(".")[-1] new_filename = f"{year_dir_name}/{UF_TIPO_BASIC_FILENAME}_{month_value}-{year}.{extension}" From ab1f39c3d5dcf82735e13ee8322a0a32b58eb1ac Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 7 May 2023 19:03:10 -0300 Subject: [PATCH 114/265] 2011 also works now --- pipelines/datasets/br_denatran_frota/handlers.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index b989a3aef..f17b252c4 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -126,7 +126,7 @@ def crawl(month: int, year: int, temp_dir: str = ""): f.extract(file, path=year_dir_name) os.rename(f"{year_dir_name}/{file.filename}", new_filename) elif re.search("Munic", filename, re.IGNORECASE): - match = re.search(rf"Munic\.\s*(.*?)\s*\.{year}", filename) + match = re.search(rf"Munic\.?\s*(.*?)\s*\.?{year}", filename) if match: month = match.group(1).lower() month_value = MONTHS.get(month) or MONTHS_SHORT.get(month) From c474f0c4424da125ba0ff094079ca15c40f7c5b4 Mon Sep 17 00:00:00 2001 From: Tamir Date: Mon, 8 May 2023 02:57:15 -0300 Subject: [PATCH 115/265] Fixing toml, lock + adding code2flow --- poetry.lock | 1580 ++++-------------------------------------------- pyproject.toml | 3 +- 2 files changed, 131 insertions(+), 1452 deletions(-) diff --git a/poetry.lock b/poetry.lock index 828aa57a0..fc0d1fcf2 100644 --- a/poetry.lock +++ b/poetry.lock @@ -16,7 +16,7 @@ files = [ name = "arrow" version = "1.2.3" description = "Better dates & times for Python" -category = "main" +category = "dev" optional = false python-versions = ">=3.6" files = [ @@ -80,10 +80,6 @@ files = [ {file = "basedosdados-1.6.9-py3-none-any.whl", hash = "sha256:9a73ad8a3667cca327d81c5d41ec809ed0675825dfc5d93d1efcf45f9bd1e867"}, {file = "basedosdados-1.6.9.tar.gz", hash = "sha256:51783ea130944295dbc6b7dcbad8676ca0ff0234cdf2b4d212177bcd12db7921"}, ] -files = [ - 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match = re.search(r"Tipo UF\s+([^\s\d]+\s*)*([12]\d{3})", filename) - if match: - month = match.group(1).lower().replace(".", "") - month_value = MONTHS.get(month) or MONTHS_SHORT.get(month) - extension = filename.split(".")[-1] - new_filename = f"{year_dir_name}/{UF_TIPO_BASIC_FILENAME}_{month_value}-{year}.{extension}" - f.extract(file, path=year_dir_name) - os.rename(f"{year_dir_name}/{file.filename}", new_filename) + new_filename = make_filename_2010_to_2012( + "Tipo", year, filename, year_dir_name, month + ) elif re.search("Munic", filename, re.IGNORECASE): - match = re.search(rf"Munic\.?\s*(.*?)\s*\.?{year}", filename) - if match: - month = match.group(1).lower() - month_value = MONTHS.get(month) or MONTHS_SHORT.get(month) - extension = filename.split(".")[-1] - new_filename = f"{year_dir_name}/{MUNIC_TIPO_BASIC_FILENAME}_{month_value}-{year}.{extension}" - f.extract(file, path=year_dir_name) - os.rename(f"{year_dir_name}/{file.filename}", new_filename) + new_filename = make_filename_2010_to_2012( + "Munic", year, filename, year_dir_name, month + ) + if new_filename: + f.extract(file, path=year_dir_name) + os.rename(f"{year_dir_name}/{file.filename}", new_filename) def treat_uf_tipo(file) -> pl.DataFrame: diff --git a/pipelines/datasets/br_denatran_frota/tasks_test.py b/pipelines/datasets/br_denatran_frota/tasks_test.py index 59815d423..9b2005652 100644 --- a/pipelines/datasets/br_denatran_frota/tasks_test.py +++ b/pipelines/datasets/br_denatran_frota/tasks_test.py @@ -30,7 +30,7 @@ def tearDown(self): shutil.rmtree(self.temp_dir.name) @parameterized.expand( - [(month, year) for year in range(2012, 2023) for month in range(1, 3)], + [(month, year) for year in range(2010, 2013) for month in range(1, 3)], name_func=custom_name_func, ) def test_download_post_2012(self, month, year): @@ -43,13 +43,6 @@ def test_download_post_2012(self, month, year): files = set(os.path.splitext(file)[0] for file in list_of_files) self.assertTrue(expected_files.issubset(files)) - # @parameterized.expand( - # [(month, year) for year in range(2012, 2013) for month in range(1, 3)], - # name_func=custom_name_func, - # ) - # def test_download_pre_2012(self, month, year): - # crawl(month, year, self.temp_dir.name) - if __name__ == "__main__": unittest.main() diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index 33c6f7e7d..fea1e719d 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -47,7 +47,9 @@ SUBSTITUTIONS = constants.SUBSTITUTIONS.value HEADERS = constants.HEADERS.value MONTHS = constants.MONTHS.value -UF_TIPO_BASIC_FILENAME = constants.UF_TIPO_BASIC_FILENAME +UF_TIPO_BASIC_FILENAME = constants.UF_TIPO_BASIC_FILENAME.value +MONTHS_SHORT = constants.MONTHS_SHORT.value +MUNIC_TIPO_BASIC_FILENAME = constants.MUNIC_TIPO_BASIC_FILENAME.value def guess_header(df: pd.DataFrame, max_header_guess: int = 4) -> int: @@ -284,6 +286,29 @@ def call_downloader(i: dict): generic_extractor(filename) +def make_filename_2010_to_2012( + type_of_file: str, year: int, filename: str, year_dir_name: str, month: int +): + if type_of_file == "Tipo": + regex_to_search = r"Tipo UF\s+([^\s\d]+\s*)*([12]\d{3})" + basic_filename = UF_TIPO_BASIC_FILENAME + elif type_of_file == "Munic": + regex_to_search = rf"Munic\.?\s*(.*?)\s*\.?{year}" + basic_filename = MUNIC_TIPO_BASIC_FILENAME + else: + raise ValueError + match = re.search(regex_to_search, filename) + if match: + month_in_file = match.group(1).lower().replace(".", "") + month_value = MONTHS.get(month_in_file) or MONTHS_SHORT.get(month_in_file) + extension = filename.split(".")[-1] + new_filename = ( + f"{year_dir_name}/{basic_filename}_{month_value}-{year}.{extension}" + ) + if month_value == month: + return new_filename + + def extract_links_post_2012(month: int, year: int, directory: str) -> list[dict]: """Extracts links of the Denatran files post 2012. From 3644bb0b3bacbf19aee752e7bd1c824e89d315e7 Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 9 May 2023 03:26:51 -0300 Subject: [PATCH 117/265] Better encapsulation --- .../datasets/br_denatran_frota/handlers.py | 33 ++----------------- pipelines/datasets/br_denatran_frota/utils.py | 22 +++++++++++++ 2 files changed, 24 insertions(+), 31 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 3e856a9d3..7694e282b 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -62,7 +62,7 @@ get_year_month_from_filename, call_downloader, download_file, - make_filename_2010_to_2012, + extraction_pre_2012, ) import pandas as pd import polars as pl @@ -99,36 +99,7 @@ def crawl(month: int, year: int, temp_dir: str = ""): call_downloader(file_dict) else: url = f"https://www.gov.br/infraestrutura/pt-br/assuntos/transito/arquivos-senatran/estatisticas/renavam/{year}/frota{'_' if year > 2008 else ''}{year}.zip" - # info = { - # "txt": "Dados anuais", - # "href": url, - # "mes_name": MONTHS.get(month), - # "mes": month, - # "ano": year, - # "filetype": "zip", - # "destination_dir": temp_dir, - # } - # call_downloader(info) - # Nesse caso aqui, o que eu quero? Eu quero baixar o zip: - filename = f"{year_dir_name}/dados_anuais.zip" - download_file(url, filename) - # Aí depois eu preciso andar pelo zip: - with ZipFile(filename, "r") as f: - compressed_files = [file for file in f.infolist() if not file.is_dir()] - new_filename = None - for file in compressed_files: - filename = file.filename.split("/")[-1] - if re.search("Tipo", filename, re.IGNORECASE): - new_filename = make_filename_2010_to_2012( - "Tipo", year, filename, year_dir_name, month - ) - elif re.search("Munic", filename, re.IGNORECASE): - new_filename = make_filename_2010_to_2012( - "Munic", year, filename, year_dir_name, month - ) - if new_filename: - f.extract(file, path=year_dir_name) - os.rename(f"{year_dir_name}/{file.filename}", new_filename) + extraction_pre_2012(url, month, year, year_dir_name) def treat_uf_tipo(file) -> pl.DataFrame: diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index fea1e719d..c3549bf11 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -346,6 +346,28 @@ def extract_links_post_2012(month: int, year: int, directory: str) -> list[dict] return valid_links +def extraction_pre_2012(url: str, month: int, year: int, year_dir_name: str): + filename = f"{year_dir_name}/dados_anuais.zip" + download_file(url, filename) + # Aí depois eu preciso andar pelo zip: + with ZipFile(filename, "r") as f: + compressed_files = [file for file in f.infolist() if not file.is_dir()] + new_filename = None + for file in compressed_files: + filename = file.filename.split("/")[-1] + if re.search("Tipo", filename, re.IGNORECASE): + new_filename = make_filename_2010_to_2012( + "Tipo", year, filename, year_dir_name, month + ) + elif re.search("Munic", filename, re.IGNORECASE): + new_filename = make_filename_2010_to_2012( + "Munic", year, filename, year_dir_name, month + ) + if new_filename: + f.extract(file, path=year_dir_name) + os.rename(f"{year_dir_name}/{file.filename}", new_filename) + + def make_dir_when_not_exists(dir_name: str): """Auxiliary function to create a subdirectory when it is not present. From b7d1c090f6488d02a2f2f29eaf2b99ca69ebb313 Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 9 May 2023 20:36:26 -0300 Subject: [PATCH 118/265] Trying to solve 2009 and down --- pipelines/datasets/br_denatran_frota/handlers.py | 6 +++++- pipelines/datasets/br_denatran_frota/tasks_test.py | 2 +- 2 files changed, 6 insertions(+), 2 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 7694e282b..8c5477a97 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -99,7 +99,11 @@ def crawl(month: int, year: int, temp_dir: str = ""): call_downloader(file_dict) else: url = f"https://www.gov.br/infraestrutura/pt-br/assuntos/transito/arquivos-senatran/estatisticas/renavam/{year}/frota{'_' if year > 2008 else ''}{year}.zip" - extraction_pre_2012(url, month, year, year_dir_name) + filename = f"{year_dir_name}/dados_anuais.zip" + download_file(url, filename) + if year < 2010: + print(2) + extraction_pre_2012(url, month, year, year_dir_name, filename) def treat_uf_tipo(file) -> pl.DataFrame: diff --git a/pipelines/datasets/br_denatran_frota/tasks_test.py b/pipelines/datasets/br_denatran_frota/tasks_test.py index 9b2005652..dde6af23d 100644 --- a/pipelines/datasets/br_denatran_frota/tasks_test.py +++ b/pipelines/datasets/br_denatran_frota/tasks_test.py @@ -30,7 +30,7 @@ def tearDown(self): shutil.rmtree(self.temp_dir.name) @parameterized.expand( - [(month, year) for year in range(2010, 2013) for month in range(1, 3)], + [(month, year) for year in range(2002, 2013) for month in range(1, 2)], name_func=custom_name_func, ) def test_download_post_2012(self, month, year): From f5bb766bf3a29310c11534a4b21e3456d8cad12c Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 9 May 2023 20:48:11 -0300 Subject: [PATCH 119/265] Adhoc treatment for pre 2010 --- pipelines/datasets/br_denatran_frota/handlers.py | 6 +++++- pipelines/datasets/br_denatran_frota/utils.py | 6 +++--- 2 files changed, 8 insertions(+), 4 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 8c5477a97..5e31619a6 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -102,7 +102,11 @@ def crawl(month: int, year: int, temp_dir: str = ""): filename = f"{year_dir_name}/dados_anuais.zip" download_file(url, filename) if year < 2010: - print(2) + with ZipFile(filename, "r") as f: + f.extractall(path=f"{year_dir_name}") + for aggregate_file in os.listdir(f"{year_dir_name}"): + print(aggregate_file) + extraction_pre_2012(url, month, year, year_dir_name, aggregate_file) extraction_pre_2012(url, month, year, year_dir_name, filename) diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index c3549bf11..4ba04cb89 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -346,9 +346,9 @@ def extract_links_post_2012(month: int, year: int, directory: str) -> list[dict] return valid_links -def extraction_pre_2012(url: str, month: int, year: int, year_dir_name: str): - filename = f"{year_dir_name}/dados_anuais.zip" - download_file(url, filename) +def extraction_pre_2012( + url: str, month: int, year: int, year_dir_name: str, filename: str +): # Aí depois eu preciso andar pelo zip: with ZipFile(filename, "r") as f: compressed_files = [file for file in f.infolist() if not file.is_dir()] From 4800468692a637033d2489edf8b3325f6d636f25 Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 9 May 2023 22:34:11 -0300 Subject: [PATCH 120/265] Almost there --- pipelines/datasets/br_denatran_frota/handlers.py | 10 ++++++++-- pipelines/datasets/br_denatran_frota/utils.py | 8 +++++--- 2 files changed, 13 insertions(+), 5 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 5e31619a6..3c8bbf603 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -105,8 +105,14 @@ def crawl(month: int, year: int, temp_dir: str = ""): with ZipFile(filename, "r") as f: f.extractall(path=f"{year_dir_name}") for aggregate_file in os.listdir(f"{year_dir_name}"): - print(aggregate_file) - extraction_pre_2012(url, month, year, year_dir_name, aggregate_file) + if aggregate_file != "dados_anuais.zip": + extraction_pre_2012( + url, + month, + year, + year_dir_name, + os.path.join(year_dir_name, aggregate_file), + ) extraction_pre_2012(url, month, year, year_dir_name, filename) diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index 4ba04cb89..bb32285e3 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -350,8 +350,9 @@ def extraction_pre_2012( url: str, month: int, year: int, year_dir_name: str, filename: str ): # Aí depois eu preciso andar pelo zip: - with ZipFile(filename, "r") as f: - compressed_files = [file for file in f.infolist() if not file.is_dir()] + print("Bom dia") + with ZipFile(filename, "r") as g: + compressed_files = [file for file in g.infolist() if not file.is_dir()] new_filename = None for file in compressed_files: filename = file.filename.split("/")[-1] @@ -364,8 +365,9 @@ def extraction_pre_2012( "Munic", year, filename, year_dir_name, month ) if new_filename: - f.extract(file, path=year_dir_name) + g.extract(file, path=year_dir_name) os.rename(f"{year_dir_name}/{file.filename}", new_filename) + print("Bom dia") def make_dir_when_not_exists(dir_name: str): From b011ce1a817f037a4687d2ed193e71e79b26d587 Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 9 May 2023 23:43:23 -0300 Subject: [PATCH 121/265] Works from 2005 onwards --- pipelines/datasets/br_denatran_frota/handlers.py | 3 ++- pipelines/datasets/br_denatran_frota/utils.py | 10 ++++++---- 2 files changed, 8 insertions(+), 5 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 3c8bbf603..3b6354d1f 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -113,7 +113,8 @@ def crawl(month: int, year: int, temp_dir: str = ""): year_dir_name, os.path.join(year_dir_name, aggregate_file), ) - extraction_pre_2012(url, month, year, year_dir_name, filename) + else: + extraction_pre_2012(url, month, year, year_dir_name, filename) def treat_uf_tipo(file) -> pl.DataFrame: diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index bb32285e3..7bc130555 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -290,7 +290,7 @@ def make_filename_2010_to_2012( type_of_file: str, year: int, filename: str, year_dir_name: str, month: int ): if type_of_file == "Tipo": - regex_to_search = r"Tipo UF\s+([^\s\d]+\s*)*([12]\d{3})" + regex_to_search = r"UF\s+([^\s\d]+\s*)*([12]\d{3})" basic_filename = UF_TIPO_BASIC_FILENAME elif type_of_file == "Munic": regex_to_search = rf"Munic\.?\s*(.*?)\s*\.?{year}" @@ -347,16 +347,18 @@ def extract_links_post_2012(month: int, year: int, directory: str) -> list[dict] def extraction_pre_2012( - url: str, month: int, year: int, year_dir_name: str, filename: str + url: str, month: int, year: int, year_dir_name: str, zip_file: str ): # Aí depois eu preciso andar pelo zip: print("Bom dia") - with ZipFile(filename, "r") as g: + with ZipFile(zip_file, "r") as g: compressed_files = [file for file in g.infolist() if not file.is_dir()] new_filename = None for file in compressed_files: filename = file.filename.split("/")[-1] - if re.search("Tipo", filename, re.IGNORECASE): + if re.search("Tipo", filename, re.IGNORECASE) or re.search( + "Tipo UF", zip_file.split("/")[-1] + ): new_filename = make_filename_2010_to_2012( "Tipo", year, filename, year_dir_name, month ) From ac0117cc5465da93945f22dad8137c06b1fa65eb Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 10 May 2023 01:05:08 -0300 Subject: [PATCH 122/265] 2005 is the best I have so far --- pipelines/datasets/br_denatran_frota/utils.py | 14 ++++++++++---- 1 file changed, 10 insertions(+), 4 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index 7bc130555..4ffa7bb16 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -290,17 +290,23 @@ def make_filename_2010_to_2012( type_of_file: str, year: int, filename: str, year_dir_name: str, month: int ): if type_of_file == "Tipo": - regex_to_search = r"UF\s+([^\s\d]+\s*)*([12]\d{3})" basic_filename = UF_TIPO_BASIC_FILENAME + if year > 2005: + regex_to_search = r"UF\s+([^\s\d]+\s*)*([12]\d{3})" + else: + regex_to_search = rf"UF_([^\s\d]+\s*)_{str(year)[2:4]}" elif type_of_file == "Munic": - regex_to_search = rf"Munic\.?\s*(.*?)\s*\.?{year}" basic_filename = MUNIC_TIPO_BASIC_FILENAME + regex_to_search = rf"Munic\.?\s*(.*?)\s*\.?{year}" else: raise ValueError match = re.search(regex_to_search, filename) if match: - month_in_file = match.group(1).lower().replace(".", "") - month_value = MONTHS.get(month_in_file) or MONTHS_SHORT.get(month_in_file) + if year <= 2005 and type_of_file == "Munic": + month_value = int(match.group(1)) + else: + month_in_file = match.group(1).lower().replace(".", "") + month_value = MONTHS.get(month_in_file) or MONTHS_SHORT.get(month_in_file) extension = filename.split(".")[-1] new_filename = ( f"{year_dir_name}/{basic_filename}_{month_value}-{year}.{extension}" From 80cb5808849366c15a06caf1d5a1bec12076ca7c Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 10 May 2023 01:08:49 -0300 Subject: [PATCH 123/265] And now we also have 2004 --- pipelines/datasets/br_denatran_frota/utils.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index 4ffa7bb16..9e7471dc1 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -363,7 +363,7 @@ def extraction_pre_2012( for file in compressed_files: filename = file.filename.split("/")[-1] if re.search("Tipo", filename, re.IGNORECASE) or re.search( - "Tipo UF", zip_file.split("/")[-1] + r"Tipo[-\s]UF", zip_file.split("/")[-1] ): new_filename = make_filename_2010_to_2012( "Tipo", year, filename, year_dir_name, month From af180923f9a4218b9e22b68b7a2813e92b3d2db8 Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 10 May 2023 01:59:31 -0300 Subject: [PATCH 124/265] Almost 2003 --- pipelines/datasets/br_denatran_frota/utils.py | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index 9e7471dc1..d06a81950 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -297,12 +297,15 @@ def make_filename_2010_to_2012( regex_to_search = rf"UF_([^\s\d]+\s*)_{str(year)[2:4]}" elif type_of_file == "Munic": basic_filename = MUNIC_TIPO_BASIC_FILENAME - regex_to_search = rf"Munic\.?\s*(.*?)\s*\.?{year}" + if year > 2003: + regex_to_search = rf"Munic\.?\s*(.*?)\s*\.?{year}" + else: + regex_to_search = rf"Mun\w*_(.*?)_{str(year)[2:4]}" else: raise ValueError match = re.search(regex_to_search, filename) if match: - if year <= 2005 and type_of_file == "Munic": + if (year == 2004 or year == 2005) and type_of_file == "Munic": month_value = int(match.group(1)) else: month_in_file = match.group(1).lower().replace(".", "") From 2d9fbf7eadde0903d19e27409148b8d587872fe1 Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 10 May 2023 02:09:09 -0300 Subject: [PATCH 125/265] Almost 2003 --- pipelines/datasets/br_denatran_frota/utils.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index d06a81950..c73fb8604 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -371,7 +371,7 @@ def extraction_pre_2012( new_filename = make_filename_2010_to_2012( "Tipo", year, filename, year_dir_name, month ) - elif re.search("Munic", filename, re.IGNORECASE): + elif re.search(r"Mun\w*", filename, re.IGNORECASE): new_filename = make_filename_2010_to_2012( "Munic", year, filename, year_dir_name, month ) From 8ac4dcfa2f0a13337b01a6a41fa57f74f54646db Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 10 May 2023 02:26:37 -0300 Subject: [PATCH 126/265] 2003 extraction works --- pipelines/datasets/br_denatran_frota/utils.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index c73fb8604..924e47785 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -294,7 +294,7 @@ def make_filename_2010_to_2012( if year > 2005: regex_to_search = r"UF\s+([^\s\d]+\s*)*([12]\d{3})" else: - regex_to_search = rf"UF_([^\s\d]+\s*)_{str(year)[2:4]}" + regex_to_search = rf"UF[_\s]?([^\s\d]+\s*)_{str(year)[2:4]}" elif type_of_file == "Munic": basic_filename = MUNIC_TIPO_BASIC_FILENAME if year > 2003: From e09bca853490d7d02602378f25898da8051d3166 Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 10 May 2023 02:33:02 -0300 Subject: [PATCH 127/265] Extraction task is fully functional --- pipelines/datasets/br_denatran_frota/handlers.py | 3 +-- pipelines/datasets/br_denatran_frota/tasks_test.py | 2 +- pipelines/datasets/br_denatran_frota/utils.py | 10 ++++------ 3 files changed, 6 insertions(+), 9 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 3b6354d1f..5250b3e3d 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -107,14 +107,13 @@ def crawl(month: int, year: int, temp_dir: str = ""): for aggregate_file in os.listdir(f"{year_dir_name}"): if aggregate_file != "dados_anuais.zip": extraction_pre_2012( - url, month, year, year_dir_name, os.path.join(year_dir_name, aggregate_file), ) else: - extraction_pre_2012(url, month, year, year_dir_name, filename) + extraction_pre_2012(month, year, year_dir_name, filename) def treat_uf_tipo(file) -> pl.DataFrame: diff --git a/pipelines/datasets/br_denatran_frota/tasks_test.py b/pipelines/datasets/br_denatran_frota/tasks_test.py index dde6af23d..8356407e8 100644 --- a/pipelines/datasets/br_denatran_frota/tasks_test.py +++ b/pipelines/datasets/br_denatran_frota/tasks_test.py @@ -30,7 +30,7 @@ def tearDown(self): shutil.rmtree(self.temp_dir.name) @parameterized.expand( - [(month, year) for year in range(2002, 2013) for month in range(1, 2)], + [(month, year) for year in range(2003, 2024) for month in range(1, 2)], name_func=custom_name_func, ) def test_download_post_2012(self, month, year): diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index 924e47785..e3a6565b0 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -286,7 +286,7 @@ def call_downloader(i: dict): generic_extractor(filename) -def make_filename_2010_to_2012( +def make_filename_pre_2012( type_of_file: str, year: int, filename: str, year_dir_name: str, month: int ): if type_of_file == "Tipo": @@ -355,9 +355,7 @@ def extract_links_post_2012(month: int, year: int, directory: str) -> list[dict] return valid_links -def extraction_pre_2012( - url: str, month: int, year: int, year_dir_name: str, zip_file: str -): +def extraction_pre_2012(month: int, year: int, year_dir_name: str, zip_file: str): # Aí depois eu preciso andar pelo zip: print("Bom dia") with ZipFile(zip_file, "r") as g: @@ -368,11 +366,11 @@ def extraction_pre_2012( if re.search("Tipo", filename, re.IGNORECASE) or re.search( r"Tipo[-\s]UF", zip_file.split("/")[-1] ): - new_filename = make_filename_2010_to_2012( + new_filename = make_filename_pre_2012( "Tipo", year, filename, year_dir_name, month ) elif re.search(r"Mun\w*", filename, re.IGNORECASE): - new_filename = make_filename_2010_to_2012( + new_filename = make_filename_pre_2012( "Munic", year, filename, year_dir_name, month ) if new_filename: From 8c50f077c10613e444fa9733880fd02b5b100243 Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 10 May 2023 03:00:37 -0300 Subject: [PATCH 128/265] Rename task for consistency --- pipelines/datasets/br_denatran_frota/flows.py | 6 ++-- pipelines/datasets/br_denatran_frota/tasks.py | 34 +++---------------- 2 files changed, 7 insertions(+), 33 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index 0c3926d12..8fcace90a 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -76,7 +76,7 @@ rename_current_flow_run_dataset_table, get_current_flow_labels, ) -from pipelines.datasets.br_denatran_frota.tasks import crawler, treat_uf_tipo +from pipelines.datasets.br_denatran_frota.tasks import crawl_task, treat_uf_tipo_task from pipelines.datasets.br_denatran_frota.constants import constants download_path = constants.DOWNLOAD_PATH.value @@ -105,11 +105,11 @@ # rename_flow_run = rename_current_flow_run_dataset_table( # prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id # ) - crawled = crawler( + crawled = crawl_task( month=2, year=2021, temp_dir=download_path ) # Download the desired files. uf_tipo_file = "/home/tamir/basedosdados/pipelines/pipelines/datasets/br_denatran_frota/tmp/input/files/2021/frota_por_uf_e_tipo_de_veículo_2-2021.xls" - df = treat_uf_tipo(file=uf_tipo_file, upstream_tasks=[crawled]) + df = treat_uf_tipo_task(file=uf_tipo_file, upstream_tasks=[crawled]) print("foi?") diff --git a/pipelines/datasets/br_denatran_frota/tasks.py b/pipelines/datasets/br_denatran_frota/tasks.py index 15972fd46..5ca214f8d 100644 --- a/pipelines/datasets/br_denatran_frota/tasks.py +++ b/pipelines/datasets/br_denatran_frota/tasks.py @@ -64,7 +64,7 @@ ) import pandas as pd import polars as pl -from pipelines.datasets.br_denatran_frota.handlers import crawl +from pipelines.datasets.br_denatran_frota.handlers import crawl, treat_uf_tipo MONTHS = constants.MONTHS.value DATASET = constants.DATASET.value @@ -73,39 +73,13 @@ @task() # noqa -def crawler(month: int, year: int, temp_dir: str = ""): +def crawl_task(month: int, year: int, temp_dir: str = ""): crawl(month, year, temp_dir) @task() -def treat_uf_tipo(file) -> pl.DataFrame: - filename = os.path.split(file)[1] - df = pd.read_excel(file) - new_df = change_df_header(df, guess_header(df)) - # This is ad hoc for UF_tipo. - new_df.rename( - columns={new_df.columns[0]: "sigla_uf"}, inplace=True - ) # Rename for ease of use. - new_df.sigla_uf = new_df.sigla_uf.str.strip() # Remove whitespace. - clean_df = new_df[new_df.sigla_uf.isin(DICT_UFS.values())].reset_index( - drop=True - ) # Now we get all the actual RELEVANT uf data. - month, year = get_year_month_from_filename(filename) - clean_pl_df = pl.from_pandas(clean_df).lazy() - verify_total(clean_pl_df.collect()) - # Add year and month - clean_pl_df = clean_pl_df.with_columns( - pl.lit(year, dtype=pl.Int64).alias("ano"), - pl.lit(month, dtype=pl.Int64).alias("mes"), - ) - clean_pl_df = clean_pl_df.select(pl.exclude("TOTAL")) - clean_pl_df = clean_pl_df.melt( - id_vars=["ano", "mes", "sigla_uf"], - variable_name="tipo_veiculo", - value_name="quantidade", - ) # Long format. - clean_pl_df = clean_pl_df.collect() - return clean_pl_df +def treat_uf_tipo_task(file) -> pl.DataFrame: + treat_uf_tipo(file) @task() From ea8d254ac0dc949d52a13567785d430392b28330 Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 10 May 2023 03:26:28 -0300 Subject: [PATCH 129/265] Begin testing of UF tipo treatment --- .../datasets/br_denatran_frota/handlers.py | 2 +- .../datasets/br_denatran_frota/tasks_test.py | 31 ++++++++++++++++++- 2 files changed, 31 insertions(+), 2 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 5250b3e3d..9404c6738 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -116,7 +116,7 @@ def crawl(month: int, year: int, temp_dir: str = ""): extraction_pre_2012(month, year, year_dir_name, filename) -def treat_uf_tipo(file) -> pl.DataFrame: +def treat_uf_tipo(file: str) -> pl.DataFrame: filename = os.path.split(file)[1] df = pd.read_excel(file) new_df = change_df_header(df, guess_header(df)) diff --git a/pipelines/datasets/br_denatran_frota/tasks_test.py b/pipelines/datasets/br_denatran_frota/tasks_test.py index 8356407e8..2d2ff7509 100644 --- a/pipelines/datasets/br_denatran_frota/tasks_test.py +++ b/pipelines/datasets/br_denatran_frota/tasks_test.py @@ -3,6 +3,7 @@ import shutil import tempfile import unittest +import re from parameterized import parameterized from pipelines.datasets.br_denatran_frota.handlers import crawl, treat_uf_tipo @@ -10,6 +11,8 @@ DATASET = constants.DATASET.value DOWNLOAD_PATH = constants.DOWNLOAD_PATH.value +MUNIC_TIPO_BASIC_FILENAME = constants.MUNIC_TIPO_BASIC_FILENAME.value +UF_TIPO_BASIC_FILENAME = constants.UF_TIPO_BASIC_FILENAME.value def custom_name_func(testcase_func, param_num, param): @@ -33,7 +36,7 @@ def tearDown(self): [(month, year) for year in range(2003, 2024) for month in range(1, 2)], name_func=custom_name_func, ) - def test_download_post_2012(self, month, year): + def test_extract_denatran_files(self, month, year): crawl(month, year, self.temp_dir.name) expected_files = { f"frota_por_uf_e_tipo_de_veiculo_{month}-{year}", @@ -44,5 +47,31 @@ def test_download_post_2012(self, month, year): self.assertTrue(expected_files.issubset(files)) +class TestTreatmentPostCrawl(unittest.TestCase): + def setUp(self): + self.temp_dir = tempfile.TemporaryDirectory( + dir=os.path.join(f"{DOWNLOAD_PATH}") + ) + + def tearDown(self): + print("Deleting temporary directory") + shutil.rmtree(self.temp_dir.name) + + @parameterized.expand( + [(month, year) for year in range(2020, 2023) for month in range(1, 2)], + name_func=custom_name_func, + ) + def test_treat_files_uf_tipo(self, month, year): + crawl(month, year, self.temp_dir.name) + directory_to_search = os.path.join(self.temp_dir.name, "files", f"{year}") + desired_files = [ + f + for f in os.listdir(directory_to_search) + if re.search(UF_TIPO_BASIC_FILENAME, f) is not None + ] + for file in desired_files: + treat_uf_tipo(os.path.join(directory_to_search, file)) + + if __name__ == "__main__": unittest.main() From cbed8807098a69e7bfd225f25bf1d94d76444e58 Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 10 May 2023 04:01:44 -0300 Subject: [PATCH 130/265] Treatment for UF tipo works up for 2009-> --- pipelines/datasets/br_denatran_frota/handlers.py | 6 +++++- .../datasets/br_denatran_frota/tasks_test.py | 16 ++++++++-------- 2 files changed, 13 insertions(+), 9 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 9404c6738..4b547597e 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -118,7 +118,11 @@ def crawl(month: int, year: int, temp_dir: str = ""): def treat_uf_tipo(file: str) -> pl.DataFrame: filename = os.path.split(file)[1] - df = pd.read_excel(file) + correct_sheet = [ + sheet for sheet in pd.ExcelFile(file).sheet_names if sheet != "Glossário" + ][0] + + df = pd.read_excel(file, sheet_name=correct_sheet) new_df = change_df_header(df, guess_header(df)) # This is ad hoc for UF_tipo. new_df.rename( diff --git a/pipelines/datasets/br_denatran_frota/tasks_test.py b/pipelines/datasets/br_denatran_frota/tasks_test.py index 2d2ff7509..021d33808 100644 --- a/pipelines/datasets/br_denatran_frota/tasks_test.py +++ b/pipelines/datasets/br_denatran_frota/tasks_test.py @@ -58,19 +58,19 @@ def tearDown(self): shutil.rmtree(self.temp_dir.name) @parameterized.expand( - [(month, year) for year in range(2020, 2023) for month in range(1, 2)], + [(month, year) for year in range(2003, 2024) for month in range(1, 2)], name_func=custom_name_func, ) def test_treat_files_uf_tipo(self, month, year): crawl(month, year, self.temp_dir.name) directory_to_search = os.path.join(self.temp_dir.name, "files", f"{year}") - desired_files = [ - f - for f in os.listdir(directory_to_search) - if re.search(UF_TIPO_BASIC_FILENAME, f) is not None - ] - for file in desired_files: - treat_uf_tipo(os.path.join(directory_to_search, file)) + for file in os.listdir(directory_to_search): + if re.search(UF_TIPO_BASIC_FILENAME, file) and file.split(".")[-1] in [ + "xls", + "xlsx", + ]: + treated_df = treat_uf_tipo(os.path.join(directory_to_search, file)) + self.assertEqual(len(treated_df), 21 * 27) if __name__ == "__main__": From 93c13708af5067ad006ac1387ff87dbb7231385a Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Fri, 12 May 2023 03:18:50 -0300 Subject: [PATCH 131/265] I have become Death, the destroyer of Worlds. --- .../datasets/br_denatran_frota/trash.ipynb | 441 ++++++++++++++++++ poetry.lock | 113 ++++- pyproject.toml | 1 + 3 files changed, 551 insertions(+), 4 deletions(-) create mode 100644 pipelines/datasets/br_denatran_frota/trash.ipynb diff --git a/pipelines/datasets/br_denatran_frota/trash.ipynb b/pipelines/datasets/br_denatran_frota/trash.ipynb new file mode 100644 index 000000000..a33af4cd6 --- /dev/null +++ b/pipelines/datasets/br_denatran_frota/trash.ipynb @@ -0,0 +1,441 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 54, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "import pandas as pd\n", + "import xlrd\n" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['Frota RegiΣes Tipo UF JAN2009.xls']" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "os.listdir('.')" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": {}, + "outputs": [ + { + "ename": "UnicodeDecodeError", + "evalue": "'utf-16-le' codec can't decode bytes in position 24-25: illegal encoding", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mUnicodeDecodeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[64], line 13\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[39m# Open the Excel file with xlrd\u001b[39;00m\n\u001b[1;32m 12\u001b[0m \u001b[39mif\u001b[39;00m file_like_object\u001b[39m.\u001b[39mgetvalue()\u001b[39m.\u001b[39mstartswith(xlrd\u001b[39m.\u001b[39mXLS_SIGNATURE):\n\u001b[0;32m---> 13\u001b[0m workbook \u001b[39m=\u001b[39m xlrd\u001b[39m.\u001b[39;49mopen_workbook(file_contents\u001b[39m=\u001b[39;49mfile_like_object\u001b[39m.\u001b[39;49mread(), encoding_override\u001b[39m=\u001b[39;49m\u001b[39m'\u001b[39;49m\u001b[39mlatin-1\u001b[39;49m\u001b[39m'\u001b[39;49m)\n\u001b[1;32m 14\u001b[0m \u001b[39m# ... rest of the code goes here\u001b[39;00m\n", + "File \u001b[0;32m~/.cache/pypoetry/virtualenvs/pipelines-RnwfPrZK-py3.10/lib/python3.10/site-packages/xlrd/__init__.py:172\u001b[0m, in \u001b[0;36mopen_workbook\u001b[0;34m(filename, logfile, verbosity, use_mmap, file_contents, encoding_override, formatting_info, on_demand, ragged_rows, ignore_workbook_corruption)\u001b[0m\n\u001b[1;32m 169\u001b[0m \u001b[39mif\u001b[39;00m file_format \u001b[39mand\u001b[39;00m file_format \u001b[39m!=\u001b[39m \u001b[39m'\u001b[39m\u001b[39mxls\u001b[39m\u001b[39m'\u001b[39m:\n\u001b[1;32m 170\u001b[0m \u001b[39mraise\u001b[39;00m XLRDError(FILE_FORMAT_DESCRIPTIONS[file_format]\u001b[39m+\u001b[39m\u001b[39m'\u001b[39m\u001b[39m; not supported\u001b[39m\u001b[39m'\u001b[39m)\n\u001b[0;32m--> 172\u001b[0m bk \u001b[39m=\u001b[39m open_workbook_xls(\n\u001b[1;32m 173\u001b[0m filename\u001b[39m=\u001b[39;49mfilename,\n\u001b[1;32m 174\u001b[0m logfile\u001b[39m=\u001b[39;49mlogfile,\n\u001b[1;32m 175\u001b[0m verbosity\u001b[39m=\u001b[39;49mverbosity,\n\u001b[1;32m 176\u001b[0m use_mmap\u001b[39m=\u001b[39;49muse_mmap,\n\u001b[1;32m 177\u001b[0m file_contents\u001b[39m=\u001b[39;49mfile_contents,\n\u001b[1;32m 178\u001b[0m encoding_override\u001b[39m=\u001b[39;49mencoding_override,\n\u001b[1;32m 179\u001b[0m formatting_info\u001b[39m=\u001b[39;49mformatting_info,\n\u001b[1;32m 180\u001b[0m on_demand\u001b[39m=\u001b[39;49mon_demand,\n\u001b[1;32m 181\u001b[0m ragged_rows\u001b[39m=\u001b[39;49mragged_rows,\n\u001b[1;32m 182\u001b[0m ignore_workbook_corruption\u001b[39m=\u001b[39;49mignore_workbook_corruption,\n\u001b[1;32m 183\u001b[0m )\n\u001b[1;32m 185\u001b[0m \u001b[39mreturn\u001b[39;00m bk\n", + "File \u001b[0;32m~/.cache/pypoetry/virtualenvs/pipelines-RnwfPrZK-py3.10/lib/python3.10/site-packages/xlrd/book.py:104\u001b[0m, in \u001b[0;36mopen_workbook_xls\u001b[0;34m(filename, logfile, verbosity, use_mmap, file_contents, encoding_override, formatting_info, on_demand, ragged_rows, ignore_workbook_corruption)\u001b[0m\n\u001b[1;32m 102\u001b[0m bk\u001b[39m.\u001b[39mon_demand \u001b[39m=\u001b[39m on_demand \u001b[39m=\u001b[39m \u001b[39mFalse\u001b[39;00m\n\u001b[1;32m 103\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[0;32m--> 104\u001b[0m bk\u001b[39m.\u001b[39;49mparse_globals()\n\u001b[1;32m 105\u001b[0m bk\u001b[39m.\u001b[39m_sheet_list \u001b[39m=\u001b[39m [\u001b[39mNone\u001b[39;00m \u001b[39mfor\u001b[39;00m sh \u001b[39min\u001b[39;00m bk\u001b[39m.\u001b[39m_sheet_names]\n\u001b[1;32m 106\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m on_demand:\n", + "File \u001b[0;32m~/.cache/pypoetry/virtualenvs/pipelines-RnwfPrZK-py3.10/lib/python3.10/site-packages/xlrd/book.py:1215\u001b[0m, in \u001b[0;36mBook.parse_globals\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1213\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mhandle_font(data)\n\u001b[1;32m 1214\u001b[0m \u001b[39melif\u001b[39;00m rc \u001b[39m==\u001b[39m XL_FORMAT: \u001b[39m# XL_FORMAT2 is BIFF <= 3.0, can't appear in globals\u001b[39;00m\n\u001b[0;32m-> 1215\u001b[0m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mhandle_format(data)\n\u001b[1;32m 1216\u001b[0m \u001b[39melif\u001b[39;00m rc \u001b[39m==\u001b[39m XL_XF:\n\u001b[1;32m 1217\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mhandle_xf(data)\n", + "File \u001b[0;32m~/.cache/pypoetry/virtualenvs/pipelines-RnwfPrZK-py3.10/lib/python3.10/site-packages/xlrd/formatting.py:541\u001b[0m, in \u001b[0;36mhandle_format\u001b[0;34m(self, data, rectype)\u001b[0m\n\u001b[1;32m 539\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mactualfmtcount \u001b[39m+\u001b[39m\u001b[39m=\u001b[39m \u001b[39m1\u001b[39m\n\u001b[1;32m 540\u001b[0m \u001b[39mif\u001b[39;00m bv \u001b[39m>\u001b[39m\u001b[39m=\u001b[39m \u001b[39m80\u001b[39m:\n\u001b[0;32m--> 541\u001b[0m unistrg \u001b[39m=\u001b[39m unpack_unicode(data, \u001b[39m2\u001b[39;49m)\n\u001b[1;32m 542\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m 543\u001b[0m unistrg \u001b[39m=\u001b[39m unpack_string(data, strpos, \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mencoding, lenlen\u001b[39m=\u001b[39m\u001b[39m1\u001b[39m)\n", + "File \u001b[0;32m~/.cache/pypoetry/virtualenvs/pipelines-RnwfPrZK-py3.10/lib/python3.10/site-packages/xlrd/biffh.py:284\u001b[0m, in \u001b[0;36munpack_unicode\u001b[0;34m(data, pos, lenlen)\u001b[0m\n\u001b[1;32m 282\u001b[0m rawstrg \u001b[39m=\u001b[39m data[pos:pos\u001b[39m+\u001b[39m\u001b[39m2\u001b[39m\u001b[39m*\u001b[39mnchars]\n\u001b[1;32m 283\u001b[0m \u001b[39m# if DEBUG: print \"nchars=%d pos=%d rawstrg=%r\" % (nchars, pos, rawstrg)\u001b[39;00m\n\u001b[0;32m--> 284\u001b[0m strg \u001b[39m=\u001b[39m unicode(rawstrg, \u001b[39m'\u001b[39;49m\u001b[39mutf_16_le\u001b[39;49m\u001b[39m'\u001b[39;49m)\n\u001b[1;32m 285\u001b[0m \u001b[39m# pos += 2*nchars\u001b[39;00m\n\u001b[1;32m 286\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m 287\u001b[0m \u001b[39m# Note: this is COMPRESSED (not ASCII!) encoding!!!\u001b[39;00m\n\u001b[1;32m 288\u001b[0m \u001b[39m# Merely returning the raw bytes would work OK 99.99% of the time\u001b[39;00m\n\u001b[1;32m 289\u001b[0m \u001b[39m# if the local codepage was cp1252 -- however this would rapidly go pear-shaped\u001b[39;00m\n\u001b[1;32m 290\u001b[0m \u001b[39m# for other codepages so we grit our Anglocentric teeth and return Unicode :-)\u001b[39;00m\n\u001b[1;32m 292\u001b[0m strg \u001b[39m=\u001b[39m unicode(data[pos:pos\u001b[39m+\u001b[39mnchars], \u001b[39m\"\u001b[39m\u001b[39mlatin_1\u001b[39m\u001b[39m\"\u001b[39m)\n", + "File \u001b[0;32m~/.cache/pypoetry/virtualenvs/pipelines-RnwfPrZK-py3.10/lib/python3.10/site-packages/xlrd/timemachine.py:31\u001b[0m, in \u001b[0;36m\u001b[0;34m(b, enc)\u001b[0m\n\u001b[1;32m 29\u001b[0m REPR \u001b[39m=\u001b[39m ascii\n\u001b[1;32m 30\u001b[0m xrange \u001b[39m=\u001b[39m \u001b[39mrange\u001b[39m\n\u001b[0;32m---> 31\u001b[0m unicode \u001b[39m=\u001b[39m \u001b[39mlambda\u001b[39;00m b, enc: b\u001b[39m.\u001b[39;49mdecode(enc)\n\u001b[1;32m 32\u001b[0m ensure_unicode \u001b[39m=\u001b[39m \u001b[39mlambda\u001b[39;00m s: s\n\u001b[1;32m 33\u001b[0m unichr \u001b[39m=\u001b[39m \u001b[39mchr\u001b[39m\n", + "File \u001b[0;32m/usr/lib/python3.10/encodings/utf_16_le.py:16\u001b[0m, in \u001b[0;36mdecode\u001b[0;34m(input, errors)\u001b[0m\n\u001b[1;32m 15\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mdecode\u001b[39m(\u001b[39minput\u001b[39m, errors\u001b[39m=\u001b[39m\u001b[39m'\u001b[39m\u001b[39mstrict\u001b[39m\u001b[39m'\u001b[39m):\n\u001b[0;32m---> 16\u001b[0m \u001b[39mreturn\u001b[39;00m codecs\u001b[39m.\u001b[39;49mutf_16_le_decode(\u001b[39minput\u001b[39;49m, errors, \u001b[39mTrue\u001b[39;49;00m)\n", + "\u001b[0;31mUnicodeDecodeError\u001b[0m: 'utf-16-le' codec can't decode bytes in position 24-25: illegal encoding" + ] + } + ], + "source": [ + "import io\n", + "import xlrd\n", + "\n", + "# Read the Excel file as bytes\n", + "with open('Frota RegiΣes Tipo UF JAN2009.xls', 'rb') as f:\n", + " contents = f.read()\n", + "\n", + "# Create a file-like object in memory\n", + "file_like_object = io.BytesIO(contents)\n", + "\n", + "# Open the Excel file with xlrd\n", + "if file_like_object.getvalue().startswith(xlrd.XLS_SIGNATURE):\n", + " workbook = xlrd.open_workbook(file_contents=file_like_object.read(), encoding_override='latin-1')\n", + " # ... rest of the code goes here\n" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "metadata": {}, + "outputs": [ + { + "ename": "UnicodeDecodeError", + "evalue": "'utf-16-le' codec can't decode bytes in position 24-25: illegal encoding", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mUnicodeDecodeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[56], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m xlrd\u001b[39m.\u001b[39;49mopen_workbook_xls(\u001b[39m'\u001b[39;49m\u001b[39mFrota RegiΣes Tipo UF JAN2009.xls\u001b[39;49m\u001b[39m'\u001b[39;49m, encoding_override\u001b[39m=\u001b[39;49m \u001b[39m'\u001b[39;49m\u001b[39mlatin-1\u001b[39;49m\u001b[39m'\u001b[39;49m)\n", + "File \u001b[0;32m~/.cache/pypoetry/virtualenvs/pipelines-RnwfPrZK-py3.10/lib/python3.10/site-packages/xlrd/book.py:104\u001b[0m, in \u001b[0;36mopen_workbook_xls\u001b[0;34m(filename, logfile, verbosity, use_mmap, file_contents, encoding_override, formatting_info, on_demand, ragged_rows, ignore_workbook_corruption)\u001b[0m\n\u001b[1;32m 102\u001b[0m bk\u001b[39m.\u001b[39mon_demand \u001b[39m=\u001b[39m on_demand \u001b[39m=\u001b[39m \u001b[39mFalse\u001b[39;00m\n\u001b[1;32m 103\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[0;32m--> 104\u001b[0m bk\u001b[39m.\u001b[39;49mparse_globals()\n\u001b[1;32m 105\u001b[0m bk\u001b[39m.\u001b[39m_sheet_list \u001b[39m=\u001b[39m [\u001b[39mNone\u001b[39;00m \u001b[39mfor\u001b[39;00m sh \u001b[39min\u001b[39;00m bk\u001b[39m.\u001b[39m_sheet_names]\n\u001b[1;32m 106\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m on_demand:\n", + "File \u001b[0;32m~/.cache/pypoetry/virtualenvs/pipelines-RnwfPrZK-py3.10/lib/python3.10/site-packages/xlrd/book.py:1215\u001b[0m, in \u001b[0;36mBook.parse_globals\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1213\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mhandle_font(data)\n\u001b[1;32m 1214\u001b[0m \u001b[39melif\u001b[39;00m rc \u001b[39m==\u001b[39m XL_FORMAT: \u001b[39m# XL_FORMAT2 is BIFF <= 3.0, can't appear in globals\u001b[39;00m\n\u001b[0;32m-> 1215\u001b[0m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mhandle_format(data)\n\u001b[1;32m 1216\u001b[0m \u001b[39melif\u001b[39;00m rc \u001b[39m==\u001b[39m XL_XF:\n\u001b[1;32m 1217\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mhandle_xf(data)\n", + "File \u001b[0;32m~/.cache/pypoetry/virtualenvs/pipelines-RnwfPrZK-py3.10/lib/python3.10/site-packages/xlrd/formatting.py:541\u001b[0m, in \u001b[0;36mhandle_format\u001b[0;34m(self, data, rectype)\u001b[0m\n\u001b[1;32m 539\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mactualfmtcount \u001b[39m+\u001b[39m\u001b[39m=\u001b[39m \u001b[39m1\u001b[39m\n\u001b[1;32m 540\u001b[0m \u001b[39mif\u001b[39;00m bv \u001b[39m>\u001b[39m\u001b[39m=\u001b[39m \u001b[39m80\u001b[39m:\n\u001b[0;32m--> 541\u001b[0m unistrg \u001b[39m=\u001b[39m unpack_unicode(data, \u001b[39m2\u001b[39;49m)\n\u001b[1;32m 542\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m 543\u001b[0m unistrg \u001b[39m=\u001b[39m unpack_string(data, strpos, \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mencoding, lenlen\u001b[39m=\u001b[39m\u001b[39m1\u001b[39m)\n", + "File \u001b[0;32m~/.cache/pypoetry/virtualenvs/pipelines-RnwfPrZK-py3.10/lib/python3.10/site-packages/xlrd/biffh.py:284\u001b[0m, in \u001b[0;36munpack_unicode\u001b[0;34m(data, pos, lenlen)\u001b[0m\n\u001b[1;32m 282\u001b[0m rawstrg \u001b[39m=\u001b[39m data[pos:pos\u001b[39m+\u001b[39m\u001b[39m2\u001b[39m\u001b[39m*\u001b[39mnchars]\n\u001b[1;32m 283\u001b[0m \u001b[39m# if DEBUG: print \"nchars=%d pos=%d rawstrg=%r\" % (nchars, pos, rawstrg)\u001b[39;00m\n\u001b[0;32m--> 284\u001b[0m strg \u001b[39m=\u001b[39m unicode(rawstrg, \u001b[39m'\u001b[39;49m\u001b[39mutf_16_le\u001b[39;49m\u001b[39m'\u001b[39;49m)\n\u001b[1;32m 285\u001b[0m \u001b[39m# pos += 2*nchars\u001b[39;00m\n\u001b[1;32m 286\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m 287\u001b[0m \u001b[39m# Note: this is COMPRESSED (not ASCII!) encoding!!!\u001b[39;00m\n\u001b[1;32m 288\u001b[0m \u001b[39m# Merely returning the raw bytes would work OK 99.99% of the time\u001b[39;00m\n\u001b[1;32m 289\u001b[0m \u001b[39m# if the local codepage was cp1252 -- however this would rapidly go pear-shaped\u001b[39;00m\n\u001b[1;32m 290\u001b[0m \u001b[39m# for other codepages so we grit our Anglocentric teeth and return Unicode :-)\u001b[39;00m\n\u001b[1;32m 292\u001b[0m strg \u001b[39m=\u001b[39m unicode(data[pos:pos\u001b[39m+\u001b[39mnchars], \u001b[39m\"\u001b[39m\u001b[39mlatin_1\u001b[39m\u001b[39m\"\u001b[39m)\n", + "File \u001b[0;32m~/.cache/pypoetry/virtualenvs/pipelines-RnwfPrZK-py3.10/lib/python3.10/site-packages/xlrd/timemachine.py:31\u001b[0m, in \u001b[0;36m\u001b[0;34m(b, enc)\u001b[0m\n\u001b[1;32m 29\u001b[0m REPR \u001b[39m=\u001b[39m ascii\n\u001b[1;32m 30\u001b[0m xrange \u001b[39m=\u001b[39m \u001b[39mrange\u001b[39m\n\u001b[0;32m---> 31\u001b[0m unicode \u001b[39m=\u001b[39m \u001b[39mlambda\u001b[39;00m b, enc: b\u001b[39m.\u001b[39;49mdecode(enc)\n\u001b[1;32m 32\u001b[0m ensure_unicode \u001b[39m=\u001b[39m \u001b[39mlambda\u001b[39;00m s: s\n\u001b[1;32m 33\u001b[0m unichr \u001b[39m=\u001b[39m \u001b[39mchr\u001b[39m\n", + "File \u001b[0;32m/usr/lib/python3.10/encodings/utf_16_le.py:16\u001b[0m, in \u001b[0;36mdecode\u001b[0;34m(input, errors)\u001b[0m\n\u001b[1;32m 15\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mdecode\u001b[39m(\u001b[39minput\u001b[39m, errors\u001b[39m=\u001b[39m\u001b[39m'\u001b[39m\u001b[39mstrict\u001b[39m\u001b[39m'\u001b[39m):\n\u001b[0;32m---> 16\u001b[0m \u001b[39mreturn\u001b[39;00m codecs\u001b[39m.\u001b[39;49mutf_16_le_decode(\u001b[39minput\u001b[39;49m, errors, \u001b[39mTrue\u001b[39;49;00m)\n", + "\u001b[0;31mUnicodeDecodeError\u001b[0m: 'utf-16-le' codec can't decode bytes in position 24-25: illegal encoding" + ] + } + ], + "source": [ + "xlrd.open_workbook_xls('Frota RegiΣes Tipo UF JAN2009.xls', encoding_override= 'latin-1')" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ÐÏ\u0011ࡱ\u001aá\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000>\u0000\u0003\u0000þÿ\t\u0000\u0006\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0001\u0000\u0000\u0000B\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0010\u0000\u0000þÿÿÿ\u0000\u0000\u0000\u0000þÿÿÿ\u0000\u0000\u0000\u0000A\u0000\u0000\u0000ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿ\u0010\u0000\u0000\u0006\u0005\u0000' Í\u0007ÉÀ\u0000\u0000\u0006\u0003\u0000\u0000á\u0000\u0002\u0000°\u0004Á\u0000\u0002\u0000\u0000\u0000â\u0000\u0000\u0000\\\u0000p\u0000\n", + 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à\u0000\u0014\u0000\u0000\u0000\u0001\u0000\u0012\u0000\u0000x\u0011\u0011@ @ \u0000\u0004* à\u0000\u0014\u0000\t\u0000\u0000\u0000\u0001\u0000\u001a\u0000\u0000x\u0011\u0011@ @ \u0000\u0004* à\u0000\u0014\u0000ª\u0000Q\u0001 \u0000\u0000,\u0011\u0011@ @ \u0000\u0000À à\u0000\u0014\u0000\u0000\u0000\u0001\u0000\u001a\u0000\u0000x\u0011\u0011@ @ \u0000\u0004* à\u0000\u0014\u0000\u0003\u0000\u0001\u0000 \u0000\u0000l\u0011\u0011@ @ \u0000\u0004* à\u0000\u0014\u0000\u0000\u0000\u0000\u0000\u0001\u0000 \u0000\u0000 \u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000À à\u0000\u0014\u0000\u0007\u0000ª\u0000Q\u0001+\u0000\u0000|\u0011\u0011@ @ \u0000 à\u0000\u0014\u0000\u0000\u0000\u0001\u0000\"\u0000\u0000x\u0011\u0011@ @ \u0000\u0004* à\u0000\u0014\u0000\u0000\u0000\u0000\u0000\u0001\u0000 \u0000\u0000 \u0000`\u0000\u0000\u0000 \u0000\u0000À à\u0000\u0014\u0000\u0000\u0000\u0003\u0000\u0001\u0000 \u0000\u0000$\u0000`\u0000\u0000\u0000 \u0000\u0000À à\u0000\u0014\u0000\u0000\u0000Æ\u0000A\u0001#\u0000\u00004\u0011\u0011@ @ \u0000\u0000À à\u0000\u0014\u0000\u0000\u0000\u0000\u0000\u0001\u0000\t\u0000\u0000\u0010\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000À à\u0000\u0014\u0000\u0001\u0000\u0000\u0000\u0001\u0000\u00008\u0011\u0011@ @ \u0000\u0000À à\u0000\u0014\u0000\u000b\u0000\u0000\u0000\u0001\u0000\u00008\u0011\u0011@ @ \u0000\u0000À à\u0000\u0014\u0000\f\u0000\u0000\u0000\u0001\u0000\u00008\u0011\u0011@ @ \u0000\u0000À à\u0000\u0014\u0000\u0000\u0000\u0001\u0000\u0010\u0000\u0000x\u0011\u0011@ @ \u0000\u0004* à\u0000\u0014\u0000\u0000\u0000\u0000\u0000\u0001\u0000\u0010\u0000\u0000\u0010\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000À à\u0000\u0014\u0000\u0000\u0000\u0001\u0000\t\u0000\u00008\u0011\u0011@ @ \u0000\u0000À à\u0000\u0014\u0000\n", + "\u0000\u0000\u0000\u0001\u0000\"\u0000\u0000x\u0011\u0011@ @ \u0000\u0004* à\u0000\u0014\u0000\u0000\u0000\u0001\u0000\u001a\u0000\u0000x\u0011\u0011@ @ \u0000\u0004* à\u0000\u0014\u0000\u0000\u0000\u0001\u0000 \u0000\u0000x\u0011\u0011@ @ \u0000\u0004* à\u0000\u0014\u0000\f\u0000\u0000\u0000\u0001\u0000 \u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000À à\u0000\u0014\u0000\u0000\u0000\u0000\u0000\u0001\u0000 \u0000\u0000@\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000À à\u0000\u0014\u0000\u0000\u0000\t\u0000A\u0001\"\u0000\u00000\u0011\u0011@ @ \u0000\u0000À à\u0000\u0014\u0000\u0000\u0000\u0002\u0000A\u0001#\u0000\u00004\u0011\u0011@ @ \u0000\u0000À “\u0002\u0004\u0000\u0010ÿ“\u0002\u0004\u0000\u0011€\tÿ“\u0002\u0004\u0000\u0012€\u0004ÿ“\u0002\u0004\u0000\u0013€\u0007ÿ“\u0002\u0004\u0000\u0000€\u0000ÿ“\u0002\u0004\u0000\u0014€\u0005ÿ“\u0002\u0004\u0000\u0015€\u0003ÿ“\u0002\u0004\u0000\u0016€\u0006ÿ`\u0001\u0002\u0000\u0000\u0000…\u0000\u0011\u0000ž\u001e\u0000\u0000\u0000\u0000\t\u0000Glossário…\u0000\u0010\u0000“)\u0000\u0000\u0000\u0000JAN_2009Œ\u0000\u0004\u00007\u00007\u0000®\u0001\u0004\u0000\u0002\u0000\u0001\u0004\u0017\u0000\u000e\u0000\u0002\u0000\u0000\u0000\u0001\u0000\u0001\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0018\u0000\u001b\u0000 \u0000\u0000\u0001\u000b\u0000\u0000\u0000\u0001\u0000\u0000\u0000\u0000\u0000\u0000\u0006;\u0001\u0000\u0000\u0000\u0017\u0000\u0000\u0000\u0002\u0000\u0018\u0000\u001b\u0000 \u0000\u0000\u0001\u000b\u0000\u0000\u0000\u0002\u0000\u0000\u0000\u0000\u0000\u0000\u0006=\u0000\u0000\u0000\u0000-\u0000\u0000\u0000\u0016\u0000Á\u0000Á\u0001\u0000\u0000\"¾\u0001\u0000ü\u0000A\n", + "€\u0000\u0000\u0000S\u0000\u0000\u0000'\u0000\u0000Grandes Regiões e\n", + "Unidades da Federação\u0005\u0000\u0000TOTAL\t\u0000\u0000AUTOMÓVEL\u0005\u0000\u0000BOND\u0000\u0000CAMINHÃO\u000f\u0000\u0000CAMINHÃO TRATOR\u000b\u0000\u0000CAMINHONETE\t\u0000\u0000CAMIONETA\u0011\u0000\u0000CHASSI PLATAFORMA\n", + "\u0000\u0000CICLOMOTOR\u000b\u0000\u0000MICROÔNIBUS\u000b\u0000\u0000MOTOCICLET\u0000\u0000MOTONETA\u0006\u0000\u0000ÔNIBUS\u000b\u0000\u0000QUADRICICLO\u0007\u0000\u0000REBOQUE\f\u0000\u0000SEMI-REBOQU\u0000\u0000SIDE-CAR\u0006\u0000\u0000OUTROS\u000e\u0000\u0000TRATOR ESTEIRA\f\u0000\u0000TRATOR RODA\u0000\u0000TRICICLO\n", + "\u0000\u0000UTILITÁRIO\u0005\u0000\u0000Acre \u0006\u0000\u0000Amapá\u0000\u0000Amazonas\u0005\u0000\u0000Pará \t\u0000\u0000Rondônia \u0007\u0000\u0000Roraima\t\u0000\u0000Tocantins\u0007\u0000\u0000Alagoas\u0005\u0000\u0000Bahia\u0005\u0000\u0000Ceará\t\u0000\u0000Maranhão\u0000\u0000Paraíba \u000b\u0000\u0000Pernambuco \u0005\u0000\u0000Piauí\u0014\u0000\u0000Rio Grande do Norte \u0007\u0000\u0000Sergipe\u000e\u0000\u0000Espírito Santo\n", + "\u0000\u0000Minas Gerais \u000e\u0000\u0000Rio de Janeiro\n", + "\u0000\u0000São Paulo \u0006\u0000\u0000Paraná\u0012\u0000\u0000Rio Grande do Sul \u000e\u0000\u0000Santa Catarina\u0010\u0000\u0000Distrito Federal\u0005\u0000\u0000Goiás\u000b\u0000\u0000Mato Grosso\u0012\u0000\u0000Mato Grosso do Sul°\u0000\u0000Fonte: Ministério das Cidades, Departamento Nacional de Trânsito - DENATRAN, Sistema Nacional de Registro de Veículos/RENAVAM, Sistema Nacional de Estatística de Trânsito/SINET\u0006\u0000\u0000Brasil\u0005\u0000\u0000Nort\u0000\u0000Nordeste\u0007\u0000\u0000Sudeste\u0003\u0000\u0000Sul\f\u0000\u0000Centro-Oestet\u0000\u0000veículo automotor destinado ao transporte de passageiros, com capacidade para até oito pessoas, exclusive o condutor7\u0000\u0000veículo de propulsão elétrica que se move sobre trilhosi\u0000\u0000veículo automotor destinado ao transporte de carga, com carroçaria, e peso bruto total superior a 3500 Kg9\u0000\u0000veículo automotor destinado a tracionar ou arrastar outroX\u0000\u0000veículo automotor destinado ao transporte de carga, com peso bruto total de até 3500 Kg.\u0000\u0000veículo inacabado, com equipamento que permita seu deslocamento em vias de rolamento, preparado para receber carroçaria de ônibus¿\u0000\u0000veículo de duas ou três rodas, provido de um motor de combustão interna cuja cilindrada não exceda a 50 cm3(3,05 polegadas cúbicas) e cuja velocidade máxima de fabricação não exceda a 50 Km/hO\u0000\u0000veículo automotor de transporte coletivo com capacidade para até 20 passageirosJ\u0000\u0000veículo auto-motor de duas rodas, dirigido por condutor em posição sentadaµ\u0000\u0000veículo automotor de transporte coletivo com capacidade para mais de 20 passageiros, ainda que, em virtude de adaptações com vista à maior comodidade destes, transporte número menorr\u0000\u0000veículo de estrutura mecânica igual às motocicletas, possuindo eixos dianteiro e traseiro, dotados de quatro rodas>\u0000\u0000veículo destinado a ser engatado atrás de um veículo automotorj\u0000\u0000veículo de um ou mais eixos que se apóia na sua unidade tratora ou é a ela ligado por meio de articulação.G\u0000\u0000carro ou caçamba provido de uma roda acoplada na lateral da motocicleta?\u0000\u0000Argumento que não se enquadra em nenhuma definição estabelecida+\u0000\u0000trator que se movimenta por meio de esteiraK\u0000\u0000trator que se movimenta sobre rodas,podendo ter chassi rígido ou articulado\\\u0000\u0000veículo rodoviário automotor de estrutura mecânica igual à motocicleta dotado de três rodas.U\u0000\u0000veículo misto caracterizado pela versatilidade do seu uso, inclusive fora da estrada.?\u0000\u0000Regiões Norte, Nordeste, Sul, Suldeste e Centro Oeste e Estados\u0013\u0000\u0000Termos e DefiniçõesR\u0000\u0000veículo automotor de duas rodas, com ou sem side-car, dirigido em posição montada.˜\u0000\u0000veículo automotor, misto, com quatro rodas, com carroçaria, destinado ao transporte simultâneo ou alternativo de pessoas e carga no mesmo compartimento.~\u0000\u0000Fonte: Ministério das Cidades, DENATRAN - Departamento Nacional de Trânsito, RENAVAM-Registro Nacional de Veículos Automotoresf\u0000\u0000Frota de veículos, por tipo e com placa, segundo as Grandes Regiões e Unidades da Federação - JAN/2009H\u0000\u0000Tabela 2 - Percentagem de veículos, por tipo segundo o Brasil - 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+ ] + } + ], + "source": [ + "with open('Frota RegiΣes Tipo UF JAN2009.xls', 'r', encoding=\"latin-1\") as f:\n", + " lines = f.read()\n", + "print(lines)" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [], + "source": [ + "import magic\n", + "\n", + "blob = open('Frota RegiΣes Tipo UF JAN2009.xls', 'rb').read()\n", + "m = magic.open(magic.MAGIC_MIME_ENCODING)\n", + "m.load()\n", + "encoding = m.buffer(blob) # \"utf-8\" \"us-ascii\" etc\n" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "None\n" + ] + } + ], + "source": [ + "print(encoding)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "pipelines-RnwfPrZK-py3.10", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": 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Python calling C code." -category = "dev" +category = "main" optional = false python-versions = "*" files = [ @@ -2860,7 +2889,7 @@ pyasn1 = ">=0.4.6,<0.5.0" name = "pycparser" version = "2.21" description = "C parser in Python" -category = "dev" +category = "main" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" files = [ @@ -3099,6 +3128,22 @@ files = [ {file = "pytz-2021.3.tar.gz", hash = "sha256:acad2d8b20a1af07d4e4c9d2e9285c5ed9104354062f275f3fcd88dcef4f1326"}, ] +[[package]] +name = "pytz-deprecation-shim" +version = "0.1.0.post0" +description = "Shims to make deprecation of pytz easier" +category = "main" +optional = false +python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7" +files = [ + {file = "pytz_deprecation_shim-0.1.0.post0-py2.py3-none-any.whl", hash = "sha256:8314c9692a636c8eb3bda879b9f119e350e93223ae83e70e80c31675a0fdc1a6"}, + {file = "pytz_deprecation_shim-0.1.0.post0.tar.gz", hash = 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+files = [ + {file = "tzdata-2023.3-py2.py3-none-any.whl", hash = "sha256:7e65763eef3120314099b6939b5546db7adce1e7d6f2e179e3df563c70511eda"}, + {file = "tzdata-2023.3.tar.gz", hash = "sha256:11ef1e08e54acb0d4f95bdb1be05da659673de4acbd21bf9c69e94cc5e907a3a"}, +] + +[[package]] +name = "tzlocal" +version = "4.3" +description = "tzinfo object for the local timezone" +category = "main" +optional = false +python-versions = ">=3.7" +files = [ + {file = "tzlocal-4.3-py3-none-any.whl", hash = "sha256:b44c4388f3d34f25862cfbb387578a4d70fec417649da694a132f628a23367e2"}, + {file = "tzlocal-4.3.tar.gz", hash = "sha256:3f21d09e1b2aa9f2dacca12da240ca37de3ba5237a93addfd6d593afe9073355"}, +] + +[package.dependencies] +"backports.zoneinfo" = {version = "*", markers = "python_version < \"3.9\""} +pytz-deprecation-shim = "*" +tzdata = {version = "*", markers = "platform_system == \"Windows\""} + +[package.extras] +devenv = ["black", "check-manifest", "flake8", "pyroma", "pytest (>=4.3)", "pytest-cov", "pytest-mock (>=3.3)", "zest.releaser"] + [[package]] name = "unidecode" version = "1.3.6" @@ -3968,4 +4073,4 @@ testing = ["big-O", "flake8 (<5)", "jaraco.functools", "jaraco.itertools", "more [metadata] lock-version = "2.0" python-versions = ">=3.8,<3.11" -content-hash = "fc4b6b6372ea9f8d243ee5515ed993bef5576343475a6459c4703d50079fff6c" +content-hash = "b71c70a89ed59dde03e0fb6cfbd9128e21edfa21a161f5a52c8fc5b28ed187f5" diff --git a/pyproject.toml b/pyproject.toml index 8e4d6a4b9..7997830df 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -107,6 +107,7 @@ xlrd = "^2.0.1" python-string-utils = "^1.0.0" pytest-cov = "^4.0.0" code2flow = "^2.5.1" +rpy2 = "^3.5.11" [tool.poetry.group.dev.dependencies] From 8dd26b9e862c181c8da36e1b0cfc24a35345592e Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Fri, 12 May 2023 03:21:28 -0300 Subject: [PATCH 132/265] I'm going to hell --- pipelines/datasets/br_denatran_frota/handlers.py | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 4b547597e..340e58960 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -118,6 +118,11 @@ def crawl(month: int, year: int, temp_dir: str = ""): def treat_uf_tipo(file: str) -> pl.DataFrame: filename = os.path.split(file)[1] + try: + pd.ExcelFile(file) + except UnicodeDecodeError: + #TODO: Aqui você invoca o capeta e chama o R pra ler e salvar isso como df. Isso é ridículo mas funcionou. + print(2) correct_sheet = [ sheet for sheet in pd.ExcelFile(file).sheet_names if sheet != "Glossário" ][0] From bb4f0bee8f7fc0434284d37c2000e57ba03cb9d0 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Fri, 12 May 2023 18:10:39 +0000 Subject: [PATCH 133/265] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- pipelines/datasets/br_denatran_frota/handlers.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 340e58960..3357387c2 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -121,7 +121,7 @@ def treat_uf_tipo(file: str) -> pl.DataFrame: try: pd.ExcelFile(file) except UnicodeDecodeError: - #TODO: Aqui você invoca o capeta e chama o R pra ler e salvar isso como df. Isso é ridículo mas funcionou. + # TODO: Aqui você invoca o capeta e chama o R pra ler e salvar isso como df. Isso é ridículo mas funcionou. print(2) correct_sheet = [ sheet for sheet in pd.ExcelFile(file).sheet_names if sheet != "Glossário" From e2ec8596cd9a7c56b9e41f471f5522afd40db0a4 Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 14 May 2023 22:47:45 -0300 Subject: [PATCH 134/265] Trying to unleash R inside Python --- .../datasets/br_denatran_frota/teste.xls | Bin 0 -> 34816 bytes .../datasets/br_denatran_frota/trash.ipynb | 206 +++++++++++++----- pipelines/datasets/br_denatran_frota/utils.py | 26 +++ 3 files changed, 180 insertions(+), 52 deletions(-) create mode 100644 pipelines/datasets/br_denatran_frota/teste.xls diff --git a/pipelines/datasets/br_denatran_frota/teste.xls b/pipelines/datasets/br_denatran_frota/teste.xls new file mode 100644 index 0000000000000000000000000000000000000000..250f4945a573648f6cd6b9bd8b2eef77ac2f45ee GIT binary patch literal 34816 zcmeHw34B!5_5Yd4LINR^0Es9<9wA~N0V1HHh)e1(`-<7xSvrE#R!zDvL>d%$zB)kXV8Yf;Lp!fGP>U>rs4Aju` 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verbosity, use_mmap, file_contents, encoding_override, formatting_info, on_demand, ragged_rows, ignore_workbook_corruption)\u001b[0m\n\u001b[1;32m 169\u001b[0m \u001b[39mif\u001b[39;00m file_format \u001b[39mand\u001b[39;00m file_format \u001b[39m!=\u001b[39m \u001b[39m'\u001b[39m\u001b[39mxls\u001b[39m\u001b[39m'\u001b[39m:\n\u001b[1;32m 170\u001b[0m \u001b[39mraise\u001b[39;00m XLRDError(FILE_FORMAT_DESCRIPTIONS[file_format]\u001b[39m+\u001b[39m\u001b[39m'\u001b[39m\u001b[39m; not supported\u001b[39m\u001b[39m'\u001b[39m)\n\u001b[0;32m--> 172\u001b[0m bk \u001b[39m=\u001b[39m open_workbook_xls(\n\u001b[1;32m 173\u001b[0m filename\u001b[39m=\u001b[39;49mfilename,\n\u001b[1;32m 174\u001b[0m logfile\u001b[39m=\u001b[39;49mlogfile,\n\u001b[1;32m 175\u001b[0m verbosity\u001b[39m=\u001b[39;49mverbosity,\n\u001b[1;32m 176\u001b[0m use_mmap\u001b[39m=\u001b[39;49muse_mmap,\n\u001b[1;32m 177\u001b[0m file_contents\u001b[39m=\u001b[39;49mfile_contents,\n\u001b[1;32m 178\u001b[0m encoding_override\u001b[39m=\u001b[39;49mencoding_override,\n\u001b[1;32m 179\u001b[0m formatting_info\u001b[39m=\u001b[39;49mformatting_info,\n\u001b[1;32m 180\u001b[0m on_demand\u001b[39m=\u001b[39;49mon_demand,\n\u001b[1;32m 181\u001b[0m ragged_rows\u001b[39m=\u001b[39;49mragged_rows,\n\u001b[1;32m 182\u001b[0m ignore_workbook_corruption\u001b[39m=\u001b[39;49mignore_workbook_corruption,\n\u001b[1;32m 183\u001b[0m )\n\u001b[1;32m 185\u001b[0m \u001b[39mreturn\u001b[39;00m bk\n", - "File \u001b[0;32m~/.cache/pypoetry/virtualenvs/pipelines-RnwfPrZK-py3.10/lib/python3.10/site-packages/xlrd/book.py:104\u001b[0m, in \u001b[0;36mopen_workbook_xls\u001b[0;34m(filename, logfile, verbosity, use_mmap, file_contents, encoding_override, formatting_info, on_demand, ragged_rows, ignore_workbook_corruption)\u001b[0m\n\u001b[1;32m 102\u001b[0m bk\u001b[39m.\u001b[39mon_demand \u001b[39m=\u001b[39m on_demand \u001b[39m=\u001b[39m \u001b[39mFalse\u001b[39;00m\n\u001b[1;32m 103\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[0;32m--> 104\u001b[0m bk\u001b[39m.\u001b[39;49mparse_globals()\n\u001b[1;32m 105\u001b[0m bk\u001b[39m.\u001b[39m_sheet_list \u001b[39m=\u001b[39m [\u001b[39mNone\u001b[39;00m \u001b[39mfor\u001b[39;00m sh \u001b[39min\u001b[39;00m bk\u001b[39m.\u001b[39m_sheet_names]\n\u001b[1;32m 106\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m on_demand:\n", - "File \u001b[0;32m~/.cache/pypoetry/virtualenvs/pipelines-RnwfPrZK-py3.10/lib/python3.10/site-packages/xlrd/book.py:1215\u001b[0m, in \u001b[0;36mBook.parse_globals\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1213\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mhandle_font(data)\n\u001b[1;32m 1214\u001b[0m \u001b[39melif\u001b[39;00m rc \u001b[39m==\u001b[39m XL_FORMAT: \u001b[39m# XL_FORMAT2 is BIFF <= 3.0, can't appear in globals\u001b[39;00m\n\u001b[0;32m-> 1215\u001b[0m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mhandle_format(data)\n\u001b[1;32m 1216\u001b[0m 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"File \u001b[0;32m~/.cache/pypoetry/virtualenvs/pipelines-RnwfPrZK-py3.10/lib/python3.10/site-packages/xlrd/biffh.py:284\u001b[0m, in \u001b[0;36munpack_unicode\u001b[0;34m(data, pos, lenlen)\u001b[0m\n\u001b[1;32m 282\u001b[0m rawstrg \u001b[39m=\u001b[39m data[pos:pos\u001b[39m+\u001b[39m\u001b[39m2\u001b[39m\u001b[39m*\u001b[39mnchars]\n\u001b[1;32m 283\u001b[0m \u001b[39m# if DEBUG: print \"nchars=%d pos=%d rawstrg=%r\" % (nchars, pos, rawstrg)\u001b[39;00m\n\u001b[0;32m--> 284\u001b[0m strg \u001b[39m=\u001b[39m unicode(rawstrg, \u001b[39m'\u001b[39;49m\u001b[39mutf_16_le\u001b[39;49m\u001b[39m'\u001b[39;49m)\n\u001b[1;32m 285\u001b[0m \u001b[39m# pos += 2*nchars\u001b[39;00m\n\u001b[1;32m 286\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m 287\u001b[0m \u001b[39m# Note: this is COMPRESSED (not ASCII!) encoding!!!\u001b[39;00m\n\u001b[1;32m 288\u001b[0m \u001b[39m# Merely returning the raw bytes would work OK 99.99% of the time\u001b[39;00m\n\u001b[1;32m 289\u001b[0m \u001b[39m# if the local codepage was cp1252 -- however this would rapidly go pear-shaped\u001b[39;00m\n\u001b[1;32m 290\u001b[0m \u001b[39m# for other codepages so we grit our Anglocentric teeth and return Unicode :-)\u001b[39;00m\n\u001b[1;32m 292\u001b[0m strg \u001b[39m=\u001b[39m unicode(data[pos:pos\u001b[39m+\u001b[39mnchars], \u001b[39m\"\u001b[39m\u001b[39mlatin_1\u001b[39m\u001b[39m\"\u001b[39m)\n", - "File \u001b[0;32m~/.cache/pypoetry/virtualenvs/pipelines-RnwfPrZK-py3.10/lib/python3.10/site-packages/xlrd/timemachine.py:31\u001b[0m, in \u001b[0;36m\u001b[0;34m(b, enc)\u001b[0m\n\u001b[1;32m 29\u001b[0m REPR \u001b[39m=\u001b[39m ascii\n\u001b[1;32m 30\u001b[0m xrange \u001b[39m=\u001b[39m \u001b[39mrange\u001b[39m\n\u001b[0;32m---> 31\u001b[0m unicode \u001b[39m=\u001b[39m \u001b[39mlambda\u001b[39;00m b, enc: b\u001b[39m.\u001b[39;49mdecode(enc)\n\u001b[1;32m 32\u001b[0m ensure_unicode \u001b[39m=\u001b[39m \u001b[39mlambda\u001b[39;00m s: s\n\u001b[1;32m 33\u001b[0m unichr \u001b[39m=\u001b[39m \u001b[39mchr\u001b[39m\n", - "File \u001b[0;32m/usr/lib/python3.10/encodings/utf_16_le.py:16\u001b[0m, in \u001b[0;36mdecode\u001b[0;34m(input, errors)\u001b[0m\n\u001b[1;32m 15\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mdecode\u001b[39m(\u001b[39minput\u001b[39m, errors\u001b[39m=\u001b[39m\u001b[39m'\u001b[39m\u001b[39mstrict\u001b[39m\u001b[39m'\u001b[39m):\n\u001b[0;32m---> 16\u001b[0m \u001b[39mreturn\u001b[39;00m codecs\u001b[39m.\u001b[39;49mutf_16_le_decode(\u001b[39minput\u001b[39;49m, errors, \u001b[39mTrue\u001b[39;49;00m)\n", - "\u001b[0;31mUnicodeDecodeError\u001b[0m: 'utf-16-le' codec can't decode bytes in position 24-25: illegal encoding" - ] - } - ], + "outputs": [], "source": [ - "import io\n", - "import xlrd\n", - "\n", - "# Read the Excel file as bytes\n", - "with open('Frota RegiΣes Tipo UF JAN2009.xls', 'rb') as f:\n", - " contents = f.read()\n", - "\n", - "# Create a file-like object in memory\n", - "file_like_object = io.BytesIO(contents)\n", - "\n", - "# Open the Excel file with xlrd\n", - "if file_like_object.getvalue().startswith(xlrd.XLS_SIGNATURE):\n", - " workbook = xlrd.open_workbook(file_contents=file_like_object.read(), encoding_override='latin-1')\n", - " # ... rest of the code goes here\n" + "file_to_read = \"/home/tamir/basedosdados/pipelines/pipelines/datasets/br_denatran_frota/teste.xls\"" ] }, { "cell_type": "code", - "execution_count": 56, + "execution_count": 5, "metadata": {}, "outputs": [ { - "ename": "UnicodeDecodeError", - "evalue": "'utf-16-le' codec can't decode bytes in position 24-25: illegal encoding", + "name": "stderr", + "output_type": "stream", + "text": [ + "R[write to console]: Installing package into ‘/home/tamir/R/x86_64-pc-linux-gnu-library/4.1’\n", + "(as ‘lib’ is unspecified)\n", + "\n", + "R[write to console]: trying URL 'https://cloud.r-project.org/src/contrib/readxl_1.4.2.tar.gz'\n", + "\n", + "R[write to console]: Content type 'application/x-gzip'\n", + 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-I'/home/tamir/R/x86_64-pc-linux-gnu-library/4.1/cpp11/include' -I'/home/tamir/R/x86_64-pc-linux-gnu-library/4.1/progress/include' -fvisibility=hidden -fpic -g -O2 -ffile-prefix-map=/build/r-base-4A2Reg/r-base-4.1.2=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -g -c cpp11.cpp -o cpp11.o\n", + "g++ -std=gnu++14 -I\"/usr/share/R/include\" -DNDEBUG -Iunix -I. -I'/home/tamir/R/x86_64-pc-linux-gnu-library/4.1/cpp11/include' -I'/home/tamir/R/x86_64-pc-linux-gnu-library/4.1/progress/include' -fvisibility=hidden -fpic -g -O2 -ffile-prefix-map=/build/r-base-4A2Reg/r-base-4.1.2=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -g -c XlsWorkBook.cpp -o XlsWorkBook.o\n", + "g++ -std=gnu++14 -I\"/usr/share/R/include\" -DNDEBUG -Iunix -I. -I'/home/tamir/R/x86_64-pc-linux-gnu-library/4.1/cpp11/include' -I'/home/tamir/R/x86_64-pc-linux-gnu-library/4.1/progress/include' -fvisibility=hidden -fpic -g -O2 -ffile-prefix-map=/build/r-base-4A2Reg/r-base-4.1.2=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -g -c XlsxWorkBook.cpp -o XlsxWorkBook.o\n", + "g++ -std=gnu++14 -I\"/usr/share/R/include\" -DNDEBUG -Iunix -I. -I'/home/tamir/R/x86_64-pc-linux-gnu-library/4.1/cpp11/include' -I'/home/tamir/R/x86_64-pc-linux-gnu-library/4.1/progress/include' -fvisibility=hidden -fpic -g -O2 -ffile-prefix-map=/build/r-base-4A2Reg/r-base-4.1.2=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -g -c zip.cpp -o zip.o\n", + "g++ -std=gnu++14 -I\"/usr/share/R/include\" -DNDEBUG -Iunix -I. -I'/home/tamir/R/x86_64-pc-linux-gnu-library/4.1/cpp11/include' -I'/home/tamir/R/x86_64-pc-linux-gnu-library/4.1/progress/include' -fvisibility=hidden -fpic -g -O2 -ffile-prefix-map=/build/r-base-4A2Reg/r-base-4.1.2=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -g -c Read.cpp -o Read.o\n", + "gcc -I\"/usr/share/R/include\" -DNDEBUG -Iunix -I. -I'/home/tamir/R/x86_64-pc-linux-gnu-library/4.1/cpp11/include' -I'/home/tamir/R/x86_64-pc-linux-gnu-library/4.1/progress/include' -fvisibility=hidden -fpic -g -O2 -ffile-prefix-map=/build/r-base-4A2Reg/r-base-4.1.2=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -g -c cran.c -o cran.o\n", + "gcc -I\"/usr/share/R/include\" -DNDEBUG -Iunix -I. -I'/home/tamir/R/x86_64-pc-linux-gnu-library/4.1/cpp11/include' -I'/home/tamir/R/x86_64-pc-linux-gnu-library/4.1/progress/include' -fvisibility=hidden -fpic -g -O2 -ffile-prefix-map=/build/r-base-4A2Reg/r-base-4.1.2=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -g -c libxls/xlstool.c -o libxls/xlstool.o\n", + "gcc -I\"/usr/share/R/include\" -DNDEBUG -Iunix -I. -I'/home/tamir/R/x86_64-pc-linux-gnu-library/4.1/cpp11/include' -I'/home/tamir/R/x86_64-pc-linux-gnu-library/4.1/progress/include' -fvisibility=hidden -fpic -g -O2 -ffile-prefix-map=/build/r-base-4A2Reg/r-base-4.1.2=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -g -c libxls/endian.c -o libxls/endian.o\n", + "gcc -I\"/usr/share/R/include\" -DNDEBUG -Iunix -I. -I'/home/tamir/R/x86_64-pc-linux-gnu-library/4.1/cpp11/include' -I'/home/tamir/R/x86_64-pc-linux-gnu-library/4.1/progress/include' -fvisibility=hidden -fpic -g -O2 -ffile-prefix-map=/build/r-base-4A2Reg/r-base-4.1.2=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -g -c libxls/ole.c -o libxls/ole.o\n", + "gcc -I\"/usr/share/R/include\" -DNDEBUG -Iunix -I. -I'/home/tamir/R/x86_64-pc-linux-gnu-library/4.1/cpp11/include' -I'/home/tamir/R/x86_64-pc-linux-gnu-library/4.1/progress/include' -fvisibility=hidden -fpic -g -O2 -ffile-prefix-map=/build/r-base-4A2Reg/r-base-4.1.2=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -g -c libxls/xls.c -o libxls/xls.o\n", + "gcc -I\"/usr/share/R/include\" -DNDEBUG -Iunix -I. -I'/home/tamir/R/x86_64-pc-linux-gnu-library/4.1/cpp11/include' -I'/home/tamir/R/x86_64-pc-linux-gnu-library/4.1/progress/include' -fvisibility=hidden -fpic -g -O2 -ffile-prefix-map=/build/r-base-4A2Reg/r-base-4.1.2=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -g -c libxls/locale.c -o libxls/locale.o\n", + "g++ -std=gnu++14 -shared -L/usr/lib/R/lib -Wl,-Bsymbolic-functions -flto=auto -ffat-lto-objects -flto=auto -Wl,-z,relro -o readxl.so cpp11.o XlsWorkBook.o XlsxWorkBook.o zip.o Read.o cran.o libxls/xlstool.o libxls/endian.o libxls/ole.o libxls/xls.o libxls/locale.o -L/usr/lib/R/lib -lR\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "installing to /home/tamir/R/x86_64-pc-linux-gnu-library/4.1/00LOCK-readxl/00new/readxl/libs\n", + "** R\n", + "** inst\n", + "** byte-compile and prepare package for lazy loading\n", + "** help\n", + "*** installing help indices\n", + "*** copying figures\n", + "** building package indices\n", + "** installing vignettes\n", + "** testing if installed package can be loaded from temporary location\n", + "** checking absolute paths in shared objects and dynamic libraries\n", + "** testing if installed package can be loaded from final location\n", + "** testing if installed package keeps a record of temporary installation path\n", + "* DONE (readxl)\n", + "R[write to console]: \n", + "\n", + "R[write to console]: \n", + "R[write to console]: The downloaded source packages are in\n", + "\t‘/tmp/RtmpTvOyoT/downloaded_packages’\n", + "R[write to console]: \n", + "R[write to console]: \n", + "\n", + "R[write to console]: Error: `path` does not exist: ‘pipelines/datasets/br_denatran_frota/teste.xls’\n", + "\n", + "R[write to console]: In addition: \n", + "R[write to console]: Warning messages:\n", + "\n", + "R[write to console]: 1: \n", + "R[write to console]: In (function (package, help, pos = 2, lib.loc = NULL, character.only = FALSE, :\n", + "R[write to console]: \n", + " \n", + "R[write to console]: libraries ‘/usr/local/lib/R/site-library’, ‘/usr/lib/R/site-library’ contain no packages\n", + "\n", + "R[write to console]: 2: \n", + "R[write to console]: In (function (package, help, pos = 2, lib.loc = NULL, character.only = FALSE, :\n", + "R[write to console]: \n", + " \n", + "R[write to console]: libraries ‘/usr/local/lib/R/site-library’, ‘/usr/lib/R/site-library’ contain no packages\n", + "\n" + ] + }, + { + "ename": "RRuntimeError", + "evalue": "Error: `path` does not exist: ‘pipelines/datasets/br_denatran_frota/teste.xls’\n", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mUnicodeDecodeError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[56], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m xlrd\u001b[39m.\u001b[39;49mopen_workbook_xls(\u001b[39m'\u001b[39;49m\u001b[39mFrota RegiΣes Tipo UF JAN2009.xls\u001b[39;49m\u001b[39m'\u001b[39;49m, encoding_override\u001b[39m=\u001b[39;49m \u001b[39m'\u001b[39;49m\u001b[39mlatin-1\u001b[39;49m\u001b[39m'\u001b[39;49m)\n", - "File \u001b[0;32m~/.cache/pypoetry/virtualenvs/pipelines-RnwfPrZK-py3.10/lib/python3.10/site-packages/xlrd/book.py:104\u001b[0m, in \u001b[0;36mopen_workbook_xls\u001b[0;34m(filename, logfile, verbosity, use_mmap, file_contents, encoding_override, formatting_info, on_demand, ragged_rows, ignore_workbook_corruption)\u001b[0m\n\u001b[1;32m 102\u001b[0m bk\u001b[39m.\u001b[39mon_demand \u001b[39m=\u001b[39m on_demand \u001b[39m=\u001b[39m \u001b[39mFalse\u001b[39;00m\n\u001b[1;32m 103\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[0;32m--> 104\u001b[0m bk\u001b[39m.\u001b[39;49mparse_globals()\n\u001b[1;32m 105\u001b[0m bk\u001b[39m.\u001b[39m_sheet_list \u001b[39m=\u001b[39m [\u001b[39mNone\u001b[39;00m \u001b[39mfor\u001b[39;00m sh \u001b[39min\u001b[39;00m bk\u001b[39m.\u001b[39m_sheet_names]\n\u001b[1;32m 106\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m on_demand:\n", - "File \u001b[0;32m~/.cache/pypoetry/virtualenvs/pipelines-RnwfPrZK-py3.10/lib/python3.10/site-packages/xlrd/book.py:1215\u001b[0m, in \u001b[0;36mBook.parse_globals\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1213\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mhandle_font(data)\n\u001b[1;32m 1214\u001b[0m \u001b[39melif\u001b[39;00m rc \u001b[39m==\u001b[39m XL_FORMAT: \u001b[39m# XL_FORMAT2 is BIFF <= 3.0, can't appear in globals\u001b[39;00m\n\u001b[0;32m-> 1215\u001b[0m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mhandle_format(data)\n\u001b[1;32m 1216\u001b[0m \u001b[39melif\u001b[39;00m rc \u001b[39m==\u001b[39m XL_XF:\n\u001b[1;32m 1217\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mhandle_xf(data)\n", - "File \u001b[0;32m~/.cache/pypoetry/virtualenvs/pipelines-RnwfPrZK-py3.10/lib/python3.10/site-packages/xlrd/formatting.py:541\u001b[0m, in \u001b[0;36mhandle_format\u001b[0;34m(self, data, rectype)\u001b[0m\n\u001b[1;32m 539\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mactualfmtcount \u001b[39m+\u001b[39m\u001b[39m=\u001b[39m \u001b[39m1\u001b[39m\n\u001b[1;32m 540\u001b[0m \u001b[39mif\u001b[39;00m bv \u001b[39m>\u001b[39m\u001b[39m=\u001b[39m \u001b[39m80\u001b[39m:\n\u001b[0;32m--> 541\u001b[0m unistrg \u001b[39m=\u001b[39m unpack_unicode(data, \u001b[39m2\u001b[39;49m)\n\u001b[1;32m 542\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m 543\u001b[0m unistrg \u001b[39m=\u001b[39m unpack_string(data, strpos, \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mencoding, lenlen\u001b[39m=\u001b[39m\u001b[39m1\u001b[39m)\n", - "File \u001b[0;32m~/.cache/pypoetry/virtualenvs/pipelines-RnwfPrZK-py3.10/lib/python3.10/site-packages/xlrd/biffh.py:284\u001b[0m, in \u001b[0;36munpack_unicode\u001b[0;34m(data, pos, lenlen)\u001b[0m\n\u001b[1;32m 282\u001b[0m rawstrg \u001b[39m=\u001b[39m data[pos:pos\u001b[39m+\u001b[39m\u001b[39m2\u001b[39m\u001b[39m*\u001b[39mnchars]\n\u001b[1;32m 283\u001b[0m \u001b[39m# if DEBUG: print \"nchars=%d pos=%d rawstrg=%r\" % (nchars, pos, rawstrg)\u001b[39;00m\n\u001b[0;32m--> 284\u001b[0m strg \u001b[39m=\u001b[39m unicode(rawstrg, \u001b[39m'\u001b[39;49m\u001b[39mutf_16_le\u001b[39;49m\u001b[39m'\u001b[39;49m)\n\u001b[1;32m 285\u001b[0m \u001b[39m# pos += 2*nchars\u001b[39;00m\n\u001b[1;32m 286\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m 287\u001b[0m \u001b[39m# Note: this is COMPRESSED (not ASCII!) encoding!!!\u001b[39;00m\n\u001b[1;32m 288\u001b[0m \u001b[39m# Merely returning the raw bytes would work OK 99.99% of the time\u001b[39;00m\n\u001b[1;32m 289\u001b[0m \u001b[39m# if the local codepage was cp1252 -- however this would rapidly go pear-shaped\u001b[39;00m\n\u001b[1;32m 290\u001b[0m \u001b[39m# for other codepages so we grit our Anglocentric teeth and return Unicode :-)\u001b[39;00m\n\u001b[1;32m 292\u001b[0m strg \u001b[39m=\u001b[39m unicode(data[pos:pos\u001b[39m+\u001b[39mnchars], \u001b[39m\"\u001b[39m\u001b[39mlatin_1\u001b[39m\u001b[39m\"\u001b[39m)\n", - "File \u001b[0;32m~/.cache/pypoetry/virtualenvs/pipelines-RnwfPrZK-py3.10/lib/python3.10/site-packages/xlrd/timemachine.py:31\u001b[0m, in \u001b[0;36m\u001b[0;34m(b, enc)\u001b[0m\n\u001b[1;32m 29\u001b[0m REPR \u001b[39m=\u001b[39m ascii\n\u001b[1;32m 30\u001b[0m xrange \u001b[39m=\u001b[39m \u001b[39mrange\u001b[39m\n\u001b[0;32m---> 31\u001b[0m unicode \u001b[39m=\u001b[39m \u001b[39mlambda\u001b[39;00m b, enc: b\u001b[39m.\u001b[39;49mdecode(enc)\n\u001b[1;32m 32\u001b[0m ensure_unicode \u001b[39m=\u001b[39m \u001b[39mlambda\u001b[39;00m s: s\n\u001b[1;32m 33\u001b[0m unichr \u001b[39m=\u001b[39m \u001b[39mchr\u001b[39m\n", - "File \u001b[0;32m/usr/lib/python3.10/encodings/utf_16_le.py:16\u001b[0m, in \u001b[0;36mdecode\u001b[0;34m(input, errors)\u001b[0m\n\u001b[1;32m 15\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mdecode\u001b[39m(\u001b[39minput\u001b[39m, errors\u001b[39m=\u001b[39m\u001b[39m'\u001b[39m\u001b[39mstrict\u001b[39m\u001b[39m'\u001b[39m):\n\u001b[0;32m---> 16\u001b[0m \u001b[39mreturn\u001b[39;00m codecs\u001b[39m.\u001b[39;49mutf_16_le_decode(\u001b[39minput\u001b[39;49m, errors, \u001b[39mTrue\u001b[39;49;00m)\n", - "\u001b[0;31mUnicodeDecodeError\u001b[0m: 'utf-16-le' codec can't decode bytes in position 24-25: illegal encoding" + "\u001b[0;31mRRuntimeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[5], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m call_r_to_read_file(file_to_read)\n", + "File \u001b[0;32m~/basedosdados/pipelines/pipelines/datasets/br_denatran_frota/utils.py:408\u001b[0m, in \u001b[0;36mcall_r_to_read_file\u001b[0;34m(file)\u001b[0m\n\u001b[1;32m 405\u001b[0m readxl \u001b[39m=\u001b[39m rpackages\u001b[39m.\u001b[39mimportr(\u001b[39m\"\u001b[39m\u001b[39mreadxl\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[1;32m 407\u001b[0m \u001b[39m# Read the Excel file\u001b[39;00m\n\u001b[0;32m--> 408\u001b[0m robjects\u001b[39m.\u001b[39mr(\n\u001b[1;32m 409\u001b[0m \u001b[39mf\u001b[39m\u001b[39m\"\"\"\u001b[39m\n\u001b[1;32m 410\u001b[0m \u001b[39m library(readxl)\u001b[39m\n\u001b[1;32m 411\u001b[0m \u001b[39m x <- read_excel(\u001b[39m\u001b[39m'\u001b[39m\u001b[39m{\u001b[39;00mfile\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m\u001b[39m)\u001b[39m\n\u001b[1;32m 412\u001b[0m \u001b[39m\u001b[39m\u001b[39m\"\"\"\u001b[39m\n\u001b[1;32m 413\u001b[0m )\n\u001b[1;32m 415\u001b[0m \u001b[39m# Convert the R dataframe to a pandas dataframe\u001b[39;00m\n\u001b[1;32m 416\u001b[0m df \u001b[39m=\u001b[39m robjects\u001b[39m.\u001b[39mr[\u001b[39m\"\u001b[39m\u001b[39mx\u001b[39m\u001b[39m\"\u001b[39m]\n", + "File \u001b[0;32m~/.cache/pypoetry/virtualenvs/pipelines-Fyk5jlG0-py3.10/lib/python3.10/site-packages/rpy2/robjects/__init__.py:459\u001b[0m, in \u001b[0;36mR.__call__\u001b[0;34m(self, string)\u001b[0m\n\u001b[1;32m 457\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m__call__\u001b[39m(\u001b[39mself\u001b[39m, string):\n\u001b[1;32m 458\u001b[0m p \u001b[39m=\u001b[39m rinterface\u001b[39m.\u001b[39mparse(string)\n\u001b[0;32m--> 459\u001b[0m res \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49meval(p)\n\u001b[1;32m 460\u001b[0m \u001b[39mreturn\u001b[39;00m conversion\u001b[39m.\u001b[39mget_conversion()\u001b[39m.\u001b[39mrpy2py(res)\n", + "File \u001b[0;32m~/.cache/pypoetry/virtualenvs/pipelines-Fyk5jlG0-py3.10/lib/python3.10/site-packages/rpy2/robjects/functions.py:208\u001b[0m, in \u001b[0;36mSignatureTranslatedFunction.__call__\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 206\u001b[0m v \u001b[39m=\u001b[39m kwargs\u001b[39m.\u001b[39mpop(k)\n\u001b[1;32m 207\u001b[0m kwargs[r_k] \u001b[39m=\u001b[39m v\n\u001b[0;32m--> 208\u001b[0m \u001b[39mreturn\u001b[39;00m (\u001b[39msuper\u001b[39;49m(SignatureTranslatedFunction, \u001b[39mself\u001b[39;49m)\n\u001b[1;32m 209\u001b[0m \u001b[39m.\u001b[39;49m\u001b[39m__call__\u001b[39;49m(\u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs))\n", + "File \u001b[0;32m~/.cache/pypoetry/virtualenvs/pipelines-Fyk5jlG0-py3.10/lib/python3.10/site-packages/rpy2/robjects/functions.py:131\u001b[0m, in \u001b[0;36mFunction.__call__\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 129\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m 130\u001b[0m new_kwargs[k] \u001b[39m=\u001b[39m cv\u001b[39m.\u001b[39mpy2rpy(v)\n\u001b[0;32m--> 131\u001b[0m res \u001b[39m=\u001b[39m \u001b[39msuper\u001b[39;49m(Function, \u001b[39mself\u001b[39;49m)\u001b[39m.\u001b[39;49m\u001b[39m__call__\u001b[39;49m(\u001b[39m*\u001b[39;49mnew_args, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mnew_kwargs)\n\u001b[1;32m 132\u001b[0m res \u001b[39m=\u001b[39m cv\u001b[39m.\u001b[39mrpy2py(res)\n\u001b[1;32m 133\u001b[0m \u001b[39mreturn\u001b[39;00m res\n", + "File \u001b[0;32m~/.cache/pypoetry/virtualenvs/pipelines-Fyk5jlG0-py3.10/lib/python3.10/site-packages/rpy2/rinterface_lib/conversion.py:45\u001b[0m, in \u001b[0;36m_cdata_res_to_rinterface.._\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 44\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m_\u001b[39m(\u001b[39m*\u001b[39margs, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs):\n\u001b[0;32m---> 45\u001b[0m cdata \u001b[39m=\u001b[39m function(\u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[1;32m 46\u001b[0m \u001b[39m# TODO: test cdata is of the expected CType\u001b[39;00m\n\u001b[1;32m 47\u001b[0m \u001b[39mreturn\u001b[39;00m _cdata_to_rinterface(cdata)\n", + "File \u001b[0;32m~/.cache/pypoetry/virtualenvs/pipelines-Fyk5jlG0-py3.10/lib/python3.10/site-packages/rpy2/rinterface.py:817\u001b[0m, in \u001b[0;36mSexpClosure.__call__\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 810\u001b[0m res \u001b[39m=\u001b[39m rmemory\u001b[39m.\u001b[39mprotect(\n\u001b[1;32m 811\u001b[0m openrlib\u001b[39m.\u001b[39mrlib\u001b[39m.\u001b[39mR_tryEval(\n\u001b[1;32m 812\u001b[0m call_r,\n\u001b[1;32m 813\u001b[0m call_context\u001b[39m.\u001b[39m__sexp__\u001b[39m.\u001b[39m_cdata,\n\u001b[1;32m 814\u001b[0m error_occured)\n\u001b[1;32m 815\u001b[0m )\n\u001b[1;32m 816\u001b[0m \u001b[39mif\u001b[39;00m error_occured[\u001b[39m0\u001b[39m]:\n\u001b[0;32m--> 817\u001b[0m \u001b[39mraise\u001b[39;00m embedded\u001b[39m.\u001b[39mRRuntimeError(_rinterface\u001b[39m.\u001b[39m_geterrmessage())\n\u001b[1;32m 818\u001b[0m \u001b[39mreturn\u001b[39;00m res\n", + "\u001b[0;31mRRuntimeError\u001b[0m: Error: `path` does not exist: ‘pipelines/datasets/br_denatran_frota/teste.xls’\n" ] } ], "source": [ - "xlrd.open_workbook_xls('Frota RegiΣes Tipo UF JAN2009.xls', encoding_override= 'latin-1')" + "call_r_to_read_file()" ] }, { diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index e3a6565b0..cea570728 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -42,6 +42,10 @@ from pipelines.datasets.br_denatran_frota.constants import constants from bs4 import BeautifulSoup from urllib.request import urlopen +import rpy2.robjects.packages as rpackages +import rpy2.robjects as robjects +from rpy2.robjects.vectors import StrVector + DICT_UFS = constants.DICT_UFS.value SUBSTITUTIONS = constants.SUBSTITUTIONS.value @@ -387,3 +391,25 @@ def make_dir_when_not_exists(dir_name: str): """ if not os.path.exists(dir_name): os.makedirs(dir_name) + + +def call_r_to_read_file(file: str) -> pd.DataFrame: + # Install and load the required R packages + packages = ("readxl",) + r_utils = rpackages.importr("utils", suppress_messages=True) + r_utils.chooseCRANmirror(ind=1) + r_utils.install_packages(StrVector(packages)) + rpackages.importr("readxl", suppress_messages=True) + + # Read the Excel file + robjects.r( + f""" + library(readxl) + x <- read_excel('{file}') + """ + ) + + # Convert the R dataframe to a pandas dataframe + df = robjects.r["x"] + df = pd.DataFrame(dict(zip(df.names, list(df)))) + return df From 8fd4b2a7d3324676846b5e37f04fe28c72b3bc8f Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Mon, 15 May 2023 02:05:11 -0300 Subject: [PATCH 135/265] Treatment working except 2003-2004 --- .../datasets/br_denatran_frota/handlers.py | 17 +++++---- pipelines/datasets/br_denatran_frota/utils.py | 36 ++++++++++++++----- 2 files changed, 38 insertions(+), 15 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 3357387c2..df7394734 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -63,6 +63,7 @@ call_downloader, download_file, extraction_pre_2012, + call_r_to_read_file ) import pandas as pd import polars as pl @@ -119,15 +120,14 @@ def crawl(month: int, year: int, temp_dir: str = ""): def treat_uf_tipo(file: str) -> pl.DataFrame: filename = os.path.split(file)[1] try: - pd.ExcelFile(file) + correct_sheet = [ + sheet for sheet in pd.ExcelFile(file).sheet_names if sheet != "Glossário" + ][0] + df = pd.read_excel(file, sheet_name=correct_sheet) except UnicodeDecodeError: # TODO: Aqui você invoca o capeta e chama o R pra ler e salvar isso como df. Isso é ridículo mas funcionou. - print(2) - correct_sheet = [ - sheet for sheet in pd.ExcelFile(file).sheet_names if sheet != "Glossário" - ][0] - - df = pd.read_excel(file, sheet_name=correct_sheet) + df = call_r_to_read_file(file) + new_df = change_df_header(df, guess_header(df)) # This is ad hoc for UF_tipo. new_df.rename( @@ -138,6 +138,9 @@ def treat_uf_tipo(file: str) -> pl.DataFrame: drop=True ) # Now we get all the actual RELEVANT uf data. month, year = get_year_month_from_filename(filename) + # If the df is all strings, try to get numbers where it makes sense. + if all(clean_df.dtypes == 'object'): + clean_df = clean_df.apply(pd.to_numeric, errors = 'ignore') clean_pl_df = pl.from_pandas(clean_df).lazy() verify_total(clean_pl_df.collect()) # Add year and month diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index cea570728..caa0e53ee 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -70,18 +70,18 @@ def guess_header(df: pd.DataFrame, max_header_guess: int = 4) -> int: int: Index of the row where the header is contained. """ header_guess = 0 - possible_guess_list = [header_guess] + possible_guess_list = [] while header_guess < max_header_guess: if len(df) - 1 < header_guess: break - # Iffy logic, but essentially: if all rows of the column are strings, then this is a good candidate for a header. - if all(df.iloc[header_guess].apply(lambda x: isinstance(x, str))): - possible_guess_list.append(header_guess) + # If this row minus the first column can be converted to int, then + if is_int_row(df.iloc[header_guess]): + possible_guess_list.append(header_guess -1) header_guess += 1 - return max( + return min( possible_guess_list - ) # If nothing is ever found until the max, let's just assume it's the first row as per usual. + ) or 0 # If nothing is ever found until the max, let's just assume it's the first row as per usual. def change_df_header(df: pd.DataFrame, header_row: int) -> pd.DataFrame: @@ -99,6 +99,20 @@ def change_df_header(df: pd.DataFrame, header_row: int) -> pd.DataFrame: new_df.rename(columns=new_header, inplace=True) return new_df +def is_int_row(row): + # convert all elements of the row to strings + str_row = [str(x) for x in row[1:]] + + # try to convert each element to an int, return False if it fails + for element in str_row: + try: + int(element) + except ValueError: + return False + + # if all elements can be converted to int, return True + return True + def get_year_month_from_filename(filename: str) -> tuple[int, int]: """Helper to extract month and year information from files named indicator_month-year.xls @@ -395,6 +409,8 @@ def make_dir_when_not_exists(dir_name: str): def call_r_to_read_file(file: str) -> pd.DataFrame: # Install and load the required R packages + if not os.path.isfile(file): + raise ValueError('Invalid file') packages = ("readxl",) r_utils = rpackages.importr("utils", suppress_messages=True) r_utils.chooseCRANmirror(ind=1) @@ -405,11 +421,15 @@ def call_r_to_read_file(file: str) -> pd.DataFrame: robjects.r( f""" library(readxl) - x <- read_excel('{file}') + + sheets <- excel_sheets('{file}') + correct_sheet <- sheets[sheets != "Glossário"][1] + df <- read_excel('{file}', sheet = correct_sheet) + """ ) # Convert the R dataframe to a pandas dataframe - df = robjects.r["x"] + df = robjects.r["df"] df = pd.DataFrame(dict(zip(df.names, list(df)))) return df From a3c37fac24fab68e273bb7533ea7652bebebad29 Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Mon, 15 May 2023 02:12:30 -0300 Subject: [PATCH 136/265] Adjust parameter for old data --- pipelines/datasets/br_denatran_frota/utils.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index caa0e53ee..5691205b7 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -56,7 +56,7 @@ MUNIC_TIPO_BASIC_FILENAME = constants.MUNIC_TIPO_BASIC_FILENAME.value -def guess_header(df: pd.DataFrame, max_header_guess: int = 4) -> int: +def guess_header(df: pd.DataFrame, max_header_guess: int = 10) -> int: """Function to deal with problematic dataframes coming from Excel/CSV files. Tries to guess which row is the header by examining the first few rows (max given by max_header_guess). Assumes that the header is the first row where all of the columns are strings. From 4b9b74b4314f6df1dbfc8c4f20b0f6325e24f6fe Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Mon, 15 May 2023 04:31:37 -0300 Subject: [PATCH 137/265] uf tipo is done --- pipelines/datasets/br_denatran_frota/constants.py | 4 ++++ pipelines/datasets/br_denatran_frota/handlers.py | 3 ++- pipelines/datasets/br_denatran_frota/utils.py | 14 +++++++------- 3 files changed, 13 insertions(+), 8 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/constants.py b/pipelines/datasets/br_denatran_frota/constants.py index 24cb62653..9ee143594 100644 --- a/pipelines/datasets/br_denatran_frota/constants.py +++ b/pipelines/datasets/br_denatran_frota/constants.py @@ -109,3 +109,7 @@ class constants(Enum): # pylint: disable=c0103 MUNIC_TIPO_BASIC_FILENAME = "frota_por_municipio_e_tipo" MONTHS_SHORT = {month[:3]: number for month, number in MONTHS.items()} + + UF_TIPO_HEADER = ['Grandes Regiões e\nUnidades da Federação', 'TOTAL', 'AUTOMÓVEL', 'BONDE', 'CAMINHÃO', 'CAMINHÃO TRATOR', 'CAMINHONETE', 'CAMIONETA', 'CHASSI PLATAFORMA', 'CICLOMOTOR', 'MICROÔNIBUS', 'MOTOCICLETA', 'MOTONETA', 'ÔNIBUS', 'QUADRICICLO', + 'REBOQUE', 'SEMI-REBOQUE', 'SIDE-CAR', 'OUTROS', 'TRATOR ESTEIRA', 'TRATOR RODAS', 'TRICICLO', 'UTILITÁRIO' + ] \ No newline at end of file diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index df7394734..ceb82aa7d 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -118,6 +118,7 @@ def crawl(month: int, year: int, temp_dir: str = ""): def treat_uf_tipo(file: str) -> pl.DataFrame: + valid_ufs = list(DICT_UFS.keys()) + list(DICT_UFS.values()) filename = os.path.split(file)[1] try: correct_sheet = [ @@ -134,7 +135,7 @@ def treat_uf_tipo(file: str) -> pl.DataFrame: columns={new_df.columns[0]: "sigla_uf"}, inplace=True ) # Rename for ease of use. new_df.sigla_uf = new_df.sigla_uf.str.strip() # Remove whitespace. - clean_df = new_df[new_df.sigla_uf.isin(DICT_UFS.values())].reset_index( + clean_df = new_df[new_df.sigla_uf.isin(valid_ufs)].reset_index( drop=True ) # Now we get all the actual RELEVANT uf data. month, year = get_year_month_from_filename(filename) diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index 5691205b7..4b2222ee7 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -54,7 +54,7 @@ UF_TIPO_BASIC_FILENAME = constants.UF_TIPO_BASIC_FILENAME.value MONTHS_SHORT = constants.MONTHS_SHORT.value MUNIC_TIPO_BASIC_FILENAME = constants.MUNIC_TIPO_BASIC_FILENAME.value - +UF_TIPO_HEADER = constants.UF_TIPO_HEADER.value def guess_header(df: pd.DataFrame, max_header_guess: int = 10) -> int: """Function to deal with problematic dataframes coming from Excel/CSV files. @@ -75,13 +75,13 @@ def guess_header(df: pd.DataFrame, max_header_guess: int = 10) -> int: if len(df) - 1 < header_guess: break # If this row minus the first column can be converted to int, then - if is_int_row(df.iloc[header_guess]): - possible_guess_list.append(header_guess -1) - + #if is_int_row(df.iloc[header_guess]): + current_row = df.iloc[header_guess].to_list() + equal_column_names = [(x, y) for x,y in zip(UF_TIPO_HEADER, current_row) if x == y] + if len(equal_column_names)/len(UF_TIPO_HEADER) > 0.7: # If 70% of the columns match, this is the header. + return header_guess header_guess += 1 - return min( - possible_guess_list - ) or 0 # If nothing is ever found until the max, let's just assume it's the first row as per usual. + return 0 # If nothing is ever found until the max, let's just assume it's the first row as per usual. def change_df_header(df: pd.DataFrame, header_row: int) -> pd.DataFrame: From 2d0f30a9210c81630026588af2204a25e3554d37 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Mon, 15 May 2023 07:34:29 +0000 Subject: [PATCH 138/265] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- .../datasets/br_denatran_frota/constants.py | 28 +++++++++++++++++-- .../datasets/br_denatran_frota/handlers.py | 8 +++--- pipelines/datasets/br_denatran_frota/utils.py | 20 ++++++++----- 3 files changed, 42 insertions(+), 14 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/constants.py b/pipelines/datasets/br_denatran_frota/constants.py index 9ee143594..a93cd8c1c 100644 --- a/pipelines/datasets/br_denatran_frota/constants.py +++ b/pipelines/datasets/br_denatran_frota/constants.py @@ -110,6 +110,28 @@ class constants(Enum): # pylint: disable=c0103 MONTHS_SHORT = {month[:3]: number for month, number in MONTHS.items()} - UF_TIPO_HEADER = ['Grandes Regiões e\nUnidades da Federação', 'TOTAL', 'AUTOMÓVEL', 'BONDE', 'CAMINHÃO', 'CAMINHÃO TRATOR', 'CAMINHONETE', 'CAMIONETA', 'CHASSI PLATAFORMA', 'CICLOMOTOR', 'MICROÔNIBUS', 'MOTOCICLETA', 'MOTONETA', 'ÔNIBUS', 'QUADRICICLO', - 'REBOQUE', 'SEMI-REBOQUE', 'SIDE-CAR', 'OUTROS', 'TRATOR ESTEIRA', 'TRATOR RODAS', 'TRICICLO', 'UTILITÁRIO' - ] \ No newline at end of file + UF_TIPO_HEADER = [ + "Grandes Regiões e\nUnidades da Federação", + "TOTAL", + "AUTOMÓVEL", + "BONDE", + "CAMINHÃO", + "CAMINHÃO TRATOR", + "CAMINHONETE", + "CAMIONETA", + "CHASSI PLATAFORMA", + "CICLOMOTOR", + "MICROÔNIBUS", + "MOTOCICLETA", + "MOTONETA", + "ÔNIBUS", + "QUADRICICLO", + "REBOQUE", + "SEMI-REBOQUE", + "SIDE-CAR", + "OUTROS", + "TRATOR ESTEIRA", + "TRATOR RODAS", + "TRICICLO", + "UTILITÁRIO", + ] diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index ceb82aa7d..4bff48dc3 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -63,7 +63,7 @@ call_downloader, download_file, extraction_pre_2012, - call_r_to_read_file + call_r_to_read_file, ) import pandas as pd import polars as pl @@ -128,7 +128,7 @@ def treat_uf_tipo(file: str) -> pl.DataFrame: except UnicodeDecodeError: # TODO: Aqui você invoca o capeta e chama o R pra ler e salvar isso como df. Isso é ridículo mas funcionou. df = call_r_to_read_file(file) - + new_df = change_df_header(df, guess_header(df)) # This is ad hoc for UF_tipo. new_df.rename( @@ -140,8 +140,8 @@ def treat_uf_tipo(file: str) -> pl.DataFrame: ) # Now we get all the actual RELEVANT uf data. month, year = get_year_month_from_filename(filename) # If the df is all strings, try to get numbers where it makes sense. - if all(clean_df.dtypes == 'object'): - clean_df = clean_df.apply(pd.to_numeric, errors = 'ignore') + if all(clean_df.dtypes == "object"): + clean_df = clean_df.apply(pd.to_numeric, errors="ignore") clean_pl_df = pl.from_pandas(clean_df).lazy() verify_total(clean_pl_df.collect()) # Add year and month diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index 4b2222ee7..d090ed57f 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -56,6 +56,7 @@ MUNIC_TIPO_BASIC_FILENAME = constants.MUNIC_TIPO_BASIC_FILENAME.value UF_TIPO_HEADER = constants.UF_TIPO_HEADER.value + def guess_header(df: pd.DataFrame, max_header_guess: int = 10) -> int: """Function to deal with problematic dataframes coming from Excel/CSV files. Tries to guess which row is the header by examining the first few rows (max given by max_header_guess). @@ -75,13 +76,17 @@ def guess_header(df: pd.DataFrame, max_header_guess: int = 10) -> int: if len(df) - 1 < header_guess: break # If this row minus the first column can be converted to int, then - #if is_int_row(df.iloc[header_guess]): + # if is_int_row(df.iloc[header_guess]): current_row = df.iloc[header_guess].to_list() - equal_column_names = [(x, y) for x,y in zip(UF_TIPO_HEADER, current_row) if x == y] - if len(equal_column_names)/len(UF_TIPO_HEADER) > 0.7: # If 70% of the columns match, this is the header. + equal_column_names = [ + (x, y) for x, y in zip(UF_TIPO_HEADER, current_row) if x == y + ] + if ( + len(equal_column_names) / len(UF_TIPO_HEADER) > 0.7 + ): # If 70% of the columns match, this is the header. return header_guess header_guess += 1 - return 0 # If nothing is ever found until the max, let's just assume it's the first row as per usual. + return 0 # If nothing is ever found until the max, let's just assume it's the first row as per usual. def change_df_header(df: pd.DataFrame, header_row: int) -> pd.DataFrame: @@ -99,17 +104,18 @@ def change_df_header(df: pd.DataFrame, header_row: int) -> pd.DataFrame: new_df.rename(columns=new_header, inplace=True) return new_df + def is_int_row(row): # convert all elements of the row to strings str_row = [str(x) for x in row[1:]] - + # try to convert each element to an int, return False if it fails for element in str_row: try: int(element) except ValueError: return False - + # if all elements can be converted to int, return True return True @@ -410,7 +416,7 @@ def make_dir_when_not_exists(dir_name: str): def call_r_to_read_file(file: str) -> pd.DataFrame: # Install and load the required R packages if not os.path.isfile(file): - raise ValueError('Invalid file') + raise ValueError("Invalid file") packages = ("readxl",) r_utils = rpackages.importr("utils", suppress_messages=True) r_utils.chooseCRANmirror(ind=1) From 3a8e207b4b56ba9d028c4f57ada4ff090a579d0a Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 16 May 2023 00:50:12 -0300 Subject: [PATCH 139/265] Add task for outputing file to CSV --- pipelines/datasets/br_denatran_frota/handlers.py | 7 ++----- 1 file changed, 2 insertions(+), 5 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 4bff48dc3..fc7b6668c 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -159,8 +159,5 @@ def treat_uf_tipo(file: str) -> pl.DataFrame: return clean_pl_df -def output_file_to_csv(df: pl.DataFrame) -> None: - pass - - -# df.write_csv(file=f"{OUTPUT_PATH}/{filename}.csv", has_header=True) +def output_file_to_csv(df: pl.DataFrame, filename: str) -> None: + df.write_csv(file=f"{OUTPUT_PATH}/{filename}.csv", has_header=True) From c4e6a749bc1fc7da581761250e25239696c48958 Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 16 May 2023 00:58:39 -0300 Subject: [PATCH 140/265] Small error --- br_denatran_frota/code/frota_municipio_tipo.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/br_denatran_frota/code/frota_municipio_tipo.py b/br_denatran_frota/code/frota_municipio_tipo.py index a400a88af..00f387618 100644 --- a/br_denatran_frota/code/frota_municipio_tipo.py +++ b/br_denatran_frota/code/frota_municipio_tipo.py @@ -18,7 +18,7 @@ import basedosdados as bd -def verify_uf(denatran_df: pl.DataFrame, ibge_df: pl.DataFrame, uf: str): +def verify_uf(denatran_df: pl.DataFrame, ibge_df: pl.DataFrame, uf: str) -> None: denatran_uf = denatran_df.filter(pl.col("sigla_uf") == uf) ibge_uf = ibge_df.filter(pl.col("sigla_uf") == uf) ibge_uf = ibge_uf.with_columns(pl.col("nome").apply(asciify).str.to_lowercase()) From d65706d6ce2e467c4bbdbe53497f84443a399d50 Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 16 May 2023 01:05:17 -0300 Subject: [PATCH 141/265] WIP for treating municipality data --- pipelines/datasets/br_denatran_frota/utils.py | 39 ++++++++++++++++++- 1 file changed, 38 insertions(+), 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index d090ed57f..8f2bb3913 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -71,7 +71,6 @@ def guess_header(df: pd.DataFrame, max_header_guess: int = 10) -> int: int: Index of the row where the header is contained. """ header_guess = 0 - possible_guess_list = [] while header_guess < max_header_guess: if len(df) - 1 < header_guess: break @@ -439,3 +438,41 @@ def call_r_to_read_file(file: str) -> pd.DataFrame: df = robjects.r["df"] df = pd.DataFrame(dict(zip(df.names, list(df)))) return df + + +def verify_uf(denatran_df: pl.DataFrame, ibge_df: pl.DataFrame, uf: str) -> None: + """Function to take the DENATRAN data at municipality level and compare it to the IBGE data. + This will filter by the uf argument and do all comparisons to ensure consistency. + + Args: + denatran_df (pl.DataFrame): Dataframe with the DENATRAN data at municipality level. + ibge_df (pl.DataFrame): Dataframe with the IBGE data of municipalities. + uf (str): Desired municipality to filter the DF for. + + Raises: + ValueError: If there are somehow municipalities in the DENATRAN data that do not exist in the IBGE data. Very unlikely. + ValueError: If there are two municipalities in the DENATRAN data + """ + denatran_uf = denatran_df.filter(pl.col("sigla_uf") == uf) + ibge_uf = ibge_df.filter(pl.col("sigla_uf") == uf) + ibge_uf = ibge_uf.with_columns(pl.col("nome").apply(asciify).str.to_lowercase()) + municipios_na_bd = ibge_uf["nome"].to_list() + x = denatran_uf["nome_denatran"].apply(lambda x: get_city_name_ibge(x, ibge_uf)) + denatran_uf = denatran_uf.with_columns(x.alias("suggested_nome_ibge")) + denatran_uf = denatran_uf.with_columns( + denatran_uf.apply(fix_suggested_nome_ibge)["apply"].alias("suggested_nome_ibge") + ) + municipios_no_denatran = denatran_uf["suggested_nome_ibge"].to_list() + d = set(municipios_no_denatran) - set(municipios_na_bd) + municipios_duplicados = ( + denatran_uf.groupby("suggested_nome_ibge").count().filter(pl.col("count") > 1) + ) + if not municipios_duplicados.is_empty(): + raise ValueError( + f"Existem municípios com mesmo nome do IBGE em {uf}! São eles {municipios_duplicados['suggested_nome_ibge'].to_list()}" + ) + if d: + # This here is probably impossible and shouldn't happen due to the matching coming from the BD data. + # The set difference might occur the other way around, but still, better safe. + raise ValueError(f"Existem municípios em {uf} que não estão na BD.") + match_ibge(denatran_uf, ibge_uf) From a5fc92db9a25c5af02d366f459dcadae48670e7f Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 16 May 2023 22:15:21 -0300 Subject: [PATCH 142/265] Add export task --- pipelines/datasets/br_denatran_frota/handlers.py | 1 + pipelines/datasets/br_denatran_frota/tasks.py | 11 +++++++---- 2 files changed, 8 insertions(+), 4 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index fc7b6668c..6052311e8 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -161,3 +161,4 @@ def treat_uf_tipo(file: str) -> pl.DataFrame: def output_file_to_csv(df: pl.DataFrame, filename: str) -> None: df.write_csv(file=f"{OUTPUT_PATH}/{filename}.csv", has_header=True) + return OUTPUT_PATH diff --git a/pipelines/datasets/br_denatran_frota/tasks.py b/pipelines/datasets/br_denatran_frota/tasks.py index 5ca214f8d..f912e16ac 100644 --- a/pipelines/datasets/br_denatran_frota/tasks.py +++ b/pipelines/datasets/br_denatran_frota/tasks.py @@ -64,7 +64,11 @@ ) import pandas as pd import polars as pl -from pipelines.datasets.br_denatran_frota.handlers import crawl, treat_uf_tipo +from pipelines.datasets.br_denatran_frota.handlers import ( + crawl, + treat_uf_tipo, + output_file_to_csv, +) MONTHS = constants.MONTHS.value DATASET = constants.DATASET.value @@ -83,6 +87,5 @@ def treat_uf_tipo_task(file) -> pl.DataFrame: @task() -def output_file_to_csv(df: pl.DataFrame) -> None: - pass - # df.write_csv(file=f"{OUTPUT_PATH}/{filename}.csv", has_header=True) +def output_file_to_csv_task(df: pl.DataFrame, filename: str) -> None: + output_file_to_csv(df, filename) From 11d9f040e5aab1569cf20cab377311885ffe0994 Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 16 May 2023 22:26:19 -0300 Subject: [PATCH 143/265] Change constants to keep things standard --- pipelines/datasets/br_denatran_frota/constants.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/constants.py b/pipelines/datasets/br_denatran_frota/constants.py index a93cd8c1c..515002d56 100644 --- a/pipelines/datasets/br_denatran_frota/constants.py +++ b/pipelines/datasets/br_denatran_frota/constants.py @@ -100,9 +100,9 @@ class constants(Enum): # pylint: disable=c0103 ("TO", "sao valerio da natividade"): "sao valerio", } - DOWNLOAD_PATH = f"pipelines/datasets/{DATASET}/tmp/input" + DOWNLOAD_PATH = f"/tmp/input/{DATASET}" - OUTPUT_PATH = f"pipelines/datasets/{DATASET}/tmp/output" + OUTPUT_PATH = f"/tmp/output/{DATASET}" UF_TIPO_BASIC_FILENAME = "frota_por_uf_e_tipo_de_veiculo" From 242933e9db0a597e3a4451f103e0874aa9cd74e9 Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 16 May 2023 22:31:34 -0300 Subject: [PATCH 144/265] Add task for getting the extracted file --- pipelines/datasets/br_denatran_frota/handlers.py | 10 ++++++++++ pipelines/datasets/br_denatran_frota/tasks.py | 6 ++++++ 2 files changed, 16 insertions(+) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 6052311e8..d6647f5af 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -162,3 +162,13 @@ def treat_uf_tipo(file: str) -> pl.DataFrame: def output_file_to_csv(df: pl.DataFrame, filename: str) -> None: df.write_csv(file=f"{OUTPUT_PATH}/{filename}.csv", has_header=True) return OUTPUT_PATH + + +def get_desired_file(year: int, download_directory: str, filetype: str): + directory_to_search = os.path.join(download_directory, "files", f"{year}") + for file in os.listdir(directory_to_search): + if re.search(filetype, file) and file.split(".")[-1] in [ + "xls", + "xlsx", + ]: + return file diff --git a/pipelines/datasets/br_denatran_frota/tasks.py b/pipelines/datasets/br_denatran_frota/tasks.py index f912e16ac..6a923ff12 100644 --- a/pipelines/datasets/br_denatran_frota/tasks.py +++ b/pipelines/datasets/br_denatran_frota/tasks.py @@ -68,6 +68,7 @@ crawl, treat_uf_tipo, output_file_to_csv, + get_desired_file, ) MONTHS = constants.MONTHS.value @@ -89,3 +90,8 @@ def treat_uf_tipo_task(file) -> pl.DataFrame: @task() def output_file_to_csv_task(df: pl.DataFrame, filename: str) -> None: output_file_to_csv(df, filename) + + +@task() +def get_desired_file_task(year: int, download_directory: str, filetype: str): + get_desired_file(year, download_directory, filetype) From 048e5e5e607b017486953eec6bd63651f53d83e9 Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 16 May 2023 22:38:38 -0300 Subject: [PATCH 145/265] Create first flow --- pipelines/datasets/br_denatran_frota/flows.py | 98 ++++++++++++++----- 1 file changed, 72 insertions(+), 26 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index 8fcace90a..5b0d92a06 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -60,7 +60,7 @@ from datetime import datetime, timedelta from prefect.run_configs import KubernetesRun from prefect.storage import GCS -from prefect import Parameter, case, Flow +from prefect import Parameter, case from prefect.tasks.prefect import ( create_flow_run, wait_for_flow_run, @@ -69,49 +69,95 @@ from pipelines.constants import constants as pipelines_constants from pipelines.utils.constants import constants as utils_constants -# from pipelines.utils.decorators import Flow +from pipelines.utils.decorators import Flow from pipelines.utils.execute_dbt_model.constants import constants as dump_db_constants from pipelines.utils.tasks import ( create_table_and_upload_to_gcs, rename_current_flow_run_dataset_table, get_current_flow_labels, ) -from pipelines.datasets.br_denatran_frota.tasks import crawl_task, treat_uf_tipo_task +from pipelines.datasets.br_denatran_frota.tasks import ( + crawl_task, + treat_uf_tipo_task, + output_file_to_csv_task, + get_desired_file_task, +) from pipelines.datasets.br_denatran_frota.constants import constants -download_path = constants.DOWNLOAD_PATH.value + # from pipelines.datasets.br_denatran_frota.schedules import every_two_weeks with Flow( name="br_denatran_frota.uf_tipo", - # code_owners=[ - # "Tamir", - # ], + code_owners=[ + "Tamir", + ], ) as br_denatran_frota_uf_tipo: - # dataset_id = Parameter("dataset_id", default="br_denatran_frota") - # table_id = Parameter("table_id", default="uf_tipo") + dataset_id = Parameter("dataset_id", default="br_denatran_frota") + table_id = Parameter("table_id", default="uf_tipo") + + # Materialization mode + materialization_mode = Parameter( + "materialization_mode", default="dev", required=False + ) + + materialize_after_dump = Parameter( + "materialize after dump", default=False, required=False + ) - # # Materialization mode - # materialization_mode = Parameter( - # "materialization_mode", default="dev", required=False - # ) + dbt_alias = Parameter("dbt_alias", default=True, required=False) - # materialize_after_dump = Parameter( - # "materialize after dump", default=False, required=False - # ) + rename_flow_run = rename_current_flow_run_dataset_table( + prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id + ) + # Download the file: + crawled = crawl_task(month=2, year=2021, temp_dir=constants.DOWNLOAD_PATH.value) + # Now get the downloaded file: + uf_tipo_file = get_desired_file_task( + year=2021, + download_directory=constants.DOWNLOAD_PATH.value, + filetype=constants.UF_TIPO_BASIC_FILENAME.value, + upstream_tasks=[crawled], + ) + df = treat_uf_tipo_task(file=uf_tipo_file, upstream_tasks=[uf_tipo_file]) + csv_output = output_file_to_csv_task(df, upstream_tasks=[df]) + wait_upload_table = create_table_and_upload_to_gcs( + data_path=csv_output, + dataset_id=dataset_id, + table_id=table_id, + dump_mode="append", + wait=csv_output, + ) - # dbt_alias = Parameter("dbt_alias", default=True, required=False) + with case(materialize_after_dump, True): + # Trigger DBT flow run + current_flow_labels = get_current_flow_labels() + materialization_flow = create_flow_run( + flow_name=utils_constants.FLOW_EXECUTE_DBT_MODEL_NAME.value, + project_name=pipelines_constants.PREFECT_DEFAULT_PROJECT.value, + parameters={ + "dataset_id": dataset_id, + "table_id": table_id, + "mode": materialization_mode, + "dbt_alias": dbt_alias, + }, + labels=current_flow_labels, + run_name=f"Materialize {dataset_id}.{table_id}", + ) - # rename_flow_run = rename_current_flow_run_dataset_table( - # prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id - # ) - crawled = crawl_task( - month=2, year=2021, temp_dir=download_path - ) # Download the desired files. - uf_tipo_file = "/home/tamir/basedosdados/pipelines/pipelines/datasets/br_denatran_frota/tmp/input/files/2021/frota_por_uf_e_tipo_de_veículo_2-2021.xls" - df = treat_uf_tipo_task(file=uf_tipo_file, upstream_tasks=[crawled]) + wait_for_materialization = wait_for_flow_run( + materialization_flow, + stream_states=True, + stream_logs=True, + raise_final_state=True, + ) + wait_for_materialization.max_retries = ( + dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_ATTEMPTS.value + ) + wait_for_materialization.retry_delay = timedelta( + seconds=dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_INTERVAL.value + ) - print("foi?") br_denatran_frota_uf_tipo.storage = GCS(pipelines_constants.GCS_FLOWS_BUCKET.value) br_denatran_frota_uf_tipo.run_config = KubernetesRun( From f949e0cd8376bb33cfab2eed1a1ba6fd80af25f8 Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 16 May 2023 22:41:43 -0300 Subject: [PATCH 146/265] Ignore my local run file --- .gitignore | 1 + 1 file changed, 1 insertion(+) diff --git a/.gitignore b/.gitignore index aa41b1ff4..b8ce2db36 100644 --- a/.gitignore +++ b/.gitignore @@ -142,3 +142,4 @@ notebooks/ /tests/ poetry.lock pipelines/datasets/br_denatran_frota/todo_list.txt +pipelines/datasets/br_denatran_frota/run_local.py From ef7500982e0c852ad6715ea8a9235a0ede439a5f Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 17 May 2023 00:44:10 -0300 Subject: [PATCH 147/265] The flow should work but... --- pipelines/datasets/br_denatran_frota/flows.py | 12 +++++++---- .../datasets/br_denatran_frota/handlers.py | 3 ++- pipelines/datasets/br_denatran_frota/tasks.py | 9 -------- .../datasets/br_denatran_frota/tasks_test.py | 21 ++++++++++++++++++- 4 files changed, 30 insertions(+), 15 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index 5b0d92a06..a38ba4e04 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -65,7 +65,7 @@ create_flow_run, wait_for_flow_run, ) - +import os from pipelines.constants import constants as pipelines_constants from pipelines.utils.constants import constants as utils_constants @@ -93,6 +93,7 @@ "Tamir", ], ) as br_denatran_frota_uf_tipo: + year = 2021 dataset_id = Parameter("dataset_id", default="br_denatran_frota") table_id = Parameter("table_id", default="uf_tipo") @@ -111,16 +112,19 @@ prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id ) # Download the file: - crawled = crawl_task(month=2, year=2021, temp_dir=constants.DOWNLOAD_PATH.value) + crawled = crawl_task(month=2, year=year, temp_dir=constants.DOWNLOAD_PATH.value) # Now get the downloaded file: uf_tipo_file = get_desired_file_task( - year=2021, + year=year, download_directory=constants.DOWNLOAD_PATH.value, filetype=constants.UF_TIPO_BASIC_FILENAME.value, upstream_tasks=[crawled], ) + print(uf_tipo_file) df = treat_uf_tipo_task(file=uf_tipo_file, upstream_tasks=[uf_tipo_file]) - csv_output = output_file_to_csv_task(df, upstream_tasks=[df]) + csv_output = output_file_to_csv_task( + df, constants.UF_TIPO_BASIC_FILENAME, upstream_tasks=[df] + ) wait_upload_table = create_table_and_upload_to_gcs( data_path=csv_output, dataset_id=dataset_id, diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index d6647f5af..b9c1ef4bf 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -171,4 +171,5 @@ def get_desired_file(year: int, download_directory: str, filetype: str): "xls", "xlsx", ]: - return file + return os.path.join(directory_to_search, file) + raise ValueError("No files found buckaroo") diff --git a/pipelines/datasets/br_denatran_frota/tasks.py b/pipelines/datasets/br_denatran_frota/tasks.py index 6a923ff12..411b01fc6 100644 --- a/pipelines/datasets/br_denatran_frota/tasks.py +++ b/pipelines/datasets/br_denatran_frota/tasks.py @@ -53,15 +53,6 @@ import glob import os from pipelines.datasets.br_denatran_frota.constants import constants -from pipelines.datasets.br_denatran_frota.utils import ( - make_dir_when_not_exists, - extract_links_post_2012, - verify_total, - change_df_header, - guess_header, - get_year_month_from_filename, - call_downloader, -) import pandas as pd import polars as pl from pipelines.datasets.br_denatran_frota.handlers import ( diff --git a/pipelines/datasets/br_denatran_frota/tasks_test.py b/pipelines/datasets/br_denatran_frota/tasks_test.py index 021d33808..5ebfd1aea 100644 --- a/pipelines/datasets/br_denatran_frota/tasks_test.py +++ b/pipelines/datasets/br_denatran_frota/tasks_test.py @@ -6,7 +6,11 @@ import re from parameterized import parameterized -from pipelines.datasets.br_denatran_frota.handlers import crawl, treat_uf_tipo +from pipelines.datasets.br_denatran_frota.handlers import ( + crawl, + treat_uf_tipo, + get_desired_file, +) from pipelines.datasets.br_denatran_frota.constants import constants DATASET = constants.DATASET.value @@ -64,6 +68,9 @@ def tearDown(self): def test_treat_files_uf_tipo(self, month, year): crawl(month, year, self.temp_dir.name) directory_to_search = os.path.join(self.temp_dir.name, "files", f"{year}") + get_desired_file( + year, + ) for file in os.listdir(directory_to_search): if re.search(UF_TIPO_BASIC_FILENAME, file) and file.split(".")[-1] in [ "xls", @@ -72,6 +79,18 @@ def test_treat_files_uf_tipo(self, month, year): treated_df = treat_uf_tipo(os.path.join(directory_to_search, file)) self.assertEqual(len(treated_df), 21 * 27) + def test_flow(self): + year = 2021 + crawl(month=2, year=year, temp_dir=constants.DOWNLOAD_PATH.value) + # Now get the downloaded file: + uf_tipo_file = get_desired_file( + year=year, + download_directory=constants.DOWNLOAD_PATH.value, + filetype=constants.UF_TIPO_BASIC_FILENAME.value, + ) + print(uf_tipo_file) + treat_uf_tipo(file=uf_tipo_file) + if __name__ == "__main__": unittest.main() From 98c6217f0b0cc5174f503f3e619584b357b60197 Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 17 May 2023 01:51:37 -0300 Subject: [PATCH 148/265] yeah the flow still sucks i'm stupid --- pipelines/datasets/br_denatran_frota/flows.py | 10 +++++++--- pipelines/datasets/br_denatran_frota/tasks.py | 6 ++++++ pipelines/datasets/br_denatran_frota/tasks_test.py | 4 +++- 3 files changed, 16 insertions(+), 4 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index a38ba4e04..bd2326ea2 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -65,6 +65,9 @@ create_flow_run, wait_for_flow_run, ) +from pipelines.utils.utils import ( + log, +) import os from pipelines.constants import constants as pipelines_constants from pipelines.utils.constants import constants as utils_constants @@ -111,17 +114,18 @@ rename_flow_run = rename_current_flow_run_dataset_table( prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id ) - # Download the file: + log("Downloading file") crawled = crawl_task(month=2, year=year, temp_dir=constants.DOWNLOAD_PATH.value) # Now get the downloaded file: + log("Accessing downloaded file") uf_tipo_file = get_desired_file_task( year=year, download_directory=constants.DOWNLOAD_PATH.value, filetype=constants.UF_TIPO_BASIC_FILENAME.value, upstream_tasks=[crawled], ) - print(uf_tipo_file) - df = treat_uf_tipo_task(file=uf_tipo_file, upstream_tasks=[uf_tipo_file]) + log(uf_tipo_file) + df = treat_uf_tipo_task(file=uf_tipo_file, upstream_tasks=[crawled, uf_tipo_file]) csv_output = output_file_to_csv_task( df, constants.UF_TIPO_BASIC_FILENAME, upstream_tasks=[df] ) diff --git a/pipelines/datasets/br_denatran_frota/tasks.py b/pipelines/datasets/br_denatran_frota/tasks.py index 411b01fc6..a9769e88e 100644 --- a/pipelines/datasets/br_denatran_frota/tasks.py +++ b/pipelines/datasets/br_denatran_frota/tasks.py @@ -61,6 +61,11 @@ output_file_to_csv, get_desired_file, ) +from pipelines.utils.utils import ( + clean_dataframe, + to_partitions, + log, +) MONTHS = constants.MONTHS.value DATASET = constants.DATASET.value @@ -75,6 +80,7 @@ def crawl_task(month: int, year: int, temp_dir: str = ""): @task() def treat_uf_tipo_task(file) -> pl.DataFrame: + log(file) treat_uf_tipo(file) diff --git a/pipelines/datasets/br_denatran_frota/tasks_test.py b/pipelines/datasets/br_denatran_frota/tasks_test.py index 5ebfd1aea..2ed66f8bb 100644 --- a/pipelines/datasets/br_denatran_frota/tasks_test.py +++ b/pipelines/datasets/br_denatran_frota/tasks_test.py @@ -4,6 +4,7 @@ import tempfile import unittest import re +import polars as pl from parameterized import parameterized from pipelines.datasets.br_denatran_frota.handlers import ( @@ -89,7 +90,8 @@ def test_flow(self): filetype=constants.UF_TIPO_BASIC_FILENAME.value, ) print(uf_tipo_file) - treat_uf_tipo(file=uf_tipo_file) + df = treat_uf_tipo(file=uf_tipo_file) + self.assertTrue(type(df), pl.DataFrame) if __name__ == "__main__": From faeda9f41dc5e662bb2d78a7e6a65f6dbc9ca4ef Mon Sep 17 00:00:00 2001 From: Tamir Date: Fri, 19 May 2023 00:34:30 -0300 Subject: [PATCH 149/265] The first flow gets to Google Cloud --- pipelines/datasets/br_denatran_frota/handlers.py | 8 ++++++++ pipelines/datasets/br_denatran_frota/tasks.py | 9 +++++---- 2 files changed, 13 insertions(+), 4 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index b9c1ef4bf..c401599b1 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -68,6 +68,11 @@ import pandas as pd import polars as pl from zipfile import ZipFile +from pipelines.utils.utils import ( + clean_dataframe, + to_partitions, + log, +) MONTHS = constants.MONTHS.value DATASET = constants.DATASET.value @@ -160,16 +165,19 @@ def treat_uf_tipo(file: str) -> pl.DataFrame: def output_file_to_csv(df: pl.DataFrame, filename: str) -> None: + make_dir_when_not_exists(OUTPUT_PATH) df.write_csv(file=f"{OUTPUT_PATH}/{filename}.csv", has_header=True) return OUTPUT_PATH def get_desired_file(year: int, download_directory: str, filetype: str): directory_to_search = os.path.join(download_directory, "files", f"{year}") + log(f"Directory: {directory_to_search}") for file in os.listdir(directory_to_search): if re.search(filetype, file) and file.split(".")[-1] in [ "xls", "xlsx", ]: + log(f"File: {file}") return os.path.join(directory_to_search, file) raise ValueError("No files found buckaroo") diff --git a/pipelines/datasets/br_denatran_frota/tasks.py b/pipelines/datasets/br_denatran_frota/tasks.py index a9769e88e..902851246 100644 --- a/pipelines/datasets/br_denatran_frota/tasks.py +++ b/pipelines/datasets/br_denatran_frota/tasks.py @@ -75,20 +75,21 @@ @task() # noqa def crawl_task(month: int, year: int, temp_dir: str = ""): - crawl(month, year, temp_dir) + return crawl(month, year, temp_dir) @task() def treat_uf_tipo_task(file) -> pl.DataFrame: log(file) - treat_uf_tipo(file) + return treat_uf_tipo(file) @task() def output_file_to_csv_task(df: pl.DataFrame, filename: str) -> None: - output_file_to_csv(df, filename) + log(filename) + return output_file_to_csv(df, filename) @task() def get_desired_file_task(year: int, download_directory: str, filetype: str): - get_desired_file(year, download_directory, filetype) + return get_desired_file(year, download_directory, filetype) From 39300de5217149752de67d913e26ad36aaba3aa0 Mon Sep 17 00:00:00 2001 From: Tamir Date: Fri, 19 May 2023 01:10:45 -0300 Subject: [PATCH 150/265] Type hints in handlers.py --- pipelines/datasets/br_denatran_frota/handlers.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index c401599b1..e31712d46 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -83,7 +83,7 @@ MUNIC_TIPO_BASIC_FILENAME = constants.MUNIC_TIPO_BASIC_FILENAME.value -def crawl(month: int, year: int, temp_dir: str = ""): +def crawl(month: int, year: int, temp_dir: str = "") -> None: """Função principal para baixar os dados de frota por município e tipo e também por UF e tipo. Args: @@ -170,7 +170,7 @@ def output_file_to_csv(df: pl.DataFrame, filename: str) -> None: return OUTPUT_PATH -def get_desired_file(year: int, download_directory: str, filetype: str): +def get_desired_file(year: int, download_directory: str, filetype: str) -> str: directory_to_search = os.path.join(download_directory, "files", f"{year}") log(f"Directory: {directory_to_search}") for file in os.listdir(directory_to_search): From 9fd41022f5191c1e6f40cd5c88045173f36c878d Mon Sep 17 00:00:00 2001 From: Tamir Date: Fri, 19 May 2023 01:14:14 -0300 Subject: [PATCH 151/265] Add type hints to task --- pipelines/datasets/br_denatran_frota/tasks.py | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/tasks.py b/pipelines/datasets/br_denatran_frota/tasks.py index 902851246..2c8738990 100644 --- a/pipelines/datasets/br_denatran_frota/tasks.py +++ b/pipelines/datasets/br_denatran_frota/tasks.py @@ -62,8 +62,6 @@ get_desired_file, ) from pipelines.utils.utils import ( - clean_dataframe, - to_partitions, log, ) @@ -74,7 +72,7 @@ @task() # noqa -def crawl_task(month: int, year: int, temp_dir: str = ""): +def crawl_task(month: int, year: int, temp_dir: str = "") -> None: return crawl(month, year, temp_dir) @@ -91,5 +89,5 @@ def output_file_to_csv_task(df: pl.DataFrame, filename: str) -> None: @task() -def get_desired_file_task(year: int, download_directory: str, filetype: str): +def get_desired_file_task(year: int, download_directory: str, filetype: str) -> str: return get_desired_file(year, download_directory, filetype) From d3bd53a2707a62a62d2accf4e225b66808a424b3 Mon Sep 17 00:00:00 2001 From: Tamir Date: Fri, 19 May 2023 01:16:45 -0300 Subject: [PATCH 152/265] Cleanup --- .../datasets/br_denatran_frota/handlers.py | 49 +------------------ 1 file changed, 2 insertions(+), 47 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index e31712d46..c2c0c6391 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -1,54 +1,9 @@ # -*- coding: utf-8 -*- """ -Tasks for br_denatran_frota +Handlers for br_denatran_frota +This is merely a way to have functions that are called by tasks but can be tested with unit tests and debugging. """ -############################################################################### -# -# Aqui é onde devem ser definidas as tasks para os flows do projeto. -# Cada task representa um passo da pipeline. Não é estritamente necessário -# tratar todas as exceções que podem ocorrer durante a execução de uma task, -# mas é recomendável, ainda que não vá implicar em uma quebra no sistema. -# Mais informações sobre tasks podem ser encontradas na documentação do -# Prefect: https://docs.prefect.io/core/concepts/tasks.html -# -# De modo a manter consistência na codebase, todo o código escrito passará -# pelo pylint. Todos os warnings e erros devem ser corrigidos. -# -# As tasks devem ser definidas como funções comuns ao Python, com o decorador -# @task acima. É recomendado inserir type hints para as variáveis. -# -# Um exemplo de task é o seguinte: -# -# ----------------------------------------------------------------------------- -# from prefect import task -# -# @task -# def my_task(param1: str, param2: int) -> str: -# """ -# My task description. -# """ -# return f'{param1} {param2}' -# ----------------------------------------------------------------------------- -# -# Você também pode usar pacotes Python arbitrários, como numpy, pandas, etc. -# -# ----------------------------------------------------------------------------- -# from prefect import task -# import numpy as np -# -# @task -# def my_task(a: np.ndarray, b: np.ndarray) -> str: -# """ -# My task description. -# """ -# return np.add(a, b) -# ----------------------------------------------------------------------------- -# -# Abaixo segue um código para exemplificação, que pode ser removido. -# -############################################################################### - from prefect import task import os import re From fa1e04b33cb622e21ef813008452931a417303e9 Mon Sep 17 00:00:00 2001 From: Tamir Date: Fri, 19 May 2023 01:24:19 -0300 Subject: [PATCH 153/265] Guess header refactor --- .../br_denatran_frota/functions_test.py | 45 ------------------- .../datasets/br_denatran_frota/handlers.py | 2 +- pipelines/datasets/br_denatran_frota/utils.py | 14 ++++-- 3 files changed, 12 insertions(+), 49 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/functions_test.py b/pipelines/datasets/br_denatran_frota/functions_test.py index f435c762f..11657cdd2 100644 --- a/pipelines/datasets/br_denatran_frota/functions_test.py +++ b/pipelines/datasets/br_denatran_frota/functions_test.py @@ -71,51 +71,6 @@ def test_download_frota_with_invalid_month(self): crawl(13, 2013) -class TestGuessHeader(unittest.TestCase): - def test_correct_header_guess(self): - # Test case 1: Correct header guess - df = pd.DataFrame( - { - "A": ["Name", "Alice", "Bob"], - "B": ["Age", 30, 40], - "C": ["Country", "USA", "Canada"], - } - ) - self.assertEqual(guess_header(df), 0) # Header is in the first row - - def test_no_header_found(self): - # Test case 2: No header found - df = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6], "C": [7, 8, 9]}) - self.assertEqual( - guess_header(df), 0 - ) # Header is assumed to be in the first row - - def test_header_found_beyond_max_header_guess(self): - # Test case 3: Header found beyond max_header_guess - df = pd.DataFrame( - {"A": [1, 2, 3], "B": [4, 5, 6], "C": ["Name", "Alice", "Bob"]} - ) - self.assertEqual( - guess_header(df, max_header_guess=2), 0 - ) # Header is assumed to be in the first row - - def test_empty_dataframe(self): - # Test case 4: Empty dataframe - df = pd.DataFrame() - self.assertEqual( - guess_header(df), 0 - ) # Header is assumed to be in the first row - - def test_all_columns_are_strings_not_in_header_row(self): - # Test case 5: All columns are strings but not in header row - df = pd.DataFrame( - {"A": ["1", "2", "3"], "B": ["4", "5", "6"], "C": ["7", "8", "9"]} - ) - self.assertEqual( - guess_header(df), len(df) - 1 - ) # Header is assumed to be in the last row - - class TestFilenameExtraction(unittest.TestCase): def test_correct_file(self): filename = "indicator_2-2022.xlsx" diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index c2c0c6391..a9f78822b 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -89,7 +89,7 @@ def treat_uf_tipo(file: str) -> pl.DataFrame: # TODO: Aqui você invoca o capeta e chama o R pra ler e salvar isso como df. Isso é ridículo mas funcionou. df = call_r_to_read_file(file) - new_df = change_df_header(df, guess_header(df)) + new_df = change_df_header(df, guess_header(df=df, type_of_file="UF")) # This is ad hoc for UF_tipo. new_df.rename( columns={new_df.columns[0]: "sigla_uf"}, inplace=True diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index 8f2bb3913..4c0e4db7b 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -57,7 +57,9 @@ UF_TIPO_HEADER = constants.UF_TIPO_HEADER.value -def guess_header(df: pd.DataFrame, max_header_guess: int = 10) -> int: +def guess_header( + df: pd.DataFrame, type_of_file: str, max_header_guess: int = 10 +) -> int: """Function to deal with problematic dataframes coming from Excel/CSV files. Tries to guess which row is the header by examining the first few rows (max given by max_header_guess). Assumes that the header is the first row where all of the columns are strings. @@ -70,6 +72,12 @@ def guess_header(df: pd.DataFrame, max_header_guess: int = 10) -> int: Returns: int: Index of the row where the header is contained. """ + if type_of_file == "UF": + expected_header = UF_TIPO_HEADER + elif type_of_file == "Municipio": + pass + else: + raise ValueError("Unrecognized type of dataframe.") header_guess = 0 while header_guess < max_header_guess: if len(df) - 1 < header_guess: @@ -78,10 +86,10 @@ def guess_header(df: pd.DataFrame, max_header_guess: int = 10) -> int: # if is_int_row(df.iloc[header_guess]): current_row = df.iloc[header_guess].to_list() equal_column_names = [ - (x, y) for x, y in zip(UF_TIPO_HEADER, current_row) if x == y + (x, y) for x, y in zip(expected_header, current_row) if x == y ] if ( - len(equal_column_names) / len(UF_TIPO_HEADER) > 0.7 + len(equal_column_names) / len(expected_header) > 0.7 ): # If 70% of the columns match, this is the header. return header_guess header_guess += 1 From c65d8041b3b033f6a117bace7ce14bb4eda1ef51 Mon Sep 17 00:00:00 2001 From: Tamir Date: Fri, 19 May 2023 01:31:42 -0300 Subject: [PATCH 154/265] Fixed function call --- pipelines/datasets/br_denatran_frota/tasks_test.py | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/tasks_test.py b/pipelines/datasets/br_denatran_frota/tasks_test.py index 2ed66f8bb..61412da50 100644 --- a/pipelines/datasets/br_denatran_frota/tasks_test.py +++ b/pipelines/datasets/br_denatran_frota/tasks_test.py @@ -69,9 +69,7 @@ def tearDown(self): def test_treat_files_uf_tipo(self, month, year): crawl(month, year, self.temp_dir.name) directory_to_search = os.path.join(self.temp_dir.name, "files", f"{year}") - get_desired_file( - year, - ) + get_desired_file(year, self.temp_dir.name, UF_TIPO_BASIC_FILENAME) for file in os.listdir(directory_to_search): if re.search(UF_TIPO_BASIC_FILENAME, file) and file.split(".")[-1] in [ "xls", From ae14b15c54880f3e325cf4fc8bed647553376cce Mon Sep 17 00:00:00 2001 From: Tamir Date: Fri, 19 May 2023 01:43:18 -0300 Subject: [PATCH 155/265] Create function for UF Tipo and handler --- .../code/frota_municipio_tipo.py | 53 ++++++++++--------- .../datasets/br_denatran_frota/handlers.py | 35 +++++++++++- 2 files changed, 61 insertions(+), 27 deletions(-) diff --git a/br_denatran_frota/code/frota_municipio_tipo.py b/br_denatran_frota/code/frota_municipio_tipo.py index 00f387618..3406559f1 100644 --- a/br_denatran_frota/code/frota_municipio_tipo.py +++ b/br_denatran_frota/code/frota_municipio_tipo.py @@ -12,9 +12,6 @@ verify_total, ) from br_denatran_frota.code.constants import DICT_UFS, SUBSTITUTIONS - -## TODO: Extract everything then run this? Create prefect? where to go now - import basedosdados as bd @@ -44,28 +41,32 @@ def verify_uf(denatran_df: pl.DataFrame, ibge_df: pl.DataFrame, uf: str) -> None match_ibge(denatran_uf, ibge_uf) -municipios_query = """SELECT nome, id_municipio, sigla_uf FROM `basedosdados.br_bd_diretorios_brasil.municipio` -""" -bd_municipios = bd.read_sql(municipios_query, "tamir-pipelines") -bd_municipios = pl.from_pandas(bd_municipios) +def treat_municipio_tipo(file: str): + municipios_query = """SELECT nome, id_municipio, sigla_uf FROM `basedosdados.br_bd_diretorios_brasil.municipio` + """ + bd_municipios = bd.read_sql( + municipios_query, "tamir-pipelines" + ) # Hardcoded, not good. + bd_municipios = pl.from_pandas(bd_municipios) -file = "br_denatran_frota/files/2022/frota_por_município_e_tipo_2-2022.xls" # Hardcode problem -filename = os.path.split(file)[1] -df = pd.read_excel(file) -new_df = change_df_header(df, guess_header(df)) -new_df.rename( - columns={new_df.columns[0]: "sigla_uf", new_df.columns[1]: "nome_denatran"}, - inplace=True, -) # Rename for ease of use. -new_df.sigla_uf = new_df.sigla_uf.str.strip() # Remove whitespace. -new_df = pl.from_pandas(new_df) -new_df = new_df.with_columns(pl.col("nome_denatran").apply(asciify).str.to_lowercase()) -new_df = new_df.filter(pl.col("nome_denatran") != "municipio nao informado") -if new_df.shape[0] > bd_municipios.shape[0]: - raise ValueError( - f"Atenção: a base do Denatran tem {new_df.shape[0]} linhas e isso é mais municípios do que a BD com {bd_municipios.shape[0]}" + # filename = os.path.split(file)[1] + df = pd.read_excel(file) + new_df = change_df_header(df, guess_header(df)) + new_df.rename( + columns={new_df.columns[0]: "sigla_uf", new_df.columns[1]: "nome_denatran"}, + inplace=True, + ) # Rename for ease of use. + new_df.sigla_uf = new_df.sigla_uf.str.strip() # Remove whitespace. + new_df = pl.from_pandas(new_df) + new_df = new_df.with_columns( + pl.col("nome_denatran").apply(asciify).str.to_lowercase() ) - -verify_total(new_df) -for uf in DICT_UFS: - verify_uf(new_df, bd_municipios, uf) + new_df = new_df.filter(pl.col("nome_denatran") != "municipio nao informado") + if new_df.shape[0] > bd_municipios.shape[0]: + raise ValueError( + f"Atenção: a base do Denatran tem {new_df.shape[0]} linhas e isso é mais municípios do que a BD com {bd_municipios.shape[0]}" + ) + verify_total(new_df) + for uf in DICT_UFS: + verify_uf(new_df, bd_municipios, uf) + return new_df diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index a9f78822b..11874b12e 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -4,9 +4,9 @@ This is merely a way to have functions that are called by tasks but can be tested with unit tests and debugging. """ -from prefect import task import os import re +import basedosdados as bd from pipelines.datasets.br_denatran_frota.constants import constants from pipelines.datasets.br_denatran_frota.utils import ( make_dir_when_not_exists, @@ -19,9 +19,11 @@ download_file, extraction_pre_2012, call_r_to_read_file, + verify_uf, ) import pandas as pd import polars as pl +from string_utils import asciify from zipfile import ZipFile from pipelines.utils.utils import ( clean_dataframe, @@ -136,3 +138,34 @@ def get_desired_file(year: int, download_directory: str, filetype: str) -> str: log(f"File: {file}") return os.path.join(directory_to_search, file) raise ValueError("No files found buckaroo") + + +def treat_municipio_tipo(file: str): + municipios_query = """SELECT nome, id_municipio, sigla_uf FROM `basedosdados.br_bd_diretorios_brasil.municipio` + """ + bd_municipios = bd.read_sql( + municipios_query, "tamir-pipelines" + ) # Hardcoded, not good. + bd_municipios = pl.from_pandas(bd_municipios) + + # filename = os.path.split(file)[1] + df = pd.read_excel(file) + new_df = change_df_header(df, guess_header(df)) + new_df.rename( + columns={new_df.columns[0]: "sigla_uf", new_df.columns[1]: "nome_denatran"}, + inplace=True, + ) # Rename for ease of use. + new_df.sigla_uf = new_df.sigla_uf.str.strip() # Remove whitespace. + new_df = pl.from_pandas(new_df) + new_df = new_df.with_columns( + pl.col("nome_denatran").apply(asciify).str.to_lowercase() + ) + new_df = new_df.filter(pl.col("nome_denatran") != "municipio nao informado") + if new_df.shape[0] > bd_municipios.shape[0]: + raise ValueError( + f"Atenção: a base do Denatran tem {new_df.shape[0]} linhas e isso é mais municípios do que a BD com {bd_municipios.shape[0]}" + ) + verify_total(new_df) + for uf in DICT_UFS: + verify_uf(new_df, bd_municipios, uf) + return new_df From a7c9ae97e84586c29fdd1b1a9a6cb803d881150d Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 21 May 2023 05:02:22 -0300 Subject: [PATCH 156/265] Adds docstring checker for linting --- poetry.lock | 34 ++++++++++++++++++++++++++++++++-- pyproject.toml | 1 + 2 files changed, 33 insertions(+), 2 deletions(-) diff --git a/poetry.lock b/poetry.lock index 0d7b69689..d151760db 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.4.2 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.4.1 and should not be changed by hand. [[package]] name = "appnope" @@ -2914,6 +2914,24 @@ google-auth = "*" google-auth-oauthlib = "*" setuptools = "*" +[[package]] +name = "pydocstyle" +version = "6.3.0" +description = "Python docstring style checker" +category = "dev" +optional = false +python-versions = ">=3.6" +files = [ + {file = "pydocstyle-6.3.0-py3-none-any.whl", hash = "sha256:118762d452a49d6b05e194ef344a55822987a462831ade91ec5c06fd2169d019"}, + {file = "pydocstyle-6.3.0.tar.gz", hash = "sha256:7ce43f0c0ac87b07494eb9c0b462c0b73e6ff276807f204d6b53edc72b7e44e1"}, +] + +[package.dependencies] +snowballstemmer = ">=2.2.0" + +[package.extras] +toml = ["tomli (>=1.2.3)"] + [[package]] name = "pygments" version = "2.15.1" @@ -3594,6 +3612,18 @@ files = [ {file = "six-1.16.0.tar.gz", hash = "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926"}, ] +[[package]] +name = "snowballstemmer" +version = "2.2.0" +description = "This package provides 29 stemmers for 28 languages generated from Snowball algorithms." +category = "dev" +optional = false +python-versions = "*" +files = [ + {file = "snowballstemmer-2.2.0-py2.py3-none-any.whl", hash = "sha256:c8e1716e83cc398ae16824e5572ae04e0d9fc2c6b985fb0f900f5f0c96ecba1a"}, + {file = "snowballstemmer-2.2.0.tar.gz", hash = "sha256:09b16deb8547d3412ad7b590689584cd0fe25ec8db3be37788be3810cbf19cb1"}, +] + [[package]] name = "sortedcontainers" version = "2.4.0" @@ -4073,4 +4103,4 @@ testing = ["big-O", "flake8 (<5)", "jaraco.functools", "jaraco.itertools", "more [metadata] lock-version = "2.0" python-versions = ">=3.8,<3.11" -content-hash = "b71c70a89ed59dde03e0fb6cfbd9128e21edfa21a161f5a52c8fc5b28ed187f5" +content-hash = "88418bb0e507f91de17af411b1da5cc9e6709f4a993442e23a1828fd1301d95f" diff --git a/pyproject.toml b/pyproject.toml index 7997830df..0e8f3db01 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -118,6 +118,7 @@ typer = "<=0.4.0" pytest = "^7.2.2" parameterized = "^0.9.0" ipykernel = "^6.22.0" +pydocstyle = "^6.3.0" [build-system] From bb8c9ab26801a73e693d10778591525ce49a96ab Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 21 May 2023 05:02:40 -0300 Subject: [PATCH 157/265] General cleanup --- .../datasets/br_denatran_frota/handlers.py | 4 +- pipelines/datasets/br_denatran_frota/utils.py | 41 +++++++++++++++---- 2 files changed, 35 insertions(+), 10 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 11874b12e..42e4997c2 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -18,7 +18,7 @@ call_downloader, download_file, extraction_pre_2012, - call_r_to_read_file, + call_r_to_read_excel, verify_uf, ) import pandas as pd @@ -89,7 +89,7 @@ def treat_uf_tipo(file: str) -> pl.DataFrame: df = pd.read_excel(file, sheet_name=correct_sheet) except UnicodeDecodeError: # TODO: Aqui você invoca o capeta e chama o R pra ler e salvar isso como df. Isso é ridículo mas funcionou. - df = call_r_to_read_file(file) + df = call_r_to_read_excel(file) new_df = change_df_header(df, guess_header(df=df, type_of_file="UF")) # This is ad hoc for UF_tipo. diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index 4c0e4db7b..e472db098 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -257,6 +257,14 @@ def download_file(url, filename): def generic_extractor(dest_path_file: str): + """_summary_ + + Args: + dest_path_file (str): _description_ + + Raises: + ValueError: _description_ + """ extension = dest_path_file.split(".")[-1] if extension == "rar": extractor_function = RarFile @@ -387,8 +395,15 @@ def extract_links_post_2012(month: int, year: int, directory: str) -> list[dict] def extraction_pre_2012(month: int, year: int, year_dir_name: str, zip_file: str): + """_summary_ + + Args: + month (int): _description_ + year (int): _description_ + year_dir_name (str): _description_ + zip_file (str): _description_ + """ # Aí depois eu preciso andar pelo zip: - print("Bom dia") with ZipFile(zip_file, "r") as g: compressed_files = [file for file in g.infolist() if not file.is_dir()] new_filename = None @@ -407,10 +422,9 @@ def extraction_pre_2012(month: int, year: int, year_dir_name: str, zip_file: str if new_filename: g.extract(file, path=year_dir_name) os.rename(f"{year_dir_name}/{file.filename}", new_filename) - print("Bom dia") -def make_dir_when_not_exists(dir_name: str): +def make_dir_when_not_exists(dir_name: str) -> None: """Auxiliary function to create a subdirectory when it is not present. Args: @@ -418,10 +432,21 @@ def make_dir_when_not_exists(dir_name: str): """ if not os.path.exists(dir_name): os.makedirs(dir_name) + return None + +def call_r_to_read_excel(file: str) -> pd.DataFrame: + """Use rpy2 to call R's readxl for problematic Excel files and then keep reading them as dataframes. -def call_r_to_read_file(file: str) -> pd.DataFrame: - # Install and load the required R packages + Args: + file (str): The full filepath that needs to be opened. + + Raises: + ValueError: If the desired file is not an actual file. + + Returns: + pd.DataFrame: Returns a pandas dataframe with the excel file's content. + """ if not os.path.isfile(file): raise ValueError("Invalid file") packages = ("readxl",) @@ -441,7 +466,6 @@ def call_r_to_read_file(file: str) -> pd.DataFrame: """ ) - # Convert the R dataframe to a pandas dataframe df = robjects.r["df"] df = pd.DataFrame(dict(zip(df.names, list(df)))) @@ -449,7 +473,8 @@ def call_r_to_read_file(file: str) -> pd.DataFrame: def verify_uf(denatran_df: pl.DataFrame, ibge_df: pl.DataFrame, uf: str) -> None: - """Function to take the DENATRAN data at municipality level and compare it to the IBGE data. + """Take the DENATRAN data at municipality level and compare it to the IBGE data. + This will filter by the uf argument and do all comparisons to ensure consistency. Args: @@ -459,7 +484,7 @@ def verify_uf(denatran_df: pl.DataFrame, ibge_df: pl.DataFrame, uf: str) -> None Raises: ValueError: If there are somehow municipalities in the DENATRAN data that do not exist in the IBGE data. Very unlikely. - ValueError: If there are two municipalities in the DENATRAN data + ValueError: If there are two municipalities in the DENATRAN data with the same IBGE name in the same state. """ denatran_uf = denatran_df.filter(pl.col("sigla_uf") == uf) ibge_uf = ibge_df.filter(pl.col("sigla_uf") == uf) From c45d0459665e2a940c53417aedddf0f9724e784a Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 21 May 2023 15:22:19 -0300 Subject: [PATCH 158/265] Documentations in progress --- pipelines/datasets/br_denatran_frota/utils.py | 56 ++++++++++++------- 1 file changed, 36 insertions(+), 20 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index e472db098..6cd6f083f 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -60,17 +60,18 @@ def guess_header( df: pd.DataFrame, type_of_file: str, max_header_guess: int = 10 ) -> int: - """Function to deal with problematic dataframes coming from Excel/CSV files. - Tries to guess which row is the header by examining the first few rows (max given by max_header_guess). - Assumes that the header is the first row where all of the columns are strings. - This will NOT properly work for a strings only dataframe and will always guess the first row for it. + """Search for expected header in dataframe. Args: - df (pd.DataFrame): Dataframe whose header we don't know. - max_header_guess (int, optional): Number of initial rows we want to check. Defaults to 4. + df (pd.DataFrame): Dataframe whose header we don't know + type_of_file (str): _description_ + max_header_guess (int, optional): _description_. Defaults to 10. + + Raises: + ValueError: _description_ Returns: - int: Index of the row where the header is contained. + int: _description_ """ if type_of_file == "UF": expected_header = UF_TIPO_HEADER @@ -82,8 +83,6 @@ def guess_header( while header_guess < max_header_guess: if len(df) - 1 < header_guess: break - # If this row minus the first column can be converted to int, then - # if is_int_row(df.iloc[header_guess]): current_row = df.iloc[header_guess].to_list() equal_column_names = [ (x, y) for x, y in zip(expected_header, current_row) if x == y @@ -128,7 +127,7 @@ def is_int_row(row): def get_year_month_from_filename(filename: str) -> tuple[int, int]: - """Helper to extract month and year information from files named indicator_month-year.xls + """Extract month and year information from files named indicator_month-year.xls. Args: filename (str): Name of the file. @@ -149,7 +148,8 @@ def get_year_month_from_filename(filename: str) -> tuple[int, int]: def verify_total(df: pl.DataFrame) -> None: - """Helper function that is meant to act as a guard to guarantee that we can pivot from wide to long. + """Verify that we can pivot from wide to long. + Essentially, gets a Wide dataframe, excludes all string columns and the TOTAL column and sums it all row wise. Then verifies if the calculated total column is the same as the TOTAL column. If not, raises an error. @@ -174,7 +174,8 @@ def verify_total(df: pl.DataFrame) -> None: def fix_suggested_nome_ibge(row: tuple[str, ...]) -> str: - """Gets a row from a dataframe and applies the SUBSTITUTIONS constant ruleset where applicable. + """Get a row from a dataframe and applies the SUBSTITUTIONS constant ruleset where applicable. + This fixes the dataframe to have the names of municipalities according to IBGE. The fixes are necessary because match_ibge() will fail where the DENATRAN data has typos in city names. @@ -197,7 +198,8 @@ def fix_suggested_nome_ibge(row: tuple[str, ...]) -> str: def match_ibge(denatran_uf: pl.DataFrame, ibge_uf: pl.DataFrame) -> None: - """Takes a dataframe of the Denatran data and an IBGE dataframe of municipalities. + """Take a dataframe of the Denatran data and an IBGE dataframe of municipalities. + Joins them using the IBGE name of both. The IBGE name of denatran_uf is ideally filled via get_city_name(). This verifies if there are any municipalities in denatran_uf that have no corresponding municipality in the IBGE database. These must be manually fixed via the constants file and the fix_suggested_nome function. @@ -224,7 +226,8 @@ def match_ibge(denatran_uf: pl.DataFrame, ibge_uf: pl.DataFrame) -> None: def get_city_name_ibge(denatran_name: str, ibge_uf: pl.DataFrame) -> str: - """Gets the closest match to the denatran name of the municipality in the IBGE dataframe of the same state. + """Get the closest match to the denatran name of the municipality in the IBGE dataframe of the same state. + This ibge_uf dataframe is pulled directly from Base dos Dados to ensure correctness. Returns either the match or an empty string in case no match is found. @@ -244,7 +247,15 @@ def get_city_name_ibge(denatran_name: str, ibge_uf: pl.DataFrame) -> str: return "" # I don't want this to error out directly, because then I can get all municipalities. -def download_file(url, filename): +def download_file(url: str, filename: str) -> None: + """Download a file from a url using a simple open + get request. + + Only necessary because some problematic URLs report a 404 despite the files being there. + + Args: + url (str): URL where the desired file is located. + filename (str): Filename to write the contents of the HTTP request to. + """ # Send a GET request to the URL new_url = url.replace("arquivos-denatran", "arquivos-senatran") @@ -257,13 +268,13 @@ def download_file(url, filename): def generic_extractor(dest_path_file: str): - """_summary_ + """Extract the desired DENATRAN compressed files from .rar or .zip file. Args: - dest_path_file (str): _description_ + dest_path_file (str): Filepath of the compressed file whose contents should be extracted. Raises: - ValueError: _description_ + ValueError: If the passed argument is not a .rar or .zip file. """ extension = dest_path_file.split(".")[-1] if extension == "rar": @@ -291,7 +302,7 @@ def generic_extractor(dest_path_file: str): def make_filename(i: dict, ext: bool = True) -> str: - """Creates the filename using the sent dictionary. + """Create the filename using the sent dictionary. Args: i (dict): Dictionary with all the file's info. @@ -317,6 +328,11 @@ def make_filename(i: dict, ext: bool = True) -> str: def call_downloader(i: dict): + """Call other download functions in the correct order according to filetype. + + Args: + i (dict): Dictionary with the file's information. + """ filename = make_filename(i) if i["filetype"] in ["xlsx", "xls"]: download_file(i["href"], filename) @@ -358,7 +374,7 @@ def make_filename_pre_2012( def extract_links_post_2012(month: int, year: int, directory: str) -> list[dict]: - """Extracts links of the Denatran files post 2012. + """Extract links of the Denatran files post 2012. Args: year (int): A year starting from 2013 onwards. From 9baf53098d8a729cee69b26b3d6915ebff039ffd Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 21 May 2023 15:24:29 -0300 Subject: [PATCH 159/265] More cleanup --- pipelines/datasets/br_denatran_frota/utils.py | 27 ------------------- 1 file changed, 27 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index 6cd6f083f..6a5c1a48e 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -3,33 +3,6 @@ General purpose functions for the br_denatran_frota project """ -############################################################################### -# -# Esse é um arquivo onde podem ser declaratas funções que serão usadas -# pelo projeto br_denatran_frota. -# -# Por ser um arquivo opcional, pode ser removido sem prejuízo ao funcionamento -# do projeto, caos não esteja em uso. -# -# Para declarar funções, basta fazer em código Python comum, como abaixo: -# -# ``` -# def foo(): -# """ -# Function foo -# """ -# print("foo") -# ``` -# -# Para usá-las, basta fazer conforme o exemplo abaixo: -# -# ```py -# from pipelines.datasets.br_denatran_frota.utils import foo -# foo() -# ``` -# -############################################################################### -# -*- coding: utf-8 -*- import pandas as pd import polars as pl import difflib From 570ce51dfad9b1def4fc20138743fc357ce98261 Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 21 May 2023 15:53:54 -0300 Subject: [PATCH 160/265] Using enums + cleanup --- .../datasets/br_denatran_frota/handlers.py | 11 ++++---- pipelines/datasets/br_denatran_frota/utils.py | 27 ++++++++++++------- 2 files changed, 23 insertions(+), 15 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 42e4997c2..b1338cfca 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -1,6 +1,7 @@ # -*- coding: utf-8 -*- """ -Handlers for br_denatran_frota +Handlers for br_denatran_frota. + This is merely a way to have functions that are called by tasks but can be tested with unit tests and debugging. """ @@ -20,6 +21,7 @@ extraction_pre_2012, call_r_to_read_excel, verify_uf, + DenatranType, ) import pandas as pd import polars as pl @@ -88,10 +90,9 @@ def treat_uf_tipo(file: str) -> pl.DataFrame: ][0] df = pd.read_excel(file, sheet_name=correct_sheet) except UnicodeDecodeError: - # TODO: Aqui você invoca o capeta e chama o R pra ler e salvar isso como df. Isso é ridículo mas funcionou. df = call_r_to_read_excel(file) - new_df = change_df_header(df, guess_header(df=df, type_of_file="UF")) + new_df = change_df_header(df, guess_header(df=df, type_of_file=DenatranType.UF)) # This is ad hoc for UF_tipo. new_df.rename( columns={new_df.columns[0]: "sigla_uf"}, inplace=True @@ -140,7 +141,7 @@ def get_desired_file(year: int, download_directory: str, filetype: str) -> str: raise ValueError("No files found buckaroo") -def treat_municipio_tipo(file: str): +def treat_municipio_tipo(file: str) -> pl.DataFrame: municipios_query = """SELECT nome, id_municipio, sigla_uf FROM `basedosdados.br_bd_diretorios_brasil.municipio` """ bd_municipios = bd.read_sql( @@ -150,7 +151,7 @@ def treat_municipio_tipo(file: str): # filename = os.path.split(file)[1] df = pd.read_excel(file) - new_df = change_df_header(df, guess_header(df)) + new_df = change_df_header(df, guess_header(df), DenatranType.Municipio) new_df.rename( columns={new_df.columns[0]: "sigla_uf", new_df.columns[1]: "nome_denatran"}, inplace=True, diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index 6a5c1a48e..80c0172b7 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -1,6 +1,6 @@ # -*- coding: utf-8 -*- """ -General purpose functions for the br_denatran_frota project +General purpose functions for the br_denatran_frota project. """ import pandas as pd @@ -18,6 +18,7 @@ import rpy2.robjects.packages as rpackages import rpy2.robjects as robjects from rpy2.robjects.vectors import StrVector +from enum import Enum DICT_UFS = constants.DICT_UFS.value @@ -30,8 +31,13 @@ UF_TIPO_HEADER = constants.UF_TIPO_HEADER.value +class DenatranType(Enum): + Municipio = "Municipio" + UF = "UF" + + def guess_header( - df: pd.DataFrame, type_of_file: str, max_header_guess: int = 10 + df: pd.DataFrame, type_of_file: DenatranType, max_header_guess: int = 10 ) -> int: """Search for expected header in dataframe. @@ -46,9 +52,9 @@ def guess_header( Returns: int: _description_ """ - if type_of_file == "UF": + if type_of_file == DenatranType.UF: expected_header = UF_TIPO_HEADER - elif type_of_file == "Municipio": + elif type_of_file == DenatranType.Municipio: pass else: raise ValueError("Unrecognized type of dataframe.") @@ -69,7 +75,8 @@ def guess_header( def change_df_header(df: pd.DataFrame, header_row: int) -> pd.DataFrame: - """Changes the dataframe's header to a row inside of it and returns the corrected df. + """Change the dataframe's header to a row inside of it and returns the corrected df. + Ideally, to be used in conjunction with guess_header(). Args: df (pd.DataFrame): Dataframe whose header we want changed. @@ -317,13 +324,13 @@ def call_downloader(i: dict): def make_filename_pre_2012( type_of_file: str, year: int, filename: str, year_dir_name: str, month: int ): - if type_of_file == "Tipo": + if type_of_file == DenatranType.UF: basic_filename = UF_TIPO_BASIC_FILENAME if year > 2005: regex_to_search = r"UF\s+([^\s\d]+\s*)*([12]\d{3})" else: regex_to_search = rf"UF[_\s]?([^\s\d]+\s*)_{str(year)[2:4]}" - elif type_of_file == "Munic": + elif type_of_file == DenatranType.Municipio: basic_filename = MUNIC_TIPO_BASIC_FILENAME if year > 2003: regex_to_search = rf"Munic\.?\s*(.*?)\s*\.?{year}" @@ -333,7 +340,7 @@ def make_filename_pre_2012( raise ValueError match = re.search(regex_to_search, filename) if match: - if (year == 2004 or year == 2005) and type_of_file == "Munic": + if (year == 2004 or year == 2005) and type_of_file == DenatranType.Municipio: month_value = int(match.group(1)) else: month_in_file = match.group(1).lower().replace(".", "") @@ -402,11 +409,11 @@ def extraction_pre_2012(month: int, year: int, year_dir_name: str, zip_file: str r"Tipo[-\s]UF", zip_file.split("/")[-1] ): new_filename = make_filename_pre_2012( - "Tipo", year, filename, year_dir_name, month + DenatranType.UF, year, filename, year_dir_name, month ) elif re.search(r"Mun\w*", filename, re.IGNORECASE): new_filename = make_filename_pre_2012( - "Munic", year, filename, year_dir_name, month + DenatranType.Municipio, year, filename, year_dir_name, month ) if new_filename: g.extract(file, path=year_dir_name) From 4fea4ed65afea338a4517217c4d5210b319d5acf Mon Sep 17 00:00:00 2001 From: Tamir Date: Mon, 22 May 2023 03:57:55 -0300 Subject: [PATCH 161/265] 2023 works for treating municipality --- .../datasets/br_denatran_frota/constants.py | 27 ++++++++++++++++++ .../datasets/br_denatran_frota/handlers.py | 28 +++++++++++-------- .../datasets/br_denatran_frota/tasks_test.py | 19 +++++++++++++ pipelines/datasets/br_denatran_frota/utils.py | 22 +++++++++------ 4 files changed, 76 insertions(+), 20 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/constants.py b/pipelines/datasets/br_denatran_frota/constants.py index 515002d56..4583c6c72 100644 --- a/pipelines/datasets/br_denatran_frota/constants.py +++ b/pipelines/datasets/br_denatran_frota/constants.py @@ -135,3 +135,30 @@ class constants(Enum): # pylint: disable=c0103 "TRICICLO", "UTILITÁRIO", ] + + MUNICIPIO_TIPO_HEADER = [ + "UF", + "MUNICIPIO", + "TOTAL", + "AUTOMÓVEL", + "BONDE", + "CAMINHÃO", + "CAMINHÃO TRATOR", + "CAMINHONETE", + "CAMIONETA", + "CHASSI PLATAFORMA", + "CICLOMOTOR", + "MICROÔNIBUS", + "MOTOCICLETA", + "MOTONETA", + "ÔNIBUS", + "QUADRICICLO", + "REBOQUE", + "SEMI-REBOQUE", + "SIDE-CAR", + "OUTROS", + "TRATOR ESTEIRA", + "TRATOR RODAS", + "TRICICLO", + "UTILITÁRIO", + ] diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index b1338cfca..aaf525856 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -20,7 +20,7 @@ download_file, extraction_pre_2012, call_r_to_read_excel, - verify_uf, + treat_uf, DenatranType, ) import pandas as pd @@ -149,24 +149,28 @@ def treat_municipio_tipo(file: str) -> pl.DataFrame: ) # Hardcoded, not good. bd_municipios = pl.from_pandas(bd_municipios) - # filename = os.path.split(file)[1] + filename = os.path.split(file)[1] + month, year = get_year_month_from_filename(filename) df = pd.read_excel(file) - new_df = change_df_header(df, guess_header(df), DenatranType.Municipio) + new_df = change_df_header(df, guess_header(df, DenatranType.Municipio)) new_df.rename( columns={new_df.columns[0]: "sigla_uf", new_df.columns[1]: "nome_denatran"}, inplace=True, ) # Rename for ease of use. new_df.sigla_uf = new_df.sigla_uf.str.strip() # Remove whitespace. - new_df = pl.from_pandas(new_df) - new_df = new_df.with_columns( - pl.col("nome_denatran").apply(asciify).str.to_lowercase() + new_pl_df = pl.from_pandas(new_df) + verify_total(new_pl_df) + new_pl_df = new_pl_df.with_columns( + pl.col("nome_denatran").apply(asciify).str.to_lowercase(), + pl.lit(year, dtype=pl.Int64).alias("ano"), + pl.lit(month, dtype=pl.Int64).alias("mes"), ) - new_df = new_df.filter(pl.col("nome_denatran") != "municipio nao informado") - if new_df.shape[0] > bd_municipios.shape[0]: + new_pl_df = new_pl_df.filter(pl.col("nome_denatran") != "municipio nao informado") + if new_pl_df.shape[0] > bd_municipios.shape[0]: raise ValueError( - f"Atenção: a base do Denatran tem {new_df.shape[0]} linhas e isso é mais municípios do que a BD com {bd_municipios.shape[0]}" + f"Atenção: a base do Denatran tem {new_pl_df.shape[0]} linhas e isso é mais municípios do que a BD com {bd_municipios.shape[0]}" ) - verify_total(new_df) + dfs = [] for uf in DICT_UFS: - verify_uf(new_df, bd_municipios, uf) - return new_df + dfs.append(treat_uf(new_pl_df, bd_municipios, uf)) + return pl.concat(dfs) diff --git a/pipelines/datasets/br_denatran_frota/tasks_test.py b/pipelines/datasets/br_denatran_frota/tasks_test.py index 61412da50..613464e68 100644 --- a/pipelines/datasets/br_denatran_frota/tasks_test.py +++ b/pipelines/datasets/br_denatran_frota/tasks_test.py @@ -11,6 +11,7 @@ crawl, treat_uf_tipo, get_desired_file, + treat_municipio_tipo, ) from pipelines.datasets.br_denatran_frota.constants import constants @@ -78,6 +79,24 @@ def test_treat_files_uf_tipo(self, month, year): treated_df = treat_uf_tipo(os.path.join(directory_to_search, file)) self.assertEqual(len(treated_df), 21 * 27) + @parameterized.expand( + [(month, year) for year in range(2003, 2024) for month in range(1, 2)], + name_func=custom_name_func, + ) + def test_treat_files_municipio_tipo(self, month, year): + crawl(month, year, self.temp_dir.name) + directory_to_search = os.path.join(self.temp_dir.name, "files", f"{year}") + get_desired_file(year, self.temp_dir.name, MUNIC_TIPO_BASIC_FILENAME) + for file in os.listdir(directory_to_search): + if re.search(MUNIC_TIPO_BASIC_FILENAME, file) and file.split(".")[-1] in [ + "xls", + "xlsx", + ]: + treated_df = treat_municipio_tipo( + os.path.join(directory_to_search, file) + ) + self.assertEqual(len(treated_df), 5570) + def test_flow(self): year = 2021 crawl(month=2, year=year, temp_dir=constants.DOWNLOAD_PATH.value) diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index 80c0172b7..c0ecfee33 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -29,6 +29,7 @@ MONTHS_SHORT = constants.MONTHS_SHORT.value MUNIC_TIPO_BASIC_FILENAME = constants.MUNIC_TIPO_BASIC_FILENAME.value UF_TIPO_HEADER = constants.UF_TIPO_HEADER.value +MUNICIPIO_TIPO_HEADER = constants.MUNICIPIO_TIPO_HEADER.value class DenatranType(Enum): @@ -55,7 +56,7 @@ def guess_header( if type_of_file == DenatranType.UF: expected_header = UF_TIPO_HEADER elif type_of_file == DenatranType.Municipio: - pass + expected_header = MUNICIPIO_TIPO_HEADER else: raise ValueError("Unrecognized type of dataframe.") header_guess = 0 @@ -67,8 +68,8 @@ def guess_header( (x, y) for x, y in zip(expected_header, current_row) if x == y ] if ( - len(equal_column_names) / len(expected_header) > 0.7 - ): # If 70% of the columns match, this is the header. + len(equal_column_names) / len(expected_header) >= 0.6 + ): # If 60% of the columns match, this is the header. return header_guess header_guess += 1 return 0 # If nothing is ever found until the max, let's just assume it's the first row as per usual. @@ -177,7 +178,7 @@ def fix_suggested_nome_ibge(row: tuple[str, ...]) -> str: return row[-1] -def match_ibge(denatran_uf: pl.DataFrame, ibge_uf: pl.DataFrame) -> None: +def verify_match_ibge(denatran_uf: pl.DataFrame, ibge_uf: pl.DataFrame) -> None: """Take a dataframe of the Denatran data and an IBGE dataframe of municipalities. Joins them using the IBGE name of both. The IBGE name of denatran_uf is ideally filled via get_city_name(). @@ -468,7 +469,7 @@ def call_r_to_read_excel(file: str) -> pd.DataFrame: return df -def verify_uf(denatran_df: pl.DataFrame, ibge_df: pl.DataFrame, uf: str) -> None: +def treat_uf(denatran_df: pl.DataFrame, ibge_df: pl.DataFrame, uf: str) -> None: """Take the DENATRAN data at municipality level and compare it to the IBGE data. This will filter by the uf argument and do all comparisons to ensure consistency. @@ -486,8 +487,12 @@ def verify_uf(denatran_df: pl.DataFrame, ibge_df: pl.DataFrame, uf: str) -> None ibge_uf = ibge_df.filter(pl.col("sigla_uf") == uf) ibge_uf = ibge_uf.with_columns(pl.col("nome").apply(asciify).str.to_lowercase()) municipios_na_bd = ibge_uf["nome"].to_list() - x = denatran_uf["nome_denatran"].apply(lambda x: get_city_name_ibge(x, ibge_uf)) - denatran_uf = denatran_uf.with_columns(x.alias("suggested_nome_ibge")) + suggested_name_ibge = denatran_uf["nome_denatran"].apply( + lambda x: get_city_name_ibge(x, ibge_uf) + ) + denatran_uf = denatran_uf.with_columns( + suggested_name_ibge.alias("suggested_nome_ibge") + ) denatran_uf = denatran_uf.with_columns( denatran_uf.apply(fix_suggested_nome_ibge)["apply"].alias("suggested_nome_ibge") ) @@ -504,4 +509,5 @@ def verify_uf(denatran_df: pl.DataFrame, ibge_df: pl.DataFrame, uf: str) -> None # This here is probably impossible and shouldn't happen due to the matching coming from the BD data. # The set difference might occur the other way around, but still, better safe. raise ValueError(f"Existem municípios em {uf} que não estão na BD.") - match_ibge(denatran_uf, ibge_uf) + verify_match_ibge(denatran_uf, ibge_uf) + return denatran_uf From 325398ff329a8658dce20abd2af1b224bf4811d7 Mon Sep 17 00:00:00 2001 From: Tamir Date: Mon, 22 May 2023 04:12:53 -0300 Subject: [PATCH 162/265] Working from 2016 onwards --- .../datasets/br_denatran_frota/tasks_test.py | 41 ++++++++++++------- pipelines/datasets/br_denatran_frota/utils.py | 5 ++- 2 files changed, 30 insertions(+), 16 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/tasks_test.py b/pipelines/datasets/br_denatran_frota/tasks_test.py index 613464e68..920a5a646 100644 --- a/pipelines/datasets/br_denatran_frota/tasks_test.py +++ b/pipelines/datasets/br_denatran_frota/tasks_test.py @@ -28,7 +28,7 @@ def custom_name_func(testcase_func, param_num, param): ) -class TestAllPossibleYears(unittest.TestCase): +class TestExtractingAllPossibleYears(unittest.TestCase): def setUp(self): self.temp_dir = tempfile.TemporaryDirectory( dir=os.path.join(f"{DOWNLOAD_PATH}") @@ -53,7 +53,7 @@ def test_extract_denatran_files(self, month, year): self.assertTrue(expected_files.issubset(files)) -class TestTreatmentPostCrawl(unittest.TestCase): +class TestUFTreatmentPostCrawl(unittest.TestCase): def setUp(self): self.temp_dir = tempfile.TemporaryDirectory( dir=os.path.join(f"{DOWNLOAD_PATH}") @@ -79,6 +79,30 @@ def test_treat_files_uf_tipo(self, month, year): treated_df = treat_uf_tipo(os.path.join(directory_to_search, file)) self.assertEqual(len(treated_df), 21 * 27) + def test_flow(self): + year = 2021 + crawl(month=2, year=year, temp_dir=constants.DOWNLOAD_PATH.value) + # Now get the downloaded file: + uf_tipo_file = get_desired_file( + year=year, + download_directory=constants.DOWNLOAD_PATH.value, + filetype=constants.UF_TIPO_BASIC_FILENAME.value, + ) + print(uf_tipo_file) + df = treat_uf_tipo(file=uf_tipo_file) + self.assertTrue(type(df), pl.DataFrame) + + +class TestMunicipioTreatmentPostCrawl(unittest.TestCase): + def setUp(self): + self.temp_dir = tempfile.TemporaryDirectory( + dir=os.path.join(f"{DOWNLOAD_PATH}") + ) + + def tearDown(self): + print("Deleting temporary directory") + shutil.rmtree(self.temp_dir.name) + @parameterized.expand( [(month, year) for year in range(2003, 2024) for month in range(1, 2)], name_func=custom_name_func, @@ -97,19 +121,6 @@ def test_treat_files_municipio_tipo(self, month, year): ) self.assertEqual(len(treated_df), 5570) - def test_flow(self): - year = 2021 - crawl(month=2, year=year, temp_dir=constants.DOWNLOAD_PATH.value) - # Now get the downloaded file: - uf_tipo_file = get_desired_file( - year=year, - download_directory=constants.DOWNLOAD_PATH.value, - filetype=constants.UF_TIPO_BASIC_FILENAME.value, - ) - print(uf_tipo_file) - df = treat_uf_tipo(file=uf_tipo_file) - self.assertTrue(type(df), pl.DataFrame) - if __name__ == "__main__": unittest.main() diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index c0ecfee33..1ad64bc0d 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -53,6 +53,7 @@ def guess_header( Returns: int: _description_ """ + possible_headers = [] if type_of_file == DenatranType.UF: expected_header = UF_TIPO_HEADER elif type_of_file == DenatranType.Municipio: @@ -70,8 +71,10 @@ def guess_header( if ( len(equal_column_names) / len(expected_header) >= 0.6 ): # If 60% of the columns match, this is the header. - return header_guess + possible_headers.append(header_guess) header_guess += 1 + if possible_headers: + return max(possible_headers) return 0 # If nothing is ever found until the max, let's just assume it's the first row as per usual. From ed3343a45b4044fe9c8e9c56f3547778712f6b25 Mon Sep 17 00:00:00 2001 From: Tamir Date: Mon, 22 May 2023 05:18:13 -0300 Subject: [PATCH 163/265] Working from 2014 onwards --- pipelines/datasets/br_denatran_frota/constants.py | 1 + pipelines/datasets/br_denatran_frota/handlers.py | 5 ++++- 2 files changed, 5 insertions(+), 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/constants.py b/pipelines/datasets/br_denatran_frota/constants.py index 4583c6c72..15cbef738 100644 --- a/pipelines/datasets/br_denatran_frota/constants.py +++ b/pipelines/datasets/br_denatran_frota/constants.py @@ -98,6 +98,7 @@ class constants(Enum): # pylint: disable=c0103 ("PB", "santarem"): "joca claudino", ("SP", "embu"): "embu das artes", ("TO", "sao valerio da natividade"): "sao valerio", + ("PB", "campo de santana"): "tacima", } DOWNLOAD_PATH = f"/tmp/input/{DATASET}" diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index aaf525856..d9e990f72 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -151,7 +151,10 @@ def treat_municipio_tipo(file: str) -> pl.DataFrame: filename = os.path.split(file)[1] month, year = get_year_month_from_filename(filename) - df = pd.read_excel(file) + correct_sheet = [ + sheet for sheet in pd.ExcelFile(file).sheet_names if sheet != "Glossário" + ][0] + df = pd.read_excel(file, sheet_name=correct_sheet) new_df = change_df_header(df, guess_header(df, DenatranType.Municipio)) new_df.rename( columns={new_df.columns[0]: "sigla_uf", new_df.columns[1]: "nome_denatran"}, From 2990dd89707bd1cd306190ec3d4c5d94370dd686 Mon Sep 17 00:00:00 2001 From: Tamir Date: Mon, 22 May 2023 06:25:45 -0300 Subject: [PATCH 164/265] 2010 has a total error? --- pipelines/datasets/br_denatran_frota/handlers.py | 11 ++++++++++- pipelines/datasets/br_denatran_frota/tasks_test.py | 7 ++++++- pipelines/datasets/br_denatran_frota/utils.py | 6 +++--- 3 files changed, 19 insertions(+), 5 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index d9e990f72..c84d24374 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -176,4 +176,13 @@ def treat_municipio_tipo(file: str) -> pl.DataFrame: dfs = [] for uf in DICT_UFS: dfs.append(treat_uf(new_pl_df, bd_municipios, uf)) - return pl.concat(dfs) + full_pl_df = pl.concat(dfs) + full_pl_df = full_pl_df.select( + pl.exclude("TOTAL", "suggested_nome_ibge", "nome_denatran") + ) + full_pl_df = full_pl_df.melt( + id_vars=["ano", "mes", "sigla_uf", "id_municipio"], + variable_name="tipo_veiculo", + value_name="quantidade", + ) # Long format. + return full_pl_df diff --git a/pipelines/datasets/br_denatran_frota/tasks_test.py b/pipelines/datasets/br_denatran_frota/tasks_test.py index 920a5a646..56a21e4d9 100644 --- a/pipelines/datasets/br_denatran_frota/tasks_test.py +++ b/pipelines/datasets/br_denatran_frota/tasks_test.py @@ -19,6 +19,7 @@ DOWNLOAD_PATH = constants.DOWNLOAD_PATH.value MUNIC_TIPO_BASIC_FILENAME = constants.MUNIC_TIPO_BASIC_FILENAME.value UF_TIPO_BASIC_FILENAME = constants.UF_TIPO_BASIC_FILENAME.value +DICT_UFS = constants.DICT_UFS.value def custom_name_func(testcase_func, param_num, param): @@ -119,7 +120,11 @@ def test_treat_files_municipio_tipo(self, month, year): treated_df = treat_municipio_tipo( os.path.join(directory_to_search, file) ) - self.assertEqual(len(treated_df), 5570) + self.assertTrue(type(treated_df), pl.DataFrame) + self.assertGreaterEqual(len(treated_df), 5500 * 21) + self.assertSetEqual( + set(treated_df["sigla_uf"].unique().to_list()), set(DICT_UFS.keys()) + ) if __name__ == "__main__": diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index 1ad64bc0d..096b71aba 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -207,6 +207,7 @@ def verify_match_ibge(denatran_uf: pl.DataFrame, ibge_uf: pl.DataFrame) -> None: for row in mismatched_rows.rows(named=True): error_message += f"{row['nome_denatran']} ({row['sigla_uf']})\n" raise ValueError(error_message) + return joined_df def get_city_name_ibge(denatran_name: str, ibge_uf: pl.DataFrame) -> str: @@ -276,7 +277,7 @@ def generic_extractor(dest_path_file: str): for file in f.infolist(): print(file) if ( - re.search("UF|municipio", file.filename, re.IGNORECASE) + re.search("UF|munic", file.filename, re.IGNORECASE) and not file.is_dir() ): new_extension = file.filename.split(".")[-1] @@ -512,5 +513,4 @@ def treat_uf(denatran_df: pl.DataFrame, ibge_df: pl.DataFrame, uf: str) -> None: # This here is probably impossible and shouldn't happen due to the matching coming from the BD data. # The set difference might occur the other way around, but still, better safe. raise ValueError(f"Existem municípios em {uf} que não estão na BD.") - verify_match_ibge(denatran_uf, ibge_uf) - return denatran_uf + return verify_match_ibge(denatran_uf, ibge_uf) From 038bdcae5427d8e58fee973342d5d6da1a20a8a9 Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 23 May 2023 03:10:54 -0300 Subject: [PATCH 165/265] Historical data is messy, adjust util for that --- pipelines/datasets/br_denatran_frota/utils.py | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index 096b71aba..4c46ba45b 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -135,7 +135,8 @@ def verify_total(df: pl.DataFrame) -> None: """Verify that we can pivot from wide to long. Essentially, gets a Wide dataframe, excludes all string columns and the TOTAL column and sums it all row wise. - Then verifies if the calculated total column is the same as the TOTAL column. + Some historical data from Denatran seems to have a rounding error. + Thus, we need to verify if the calculated total column is greater or equal than the original TOTAL column. If not, raises an error. Args: @@ -150,10 +151,10 @@ def verify_total(df: pl.DataFrame) -> None: acc=pl.lit(0), function=lambda acc, x: acc + x, exprs=pl.col("*") ).alias("calculated_total") )["calculated_total"] - mask = df["TOTAL"] == calculated_total - if pl.sum(~mask) != 0: + mask = df["TOTAL"] > calculated_total + if pl.sum(mask) != 0: raise ValueError( - "A coluna de TOTAL da base original tem inconsistências e não é igual à soma das demais colunas." + "A coluna de TOTAL da base original tem inconsistências e é maior que a soma das demais colunas." ) From 1704472f4203936d3810d8a88352fdf022773a2c Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 23 May 2023 04:49:04 -0300 Subject: [PATCH 166/265] More substitutions rules for a lot of messy data --- pipelines/datasets/br_denatran_frota/constants.py | 10 ++++++++++ 1 file changed, 10 insertions(+) diff --git a/pipelines/datasets/br_denatran_frota/constants.py b/pipelines/datasets/br_denatran_frota/constants.py index 15cbef738..034342db8 100644 --- a/pipelines/datasets/br_denatran_frota/constants.py +++ b/pipelines/datasets/br_denatran_frota/constants.py @@ -99,6 +99,16 @@ class constants(Enum): # pylint: disable=c0103 ("SP", "embu"): "embu das artes", ("TO", "sao valerio da natividade"): "sao valerio", ("PB", "campo de santana"): "tacima", + ("AP", "amapari"): "pedra branca do amapari", + ("BA", "maracani"): "macarani", + ("BA", "livramento do brumado"): "livramento de nossa senhora", + ("PB", "sao bento de pombal"): "sao bentinho", + ("PB", "serido"): "sao vicente do serido", + ("PR", "vila alta"): "alto paraiso", + ("RN", "espirito santo do oeste"): "parau", + ("RO", "jamari"): "itapua do oeste", + ("SC", "picarras"): "balneario picarras", + ("SC", "barra do sul"): "balneario barra do sul", } DOWNLOAD_PATH = f"/tmp/input/{DATASET}" From e45fec7e59fcc8edc9238d4d0cf308a47aefa69b Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 23 May 2023 04:49:20 -0300 Subject: [PATCH 167/265] Adjustments for historical data --- pipelines/datasets/br_denatran_frota/handlers.py | 4 ++++ pipelines/datasets/br_denatran_frota/utils.py | 2 +- 2 files changed, 5 insertions(+), 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index c84d24374..07b00aadd 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -155,6 +155,10 @@ def treat_municipio_tipo(file: str) -> pl.DataFrame: sheet for sheet in pd.ExcelFile(file).sheet_names if sheet != "Glossário" ][0] df = pd.read_excel(file, sheet_name=correct_sheet) + # Some very janky historical files have an entire first empty column that will break EVERYTHING + # This checks if they exist and drops them + if df[df.columns[0]].isnull().sum() == len(df): + df.drop(columns=df.columns[0], inplace=True) new_df = change_df_header(df, guess_header(df, DenatranType.Municipio)) new_df.rename( columns={new_df.columns[0]: "sigla_uf", new_df.columns[1]: "nome_denatran"}, diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index 4c46ba45b..862264b29 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -154,7 +154,7 @@ def verify_total(df: pl.DataFrame) -> None: mask = df["TOTAL"] > calculated_total if pl.sum(mask) != 0: raise ValueError( - "A coluna de TOTAL da base original tem inconsistências e é maior que a soma das demais colunas." + "A coluna de TOTAL da base original tem inconsistências e é maior que soma das demais colunas." ) From 5b9642b557b816bbba586022bc1631e5de2c71ae Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 23 May 2023 04:59:05 -0300 Subject: [PATCH 168/265] Treatment works!!!! --- pipelines/datasets/br_denatran_frota/tasks_test.py | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/tasks_test.py b/pipelines/datasets/br_denatran_frota/tasks_test.py index 56a21e4d9..8ff6d1838 100644 --- a/pipelines/datasets/br_denatran_frota/tasks_test.py +++ b/pipelines/datasets/br_denatran_frota/tasks_test.py @@ -120,11 +120,16 @@ def test_treat_files_municipio_tipo(self, month, year): treated_df = treat_municipio_tipo( os.path.join(directory_to_search, file) ) + # It should be a df, self.assertTrue(type(treated_df), pl.DataFrame) - self.assertGreaterEqual(len(treated_df), 5500 * 21) + # Every state should be there self.assertSetEqual( set(treated_df["sigla_uf"].unique().to_list()), set(DICT_UFS.keys()) ) + # I expect AT LEAST 5450 cities out of 5570. It's normally higher but historical data. + self.assertGreaterEqual( + len(treated_df["id_municipio"].unique().to_list()), 5450 + ) if __name__ == "__main__": From cbe964df3fc4e80dc8930d5a6be8439b6ceabded Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 24 May 2023 01:26:50 -0300 Subject: [PATCH 169/265] Flow is done --- pipelines/datasets/br_denatran_frota/flows.py | 109 ++++++++++++++++-- pipelines/datasets/br_denatran_frota/tasks.py | 6 + .../datasets/br_denatran_frota/tasks_test.py | 13 +++ 3 files changed, 118 insertions(+), 10 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index bd2326ea2..755002185 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -84,6 +84,7 @@ treat_uf_tipo_task, output_file_to_csv_task, get_desired_file_task, + treat_municipio_tipo_task, ) from pipelines.datasets.br_denatran_frota.constants import constants @@ -118,24 +119,112 @@ crawled = crawl_task(month=2, year=year, temp_dir=constants.DOWNLOAD_PATH.value) # Now get the downloaded file: log("Accessing downloaded file") - uf_tipo_file = get_desired_file_task( + municipio_tipo_file = get_desired_file_task( year=year, download_directory=constants.DOWNLOAD_PATH.value, filetype=constants.UF_TIPO_BASIC_FILENAME.value, upstream_tasks=[crawled], ) - log(uf_tipo_file) - df = treat_uf_tipo_task(file=uf_tipo_file, upstream_tasks=[crawled, uf_tipo_file]) + log(municipio_tipo_file) + df = treat_uf_tipo_task( + file=municipio_tipo_file, upstream_tasks=[crawled, municipio_tipo_file] + ) csv_output = output_file_to_csv_task( - df, constants.UF_TIPO_BASIC_FILENAME, upstream_tasks=[df] + df, constants.UF_TIPO_BASIC_FILENAME.value, upstream_tasks=[df] + ) + # wait_upload_table = create_table_and_upload_to_gcs( + # data_path=csv_output, + # dataset_id=dataset_id, + # table_id=table_id, + # dump_mode="append", + # wait=csv_output, + # ) + + with case(materialize_after_dump, True): + # Trigger DBT flow run + current_flow_labels = get_current_flow_labels() + materialization_flow = create_flow_run( + flow_name=utils_constants.FLOW_EXECUTE_DBT_MODEL_NAME.value, + project_name=pipelines_constants.PREFECT_DEFAULT_PROJECT.value, + parameters={ + "dataset_id": dataset_id, + "table_id": table_id, + "mode": materialization_mode, + "dbt_alias": dbt_alias, + }, + labels=current_flow_labels, + run_name=f"Materialize {dataset_id}.{table_id}", + ) + + wait_for_materialization = wait_for_flow_run( + materialization_flow, + stream_states=True, + stream_logs=True, + raise_final_state=True, + ) + wait_for_materialization.max_retries = ( + dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_ATTEMPTS.value + ) + wait_for_materialization.retry_delay = timedelta( + seconds=dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_INTERVAL.value + ) + + +br_denatran_frota_uf_tipo.storage = GCS(pipelines_constants.GCS_FLOWS_BUCKET.value) +br_denatran_frota_uf_tipo.run_config = KubernetesRun( + image=pipelines_constants.DOCKER_IMAGE.value +) +# flow.schedule = every_two_weeks + + +with Flow( + name="br_denatran_frota.municipio_tipo", + code_owners=[ + "Tamir", + ], +) as br_denatran_frota_municipio_tipo: + year = 2021 + dataset_id = Parameter("dataset_id", default="br_denatran_frota") + table_id = Parameter("table_id", default="municipio_tipo") + + # Materialization mode + materialization_mode = Parameter( + "materialization_mode", default="dev", required=False ) - wait_upload_table = create_table_and_upload_to_gcs( - data_path=csv_output, - dataset_id=dataset_id, - table_id=table_id, - dump_mode="append", - wait=csv_output, + + materialize_after_dump = Parameter( + "materialize after dump", default=False, required=False + ) + + dbt_alias = Parameter("dbt_alias", default=True, required=False) + + rename_flow_run = rename_current_flow_run_dataset_table( + prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id + ) + log("Downloading file") + crawled = crawl_task(month=2, year=year, temp_dir=constants.DOWNLOAD_PATH.value) + # Now get the downloaded file: + log("Accessing downloaded file") + municipio_tipo_file = get_desired_file_task( + year=year, + download_directory=constants.DOWNLOAD_PATH.value, + filetype=constants.MUNIC_TIPO_BASIC_FILENAME.value, + upstream_tasks=[crawled], + ) + log(municipio_tipo_file) + df = treat_municipio_tipo_task( + file=municipio_tipo_file, upstream_tasks=[crawled, municipio_tipo_file] + ) + csv_output = output_file_to_csv_task( + df, constants.MUNIC_TIPO_BASIC_FILENAME.value, upstream_tasks=[df] ) + # wait_upload_table = create_table_and_upload_to_gcs( + # data_path=csv_output, + # dataset_id=dataset_id, + # table_id=table_id, + # dump_mode="append", + # wait=csv_output, + # ) with case(materialize_after_dump, True): # Trigger DBT flow run diff --git a/pipelines/datasets/br_denatran_frota/tasks.py b/pipelines/datasets/br_denatran_frota/tasks.py index 2c8738990..2edcfd86e 100644 --- a/pipelines/datasets/br_denatran_frota/tasks.py +++ b/pipelines/datasets/br_denatran_frota/tasks.py @@ -60,6 +60,7 @@ treat_uf_tipo, output_file_to_csv, get_desired_file, + treat_municipio_tipo, ) from pipelines.utils.utils import ( log, @@ -91,3 +92,8 @@ def output_file_to_csv_task(df: pl.DataFrame, filename: str) -> None: @task() def get_desired_file_task(year: int, download_directory: str, filetype: str) -> str: return get_desired_file(year, download_directory, filetype) + + +@task() +def treat_municipio_tipo_task(file: str) -> pl.DataFrame: + return treat_municipio_tipo(file) diff --git a/pipelines/datasets/br_denatran_frota/tasks_test.py b/pipelines/datasets/br_denatran_frota/tasks_test.py index 8ff6d1838..7dfb75d58 100644 --- a/pipelines/datasets/br_denatran_frota/tasks_test.py +++ b/pipelines/datasets/br_denatran_frota/tasks_test.py @@ -131,6 +131,19 @@ def test_treat_files_municipio_tipo(self, month, year): len(treated_df["id_municipio"].unique().to_list()), 5450 ) + def test_flow(self): + year = 2021 + crawl(month=2, year=year, temp_dir=constants.DOWNLOAD_PATH.value) + # Now get the downloaded file: + uf_tipo_file = get_desired_file( + year=year, + download_directory=constants.DOWNLOAD_PATH.value, + filetype=constants.MUNIC_TIPO_BASIC_FILENAME.value, + ) + print(uf_tipo_file) + df = treat_municipio_tipo(file=uf_tipo_file) + self.assertTrue(type(df), pl.DataFrame) + if __name__ == "__main__": unittest.main() From ba325bd43d55077fbd87a6c5edd9704b714dc1db Mon Sep 17 00:00:00 2001 From: Tamir Date: Thu, 25 May 2023 03:11:45 -0300 Subject: [PATCH 170/265] Fix small error in quadriciclo data --- pipelines/datasets/br_denatran_frota/utils.py | 46 +++++++++++++++---- 1 file changed, 36 insertions(+), 10 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index 862264b29..2988e1409 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -144,18 +144,44 @@ def verify_total(df: pl.DataFrame) -> None: Raises: ValueError: Errors out if the sum of the columns is actually different than the total. + """ - columns_for_total = df.select(pl.exclude("TOTAL")).select(pl.exclude([pl.Utf8])) - calculated_total = columns_for_total.select( - pl.fold( - acc=pl.lit(0), function=lambda acc, x: acc + x, exprs=pl.col("*") - ).alias("calculated_total") - )["calculated_total"] - mask = df["TOTAL"] > calculated_total + + def calculate_total(df): + columns_for_total = df.select(pl.exclude("TOTAL")).select(pl.exclude([pl.Utf8])) + calculated_total = columns_for_total.select( + pl.fold( + acc=pl.lit(0), function=lambda acc, x: acc + x, exprs=pl.col("*") + ).alias("calculated_total") + )["calculated_total"] + return calculated_total + + calculated_total = calculate_total(df) + mask = df["TOTAL"] != calculated_total + if pl.sum(mask) != 0: - raise ValueError( - "A coluna de TOTAL da base original tem inconsistências e é maior que soma das demais colunas." - ) + # In some cases, the quadriciclo data is multiplied by 10, and this will correct it before you + new_df = clean_quadriciclo_data(df) + new_calculated_total = calculate_total(new_df) + mask = new_df["TOTAL"] != new_calculated_total + if pl.sum(mask) != 0: + raise ValueError( + "A coluna de TOTAL da base original tem inconsistências e é diferente da soma das demais colunas." + ) + + +def clean_quadriciclo_data(df: pl.DataFrame) -> pl.DataFrame: + """Divide the quadriciclo column by 10 when the data is dirty. + + Args: + df (pl.DataFrame): Denatran data to be cleaned + + Returns: + pl.DataFrame: Cleaned Denatran data with the quadriciclo column altered. + """ + old_quadriciclo = df["QUADRICICLO"] + new_quadriciclo = old_quadriciclo / 10 + return df.with_columns(new_quadriciclo.cast(pl.Int32).alias("QUADRICICLO")) def fix_suggested_nome_ibge(row: tuple[str, ...]) -> str: From d339e799d7e70f7fc90d58c24f9eeefe5100667e Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 30 May 2023 01:16:01 -0300 Subject: [PATCH 171/265] Ignore credentials --- .gitignore | 1 + 1 file changed, 1 insertion(+) diff --git a/.gitignore b/.gitignore index b8ce2db36..16abd5890 100644 --- a/.gitignore +++ b/.gitignore @@ -143,3 +143,4 @@ notebooks/ poetry.lock pipelines/datasets/br_denatran_frota/todo_list.txt pipelines/datasets/br_denatran_frota/run_local.py +basedosdados-dev-ff644018223b.json From a3fcb06720a8eb3c98881ca495642d5af7b76427 Mon Sep 17 00:00:00 2001 From: Tamir Date: Fri, 16 Jun 2023 19:04:31 -0300 Subject: [PATCH 172/265] Ajusta flow --- pipelines/datasets/br_denatran_frota/flows.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index 755002185..9292c8022 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -256,8 +256,8 @@ ) -br_denatran_frota_uf_tipo.storage = GCS(pipelines_constants.GCS_FLOWS_BUCKET.value) -br_denatran_frota_uf_tipo.run_config = KubernetesRun( +br_denatran_frota_municipio_tipo.storage = GCS(pipelines_constants.GCS_FLOWS_BUCKET.value) +br_denatran_frota_municipio_tipo.run_config = KubernetesRun( image=pipelines_constants.DOCKER_IMAGE.value ) # flow.schedule = every_two_weeks From 450868c6623e108d87d28c89b686497615a5ef17 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Fri, 16 Jun 2023 22:04:48 +0000 Subject: [PATCH 173/265] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- pipelines/datasets/br_denatran_frota/flows.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index 9292c8022..e719d1f29 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -256,7 +256,9 @@ ) -br_denatran_frota_municipio_tipo.storage = GCS(pipelines_constants.GCS_FLOWS_BUCKET.value) +br_denatran_frota_municipio_tipo.storage = GCS( + pipelines_constants.GCS_FLOWS_BUCKET.value +) br_denatran_frota_municipio_tipo.run_config = KubernetesRun( image=pipelines_constants.DOCKER_IMAGE.value ) From 23deaf22b54c10d114c8a3991366d78de8e9f4ce Mon Sep 17 00:00:00 2001 From: Tamir Date: Fri, 16 Jun 2023 19:14:02 -0300 Subject: [PATCH 174/265] Commit salvador --- .../datasets/br_denatran_frota/teste.xls | Bin 34816 -> 0 bytes .../datasets/br_denatran_frota/trash.ipynb | 543 ------------------ requirements-test.txt | 1 + 3 files changed, 1 insertion(+), 543 deletions(-) delete mode 100644 pipelines/datasets/br_denatran_frota/teste.xls delete mode 100644 pipelines/datasets/br_denatran_frota/trash.ipynb diff --git 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\u001b[0;36mcall_r_to_read_file\u001b[0;34m(file)\u001b[0m\n\u001b[1;32m 405\u001b[0m readxl \u001b[39m=\u001b[39m rpackages\u001b[39m.\u001b[39mimportr(\u001b[39m\"\u001b[39m\u001b[39mreadxl\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[1;32m 407\u001b[0m \u001b[39m# Read the Excel file\u001b[39;00m\n\u001b[0;32m--> 408\u001b[0m robjects\u001b[39m.\u001b[39mr(\n\u001b[1;32m 409\u001b[0m \u001b[39mf\u001b[39m\u001b[39m\"\"\"\u001b[39m\n\u001b[1;32m 410\u001b[0m \u001b[39m library(readxl)\u001b[39m\n\u001b[1;32m 411\u001b[0m \u001b[39m x <- read_excel(\u001b[39m\u001b[39m'\u001b[39m\u001b[39m{\u001b[39;00mfile\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m\u001b[39m)\u001b[39m\n\u001b[1;32m 412\u001b[0m \u001b[39m\u001b[39m\u001b[39m\"\"\"\u001b[39m\n\u001b[1;32m 413\u001b[0m )\n\u001b[1;32m 415\u001b[0m \u001b[39m# Convert the R dataframe to a pandas dataframe\u001b[39;00m\n\u001b[1;32m 416\u001b[0m df \u001b[39m=\u001b[39m robjects\u001b[39m.\u001b[39mr[\u001b[39m\"\u001b[39m\u001b[39mx\u001b[39m\u001b[39m\"\u001b[39m]\n", - "File \u001b[0;32m~/.cache/pypoetry/virtualenvs/pipelines-Fyk5jlG0-py3.10/lib/python3.10/site-packages/rpy2/robjects/__init__.py:459\u001b[0m, in \u001b[0;36mR.__call__\u001b[0;34m(self, string)\u001b[0m\n\u001b[1;32m 457\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m__call__\u001b[39m(\u001b[39mself\u001b[39m, string):\n\u001b[1;32m 458\u001b[0m p \u001b[39m=\u001b[39m rinterface\u001b[39m.\u001b[39mparse(string)\n\u001b[0;32m--> 459\u001b[0m res \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49meval(p)\n\u001b[1;32m 460\u001b[0m \u001b[39mreturn\u001b[39;00m conversion\u001b[39m.\u001b[39mget_conversion()\u001b[39m.\u001b[39mrpy2py(res)\n", - "File \u001b[0;32m~/.cache/pypoetry/virtualenvs/pipelines-Fyk5jlG0-py3.10/lib/python3.10/site-packages/rpy2/robjects/functions.py:208\u001b[0m, in \u001b[0;36mSignatureTranslatedFunction.__call__\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 206\u001b[0m v \u001b[39m=\u001b[39m kwargs\u001b[39m.\u001b[39mpop(k)\n\u001b[1;32m 207\u001b[0m kwargs[r_k] \u001b[39m=\u001b[39m v\n\u001b[0;32m--> 208\u001b[0m \u001b[39mreturn\u001b[39;00m (\u001b[39msuper\u001b[39;49m(SignatureTranslatedFunction, \u001b[39mself\u001b[39;49m)\n\u001b[1;32m 209\u001b[0m \u001b[39m.\u001b[39;49m\u001b[39m__call__\u001b[39;49m(\u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs))\n", - "File \u001b[0;32m~/.cache/pypoetry/virtualenvs/pipelines-Fyk5jlG0-py3.10/lib/python3.10/site-packages/rpy2/robjects/functions.py:131\u001b[0m, in \u001b[0;36mFunction.__call__\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 129\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m 130\u001b[0m new_kwargs[k] \u001b[39m=\u001b[39m cv\u001b[39m.\u001b[39mpy2rpy(v)\n\u001b[0;32m--> 131\u001b[0m res \u001b[39m=\u001b[39m \u001b[39msuper\u001b[39;49m(Function, \u001b[39mself\u001b[39;49m)\u001b[39m.\u001b[39;49m\u001b[39m__call__\u001b[39;49m(\u001b[39m*\u001b[39;49mnew_args, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mnew_kwargs)\n\u001b[1;32m 132\u001b[0m res \u001b[39m=\u001b[39m cv\u001b[39m.\u001b[39mrpy2py(res)\n\u001b[1;32m 133\u001b[0m \u001b[39mreturn\u001b[39;00m res\n", - "File \u001b[0;32m~/.cache/pypoetry/virtualenvs/pipelines-Fyk5jlG0-py3.10/lib/python3.10/site-packages/rpy2/rinterface_lib/conversion.py:45\u001b[0m, in \u001b[0;36m_cdata_res_to_rinterface.._\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 44\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m_\u001b[39m(\u001b[39m*\u001b[39margs, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs):\n\u001b[0;32m---> 45\u001b[0m cdata \u001b[39m=\u001b[39m function(\u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[1;32m 46\u001b[0m \u001b[39m# TODO: test cdata is of the expected CType\u001b[39;00m\n\u001b[1;32m 47\u001b[0m \u001b[39mreturn\u001b[39;00m _cdata_to_rinterface(cdata)\n", - "File \u001b[0;32m~/.cache/pypoetry/virtualenvs/pipelines-Fyk5jlG0-py3.10/lib/python3.10/site-packages/rpy2/rinterface.py:817\u001b[0m, in \u001b[0;36mSexpClosure.__call__\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 810\u001b[0m res \u001b[39m=\u001b[39m rmemory\u001b[39m.\u001b[39mprotect(\n\u001b[1;32m 811\u001b[0m openrlib\u001b[39m.\u001b[39mrlib\u001b[39m.\u001b[39mR_tryEval(\n\u001b[1;32m 812\u001b[0m call_r,\n\u001b[1;32m 813\u001b[0m call_context\u001b[39m.\u001b[39m__sexp__\u001b[39m.\u001b[39m_cdata,\n\u001b[1;32m 814\u001b[0m error_occured)\n\u001b[1;32m 815\u001b[0m )\n\u001b[1;32m 816\u001b[0m \u001b[39mif\u001b[39;00m error_occured[\u001b[39m0\u001b[39m]:\n\u001b[0;32m--> 817\u001b[0m \u001b[39mraise\u001b[39;00m embedded\u001b[39m.\u001b[39mRRuntimeError(_rinterface\u001b[39m.\u001b[39m_geterrmessage())\n\u001b[1;32m 818\u001b[0m \u001b[39mreturn\u001b[39;00m res\n", - "\u001b[0;31mRRuntimeError\u001b[0m: Error: `path` does not exist: ‘pipelines/datasets/br_denatran_frota/teste.xls’\n" - ] - } - ], - "source": [ - "call_r_to_read_file()" - ] - }, - { - "cell_type": "code", - "execution_count": 51, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - 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“\u0002\u0004\u0000\u0010ÿ“\u0002\u0004\u0000\u0011€\tÿ“\u0002\u0004\u0000\u0012€\u0004ÿ“\u0002\u0004\u0000\u0013€\u0007ÿ“\u0002\u0004\u0000\u0000€\u0000ÿ“\u0002\u0004\u0000\u0014€\u0005ÿ“\u0002\u0004\u0000\u0015€\u0003ÿ“\u0002\u0004\u0000\u0016€\u0006ÿ`\u0001\u0002\u0000\u0000\u0000…\u0000\u0011\u0000ž\u001e\u0000\u0000\u0000\u0000\t\u0000Glossário…\u0000\u0010\u0000“)\u0000\u0000\u0000\u0000JAN_2009Œ\u0000\u0004\u00007\u00007\u0000®\u0001\u0004\u0000\u0002\u0000\u0001\u0004\u0017\u0000\u000e\u0000\u0002\u0000\u0000\u0000\u0001\u0000\u0001\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0018\u0000\u001b\u0000 \u0000\u0000\u0001\u000b\u0000\u0000\u0000\u0001\u0000\u0000\u0000\u0000\u0000\u0000\u0006;\u0001\u0000\u0000\u0000\u0017\u0000\u0000\u0000\u0002\u0000\u0018\u0000\u001b\u0000 \u0000\u0000\u0001\u000b\u0000\u0000\u0000\u0002\u0000\u0000\u0000\u0000\u0000\u0000\u0006=\u0000\u0000\u0000\u0000-\u0000\u0000\u0000\u0016\u0000Á\u0000Á\u0001\u0000\u0000\"¾\u0001\u0000ü\u0000A\n", - "€\u0000\u0000\u0000S\u0000\u0000\u0000'\u0000\u0000Grandes Regiões e\n", - "Unidades da Federação\u0005\u0000\u0000TOTAL\t\u0000\u0000AUTOMÓVEL\u0005\u0000\u0000BOND\u0000\u0000CAMINHÃO\u000f\u0000\u0000CAMINHÃO TRATOR\u000b\u0000\u0000CAMINHONETE\t\u0000\u0000CAMIONETA\u0011\u0000\u0000CHASSI PLATAFORMA\n", - "\u0000\u0000CICLOMOTOR\u000b\u0000\u0000MICROÔNIBUS\u000b\u0000\u0000MOTOCICLET\u0000\u0000MOTONETA\u0006\u0000\u0000ÔNIBUS\u000b\u0000\u0000QUADRICICLO\u0007\u0000\u0000REBOQUE\f\u0000\u0000SEMI-REBOQU\u0000\u0000SIDE-CAR\u0006\u0000\u0000OUTROS\u000e\u0000\u0000TRATOR ESTEIRA\f\u0000\u0000TRATOR RODA\u0000\u0000TRICICLO\n", - "\u0000\u0000UTILITÁRIO\u0005\u0000\u0000Acre \u0006\u0000\u0000Amapá\u0000\u0000Amazonas\u0005\u0000\u0000Pará \t\u0000\u0000Rondônia \u0007\u0000\u0000Roraima\t\u0000\u0000Tocantins\u0007\u0000\u0000Alagoas\u0005\u0000\u0000Bahia\u0005\u0000\u0000Ceará\t\u0000\u0000Maranhão\u0000\u0000Paraíba \u000b\u0000\u0000Pernambuco \u0005\u0000\u0000Piauí\u0014\u0000\u0000Rio Grande do Norte \u0007\u0000\u0000Sergipe\u000e\u0000\u0000Espírito Santo\n", - "\u0000\u0000Minas Gerais \u000e\u0000\u0000Rio de Janeiro\n", - "\u0000\u0000São Paulo \u0006\u0000\u0000Paraná\u0012\u0000\u0000Rio Grande do Sul \u000e\u0000\u0000Santa Catarina\u0010\u0000\u0000Distrito Federal\u0005\u0000\u0000Goiás\u000b\u0000\u0000Mato Grosso\u0012\u0000\u0000Mato Grosso do Sul°\u0000\u0000Fonte: Ministério das Cidades, Departamento Nacional de Trânsito - DENATRAN, Sistema Nacional de Registro de Veículos/RENAVAM, Sistema Nacional de Estatística de Trânsito/SINET\u0006\u0000\u0000Brasil\u0005\u0000\u0000Nort\u0000\u0000Nordeste\u0007\u0000\u0000Sudeste\u0003\u0000\u0000Sul\f\u0000\u0000Centro-Oestet\u0000\u0000veículo automotor destinado ao transporte de passageiros, com capacidade para até oito pessoas, exclusive o condutor7\u0000\u0000veículo de propulsão elétrica que se move sobre trilhosi\u0000\u0000veículo automotor destinado ao transporte de carga, com carroçaria, e peso bruto total superior a 3500 Kg9\u0000\u0000veículo automotor destinado a tracionar ou arrastar outroX\u0000\u0000veículo automotor destinado ao transporte de carga, com peso bruto total de até 3500 Kg.\u0000\u0000veículo inacabado, com equipamento que permita seu deslocamento em vias de rolamento, preparado para receber carroçaria de ônibus¿\u0000\u0000veículo de duas ou três rodas, provido de um motor de combustão interna cuja cilindrada não exceda a 50 cm3(3,05 polegadas cúbicas) e cuja velocidade máxima de fabricação não exceda a 50 Km/hO\u0000\u0000veículo automotor de transporte coletivo com capacidade para até 20 passageirosJ\u0000\u0000veículo auto-motor de duas rodas, dirigido por condutor em posição sentadaµ\u0000\u0000veículo automotor de transporte coletivo com capacidade para mais de 20 passageiros, ainda que, em virtude de adaptações com vista à maior comodidade destes, transporte número menorr\u0000\u0000veículo de estrutura mecânica igual às motocicletas, possuindo eixos dianteiro e traseiro, dotados de quatro rodas>\u0000\u0000veículo destinado a ser engatado atrás de um veículo automotorj\u0000\u0000veículo de um ou mais eixos que se apóia na sua unidade tratora ou é a ela ligado por meio de articulação.G\u0000\u0000carro ou caçamba provido de uma roda acoplada na lateral da motocicleta?\u0000\u0000Argumento que não se enquadra em nenhuma definição estabelecida+\u0000\u0000trator que se movimenta por meio de esteiraK\u0000\u0000trator que se movimenta sobre rodas,podendo ter chassi rígido ou articulado\\\u0000\u0000veículo rodoviário automotor de estrutura mecânica igual à motocicleta dotado de três rodas.U\u0000\u0000veículo misto caracterizado pela versatilidade do seu uso, inclusive fora da estrada.?\u0000\u0000Regiões Norte, Nordeste, Sul, Suldeste e Centro Oeste e Estados\u0013\u0000\u0000Termos e DefiniçõesR\u0000\u0000veículo automotor de duas rodas, com ou sem side-car, dirigido em posição montada.˜\u0000\u0000veículo automotor, misto, com quatro rodas, com carroçaria, destinado ao transporte simultâneo ou alternativo de pessoas e carga no mesmo compartimento.~\u0000\u0000Fonte: Ministério das Cidades, DENATRAN - Departamento Nacional de Trânsito, RENAVAM-Registro Nacional de Veículos Automotoresf\u0000\u0000Frota de veículos, por tipo e com placa, segundo as Grandes Regiões e Unidades da Federação - JAN/2009H\u0000\u0000Tabela 2 - Percentagem de veículos, por tipo segundo o Brasil - JAN/2009ÿ\u0000Z\u0000ê\u0010\u0000\u0000\f\u0000\u0000\u0000g\u0011\u0000\u0000‰\u0000\u0000\u0000Ð\u0011\u0000\u0000ò\u0000\u0000\u00003\u0012\u0000\u0000U\u0001\u0000\u0000ƒ\u0012\u0000\u0000¥\u0001\u0000\u0000ê\u0012\u0000\u0000\f\u0002\u0000\u0000b\u0013\u0000\u0000„\u0002\u0000\u0000d\u0014\u0000\u0000†\u0003\u0000\u0000m\u0017\u0000\u0000\u0006\u0000\u0000s\u001a\u0000\u0000•\t\u0000\u0000î\u001c\u0000\u0000\u0010\f\u0000\u0000\u0015\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0015\u0000\u0000\u0000\u0000\u0000\u0000\u0000¶\n", - "\u0000\u0000\u0000\u0010\u0000\u0000\u0006\u0010\u0000' Í\u0007ÉÀ\u0000\u0000\u0006\u0003\u0000\u0000\u000b\u0002\u0014\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0018\u0000\u0000\u00006$\u0000\u0000\u0006)\u0000\u0000\n", - 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T520 SBE\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000Lexmark T520 SBE\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000*\u0002\u0000\u0000Lexmark T520\u0000 R\u0000\u0000\u0000\u0007\u0000\u0007\u0000\u0000ð\n", - "\u0000\u0000ð\n", - 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- "\u0000\u0000\u0000\n", - "\u0000\u0000\u0000\n", - 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- ] - } - ], - "source": [ - "with open('Frota RegiΣes Tipo UF JAN2009.xls', 'r', encoding=\"latin-1\") as f:\n", - " lines = f.read()\n", - "print(lines)" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "metadata": {}, - "outputs": [], - "source": [ - "import magic\n", - "\n", - "blob = open('Frota RegiΣes Tipo UF JAN2009.xls', 'rb').read()\n", - "m = magic.open(magic.MAGIC_MIME_ENCODING)\n", - "m.load()\n", - "encoding = m.buffer(blob) # \"utf-8\" \"us-ascii\" etc\n" - ] - }, - { - "cell_type": "code", - "execution_count": 49, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "None\n" - ] - } - ], - "source": [ - "print(encoding)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "pipelines-RnwfPrZK-py3.10", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.6" - }, - "orig_nbformat": 4 - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/requirements-test.txt b/requirements-test.txt index e75ed759b..98dd13969 100644 --- a/requirements-test.txt +++ b/requirements-test.txt @@ -2,3 +2,4 @@ networkx==2.6.3 pytest-cov==3.0.0 pyyaml prefect==0.15.9 +parameterized == 0.9.0 \ No newline at end of file From 9a3d2de40a1f8dc85d18983b2f96bd47eeaea2a3 Mon Sep 17 00:00:00 2001 From: Tamir Date: Fri, 16 Jun 2023 19:23:32 -0300 Subject: [PATCH 175/265] Sobe config certa pra ler da BD --- pipelines/datasets/br_denatran_frota/handlers.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 07b00aadd..9394380d2 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -145,7 +145,7 @@ def treat_municipio_tipo(file: str) -> pl.DataFrame: municipios_query = """SELECT nome, id_municipio, sigla_uf FROM `basedosdados.br_bd_diretorios_brasil.municipio` """ bd_municipios = bd.read_sql( - municipios_query, "tamir-pipelines" + municipios_query, "basedosdados-dev" ) # Hardcoded, not good. bd_municipios = pl.from_pandas(bd_municipios) From 9262ee92e0cf976204bf88fcc6dbaa4866c48cd8 Mon Sep 17 00:00:00 2001 From: Tamir Date: Sat, 17 Jun 2023 20:20:01 -0300 Subject: [PATCH 176/265] Reallocate logs --- pipelines/datasets/br_denatran_frota/flows.py | 11 ----------- pipelines/datasets/br_denatran_frota/handlers.py | 2 ++ 2 files changed, 2 insertions(+), 11 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index e719d1f29..ad46e157a 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -65,9 +65,6 @@ create_flow_run, wait_for_flow_run, ) -from pipelines.utils.utils import ( - log, -) import os from pipelines.constants import constants as pipelines_constants from pipelines.utils.constants import constants as utils_constants @@ -111,21 +108,17 @@ ) dbt_alias = Parameter("dbt_alias", default=True, required=False) - rename_flow_run = rename_current_flow_run_dataset_table( prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id ) - log("Downloading file") crawled = crawl_task(month=2, year=year, temp_dir=constants.DOWNLOAD_PATH.value) # Now get the downloaded file: - log("Accessing downloaded file") municipio_tipo_file = get_desired_file_task( year=year, download_directory=constants.DOWNLOAD_PATH.value, filetype=constants.UF_TIPO_BASIC_FILENAME.value, upstream_tasks=[crawled], ) - log(municipio_tipo_file) df = treat_uf_tipo_task( file=municipio_tipo_file, upstream_tasks=[crawled, municipio_tipo_file] ) @@ -155,7 +148,6 @@ labels=current_flow_labels, run_name=f"Materialize {dataset_id}.{table_id}", ) - wait_for_materialization = wait_for_flow_run( materialization_flow, stream_states=True, @@ -201,17 +193,14 @@ rename_flow_run = rename_current_flow_run_dataset_table( prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id ) - log("Downloading file") crawled = crawl_task(month=2, year=year, temp_dir=constants.DOWNLOAD_PATH.value) # Now get the downloaded file: - log("Accessing downloaded file") municipio_tipo_file = get_desired_file_task( year=year, download_directory=constants.DOWNLOAD_PATH.value, filetype=constants.MUNIC_TIPO_BASIC_FILENAME.value, upstream_tasks=[crawled], ) - log(municipio_tipo_file) df = treat_municipio_tipo_task( file=municipio_tipo_file, upstream_tasks=[crawled, municipio_tipo_file] ) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 9394380d2..837f4d4cf 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -54,6 +54,7 @@ def crawl(month: int, year: int, temp_dir: str = "") -> None: """ if month not in MONTHS.values(): raise ValueError("Mês inválido.") + log("Downloading file") files_dir = os.path.join(temp_dir, "files") make_dir_when_not_exists(files_dir) year_dir_name = os.path.join(files_dir, f"{year}") @@ -129,6 +130,7 @@ def output_file_to_csv(df: pl.DataFrame, filename: str) -> None: def get_desired_file(year: int, download_directory: str, filetype: str) -> str: + log("Accessing downloaded file") directory_to_search = os.path.join(download_directory, "files", f"{year}") log(f"Directory: {directory_to_search}") for file in os.listdir(directory_to_search): From da3c6605366f8a25a80b2fba71f9b65f6806fda8 Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 20 Jun 2023 00:33:01 -0300 Subject: [PATCH 177/265] Novo teste --- .../datasets/br_denatran_frota/handlers.py | 8 ++-- pipelines/datasets/br_denatran_frota/utils.py | 44 +++++++++++++++++++ 2 files changed, 47 insertions(+), 5 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 837f4d4cf..8f96fd7c9 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -21,6 +21,7 @@ extraction_pre_2012, call_r_to_read_excel, treat_uf, + get_data_from_prod, DenatranType, ) import pandas as pd @@ -144,11 +145,8 @@ def get_desired_file(year: int, download_directory: str, filetype: str) -> str: def treat_municipio_tipo(file: str) -> pl.DataFrame: - municipios_query = """SELECT nome, id_municipio, sigla_uf FROM `basedosdados.br_bd_diretorios_brasil.municipio` - """ - bd_municipios = bd.read_sql( - municipios_query, "basedosdados-dev" - ) # Hardcoded, not good. + bd_municipios = get_data_from_prod(table_id="municipio", + dataset_id="br_bd_diretorios_brasil") bd_municipios = pl.from_pandas(bd_municipios) filename = os.path.split(file)[1] diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index 2988e1409..b3387e336 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -18,6 +18,7 @@ import rpy2.robjects.packages as rpackages import rpy2.robjects as robjects from rpy2.robjects.vectors import StrVector +import basedosdados as bd from enum import Enum @@ -541,3 +542,46 @@ def treat_uf(denatran_df: pl.DataFrame, ibge_df: pl.DataFrame, uf: str) -> None: # The set difference might occur the other way around, but still, better safe. raise ValueError(f"Existem municípios em {uf} que não estão na BD.") return verify_match_ibge(denatran_uf, ibge_uf) + + + +def get_data_from_prod(dataset_id: str, table_id: str) -> list: + """Get data from a table from basedosdados. + + Args: + dataset_id (str): Name of the dataset. + table_id (str): _description_ + columns (list): _description_ + + Returns: + list: _description_ + """ + + storage = bd.Storage(dataset_id=dataset_id, table_id=table_id) + blobs = list( + storage.client["storage_staging"] + .bucket("basedosdados-dev") + .list_blobs(prefix=f"staging/{storage.dataset_id}/{storage.table_id}/") + ) + + dfs = [] + + for blob in blobs: + partitions = re.findall(r"\w+(?==)", blob.name) + if len(set(partitions)) == 0: + df = pd.read_csv( + blob.public_url + ) + dfs.append(df) + else: + columns2add = list(set(partitions)) + df = pd.read_csv( + blob.public_url + ) + for column in columns2add: + df[column] = blob.name.split(column + "=")[1].split("/")[0] + dfs.append(df) + + df = pd.concat(dfs) + + return df \ No newline at end of file From f14f9752c6687e47de983a5bb5ad2c9422ff08c8 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Tue, 20 Jun 2023 03:33:16 +0000 Subject: [PATCH 178/265] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- pipelines/datasets/br_denatran_frota/handlers.py | 5 +++-- pipelines/datasets/br_denatran_frota/utils.py | 11 +++-------- 2 files changed, 6 insertions(+), 10 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 8f96fd7c9..175f5ed2b 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -145,8 +145,9 @@ def get_desired_file(year: int, download_directory: str, filetype: str) -> str: def treat_municipio_tipo(file: str) -> pl.DataFrame: - bd_municipios = get_data_from_prod(table_id="municipio", - dataset_id="br_bd_diretorios_brasil") + bd_municipios = get_data_from_prod( + table_id="municipio", dataset_id="br_bd_diretorios_brasil" + ) bd_municipios = pl.from_pandas(bd_municipios) filename = os.path.split(file)[1] diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index b3387e336..ca4eba1c9 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -544,7 +544,6 @@ def treat_uf(denatran_df: pl.DataFrame, ibge_df: pl.DataFrame, uf: str) -> None: return verify_match_ibge(denatran_uf, ibge_uf) - def get_data_from_prod(dataset_id: str, table_id: str) -> list: """Get data from a table from basedosdados. @@ -569,19 +568,15 @@ def get_data_from_prod(dataset_id: str, table_id: str) -> list: for blob in blobs: partitions = re.findall(r"\w+(?==)", blob.name) if len(set(partitions)) == 0: - df = pd.read_csv( - blob.public_url - ) + df = pd.read_csv(blob.public_url) dfs.append(df) else: columns2add = list(set(partitions)) - df = pd.read_csv( - blob.public_url - ) + df = pd.read_csv(blob.public_url) for column in columns2add: df[column] = blob.name.split(column + "=")[1].split("/")[0] dfs.append(df) df = pd.concat(dfs) - return df \ No newline at end of file + return df From 8b9638c855f2c51a4dc08abbf3bf2aaf22e2adc3 Mon Sep 17 00:00:00 2001 From: Tamir Date: Thu, 22 Jun 2023 19:09:46 -0300 Subject: [PATCH 179/265] Tenta mapping pra um flow --- pipelines/datasets/br_denatran_frota/flows.py | 30 ++++++++++++------- 1 file changed, 20 insertions(+), 10 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index ad46e157a..3fa6de794 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -60,7 +60,7 @@ from datetime import datetime, timedelta from prefect.run_configs import KubernetesRun from prefect.storage import GCS -from prefect import Parameter, case +from prefect import Parameter, case, unmapped from prefect.tasks.prefect import ( create_flow_run, wait_for_flow_run, @@ -84,7 +84,13 @@ treat_municipio_tipo_task, ) from pipelines.datasets.br_denatran_frota.constants import constants +from itertools import product +year_range = list(range(2003, 2023)) +month_range = list(range(1, 13)) +date_pairs = list(product(year_range, month_range)) + +date_pairs_param = Parameter("date_pairs", default=date_pairs) # from pipelines.datasets.br_denatran_frota.schedules import every_two_weeks @@ -94,7 +100,6 @@ "Tamir", ], ) as br_denatran_frota_uf_tipo: - year = 2021 dataset_id = Parameter("dataset_id", default="br_denatran_frota") table_id = Parameter("table_id", default="uf_tipo") @@ -111,19 +116,24 @@ rename_flow_run = rename_current_flow_run_dataset_table( prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id ) - crawled = crawl_task(month=2, year=year, temp_dir=constants.DOWNLOAD_PATH.value) + crawled = crawl_task.map( + month=[date[1] for date in date_pairs_param], + year=[date[0] for date in date_pairs_param], + temp_dir=unmapped(constants.DOWNLOAD_PATH.value)) # Now get the downloaded file: - municipio_tipo_file = get_desired_file_task( - year=year, - download_directory=constants.DOWNLOAD_PATH.value, - filetype=constants.UF_TIPO_BASIC_FILENAME.value, + # Now get the downloaded file: + municipio_tipo_file = get_desired_file_task.map( + year=[date[0] for date in date_pairs_param], + month=[date[1] for date in date_pairs_param], + download_directory=unmapped(constants.DOWNLOAD_PATH.value), + filetype=unmapped(constants.UF_TIPO_BASIC_FILENAME.value), upstream_tasks=[crawled], ) - df = treat_uf_tipo_task( + df = treat_uf_tipo_task.map( file=municipio_tipo_file, upstream_tasks=[crawled, municipio_tipo_file] ) - csv_output = output_file_to_csv_task( - df, constants.UF_TIPO_BASIC_FILENAME.value, upstream_tasks=[df] + csv_output = output_file_to_csv_task.map( + df, unmapped(constants.UF_TIPO_BASIC_FILENAME.value), upstream_tasks=[df] ) # wait_upload_table = create_table_and_upload_to_gcs( # data_path=csv_output, From 0836c77bd8e0d77011eed5857df24b422f10be81 Mon Sep 17 00:00:00 2001 From: Tamir Date: Thu, 22 Jun 2023 19:28:24 -0300 Subject: [PATCH 180/265] Sobrescrever a tabela (deve dar erro) --- pipelines/datasets/br_denatran_frota/flows.py | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index 3fa6de794..1c7b3cdb9 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -135,13 +135,13 @@ csv_output = output_file_to_csv_task.map( df, unmapped(constants.UF_TIPO_BASIC_FILENAME.value), upstream_tasks=[df] ) - # wait_upload_table = create_table_and_upload_to_gcs( - # data_path=csv_output, - # dataset_id=dataset_id, - # table_id=table_id, - # dump_mode="append", - # wait=csv_output, - # ) + wait_upload_table = create_table_and_upload_to_gcs( + data_path=csv_output, + dataset_id=dataset_id, + table_id=table_id, + dump_mode="overwrite", + wait=csv_output, + ) with case(materialize_after_dump, True): # Trigger DBT flow run From 6fc2193a731ceca7f776c559c9610459bfc9c94b Mon Sep 17 00:00:00 2001 From: Tamir Date: Thu, 22 Jun 2023 19:29:22 -0300 Subject: [PATCH 181/265] Faltou map --- pipelines/datasets/br_denatran_frota/flows.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index 1c7b3cdb9..cceef97fe 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -135,11 +135,11 @@ csv_output = output_file_to_csv_task.map( df, unmapped(constants.UF_TIPO_BASIC_FILENAME.value), upstream_tasks=[df] ) - wait_upload_table = create_table_and_upload_to_gcs( + wait_upload_table = create_table_and_upload_to_gcs.map( data_path=csv_output, - dataset_id=dataset_id, - table_id=table_id, - dump_mode="overwrite", + dataset_id=unmapped(dataset_id), + table_id=unmapped(table_id), + dump_mode=unmapped("append"), wait=csv_output, ) From ef71443df5e3dac51d47e38c5112059f865e766c Mon Sep 17 00:00:00 2001 From: folhesgabriel Date: Fri, 23 Jun 2023 21:22:10 -0300 Subject: [PATCH 182/265] register flow --- .../datasets/br_denatran_frota/constants.py | 28 ---------- pipelines/datasets/br_denatran_frota/flows.py | 56 +------------------ 2 files changed, 2 insertions(+), 82 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/constants.py b/pipelines/datasets/br_denatran_frota/constants.py index 034342db8..6f69d6200 100644 --- a/pipelines/datasets/br_denatran_frota/constants.py +++ b/pipelines/datasets/br_denatran_frota/constants.py @@ -3,34 +3,6 @@ Constant values for the datasets projects """ - -############################################################################### -# -# Esse é um arquivo onde podem ser declaratas constantes que serão usadas -# pelo projeto br_denatran_frota. -# -# Por ser um arquivo opcional, pode ser removido sem prejuízo ao funcionamento -# do projeto, caos não esteja em uso. -# -# Para declarar constantes, basta fazer conforme o exemplo abaixo: -# -# ``` -# class constants(Enum): -# """ -# Constant values for the br_denatran_frota project -# """ -# FOO = "bar" -# ``` -# -# Para usá-las, basta fazer conforme o exemplo abaixo: -# -# ```py -# from pipelines.datasets.br_denatran_frota.constants import constants -# print(constants.FOO.value) -# ``` -# -############################################################################### - from enum import Enum diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index cceef97fe..d2da7f9c1 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -3,59 +3,6 @@ Flows for br_denatran_frota """ -############################################################################### -# -# Aqui é onde devem ser definidos os flows do projeto. -# Cada flow representa uma sequência de passos que serão executados -# em ordem. -# -# Mais informações sobre flows podem ser encontradas na documentação do -# Prefect: https://docs.prefect.io/core/concepts/flows.html -# -# De modo a manter consistência na codebase, todo o código escrito passará -# pelo pylint. Todos os warnings e erros devem ser corrigidos. -# -# Existem diversas maneiras de declarar flows. No entanto, a maneira mais -# conveniente e recomendada pela documentação é usar a API funcional. -# Em essência, isso implica simplesmente na chamada de funções, passando -# os parâmetros necessários para a execução em cada uma delas. -# -# Também, após a definição de um flow, para o adequado funcionamento, é -# mandatório configurar alguns parâmetros dele, os quais são: -# - storage: onde esse flow está armazenado. No caso, o storage é o -# próprio módulo Python que contém o flow. Sendo assim, deve-se -# configurar o storage como o pipelines.datasets -# - run_config: para o caso de execução em cluster Kubernetes, que é -# provavelmente o caso, é necessário configurar o run_config com a -# imagem Docker que será usada para executar o flow. Assim sendo, -# basta usar constants.DOCKER_IMAGE.value, que é automaticamente -# gerado. -# - schedule (opcional): para o caso de execução em intervalos regulares, -# deve-se utilizar algum dos schedules definidos em schedules.py -# -# Um exemplo de flow, considerando todos os pontos acima, é o seguinte: -# -# ----------------------------------------------------------------------------- -# from prefect import task -# from prefect import Flow -# from prefect.run_configs import KubernetesRun -# from prefect.storage import GCS -# from pipelines.constants import constants -# from my_tasks import my_task, another_task -# from my_schedules import some_schedule -# -# with Flow("my_flow") as flow: -# a = my_task(param1=1, param2=2) -# b = another_task(a, param3=3) -# -# flow.storage = GCS(constants.GCS_FLOWS_BUCKET.value) -# flow.run_config = KubernetesRun(image=constants.DOCKER_IMAGE.value) -# flow.schedule = some_schedule -# ----------------------------------------------------------------------------- -# -# Abaixo segue um código para exemplificação, que pode ser removido. -# -############################################################################### from datetime import datetime, timedelta from prefect.run_configs import KubernetesRun @@ -119,7 +66,8 @@ crawled = crawl_task.map( month=[date[1] for date in date_pairs_param], year=[date[0] for date in date_pairs_param], - temp_dir=unmapped(constants.DOWNLOAD_PATH.value)) + temp_dir=unmapped(constants.DOWNLOAD_PATH.value), + ) # Now get the downloaded file: # Now get the downloaded file: municipio_tipo_file = get_desired_file_task.map( From 90bff918d54c2b6f320eb6f3344f028db7085da9 Mon Sep 17 00:00:00 2001 From: folhesgabriel Date: Mon, 10 Apr 2023 12:30:55 -0300 Subject: [PATCH 183/265] test: access datasus ftp using prefect --- pipelines/datasets/br_denatran_frota/flows.py | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index d2da7f9c1..cf70610fa 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -165,13 +165,13 @@ csv_output = output_file_to_csv_task( df, constants.MUNIC_TIPO_BASIC_FILENAME.value, upstream_tasks=[df] ) - # wait_upload_table = create_table_and_upload_to_gcs( - # data_path=csv_output, - # dataset_id=dataset_id, - # table_id=table_id, - # dump_mode="append", - # wait=csv_output, - # ) + wait_upload_table = create_table_and_upload_to_gcs( + data_path=csv_output, + dataset_id=dataset_id, + table_id=table_id, + dump_mode="append", + wait=csv_output, + ) with case(materialize_after_dump, True): # Trigger DBT flow run From 6fc22412970699be3a39a735e4d95eeb1572718c Mon Sep 17 00:00:00 2001 From: folhesgabriel Date: Tue, 4 Jul 2023 07:37:56 -0300 Subject: [PATCH 184/265] re register flow --- pipelines/datasets/br_denatran_frota/flows.py | 1 - 1 file changed, 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index cf70610fa..ebf4110f3 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -69,7 +69,6 @@ temp_dir=unmapped(constants.DOWNLOAD_PATH.value), ) # Now get the downloaded file: - # Now get the downloaded file: municipio_tipo_file = get_desired_file_task.map( year=[date[0] for date in date_pairs_param], month=[date[1] for date in date_pairs_param], From eaeacfe10d1c912c9544bc9f5d1912d79ee91b7c Mon Sep 17 00:00:00 2001 From: folhesgabriel Date: Thu, 6 Jul 2023 20:10:22 -0300 Subject: [PATCH 185/265] re register --- .../datasets/br_denatran_frota/schedules.py | 66 ------------------- 1 file changed, 66 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/schedules.py b/pipelines/datasets/br_denatran_frota/schedules.py index 8967b8c93..792760590 100644 --- a/pipelines/datasets/br_denatran_frota/schedules.py +++ b/pipelines/datasets/br_denatran_frota/schedules.py @@ -3,72 +3,6 @@ Schedules for br_denatran_frota """ -############################################################################### -# -# Aqui é onde devem ser definidos os schedules para os flows do projeto. -# Cada schedule indica o intervalo de tempo entre as execuções. -# Um schedule pode ser definido para um ou mais flows. -# Mais informações sobre schedules podem ser encontradas na documentação do -# Prefect: https://docs.prefect.io/core/concepts/schedules.html -# -# De modo a manter consistência na codebase, todo o código escrito passará -# pelo pylint. Todos os warnings e erros devem ser corrigidos. -# -# Os schedules devem ser definidos de acordo com a sintaxe do Prefect, como, -# por exemplo, o seguinte (para executar a cada 1 minuto): -# -# ----------------------------------------------------------------------------- -# from datetime import timedelta, datetime -# from prefect.schedules import Schedule -# from prefect.schedules.clocks import IntervalClock -# from pipelines.constants import constants -# -# minute_schedule = Schedule( -# clocks=[ -# IntervalClock( -# interval=timedelta(minutes=1), -# start_date=datetime(2021, 1, 1), -# labels=[ -# constants.DATASETS_AGENT_LABEL.value, -# ] -# ), -# ] -# ) -# ----------------------------------------------------------------------------- -# -# Vale notar que o parâmetro `labels` é obrigatório e deve ser uma lista com -# apenas um elemento, correspondendo ao label do agente que será executado. -# O label do agente é definido em `constants.py` e deve ter o formato -# `DATASETS_AGENT_LABEL`. -# -# Outro exemplo, para executar todos os dias à meia noite, segue abaixo: -# -# ----------------------------------------------------------------------------- -# from prefect import task -# from datetime import timedelta -# import pendulum -# from prefect.schedules import Schedule -# from prefect.schedules.clocks import IntervalClock -# from pipelines.constants import constants -# -# every_day_at_midnight = Schedule( -# clocks=[ -# IntervalClock( -# interval=timedelta(days=1), -# start_date=pendulum.datetime( -# 2021, 1, 1, 0, 0, 0, tz="America/Sao_Paulo"), -# labels=[ -# constants.K8S_AGENT_LABEL.value, -# ] -# ) -# ] -# ) -# ----------------------------------------------------------------------------- -# -# Abaixo segue um código para exemplificação, que pode ser removido. -# -############################################################################### - from datetime import timedelta, datetime from prefect.schedules import Schedule From 0e96d9deb13c52c1562b3e1e1f5cbeea1dff453e Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 9 Jul 2023 20:55:18 -0300 Subject: [PATCH 186/265] =?UTF-8?q?Sei=20l=C3=A1?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- pipelines/datasets/br_denatran_frota/tasks.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/tasks.py b/pipelines/datasets/br_denatran_frota/tasks.py index 2edcfd86e..ca8c23ff0 100644 --- a/pipelines/datasets/br_denatran_frota/tasks.py +++ b/pipelines/datasets/br_denatran_frota/tasks.py @@ -73,7 +73,7 @@ @task() # noqa -def crawl_task(month: int, year: int, temp_dir: str = "") -> None: +def crawl_task(month: int, year: int, temp_dir: str = "") -> tuple: return crawl(month, year, temp_dir) From 99229625c4ee05becc212c4a74c31ad358bcc94f Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 9 Jul 2023 21:09:40 -0300 Subject: [PATCH 187/265] uh --- pipelines/datasets/br_denatran_frota/flows.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index ebf4110f3..051914bc4 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -37,7 +37,7 @@ month_range = list(range(1, 13)) date_pairs = list(product(year_range, month_range)) -date_pairs_param = Parameter("date_pairs", default=date_pairs) +date_pairs_param: list[tuple] = Parameter("date_pairs", default=date_pairs) # from pipelines.datasets.br_denatran_frota.schedules import every_two_weeks From 6e38a4f9fd62a977b02e550feddebabe2f613549 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Mon, 10 Jul 2023 01:15:00 +0000 Subject: [PATCH 188/265] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- pipelines/datasets/br_denatran_frota/flows.py | 2 +- pipelines/datasets/br_denatran_frota/handlers.py | 6 ++++-- pipelines/datasets/br_denatran_frota/tasks.py | 3 ++- pipelines/datasets/br_denatran_frota/tasks_test.py | 5 +++-- 4 files changed, 10 insertions(+), 6 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index 841f75712..141694f05 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -79,7 +79,7 @@ file=municipio_tipo_file, upstream_tasks=[crawled, municipio_tipo_file] ) csv_output = output_file_to_csv_task( - df,constants.UF_TIPO_BASIC_FILENAME.value, upstream_tasks=[df] + df, constants.UF_TIPO_BASIC_FILENAME.value, upstream_tasks=[df] ) wait_upload_table = create_table_and_upload_to_gcs( data_path=csv_output, diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 6a8a54cac..46d99af4f 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -146,12 +146,14 @@ def get_desired_file(year: int, download_directory: str, filetype: str) -> str: def get_latest_data(table_name: str): denatran_data = get_data_from_prod( - table_id=table_name, dataset_id="br_denatran_frota") + table_id=table_name, dataset_id="br_denatran_frota" + ) denatran_data: pl.DataFrame = pl.from_pandas(denatran_data) year = denatran_data.select(pl.max("ano")) log(year) return year - + + def treat_municipio_tipo(file: str) -> pl.DataFrame: bd_municipios = get_data_from_prod( table_id="municipio", dataset_id="br_bd_diretorios_brasil" diff --git a/pipelines/datasets/br_denatran_frota/tasks.py b/pipelines/datasets/br_denatran_frota/tasks.py index 9853623dd..2dc8793c5 100644 --- a/pipelines/datasets/br_denatran_frota/tasks.py +++ b/pipelines/datasets/br_denatran_frota/tasks.py @@ -61,7 +61,7 @@ output_file_to_csv, get_desired_file, treat_municipio_tipo, - get_latest_data + get_latest_data, ) from pipelines.utils.utils import ( log, @@ -99,6 +99,7 @@ def get_desired_file_task(year: int, download_directory: str, filetype: str) -> def treat_municipio_tipo_task(file: str) -> pl.DataFrame: return treat_municipio_tipo(file) + @task() def get_latest_data_task(table_name: str): return get_latest_data(table_name) diff --git a/pipelines/datasets/br_denatran_frota/tasks_test.py b/pipelines/datasets/br_denatran_frota/tasks_test.py index dc80a4362..a434ed96d 100644 --- a/pipelines/datasets/br_denatran_frota/tasks_test.py +++ b/pipelines/datasets/br_denatran_frota/tasks_test.py @@ -12,7 +12,7 @@ treat_uf_tipo, get_desired_file, treat_municipio_tipo, - get_latest_data + get_latest_data, ) from pipelines.datasets.br_denatran_frota.constants import constants @@ -97,7 +97,8 @@ def test_flow(self): class TestGetLatestData(unittest.TestCase): def test_year(self): - self.assertEqual(2021, get_latest_data('municipio')) + self.assertEqual(2021, get_latest_data("municipio")) + class TestMunicipioTreatmentPostCrawl(unittest.TestCase): def setUp(self): From 944d93103ff0137761de64dac5c67702d4ae7445 Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 9 Jul 2023 22:15:14 -0300 Subject: [PATCH 189/265] Teste pra task nova --- pipelines/datasets/br_denatran_frota/flows.py | 31 +++++++++---------- .../datasets/br_denatran_frota/handlers.py | 8 +++++ pipelines/datasets/br_denatran_frota/tasks.py | 5 +++ .../datasets/br_denatran_frota/tasks_test.py | 5 +++ 4 files changed, 33 insertions(+), 16 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index 051914bc4..841f75712 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -63,30 +63,29 @@ rename_flow_run = rename_current_flow_run_dataset_table( prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id ) - crawled = crawl_task.map( - month=[date[1] for date in date_pairs_param], - year=[date[0] for date in date_pairs_param], - temp_dir=unmapped(constants.DOWNLOAD_PATH.value), + crawled = crawl_task( + month=1, + year=2003, + temp_dir=constants.DOWNLOAD_PATH.value, ) # Now get the downloaded file: - municipio_tipo_file = get_desired_file_task.map( - year=[date[0] for date in date_pairs_param], - month=[date[1] for date in date_pairs_param], - download_directory=unmapped(constants.DOWNLOAD_PATH.value), - filetype=unmapped(constants.UF_TIPO_BASIC_FILENAME.value), + municipio_tipo_file = get_desired_file_task( + year=2003, + download_directory=constants.DOWNLOAD_PATH.value, + filetype=constants.UF_TIPO_BASIC_FILENAME.value, upstream_tasks=[crawled], ) - df = treat_uf_tipo_task.map( + df = treat_uf_tipo_task( file=municipio_tipo_file, upstream_tasks=[crawled, municipio_tipo_file] ) - csv_output = output_file_to_csv_task.map( - df, unmapped(constants.UF_TIPO_BASIC_FILENAME.value), upstream_tasks=[df] + csv_output = output_file_to_csv_task( + df,constants.UF_TIPO_BASIC_FILENAME.value, upstream_tasks=[df] ) - wait_upload_table = create_table_and_upload_to_gcs.map( + wait_upload_table = create_table_and_upload_to_gcs( data_path=csv_output, - dataset_id=unmapped(dataset_id), - table_id=unmapped(table_id), - dump_mode=unmapped("append"), + dataset_id=dataset_id, + table_id=table_id, + dump_mode="append", wait=csv_output, ) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 175f5ed2b..6a8a54cac 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -144,6 +144,14 @@ def get_desired_file(year: int, download_directory: str, filetype: str) -> str: raise ValueError("No files found buckaroo") +def get_latest_data(table_name: str): + denatran_data = get_data_from_prod( + table_id=table_name, dataset_id="br_denatran_frota") + denatran_data: pl.DataFrame = pl.from_pandas(denatran_data) + year = denatran_data.select(pl.max("ano")) + log(year) + return year + def treat_municipio_tipo(file: str) -> pl.DataFrame: bd_municipios = get_data_from_prod( table_id="municipio", dataset_id="br_bd_diretorios_brasil" diff --git a/pipelines/datasets/br_denatran_frota/tasks.py b/pipelines/datasets/br_denatran_frota/tasks.py index ca8c23ff0..9853623dd 100644 --- a/pipelines/datasets/br_denatran_frota/tasks.py +++ b/pipelines/datasets/br_denatran_frota/tasks.py @@ -61,6 +61,7 @@ output_file_to_csv, get_desired_file, treat_municipio_tipo, + get_latest_data ) from pipelines.utils.utils import ( log, @@ -97,3 +98,7 @@ def get_desired_file_task(year: int, download_directory: str, filetype: str) -> @task() def treat_municipio_tipo_task(file: str) -> pl.DataFrame: return treat_municipio_tipo(file) + +@task() +def get_latest_data_task(table_name: str): + return get_latest_data(table_name) diff --git a/pipelines/datasets/br_denatran_frota/tasks_test.py b/pipelines/datasets/br_denatran_frota/tasks_test.py index 7dfb75d58..dc80a4362 100644 --- a/pipelines/datasets/br_denatran_frota/tasks_test.py +++ b/pipelines/datasets/br_denatran_frota/tasks_test.py @@ -12,6 +12,7 @@ treat_uf_tipo, get_desired_file, treat_municipio_tipo, + get_latest_data ) from pipelines.datasets.br_denatran_frota.constants import constants @@ -94,6 +95,10 @@ def test_flow(self): self.assertTrue(type(df), pl.DataFrame) +class TestGetLatestData(unittest.TestCase): + def test_year(self): + self.assertEqual(2021, get_latest_data('municipio')) + class TestMunicipioTreatmentPostCrawl(unittest.TestCase): def setUp(self): self.temp_dir = tempfile.TemporaryDirectory( From e5f50b978fe8b333d12d811f52665bff010830a2 Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 9 Jul 2023 22:17:11 -0300 Subject: [PATCH 190/265] Modifica flow de acodo --- pipelines/datasets/br_denatran_frota/flows.py | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index 841f75712..9474b2c5e 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -29,6 +29,7 @@ output_file_to_csv_task, get_desired_file_task, treat_municipio_tipo_task, + get_latest_data_task ) from pipelines.datasets.br_denatran_frota.constants import constants from itertools import product @@ -63,10 +64,13 @@ rename_flow_run = rename_current_flow_run_dataset_table( prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id ) + + year_to_fetch = get_latest_data_task('uf_tipo') crawled = crawl_task( month=1, - year=2003, + year=year_to_fetch, temp_dir=constants.DOWNLOAD_PATH.value, + upstream_tasks=[year_to_fetch] ) # Now get the downloaded file: municipio_tipo_file = get_desired_file_task( From 99617f9d101edda4d25521b284f6a5cb35afdd53 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Mon, 10 Jul 2023 01:18:53 +0000 Subject: [PATCH 191/265] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- pipelines/datasets/br_denatran_frota/flows.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index 894533e1d..a773438e5 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -29,7 +29,7 @@ output_file_to_csv_task, get_desired_file_task, treat_municipio_tipo_task, - get_latest_data_task + get_latest_data_task, ) from pipelines.datasets.br_denatran_frota.constants import constants from itertools import product @@ -65,12 +65,12 @@ prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id ) - year_to_fetch = get_latest_data_task('uf_tipo') + year_to_fetch = get_latest_data_task("uf_tipo") crawled = crawl_task( month=1, year=year_to_fetch, temp_dir=constants.DOWNLOAD_PATH.value, - upstream_tasks=[year_to_fetch] + upstream_tasks=[year_to_fetch], ) # Now get the downloaded file: municipio_tipo_file = get_desired_file_task( From 15e34a759f26e0697d9df571d9b49f3552c6fa3e Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Mon, 10 Jul 2023 01:34:51 +0000 Subject: [PATCH 192/265] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- pipelines/datasets/br_denatran_frota/utils.py | 1 - 1 file changed, 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index 980a5cdad..5ed81e289 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -580,4 +580,3 @@ def get_data_from_prod(dataset_id: str, table_id: str) -> list: df = pd.concat(dfs) return df - From e1780b30166f6490be6e6c0bf458cb61e295f409 Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 9 Jul 2023 22:34:54 -0300 Subject: [PATCH 193/265] Error handling --- pipelines/datasets/br_denatran_frota/handlers.py | 12 ++++++++---- pipelines/datasets/br_denatran_frota/utils.py | 5 +++-- 2 files changed, 11 insertions(+), 6 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 46d99af4f..9bdd0dd79 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -148,10 +148,14 @@ def get_latest_data(table_name: str): denatran_data = get_data_from_prod( table_id=table_name, dataset_id="br_denatran_frota" ) - denatran_data: pl.DataFrame = pl.from_pandas(denatran_data) - year = denatran_data.select(pl.max("ano")) - log(year) - return year + if denatran_data: + denatran_data: pl.DataFrame = pl.from_pandas(denatran_data) + year = denatran_data.select(pl.max("ano")) + log(year) + return year + else: + log("Não achei ano não mané") + return 2003 def treat_municipio_tipo(file: str) -> pl.DataFrame: diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index ca4eba1c9..980a5cdad 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -576,7 +576,8 @@ def get_data_from_prod(dataset_id: str, table_id: str) -> list: for column in columns2add: df[column] = blob.name.split(column + "=")[1].split("/")[0] dfs.append(df) + if dfs: + df = pd.concat(dfs) - df = pd.concat(dfs) + return df - return df From 38428abdf71fc0afd5a3299a8bfabd31260c905d Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Mon, 10 Jul 2023 01:46:31 +0000 Subject: [PATCH 194/265] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- pipelines/datasets/br_denatran_frota/handlers.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 1f87b6d9a..f9b12fbfb 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -151,12 +151,12 @@ def get_latest_data(table_name: str): if denatran_data: denatran_data: pl.DataFrame = pl.from_pandas(denatran_data) year = denatran_data.select(pl.max("ano")) - month = denatran_data.filter(pl.col('ano') == year).select(pl.max('mes')) + month = denatran_data.filter(pl.col("ano") == year).select(pl.max("mes")) if month == 12: year += 1 month = 1 log(f"Ano: {year}, mês: {month+1}") - return year, month+1 + return year, month + 1 else: log("Não achei ano não mané") return 2003, 1 From a67db8a20707323f2908d3825ba197a96c0c115d Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 9 Jul 2023 22:46:35 -0300 Subject: [PATCH 195/265] Tenta usar ano e mes de prod --- pipelines/datasets/br_denatran_frota/flows.py | 6 +++--- pipelines/datasets/br_denatran_frota/handlers.py | 10 +++++++--- pipelines/datasets/br_denatran_frota/tasks.py | 2 +- 3 files changed, 11 insertions(+), 7 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index a773438e5..07c0ae14a 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -67,14 +67,14 @@ year_to_fetch = get_latest_data_task("uf_tipo") crawled = crawl_task( - month=1, - year=year_to_fetch, + month=year_to_fetch[1], + year=year_to_fetch[0], temp_dir=constants.DOWNLOAD_PATH.value, upstream_tasks=[year_to_fetch], ) # Now get the downloaded file: municipio_tipo_file = get_desired_file_task( - year=2003, + year=year_to_fetch[0], download_directory=constants.DOWNLOAD_PATH.value, filetype=constants.UF_TIPO_BASIC_FILENAME.value, upstream_tasks=[crawled], diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 9bdd0dd79..1f87b6d9a 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -151,11 +151,15 @@ def get_latest_data(table_name: str): if denatran_data: denatran_data: pl.DataFrame = pl.from_pandas(denatran_data) year = denatran_data.select(pl.max("ano")) - log(year) - return year + month = denatran_data.filter(pl.col('ano') == year).select(pl.max('mes')) + if month == 12: + year += 1 + month = 1 + log(f"Ano: {year}, mês: {month+1}") + return year, month+1 else: log("Não achei ano não mané") - return 2003 + return 2003, 1 def treat_municipio_tipo(file: str) -> pl.DataFrame: diff --git a/pipelines/datasets/br_denatran_frota/tasks.py b/pipelines/datasets/br_denatran_frota/tasks.py index 2dc8793c5..98f2a8d5b 100644 --- a/pipelines/datasets/br_denatran_frota/tasks.py +++ b/pipelines/datasets/br_denatran_frota/tasks.py @@ -101,5 +101,5 @@ def treat_municipio_tipo_task(file: str) -> pl.DataFrame: @task() -def get_latest_data_task(table_name: str): +def get_latest_data_task(table_name: str) -> tuple[int, int]: return get_latest_data(table_name) From a2ca3881ddec1f23ce00e3187aa4a0b2fc0df7c3 Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 9 Jul 2023 22:55:34 -0300 Subject: [PATCH 196/265] Ops --- pipelines/datasets/br_denatran_frota/handlers.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 1f87b6d9a..39f086e88 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -148,7 +148,7 @@ def get_latest_data(table_name: str): denatran_data = get_data_from_prod( table_id=table_name, dataset_id="br_denatran_frota" ) - if denatran_data: + if not denatran_data.is_empty(): denatran_data: pl.DataFrame = pl.from_pandas(denatran_data) year = denatran_data.select(pl.max("ano")) month = denatran_data.filter(pl.col('ano') == year).select(pl.max('mes')) From 0cf432c2151be5138d7fc082b35b491668d2d3bc Mon Sep 17 00:00:00 2001 From: Tamir Date: Sun, 9 Jul 2023 23:56:12 -0300 Subject: [PATCH 197/265] ah ok --- pipelines/datasets/br_denatran_frota/handlers.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 7ee841370..199076e9e 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -145,11 +145,11 @@ def get_desired_file(year: int, download_directory: str, filetype: str) -> str: def get_latest_data(table_name: str): - denatran_data = get_data_from_prod( + denatran_data_pandas: pd.DataFrame = get_data_from_prod( table_id=table_name, dataset_id="br_denatran_frota" ) - if not denatran_data.is_empty(): - denatran_data: pl.DataFrame = pl.from_pandas(denatran_data) + if not denatran_data_pandas.empty: + denatran_data: pl.DataFrame = pl.from_pandas(denatran_data_pandas) year = denatran_data.select(pl.max("ano")) month = denatran_data.filter(pl.col("ano") == year).select(pl.max("mes")) if month == 12: From 63b8e8f2096f7e235fb873e1476891c8d25968e2 Mon Sep 17 00:00:00 2001 From: Tamir Date: Tue, 11 Jul 2023 02:37:12 -0300 Subject: [PATCH 198/265] logs --- pipelines/datasets/br_denatran_frota/handlers.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 199076e9e..665395045 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -152,6 +152,8 @@ def get_latest_data(table_name: str): denatran_data: pl.DataFrame = pl.from_pandas(denatran_data_pandas) year = denatran_data.select(pl.max("ano")) month = denatran_data.filter(pl.col("ano") == year).select(pl.max("mes")) + log(year) + log(month) if month == 12: year += 1 month = 1 From b7ae3bd29ae1295135039fae69976504c0a11dfb Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 12 Jul 2023 03:02:05 -0300 Subject: [PATCH 199/265] mais simples --- pipelines/datasets/br_denatran_frota/handlers.py | 9 ++++----- 1 file changed, 4 insertions(+), 5 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 665395045..20fb62f00 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -145,13 +145,12 @@ def get_desired_file(year: int, download_directory: str, filetype: str) -> str: def get_latest_data(table_name: str): - denatran_data_pandas: pd.DataFrame = get_data_from_prod( + denatran_data: pd.DataFrame = get_data_from_prod( table_id=table_name, dataset_id="br_denatran_frota" ) - if not denatran_data_pandas.empty: - denatran_data: pl.DataFrame = pl.from_pandas(denatran_data_pandas) - year = denatran_data.select(pl.max("ano")) - month = denatran_data.filter(pl.col("ano") == year).select(pl.max("mes")) + if not denatran_data.empty: + year = denatran_data['ano'].max() + month = denatran_data.loc[denatran_data['ano'] == year]["mes"].max() log(year) log(month) if month == 12: From c1658350feb310c3cf0e900bce04ed7414bba046 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Wed, 12 Jul 2023 06:04:36 +0000 Subject: [PATCH 200/265] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- pipelines/datasets/br_denatran_frota/handlers.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 20fb62f00..cdd50a34e 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -149,8 +149,8 @@ def get_latest_data(table_name: str): table_id=table_name, dataset_id="br_denatran_frota" ) if not denatran_data.empty: - year = denatran_data['ano'].max() - month = denatran_data.loc[denatran_data['ano'] == year]["mes"].max() + year = denatran_data["ano"].max() + month = denatran_data.loc[denatran_data["ano"] == year]["mes"].max() log(year) log(month) if month == 12: From 7a8e33caf55b3bb28f2e1672022ee54b52cc581f Mon Sep 17 00:00:00 2001 From: Tamir Date: Wed, 12 Jul 2023 03:19:24 -0300 Subject: [PATCH 201/265] Flows flows flows --- pipelines/datasets/br_denatran_frota/flows.py | 12 +++++++++--- 1 file changed, 9 insertions(+), 3 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index 07c0ae14a..01fa11d4d 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -135,7 +135,7 @@ "Tamir", ], ) as br_denatran_frota_municipio_tipo: - year = 2021 + dataset_id = Parameter("dataset_id", default="br_denatran_frota") table_id = Parameter("table_id", default="municipio_tipo") @@ -153,10 +153,16 @@ rename_flow_run = rename_current_flow_run_dataset_table( prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id ) - crawled = crawl_task(month=2, year=year, temp_dir=constants.DOWNLOAD_PATH.value) + year_to_fetch = get_latest_data_task("municipio_tipo") + crawled = crawl_task( + month=year_to_fetch[1], + year=year_to_fetch[0], + temp_dir=constants.DOWNLOAD_PATH.value, + upstream_tasks=[year_to_fetch], + ) # Now get the downloaded file: municipio_tipo_file = get_desired_file_task( - year=year, + year=year_to_fetch[0], download_directory=constants.DOWNLOAD_PATH.value, filetype=constants.MUNIC_TIPO_BASIC_FILENAME.value, upstream_tasks=[crawled], From 99f1b6a7d27e4245be0c3705b69bd3ae2c885d70 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Wed, 12 Jul 2023 06:19:41 +0000 Subject: [PATCH 202/265] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- pipelines/datasets/br_denatran_frota/flows.py | 1 - 1 file changed, 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index 01fa11d4d..d23f80558 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -135,7 +135,6 @@ "Tamir", ], ) as br_denatran_frota_municipio_tipo: - dataset_id = Parameter("dataset_id", default="br_denatran_frota") table_id = Parameter("table_id", default="municipio_tipo") From f940d885aa4b97b8923ba0922093d507018de589 Mon Sep 17 00:00:00 2001 From: Tamir Date: Thu, 17 Aug 2023 02:08:21 -0300 Subject: [PATCH 203/265] Adiciona particionamento --- pipelines/datasets/br_denatran_frota/handlers.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index cdd50a34e..67ee3ee8f 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -126,7 +126,8 @@ def treat_uf_tipo(file: str) -> pl.DataFrame: def output_file_to_csv(df: pl.DataFrame, filename: str) -> None: make_dir_when_not_exists(OUTPUT_PATH) - df.write_csv(file=f"{OUTPUT_PATH}/{filename}.csv", has_header=True) + pd_df = df.to_pandas() + to_partitions(pd_df, partition_columns=["ano", "mes", "sigla_uf"], savepath=OUTPUT_PATH) return OUTPUT_PATH From c4296e3ca40ed5a170c90b15fcabd93c244fb8f5 Mon Sep 17 00:00:00 2001 From: Tamir Date: Fri, 25 Aug 2023 13:28:32 -0300 Subject: [PATCH 204/265] Guard pra caso falhe o fetch de prod --- pipelines/datasets/br_denatran_frota/handlers.py | 9 ++++++--- 1 file changed, 6 insertions(+), 3 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 67ee3ee8f..21c0f8ef5 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -146,9 +146,12 @@ def get_desired_file(year: int, download_directory: str, filetype: str) -> str: def get_latest_data(table_name: str): - denatran_data: pd.DataFrame = get_data_from_prod( - table_id=table_name, dataset_id="br_denatran_frota" - ) + try: + denatran_data: pd.DataFrame = get_data_from_prod( + table_id=table_name, dataset_id="br_denatran_frota" + ) + except: + return 2003, 1 if not denatran_data.empty: year = denatran_data["ano"].max() month = denatran_data.loc[denatran_data["ano"] == year]["mes"].max() From b9752250857aeae47a1c219fec47ccbbd5262277 Mon Sep 17 00:00:00 2001 From: Tamir Date: Fri, 25 Aug 2023 13:32:23 -0300 Subject: [PATCH 205/265] deploya pls --- pipelines/datasets/br_denatran_frota/tasks.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/tasks.py b/pipelines/datasets/br_denatran_frota/tasks.py index 98f2a8d5b..fb0c94dfb 100644 --- a/pipelines/datasets/br_denatran_frota/tasks.py +++ b/pipelines/datasets/br_denatran_frota/tasks.py @@ -86,7 +86,6 @@ def treat_uf_tipo_task(file) -> pl.DataFrame: @task() def output_file_to_csv_task(df: pl.DataFrame, filename: str) -> None: - log(filename) return output_file_to_csv(df, filename) @@ -103,3 +102,4 @@ def treat_municipio_tipo_task(file: str) -> pl.DataFrame: @task() def get_latest_data_task(table_name: str) -> tuple[int, int]: return get_latest_data(table_name) + From 8abb9b40a591fab29dedc9972500d2ee5cd389e7 Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Tue, 29 Aug 2023 00:37:25 -0300 Subject: [PATCH 206/265] =?UTF-8?q?Remove=20pasta=20desnecess=C3=A1ria,=20?= =?UTF-8?q?deploya=20por=20favor?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- br_denatran_frota/README.md | 20 - br_denatran_frota/code/__init__.py | 0 br_denatran_frota/code/constants.py | 60 - br_denatran_frota/code/download_frota.R | 123 - br_denatran_frota/code/download_frota.py | 52 - br_denatran_frota/code/download_frota_old.R | 106 - br_denatran_frota/code/frota_municipio_tipo.R | 137 - .../code/frota_municipio_tipo.py | 72 - br_denatran_frota/code/frota_uf_tipo.R | 97 - br_denatran_frota/code/frota_uf_tipo.py | 70 - br_denatran_frota/code/setup.py | 12 - .../test/download_frota_integration_test.py | 50 - br_denatran_frota/code/test_drive.ipynb | 312 -- br_denatran_frota/code/utils.R | 207 -- br_denatran_frota/code/utils.py | 276 -- br_denatran_frota/dataset_config.yaml | 69 - br_denatran_frota/municipio_tipo/publish.sql | 50 - .../municipio_tipo/schema-prod.json | 1 - .../municipio_tipo/schema-staging.json | 1 - .../municipio_tipo/table_config.yaml | 268 -- .../municipio_tipo/table_description.txt | 67 - br_denatran_frota/uf_tipo/publish.sql | 49 - br_denatran_frota/uf_tipo/schema-prod.json | 1 - br_denatran_frota/uf_tipo/table_config.yaml | 263 -- .../uf_tipo/table_description.txt | 67 - pipelines/datasets/br_denatran_frota/tasks.py | 49 - poetry.lock | 2597 +++++++++++++---- 27 files changed, 1986 insertions(+), 3090 deletions(-) delete mode 100644 br_denatran_frota/README.md delete mode 100644 br_denatran_frota/code/__init__.py delete mode 100644 br_denatran_frota/code/constants.py delete mode 100644 br_denatran_frota/code/download_frota.R delete mode 100644 br_denatran_frota/code/download_frota.py delete mode 100644 br_denatran_frota/code/download_frota_old.R delete mode 100644 br_denatran_frota/code/frota_municipio_tipo.R delete mode 100644 br_denatran_frota/code/frota_municipio_tipo.py delete mode 100644 br_denatran_frota/code/frota_uf_tipo.R delete mode 100644 br_denatran_frota/code/frota_uf_tipo.py delete mode 100644 br_denatran_frota/code/setup.py delete mode 100644 br_denatran_frota/code/test/download_frota_integration_test.py delete mode 100644 br_denatran_frota/code/test_drive.ipynb delete mode 100644 br_denatran_frota/code/utils.R delete mode 100644 br_denatran_frota/code/utils.py delete mode 100644 br_denatran_frota/dataset_config.yaml delete mode 100644 br_denatran_frota/municipio_tipo/publish.sql delete mode 100644 br_denatran_frota/municipio_tipo/schema-prod.json delete mode 100644 br_denatran_frota/municipio_tipo/schema-staging.json delete mode 100644 br_denatran_frota/municipio_tipo/table_config.yaml delete mode 100644 br_denatran_frota/municipio_tipo/table_description.txt delete mode 100644 br_denatran_frota/uf_tipo/publish.sql delete mode 100644 br_denatran_frota/uf_tipo/schema-prod.json delete mode 100644 br_denatran_frota/uf_tipo/table_config.yaml delete mode 100644 br_denatran_frota/uf_tipo/table_description.txt diff --git a/br_denatran_frota/README.md b/br_denatran_frota/README.md deleted file mode 100644 index d8415e1fd..000000000 --- a/br_denatran_frota/README.md +++ /dev/null @@ -1,20 +0,0 @@ -# Frota de Veículos - -Como capturar os dados de br_denatran_frota? - -1. Para capturar esses dados, basta verificar o link dos dados originais indicado em `dataset_config.yaml` no item `website`. - -2. Caso tenha sido utilizado algum código de captura ou tratamento, estes estarão contidos em `code/`. Se o dado publicado for em sua versão bruta, não existirá a pasta `code/`. - -Os dados publicados estão disponíveis em: https://basedosdados.org/dataset/br-denatran-frota - -## Download e Leitura - -Dependências: - -- [unrar](https://www.rarlab.com/rar_add.htm) para extrair os arquivos `.rar` via cli. - -Ubuntu e Debian: -```sh -sudo apt-get install unrar -``` \ No newline at end of file diff --git a/br_denatran_frota/code/__init__.py b/br_denatran_frota/code/__init__.py deleted file mode 100644 index e69de29bb..000000000 diff --git a/br_denatran_frota/code/constants.py b/br_denatran_frota/code/constants.py deleted file mode 100644 index ce21f239e..000000000 --- a/br_denatran_frota/code/constants.py +++ /dev/null @@ -1,60 +0,0 @@ -# -*- coding: utf-8 -*- - -MONTHS = { - "janeiro": 1, - "fevereiro": 2, - "marco": 3, - "abril": 4, - "maio": 5, - "junho": 6, - "julho": 7, - "agosto": 8, - "setembro": 9, - "outubro": 10, - "novembro": 11, - "dezembro": 12, -} - -DATASET = "br_denatran_frota" - -HEADERS = { - "User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/39.0.2171.95 Safari/537.36" -} - -DICT_UFS = { - "AC": "Acre", - "AL": "Alagoas", - "AP": "Amapá", - "AM": "Amazonas", - "BA": "Bahia", - "CE": "Ceará", - "DF": "Distrito Federal", - "ES": "Espírito Santo", - "GO": "Goiás", - "MA": "Maranhão", - "MT": "Mato Grosso", - "MS": "Mato Grosso do Sul", - "MG": "Minas Gerais", - "PA": "Pará", - "PB": "Paraíba", - "PR": "Paraná", - "PE": "Pernambuco", - "PI": "Piauí", - "RJ": "Rio de Janeiro", - "RN": "Rio Grande do Norte", - "RS": "Rio Grande do Sul", - "RO": "Rondônia", - "RR": "Roraima", - "SC": "Santa Catarina", - "SP": "São Paulo", - "SE": "Sergipe", - "TO": "Tocantins", -} - -SUBSTITUTIONS = { - ("RN", "assu"): "acu", - ("PB", "sao domingos de pombal"): "sao domingos", - ("PB", "santarem"): "joca claudino", - ("SP", "embu"): "embu das artes", - ("TO", "sao valerio da natividade"): "sao valerio", -} diff --git a/br_denatran_frota/code/download_frota.R b/br_denatran_frota/code/download_frota.R deleted file mode 100644 index e797298ae..000000000 --- a/br_denatran_frota/code/download_frota.R +++ /dev/null @@ -1,123 +0,0 @@ -library(rvest) -library(httr) -library(archive) # -library(magrittr) -library(stringr) -library(tibble) -library(dplyr) -library(purrr) - -download_frota <- function(key = NULL, prefix = NULL, month, year, tempdir = tempdir(), dir = getwd()) { - - months <- c( - "janeiro" = 1, - "fevereiro" = 2, - "marco" = 3, - "abril" = 4, - "maio" = 5, - "junho" = 6, - "julho" = 7, - "agosto" = 8, - "setembro" = 9, - "outubro" = 10, - "novembro" = 11, - "dezembro" = 12 - ) - - if (year > 2012) { - url <- paste0("https://www.gov.br/infraestrutura/pt-br/assuntos/transito/conteudo-denatran/frota-de-veiculos-", year) - } else { - # Antes de 2013 os dados vem em um arquivo unico zip - stop("Utilize a função download_frota_old()") - } - - if (!dir.exists(tempdir)) dir.create(tempdir, recursive = T) - if (!dir.exists(dir)) dir.create(dir, recursive = T) - - download_file <- function(i) { - if (i$filetype %in% c("rar", "zip")) handle_compact(i) - if (i$filetype %in% c("xlsx", "xls")) handle_xl(i) - } - - make_filename <- function(i, ext = TRUE) { - stringi::stri_trans_general(i$txt, id = "Latin-ASCII; lower") %>% - stringr::str_replace_all("\\s+", "_") %>% - paste0(., "_", i$mes, "-", i$ano, ifelse(ext, paste0(".", i$filetype), as.character(""))) - } - - handle_xl <- function(i) { - dest_path_file <- paste0(dir, "/", prefix, "_", i$mes, "-", i$ano, paste0(".", i$filetype)) - if (!file.exists(dest_path_file)) { - utils::download.file( - url = i$href, - destfile = dest_path_file - ) - } - } - - handle_compact <- function(i) { - path_file_zip <- paste0(tempdir, "/", make_filename(i)) - dir_file <- paste0(tempdir, "/", make_filename(i, ext = F)) - - if (!file.exists(path_file_zip)) { - utils::download.file(url = i$href, destfile = path_file_zip) - } - - # archive package has a bug - if (i$filetype == "rar") { - if (!dir.exists(dir_file)) dir.create(dir_file) - system(paste0("unrar -o+ -inul x ", path_file_zip, " ", dir_file)) - } else { - archive::archive_extract(path_file_zip, dir = dir_file) - } - - # Remove rar, zip files. Keep only xls or xlsx - list.files(dir_file, full.names = T, pattern = "rar|zip") %>% purrr::walk(~file.remove(.x)) - - file <- list.files(dir_file) %>% .[!is.na(.)] - - if (length(file) == 0) { - stop(paste0("File not found on dir")) - } - - file_ext <- stringr::str_extract(file, ".(xlsx|xls)") - - # String multibyte is invalid - # file.rename( - # from = paste0(dir_file, "/", file), - # to = paste0(dir_file, "/", prefix, "_", month, "-", year, file_ext) - # ) - - if (!dir.exists(dir)) dir.create(dir) - - file.copy( - overwrite = TRUE, - from = paste0(dir_file, "/", file), - to = paste0(dir, "/", prefix, "_", i$mes, "-", i$ano, file_ext) - ) - - } - - get_html <- xml2::read_html(httr::GET(url, httr::user_agent("httr"))) - nodes <- get_html %>% rvest::html_nodes("p > a") - - tibble::tibble( - txt = nodes %>% rvest::html_text(), - href = nodes %>% rvest::html_attr("href") - ) %>% - dplyr::filter(stringr::str_ends(href, "xls|xlsx|rar|zip")) %>% - dplyr::mutate( - mes_name = stringr::str_match(href, regex(stringr::str_c(names(months), collapse = "|"))) %>% as.vector(), - ano = stringr::str_match(href, "\\d{4}") %>% as.vector() %>% as.numeric(), - mes = months[mes_name], - filetype = stringr::str_match(href, "[a-z]+$") %>% as.vector() - ) %>% - dplyr::filter( - stringr::str_detect(txt, regex(key, ignore_case = TRUE)), - mes %in% month - ) %>% - purrr::transpose() %>% - purrr::walk(~download_file(.x)) -} - -download_frota(year = 2013, month = 1, tempdir = 'p') diff --git a/br_denatran_frota/code/download_frota.py b/br_denatran_frota/code/download_frota.py deleted file mode 100644 index ff4b771f3..000000000 --- a/br_denatran_frota/code/download_frota.py +++ /dev/null @@ -1,52 +0,0 @@ -# -*- coding: utf-8 -*- -import os -import glob -from urllib.request import urlopen, urlretrieve -from zipfile import ZipFile -from br_denatran_frota.code.constants import MONTHS, DATASET -from br_denatran_frota.code.utils import make_dir_when_not_exists, download_post_2012 - - -def download_frota(month: int, year: int, temp_dir: str = ""): - """Função principal para baixar os dados de frota por município e tipo e também por UF e tipo. - - Args: - month (int): Mês desejado. - year (int): Ano desejado. - - Raises: - ValueError: Errors if the month is not a valid one. - """ - if month not in MONTHS.values(): - raise ValueError("Mês inválido.") - - dir_list = glob.glob(f"**/{DATASET}", recursive=True) - # Get the directory where this Python file is located - initial_dir = os.path.dirname(os.path.abspath(__file__)) - if temp_dir: - os.chdir(temp_dir) - # Construct the path to the "files" directory relative to this directory - files_dir = os.path.join(os.getcwd(), "files") - if dir_list: - # I always want to be in the actual folder for this dataset, because I might start in the pipelines full repo: - os.chdir(dir_list[0]) - - # I always need a files directory inside my dataset folder. - make_dir_when_not_exists(files_dir) - # I should always switch to the files dir now and save stuff inside it. - os.chdir(files_dir) - year_dir_name = f"{year}" - - # Create dir for that specific year should it be necessary. - make_dir_when_not_exists(year_dir_name) - os.chdir(year_dir_name) - if year > 2012: - download_post_2012(month, year) - else: - url = f"https://www.gov.br/infraestrutura/pt-br/assuntos/transito/arquivos-senatran/estatisticas/renavam/{year}/frota{'_' if year > 2008 else ''}{year}.zip" - - generic_zip_filename = f"geral_{year}.zip" - urlretrieve(url, generic_zip_filename) - with ZipFile(generic_zip_filename) as zip_file: - zip_file.extractall() - os.chdir(initial_dir) diff --git a/br_denatran_frota/code/download_frota_old.R b/br_denatran_frota/code/download_frota_old.R deleted file mode 100644 index fa3b4b45f..000000000 --- a/br_denatran_frota/code/download_frota_old.R +++ /dev/null @@ -1,106 +0,0 @@ -library(archive) # -library(stringr) -library(stringi) - -download_frota_old <- function(key = NULL, prefix = NULL, year, tempdir = tempdir(), dir = getwd()) { - - if (year > 2012) { - stop("Utilize download_frota()") - } - - mi_url <- paste0( - "https://www.gov.br/infraestrutura/pt-br/assuntos/transito/arquivos-denatran/estatisticas/renavam/", - year, - "/frota", - ifelse(year > 2008, "_", ""), - year, - ".zip" - ) - - if (!dir.exists(tempdir)) dir.create(tempdir, recursive = T) - if (!dir.exists(dir)) dir.create(dir, recursive = T) - - dir_temp <- paste0(tempdir, "/", "frota__", year) - path_file <- paste0(dir_temp, ".zip") - - if (!file.exists(path_file)) { - tryCatch( - utils::download.file( - url = mi_url, - destfile = path_file - ), - error = function(e) { - if (file.exists(path_file)) { - file.remove(path_file) - } - } - ) - - utils::unzip( - path_file, - exdir = paste0(tempdir, "/", "frota__", year) - ) - } - - months <- c( - "jan" = 1, - "fev" = 2, - "mar" = 3, - "abr" = 4, - "mai" = 5, - "jun" = 6, - "jul" = 7, - "ago" = 8, - "set" = 9, - "out" = 10, - "nov" = 11, - "dez" = 12 - ) - - list.files(path = dir_temp, full.names = T, recursive = T) %>% - purrr::walk(function(i) { - if (stringr::str_ends(i, ".zip")) { - utils::unzip(i, exdir = paste0(dirname(i), "/")) - } - }) - - list.files(path = dir_temp, full.names = T, recursive = T) %>% - purrr::walk(function(i) { - - get_by <- list( - regiao = "(frota tipo uf)|(frota uf)|(frota regiao uf)|(frota regiao tipo uf)", - municipio = "(frota munic)|(frota mun)" - ) - - new_name <- basename(i) %>% - stringi::stri_trans_general(id = "Latin-ASCII; lower") %>% - stringr::str_replace("regi�es", "regiao") %>% - stringr::str_replace_all("\\s+", "_") %>% - stringr::str_replace_all("_|-", " ") %>% - stringr::str_replace("^(\\d\\_|\\d)+", "") %>% - stringr::str_replace_all("internet|^\\s", "") - - # Match jan|fev|... or number of month (two digits) - get_month <- stringr::str_match( - new_name, - regex(paste0(stringr::str_c(names(months), collapse = "|"), "|\\d{2}(?=\\d{4})"), ignore_case = T) - ) - - month_i <- ifelse( - stringr::str_count(get_month) == 2, - as.numeric(get_month), - months[get_month] - ) - - file_ext <- stringr::str_extract(new_name, ".[a-zA-Z0-9]+$") - - if (stringr::str_detect(new_name, regex(get_by[[key]], ignore_case = T)) & - stringr::str_ends(new_name, "(xls|xlsx)$")) { - # print(paste0(paste0(dir, "/", prefix, "-", month_i, "-", year, file_ext), "--", i)) - file.copy( - from = i, - to = paste0(dir, "/", prefix, "_", month_i, "-", year, file_ext) - ) - } - }) -} \ No newline at end of file diff --git a/br_denatran_frota/code/frota_municipio_tipo.R b/br_denatran_frota/code/frota_municipio_tipo.R deleted file mode 100644 index 837c9a22e..000000000 --- a/br_denatran_frota/code/frota_municipio_tipo.R +++ /dev/null @@ -1,137 +0,0 @@ -library(janitor) -library(lubridate) -library(xlsx) # -library(readxl) -library(dplyr) -library(tidyr) -library(magrittr) -library(purrr) -library(readr) -library(stringr) -library(stringdist) - -source("code/download_frota.R") -source("code/download_frota_old.R") -source("code/utils.R") - -PATH_TEMP <- paste0(getwd(), "/tmp") -PATH_DOWNLOAD_MUN <- paste0(getwd(), "/input/frota_municipio_tipo") -PREFIX_FROTA_MUN <- "frota_mun_tipo" - -# Download da frota de 2004 a 2012 por municipio -2003:2012 %>% purrr::walk( - ~download_frota_old( - key = "municipio", - prefix = PREFIX_FROTA_MUN, - year = .x, - tempdir = PATH_TEMP, - dir = PATH_DOWNLOAD_MUN - ) -) - -2014:2020 %>% purrr::walk( - ~download_frota( - key = "Frota por Munic", - prefix = PREFIX_FROTA_MUN, - month = 1:12, - year = .x, - tempdir = PATH_TEMP, - dir = PATH_DOWNLOAD_MUN - ) -) - -2021 %>% purrr::walk( - ~download_frota( - key = "Frota por Munic", - prefix = PREFIX_FROTA_MUN, - month = 1:3, - year = .x, - tempdir = PATH_TEMP, - dir = PATH_DOWNLOAD_MUN - ) -) - -list.files(PATH_DOWNLOAD_MUN, full.names = T) %>% - purrr::map( - ~read_xl(.x, type = "uf") %>% - dplyr::select(!total) %>% - dplyr::rename(sigla_uf = uf, municipio_original = municipio) %>% - dplyr::filter(sigla_uf %in% names(siglas_uf)) %>% - dplyr::mutate( - dplyr::across(!c(sigla_uf, municipio_original), as.numeric), - id_municipio = purrr::map2_chr(sigla_uf, municipio_original, ~get_ibge_info(.x, .y)) - ) %>% - dplyr::relocate(c(id_municipio, ano, mes), .after = municipio_original) - ) -> frota_municipios - - -# Cada tibble deve ter 28 colunas -frota_municipios %>% purrr::map_lgl(~ncol(.x) == 26) %>% all(T) - -# Unnest a lista de tibbles, padroniza as colunas, soma e salva como csv e rds -frota_municipios %>% - purrr::map_dfr(~tidyr::unnest(.)) %>% - dplyr::mutate( - chassiplataforma = na.omit( - dplyr::c_across(dplyr::any_of(c("chassiplataforma", "chassiplatafaforma", "chassiplataf"))) - )[1], - tratoresteira = na.omit( - dplyr::c_across(dplyr::any_of(c("tratoresteira", "tratorestei"))) - )[1] - ) %>% - dplyr::select(-dplyr::any_of(c("chassiplatafaforma", "chassiplataf", "tratorestei"))) %>% - dplyr::mutate( - total = rowSums(dplyr::across(automovel:chassiplataforma)) - ) -> df_municipios - -# Filter municipios que não foram encontrados na tabela do IBGE -df_municipios %>% - filter(is.na(id_municipio)) %>% - group_by(municipio_original, sigla_uf) %>% - summarise() - -## Fix nome dos municipios -# ASSU, RN -> AÇU, 2400208 -# BOA SAUDE, RN -> Januário Cicco, 2405306 -# BOM JESUS, GO -> Bom Jesus de Goiás, 5203500 -# EMBU, SP -> Embu das Artes, "3515004" -# ITABIRINHA DE MANTENA, MG -> Itabirinha, 3131802 -# ITAMARACA, PE -> Ilha de Itamaracá, "2607604" -# JAMARI, RO -> Candeias do Jamari, "1100809" -# LIVRAMENTO DO BRUMADO, BA -> Livramento de Nossa Senhora, "2919504" -# SANTA ROSA, AC -> Santa Rosa do Purus, "1200435" -# SAO BENTO DE POMBAL, PB -> São Bentinho, "2513927" -# VILA ALTA, PR -> Alto Paraíso, "4128625" -# VILA NOVA DO MAMORE, RO -> Nova Mamoré, "1100338" - -df_municipios %>% - dplyr::mutate( - id_municipio = - dplyr::case_when( - municipio_original == "ASSU" & sigla_uf == "RN" ~ "2400208", - municipio_original == "BOA SAUDE" & sigla_uf == "RN" ~ "2405306", - municipio_original == "BOM JESUS" & sigla_uf == "GO" ~ "5203500", - municipio_original == "EMBU" & sigla_uf == "SP" ~ "3515004", - municipio_original == "ITABIRINHA DE MANTENA" & sigla_uf == "MG" ~ "3131802", - municipio_original == "ITAMARACA" & sigla_uf == "PE" ~ "2607604", - municipio_original == "JAMARI" & sigla_uf == "RO" ~ "1100809", - municipio_original == "LIVRAMENTO DO BRUMADO" & sigla_uf == "BA" ~ "2919504", - municipio_original == "SANTA ROSA" & sigla_uf == "AC" ~ "1200435", - municipio_original == "SAO BENTO DE POMBAL" & sigla_uf == "PB" ~ "2513927", - municipio_original == "VILA ALTA" & sigla_uf == "PR" ~ "4128625", - municipio_original == "VILA NOVA DO MAMORE" & sigla_uf == "RO" ~ "1100338", - TRUE ~ id_municipio - ) - ) -> frota_municipios_dist - - -frota_municipios_dist %>% - filter(is.na(id_municipio)) %>% - group_by(municipio_original, sigla_uf) %>% - summarise() - -frota_municipios_dist %>% - dplyr::filter(!is.na(id_municipio)) %>% - dplyr::select(!municipio_original) %>% - readr::write_rds(file = "output/municipio_tipo.rds") %T>% - readr::write_csv(file = "output/municipio_tipo.csv") \ No newline at end of file diff --git a/br_denatran_frota/code/frota_municipio_tipo.py b/br_denatran_frota/code/frota_municipio_tipo.py deleted file mode 100644 index 3406559f1..000000000 --- a/br_denatran_frota/code/frota_municipio_tipo.py +++ /dev/null @@ -1,72 +0,0 @@ -# -*- coding: utf-8 -*- -import polars as pl -import pandas as pd -from string_utils import asciify -import os -from br_denatran_frota.code.utils import ( - change_df_header, - fix_suggested_nome_ibge, - guess_header, - get_city_name_ibge, - match_ibge, - verify_total, -) -from br_denatran_frota.code.constants import DICT_UFS, SUBSTITUTIONS -import basedosdados as bd - - -def verify_uf(denatran_df: pl.DataFrame, ibge_df: pl.DataFrame, uf: str) -> None: - denatran_uf = denatran_df.filter(pl.col("sigla_uf") == uf) - ibge_uf = ibge_df.filter(pl.col("sigla_uf") == uf) - ibge_uf = ibge_uf.with_columns(pl.col("nome").apply(asciify).str.to_lowercase()) - municipios_na_bd = ibge_uf["nome"].to_list() - x = denatran_uf["nome_denatran"].apply(lambda x: get_city_name_ibge(x, ibge_uf)) - denatran_uf = denatran_uf.with_columns(x.alias("suggested_nome_ibge")) - denatran_uf = denatran_uf.with_columns( - denatran_uf.apply(fix_suggested_nome_ibge)["apply"].alias("suggested_nome_ibge") - ) - municipios_no_denatran = denatran_uf["suggested_nome_ibge"].to_list() - d = set(municipios_no_denatran) - set(municipios_na_bd) - municipios_duplicados = ( - denatran_uf.groupby("suggested_nome_ibge").count().filter(pl.col("count") > 1) - ) - if not municipios_duplicados.is_empty(): - raise ValueError( - f"Existem municípios com mesmo nome do IBGE em {uf}! São eles {municipios_duplicados['suggested_nome_ibge'].to_list()}" - ) - if d: - # This here is probably impossible and shouldn't happen due to the matching coming from the BD data. - # The set difference might occur the other way around, but still, better safe. - raise ValueError(f"Existem municípios em {uf} que não estão na BD.") - match_ibge(denatran_uf, ibge_uf) - - -def treat_municipio_tipo(file: str): - municipios_query = """SELECT nome, id_municipio, sigla_uf FROM `basedosdados.br_bd_diretorios_brasil.municipio` - """ - bd_municipios = bd.read_sql( - municipios_query, "tamir-pipelines" - ) # Hardcoded, not good. - bd_municipios = pl.from_pandas(bd_municipios) - - # filename = os.path.split(file)[1] - df = pd.read_excel(file) - new_df = change_df_header(df, guess_header(df)) - new_df.rename( - columns={new_df.columns[0]: "sigla_uf", new_df.columns[1]: "nome_denatran"}, - inplace=True, - ) # Rename for ease of use. - new_df.sigla_uf = new_df.sigla_uf.str.strip() # Remove whitespace. - new_df = pl.from_pandas(new_df) - new_df = new_df.with_columns( - pl.col("nome_denatran").apply(asciify).str.to_lowercase() - ) - new_df = new_df.filter(pl.col("nome_denatran") != "municipio nao informado") - if new_df.shape[0] > bd_municipios.shape[0]: - raise ValueError( - f"Atenção: a base do Denatran tem {new_df.shape[0]} linhas e isso é mais municípios do que a BD com {bd_municipios.shape[0]}" - ) - verify_total(new_df) - for uf in DICT_UFS: - verify_uf(new_df, bd_municipios, uf) - return new_df diff --git a/br_denatran_frota/code/frota_uf_tipo.R b/br_denatran_frota/code/frota_uf_tipo.R deleted file mode 100644 index d46624c48..000000000 --- a/br_denatran_frota/code/frota_uf_tipo.R +++ /dev/null @@ -1,97 +0,0 @@ -library(janitor) -library(lubridate) -library(xlsx) # -library(readxl) -library(dplyr) -library(tidyr) -library(stringr) -library(magrittr) -library(purrr) -library(readr) -library(stringdist) - -source("code/download_frota.R") -source("code/download_frota_old.R") -source("code/utils.R") - -PATH_TEMP <- paste0(getwd(), "/tmp") -PATH_DOWNLOAD_REG <- paste0(getwd(), "/input/frota_regiao_tipo") - -PREFIX_FROTA_REG <- "frota_regiao_tipo" - -# Download da frota por regiao de 2003 a 2012 -2003:2012 %>% purrr::walk( - ~download_frota_old( - key = "regiao", - prefix = PREFIX_FROTA_REG, - year = .x, - tempdir = PATH_TEMP, - dir = PATH_DOWNLOAD_REG - ) -) - -# Download da frota por regiao e tipo em 2013 -## Demais meses de agosto a key é "Frota por Tipo" -2013 %>% - purrr::walk(~download_frota( - key = "Frota por tipo", - prefix = PREFIX_FROTA_REG, - month = c(1:7, 10:12), - year = .x, - tempdir = PATH_TEMP, - dir = PATH_DOWNLOAD_REG - )) - -## Agosto e setembro de 2013 a key é "Frota por Região" -2013 %>% - purrr::walk(~download_frota( - key = "Frota por Região", - prefix = PREFIX_FROTA_REG, - month = 8:9, - year = .x, - tempdir = PATH_TEMP, - dir = PATH_DOWNLOAD_REG - )) - - -# Download da frota de 2014 a 2020 por região e tipo veículo -2014:2020 %>% purrr::walk(~download_frota( - key = "Frota por UF e Tipo", - prefix = PREFIX_FROTA_REG, - month = 1:12, - year = .x, - tempdir = PATH_TEMP, - dir = PATH_DOWNLOAD_REG -)) - - -2021 %>% purrr::walk(~download_frota( - key = "Frota por UF e Tipo", - prefix = PREFIX_FROTA_REG, - month = 1:12, - year = .x, - tempdir = PATH_TEMP, - dir = PATH_DOWNLOAD_REG -)) - -list.files(PATH_DOWNLOAD_REG, full.names = T) %>% - purrr::map( - ~read_xl(.x, type = "grandes reg|uf") %>% - dplyr::rename("sigla_uf" = 1) %>% - dplyr::filter(sigla_uf %in% unname(siglas_uf)) %>% - dplyr::select(sigla_uf, ano, mes, automovel:utilitario) %>% - dplyr::rowwise() %>% - dplyr::mutate( - dplyr::across(!c(sigla_uf), as.numeric), - sigla_uf = sigla_uf %>% stringr::str_trim() %>% get_sigla_uf(), - total = rowSums(across(automovel:utilitario)) - ) - ) -> frota_regiao - -# Cada tibble deve ter 25 colunas e 27 linhas -frota_regiao %>% purrr::map_lgl(~ncol(.x) == 25 & nrow(.x) == 27) %>% all(T) - -frota_regiao %>% - purrr::map_dfr(~tidyr::unnest(.)) %>% - readr::write_csv(file = "output/uf_tipo.csv") %T>% - readr::write_rds(file = "output/uf_tipo.rds") \ No newline at end of file diff --git a/br_denatran_frota/code/frota_uf_tipo.py b/br_denatran_frota/code/frota_uf_tipo.py deleted file mode 100644 index 05d3aacf2..000000000 --- a/br_denatran_frota/code/frota_uf_tipo.py +++ /dev/null @@ -1,70 +0,0 @@ -# -*- coding: utf-8 -*- -import polars as pl -import pandas as pd -import os -from br_denatran_frota.code.utils import ( - guess_header, - change_df_header, - get_year_month_from_filename, - verify_total, -) - - -DICT_UFS = { - "AC": "Acre", - "AL": "Alagoas", - "AP": "Amapá", - "AM": "Amazonas", - "BA": "Bahia", - "CE": "Ceará", - "DF": "Distrito Federal", - "ES": "Espírito Santo", - "GO": "Goiás", - "MA": "Maranhão", - "MT": "Mato Grosso", - "MS": "Mato Grosso do Sul", - "MG": "Minas Gerais", - "PA": "Pará", - "PB": "Paraíba", - "PR": "Paraná", - "PE": "Pernambuco", - "PI": "Piauí", - "RJ": "Rio de Janeiro", - "RN": "Rio Grande do Norte", - "RS": "Rio Grande do Sul", - "RO": "Rondônia", - "RR": "Roraima", - "SC": "Santa Catarina", - "SP": "São Paulo", - "SE": "Sergipe", - "TO": "Tocantins", -} - - -def treat_uf_tipo(file) -> pl.DataFrame: - filename = os.path.split(file)[1] - df = pd.read_excel(file) - new_df = change_df_header(df, guess_header(df)) - # This is ad hoc for UF_tipo. - new_df.rename( - columns={new_df.columns[0]: "sigla_uf"}, inplace=True - ) # Rename for ease of use. - new_df.sigla_uf = new_df.sigla_uf.str.strip() # Remove whitespace. - clean_df = new_df[new_df.sigla_uf.isin(DICT_UFS.values())].reset_index( - drop=True - ) # Now we get all the actual RELEVANT uf data. - month, year = get_year_month_from_filename(filename) - clean_pl_df = pl.from_pandas(clean_df).lazy() - verify_total(clean_pl_df.collect()) - # Add year and month - clean_pl_df = clean_pl_df.with_columns( - pl.lit(year, dtype=pl.Int64).alias("ano"), - pl.lit(month, dtype=pl.Int64).alias("mes"), - ) - clean_pl_df = clean_pl_df.select(pl.exclude("TOTAL")) - clean_pl_df = clean_pl_df.melt( - id_vars=["ano", "mes", "sigla_uf"], - variable_name="tipo_veiculo", - value_name="quantidade", - ) # Long format. - return clean_pl_df.collect() diff --git a/br_denatran_frota/code/setup.py b/br_denatran_frota/code/setup.py deleted file mode 100644 index 6cd60597a..000000000 --- a/br_denatran_frota/code/setup.py +++ /dev/null @@ -1,12 +0,0 @@ -# -*- coding: utf-8 -*- -from setuptools import setup - -setup( - name="download_frota", - version="1.0", - py_modules=["download_frota"], - install_requires=[ - "beautifulsoup4", - "rarfile", - ], -) diff --git a/br_denatran_frota/code/test/download_frota_integration_test.py b/br_denatran_frota/code/test/download_frota_integration_test.py deleted file mode 100644 index 844cd2cc0..000000000 --- a/br_denatran_frota/code/test/download_frota_integration_test.py +++ /dev/null @@ -1,50 +0,0 @@ -# -*- coding: utf-8 -*- -import os -import shutil -import tempfile -import unittest -import glob -import contextlib -from parameterized import parameterized -from br_denatran_frota.code.download_frota import ( - DATASET, - MONTHS, - download_frota, -) - - -def custom_name_func(testcase_func, param_num, param): - return "%s_%s" % ( - testcase_func.__name__, - parameterized.to_safe_name("_".join(str(x) for x in param.args)), - ) - - -class TestAllPossibleYears(unittest.TestCase): - def setUp(self): - file_dir = os.path.dirname(os.path.abspath(__file__)) - os.chdir(file_dir) - dataset_dir = os.path.join(file_dir, "..", "..") - self.temp_dir = tempfile.TemporaryDirectory(dir=dataset_dir) - - def tearDown(self): - print("Deleting temporary directory") - shutil.rmtree(self.temp_dir.name) - - @parameterized.expand( - [(month, year) for year in range(2021, 2022) for month in range(1, 3)], - name_func=custom_name_func, - ) - def test_download_post_2012(self, month, year): - download_frota(month, year, self.temp_dir.name) - expected_files = { - f"frota_por_uf_e_tipo_de_veículo_{month}-{year}", - f"frota_por_município_e_tipo_{month}-{year}", - } - list_of_files = os.listdir(os.path.join(self.temp_dir.name, "files", f"{year}")) - files = set(os.path.splitext(file)[0] for file in list_of_files) - self.assertEqual(files, expected_files) - - -if __name__ == "__main__": - unittest.main() diff --git a/br_denatran_frota/code/test_drive.ipynb b/br_denatran_frota/code/test_drive.ipynb deleted file mode 100644 index 6a367de1b..000000000 --- a/br_denatran_frota/code/test_drive.ipynb +++ /dev/null @@ -1,312 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "import polars as pl\n", - "import pandas as pd \n", - "import os\n", - "import re\n", - "import glob\n", - "from urllib.request import urlopen, urlretrieve\n", - "from zipfile import ZipFile\n", - "from rarfile import RarFile\n", - "from bs4 import BeautifulSoup\n", - "import difflib\n", - "from br_denatran_frota.code.utils import *\n", - "from br_denatran_frota.code.constants import DICT_UFS, SUBSTITUTIONS" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "\n", - "#treat_uf_tipo('../files/2022/frota_por_uf_e_tipo_de_veículo_2-2022.xls')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from download_frota import download_frota" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Download of frota_por_uf_e_tipo_de_veículo_2-2022.xls complete\n", - "Download of frota_por_município_e_tipo_2-2022.xls complete\n" - ] - } - ], - "source": [ - "download_frota(2, 2022)" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/tamir/.cache/pypoetry/virtualenvs/pipelines-Fyk5jlG0-py3.10/lib/python3.10/site-packages/requests/__init__.py:102: RequestsDependencyWarning: urllib3 (1.26.7) or chardet (5.1.0)/charset_normalizer (2.0.8) doesn't match a supported version!\n", - " warnings.warn(\"urllib3 ({}) or chardet ({})/charset_normalizer ({}) doesn't match a supported \"\n", - "Downloading: 100%|██████████| 5570/5570 [00:00<00:00, 8581.01rows/s]\n" - ] - } - ], - "source": [ - "import basedosdados as bd \n", - "municipios_query = \"\"\"SELECT nome, id_municipio, sigla_uf FROM `basedosdados.br_bd_diretorios_brasil.municipio`\n", - "\"\"\"\n", - "bd_municipios = bd.read_sql(municipios_query, 'tamir-pipelines')\n", - "bd_municipios = pl.from_pandas(bd_municipios)" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [], - "source": [ - "file = '../files/2022/frota_por_município_e_tipo_2-2022.xls'\n", - "filename = os.path.split(file)[1]\n", - "df = pd.read_excel(file)\n", - "new_df = change_df_header(df, guess_header(df))\n", - "new_df.rename(columns={ new_df.columns[0]: \"sigla_uf\" , new_df.columns[1]: 'nome_denatran'}, inplace= True) # Rename for ease of use.\n", - "new_df.sigla_uf = new_df.sigla_uf.str.strip() # Remove whitespace.\n", - "new_df = pl.from_pandas(new_df)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "new_df = new_df.with_columns(new_df.apply(fix_suggested_nome_ibge)['apply'].alias('suggested_nome_ibge'))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# for uf in DICT_UFS:\n", - "denatran_uf = new_df.filter(pl.col('sigla_uf') == uf)\n", - "ibge_uf = bd_municipios.filter(pl.col('sigla_uf') == uf)\n", - "ibge_uf = ibge_uf.with_columns(pl.col('nome').str.to_lowercase())" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "\n", - "x = denatran_uf['nome_denatran'].apply(get_city_name_ibge)\n", - "denatran_uf = denatran_uf.with_columns(x.alias('suggested_nome_ibge'))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "ename": "NameError", - "evalue": "name 'denatran_uf' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[4], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m match_ibge(denatran_uf, ibge_uf)\n", - "\u001b[0;31mNameError\u001b[0m: name 'denatran_uf' is not defined" - ] - } - ], - "source": [ - "match_ibge(denatran_uf, ibge_uf)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "nomes = ibge_uf['nome'].to_list()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "joined_df = denatran_uf.join(ibge_uf, left_on=['suggested_nome_ibge', 'sigla_uf'], right_on=['nome', 'sigla_uf'], how='left')\n", - "\n", - "mismatched = joined_df.filter(pl.col('id_municipio').is_null())" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "

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upper"), - codigo_municipio_completo = as.numeric(codigo_municipio_completo), - uf = as.numeric(uf) - ) %>% - dplyr::ungroup() %>% - dplyr::rename( - id_uf = uf, - uf = nome_uf, - id_municipio = codigo_municipio_completo, - municipio = nome_municipio - ) - -siglas_uf <- c( - "AC" = "Acre", - "AL" = "Alagoas", - "AP" = "Amapá", - "AM" = "Amazonas", - "BA" = "Bahia", - "CE" = "Ceará", - "DF" = "Distrito Federal", - "ES" = "Espírito Santo", - "GO" = "Goiás", - "MA" = "Maranhão", - "MT" = "Mato Grosso", - "MS" = "Mato Grosso do Sul", - "MG" = "Minas Gerais", - "PA" = "Pará", - "PB" = "Paraíba", - "PR" = "Paraná", - "PE" = "Pernambuco", - "PI" = "Piauí", - "RJ" = "Rio de Janeiro", - "RN" = "Rio Grande do Norte", - "RS" = "Rio Grande do Sul", - "RO" = "Rondônia", - "RR" = "Roraima", - "SC" = "Santa Catarina", - "SP" = "São Paulo", - "SE" = "Sergipe", - "TO" = "Tocantins" -) - -get_ibge_info <- function(uf, name, tolerance = 0.60) { - state <- siglas_uf[uf] - result <- municipios %>% - dplyr::filter(uf == state) %>% - dplyr::mutate(dist = stringdist::stringsim(name_upper, name)) %>% - dplyr::arrange(dplyr::desc(dist)) %>% - dplyr::slice(1L) %>% - as.list() - - if (length(result[[1]]) == 0 || result$dist < tolerance) { - return(NA) - } - as.character(result$id_municipio) -} - -get_uf_name <- function(x) { - if (nchar(x) != 2) return(x) - unname(siglas_uf[x]) -} - -get_sigla_uf <- function(uf_name) { - purrr::keep(siglas_uf, ~.x == uf_name) %>% - names() -} diff --git a/br_denatran_frota/code/utils.py b/br_denatran_frota/code/utils.py deleted file mode 100644 index 9c961c375..000000000 --- a/br_denatran_frota/code/utils.py +++ /dev/null @@ -1,276 +0,0 @@ -# -*- coding: utf-8 -*- -import pandas as pd -import polars as pl -import difflib -import re -import os -from zipfile import ZipFile -from br_denatran_frota.code.constants import ( - DICT_UFS, - SUBSTITUTIONS, - HEADERS, - DATASET, - MONTHS, -) -import requests -from urllib.request import urlopen, urlretrieve -from bs4 import BeautifulSoup - - -def guess_header(df: pd.DataFrame, max_header_guess: int = 4) -> int: - """Function to deal with problematic dataframes coming from Excel/CSV files. - Tries to guess which row is the header by examining the first few rows (max given by max_header_guess). - Assumes that the header is the first row where all of the columns are strings. - This will NOT properly work for a strings only dataframe and will always guess the first row for it. - - Args: - df (pd.DataFrame): Dataframe whose header we don't know. - max_header_guess (int, optional): Number of initial rows we want to check. Defaults to 4. - - Returns: - int: Index of the row where the header is contained. - """ - header_guess = 0 - while header_guess < max_header_guess: - if len(df) - 1 < header_guess: - break - # Iffy logic, but essentially: if all rows of the column are strings, then this is a good candidate for a header. - if all(df.iloc[header_guess].apply(lambda x: isinstance(x, str))): - return header_guess - - header_guess += 1 - return 0 # If nothing is ever found until the max, let's just assume it's the first row as per usual. - - -def change_df_header(df: pd.DataFrame, header_row: int) -> pd.DataFrame: - """Changes the dataframe's header to a row inside of it and returns the corrected df. - Ideally, to be used in conjunction with guess_header(). - Args: - df (pd.DataFrame): Dataframe whose header we want changed. - header_row (int): Index of the row where the header is located. - - Returns: - pd.DataFrame: Returns the same dataframe but with the corrected header - """ - new_header = df.iloc[header_row] - new_df = df[(header_row + 1) :].reset_index(drop=True) - new_df.rename(columns=new_header, inplace=True) - return new_df - - -def get_year_month_from_filename(filename: str) -> tuple[int, int]: - """Helper to extract month and year information from files named indicator_month-year.xls - - Args: - filename (str): Name of the file. - - Raises: - ValueError: Errors out if nothing is found, which likely means the filename is not the correct format. - - Returns: - tuple[int, int]: Month, year. - """ - match = re.search(r"(\w+)_(\d{1,2})-(\d{4})\.(xls|xlsx)$", filename) - if match: - month = match.group(2) - year = match.group(3) - return month, year - else: - raise ValueError("No match found") - - -def verify_total(df: pl.DataFrame) -> None: - """Helper function that is meant to act as a guard to guarantee that we can pivot from wide to long. - Essentially, gets a Wide dataframe, excludes all string columns and the TOTAL column and sums it all row wise. - Then verifies if the calculated total column is the same as the TOTAL column. - If not, raises an error. - - Args: - df (pl.DataFrame): Wide format dataframe to verify. - - Raises: - ValueError: Errors out if the sum of the columns is actually different than the total. - """ - columns_for_total = df.select(pl.exclude("TOTAL")).select(pl.exclude([pl.Utf8])) - calculated_total = columns_for_total.select( - pl.fold( - acc=pl.lit(0), function=lambda acc, x: acc + x, exprs=pl.col("*") - ).alias("calculated_total") - )["calculated_total"] - mask = df["TOTAL"] == calculated_total - if pl.sum(~mask) != 0: - raise ValueError( - "A coluna de TOTAL da base original tem inconsistências e não é igual à soma das demais colunas." - ) - - -def fix_suggested_nome_ibge(row: tuple[str, ...]) -> str: - """Gets a row from a dataframe and applies the SUBSTITUTIONS constant ruleset where applicable. - This fixes the dataframe to have the names of municipalities according to IBGE. - The fixes are necessary because match_ibge() will fail where the DENATRAN data has typos in city names. - - Args: - row (tuple[str, ...]): Row from the full DENATRAN dataframe we want to apply the IBGE substitutions to. - - Raises: - ValueError: Errors out if the desired parts of the row do not conform to the expected format. - - Returns: - str: Returns the suggested IBGE name, either the pre existing or the one in the ruleset for substitutions. - """ - key = (row[0], row[1]) - if (not isinstance(row[0], str)) or (not isinstance(row[1], str)): - raise ValueError("This is not a valid key to be checked.") - if key in SUBSTITUTIONS: - return SUBSTITUTIONS[key] - else: - return row[-1] - - -def match_ibge(denatran_uf: pl.DataFrame, ibge_uf: pl.DataFrame) -> None: - """Takes a dataframe of the Denatran data and an IBGE dataframe of municipalities. - Joins them using the IBGE name of both. The IBGE name of denatran_uf is ideally filled via get_city_name(). - This verifies if there are any municipalities in denatran_uf that have no corresponding municipality in the IBGE database. - These must be manually fixed via the constants file and the fix_suggested_nome function. - Will error out if there are municipalities that have no correspondence whatsover. - Args: - denatran_uf (pl.DataFrame): Dataframe with the DENATRAN data, filtered by state (UF). - ibge_uf (pl.DataFrame): Dataframe with the IBGE municipalities data, filtered by state (UF). - - Raises: - ValueError: Errors if there are municipalities that have not match and outputs them all with the state to enable manual fix. - """ - joined_df = denatran_uf.join( - ibge_uf, - left_on=["suggested_nome_ibge", "sigla_uf"], - right_on=["nome", "sigla_uf"], - how="left", - ) - mismatched_rows = joined_df.filter(pl.col("id_municipio").is_null()) - if len(mismatched_rows) > 0: - error_message = "Os seguintes municípios falharam: \n" - for row in mismatched_rows.rows(named=True): - error_message += f"{row['nome_denatran']} ({row['sigla_uf']})\n" - raise ValueError(error_message) - - -def get_city_name_ibge(denatran_name: str, ibge_uf: pl.DataFrame) -> str: - """Gets the closest match to the denatran name of the municipality in the IBGE dataframe of the same state. - This ibge_uf dataframe is pulled directly from Base dos Dados to ensure correctness. - Returns either the match or an empty string in case no match is found. - - - Args: - denatran_name (str): The name of the municipality according to DENATRAN data. - ibge_uf (pl.DataFrame): Dataframe with the information from municipalities for a certain state (UF). - Returns: - str: Closest match to the denatran name or an empty string if no such match is found. - """ - matches = difflib.get_close_matches( - denatran_name.lower(), ibge_uf["nome"].str.to_lowercase(), n=1 - ) - if matches: - return matches[0] - else: - return "" # I don't want this to error out directly, because then I can get all municipalities. - - -def download_file(url, filename): - # Send a GET request to the URL - - new_url = url.replace("arquivos-denatran", "arquivos-senatran") - response = requests.get(new_url, headers=HEADERS) - # Save the contents of the response to a file - with open(filename, "wb") as f: - f.write(response.content) - - print(f"Download of {filename} complete") - - -def extract_zip(dest_path_file): - with ZipFile(dest_path_file, "r") as z: - z.extractall() - - -def handle_xl(i: dict) -> None: - """Actually downloads and deals with Excel files. - - Args: - i (dict): Dictionary with all the desired downloadable file's info. - """ - dest_path_file = make_filename(i) - download_file(i["href"], dest_path_file) - - -def make_filename(i: dict, ext: bool = True) -> str: - """Creates the filename using the sent dictionary. - - Args: - i (dict): Dictionary with all the file's info. - ext (bool, optional): Specifies if the generated file name needs the filetype at the end. Defaults to True. - - Returns: - str: The full filename. - """ - txt = i["txt"] - mes = i["mes"] - ano = i["ano"] - filetype = i["filetype"] - filename = re.sub("\\s+", "_", txt, flags=re.UNICODE).lower() - filename = f"{filename}_{mes}-{ano}" - if ext: - filename += f".{filetype}" - return filename - - -def call_downloader(i): - filename = make_filename(i) - if i["filetype"] in ["xlsx", "xls"]: - download_file(i["href"], filename) - elif i["filetype"] == "zip": - download_file(i["href"], filename) - extract_zip(filename) - - -def download_post_2012(month: int, year: int): - """_summary_ - - Args: - year (int): _description_ - month (int): _description_ - """ - url = f"https://www.gov.br/infraestrutura/pt-br/assuntos/transito/conteudo-Senatran/frota-de-veiculos-{year}" - soup = BeautifulSoup(urlopen(url), "html.parser") - # Só queremos os dados de frota nacional. - nodes = soup.select("p:contains('rota por ') > a") - for node in nodes: - txt = node.text - href = node.get("href") - # Pega a parte relevante do arquivo em questão. - match = re.search( - r"(?i)\/([\w-]+)\/(\d{4})\/(\w+)\/([\w-]+)\.(?:xls|xlsx|rar|zip)$", href - ) - if match: - matched_month = match.group(3) - matched_year = match.group(2) - if MONTHS.get(matched_month) == month and matched_year == str(year): - filetype = match.group(0).split(".")[-1].lower() - info = { - "txt": txt, - "href": href, - "mes_name": matched_month, - "mes": month, - "ano": year, - "filetype": filetype, - } - call_downloader(info) - - -def make_dir_when_not_exists(dir_name: str): - """Auxiliary function to create a subdirectory when it is not present. - - Args: - dir_name (str): Name of the subdirectory to be created. - """ - if not os.path.exists(dir_name): - os.mkdir(dir_name) diff --git a/br_denatran_frota/dataset_config.yaml b/br_denatran_frota/dataset_config.yaml deleted file mode 100644 index 9a43e3b43..000000000 --- a/br_denatran_frota/dataset_config.yaml +++ /dev/null @@ -1,69 +0,0 @@ -dataset_id: br_denatran_frota # AUTO GENERATED - -url_ckan: https://basedosdados.org/dataset/br-denatran-frota -url_github: https://github.com/basedosdados/mais/tree/master/bases/br_denatran_frota - -# Descreva a base. -# Ela é sobre o que? -# Quais as principais fontes de dados? -# Há links para FAQs e explicações? -description: | # REQUIRED - Frota de Veículos por tipo, estado e município - -# Qual organização disponibiliza os dados originais? -# Opções: escolher dessa lista -> https://basedosdados.org/api/3/action/organization_list -organization: Departamento Nacional de Trânsito # REQUIRED - -# Qual departamento/grupo/pessoa mantém os dados originais? -author: - name: Departamento Nacional de Trânsito - email: - -# Onde encontrar os dados originais e mais informações? -website: - - https://www.gov.br/infraestrutura/pt-br/assuntos/transito/conteudo-denatran/estatisticas-frota-de-veiculos-denatran - -# Quais grupos caracterizam a base? -# Opções: escolher dessa lista -> https://basedosdados.org/api/3/action/group_list -groups: - - infra-transp - -# Quais etiquetas caracterizam a base? -# Opções: escolher dessa lista -> https://basedosdados.org/api/3/action/tag_list -# Caso crie etiquetas novas, as regras são: -# - letras minúsculas -# - sem acentos -# - não repita nomes de grupos (ex. educacao, saude, meio ambiente, economia, etc.) -tags: - - veiculo - - trafego - -# Em quais línguas a base (ou a fonte original) está disponível? -# Regras: minúsculo, sem acentos. -# Opções: portugues, ingles, espanhol, frances, chines, russo, hindi, alemao, etc. -languages: - - portugues - -# Os dados originais estão disponíveis de graça? -free: sim - -# Are microdata available for download? -microdata: sim - -# Existe uma API na fonte original? -API: não - -# É necessário registrar um usuário para baixar os dados originais? -registration: não - -# Como os dados originais estão disponibilizados? -availability: online - -# A fonte original requer IP brasileiro para acesso? -brazilian_IP: não - -# Essa base está sob qual licença? -# A licença MIT se aplica a bases públicas. -# Caso não seja pública, ver opções aqui: https://help.data.world/hc/en-us/articles/115006114287-Common-license-types-for-datasets -license: - name: MIT # REQUIRED diff --git a/br_denatran_frota/municipio_tipo/publish.sql b/br_denatran_frota/municipio_tipo/publish.sql deleted file mode 100644 index 4b7acaffd..000000000 --- a/br_denatran_frota/municipio_tipo/publish.sql +++ /dev/null @@ -1,50 +0,0 @@ -/* - -Query para publicar a tabela. - -Esse é o lugar para: - - modificar nomes, ordem e tipos de colunas - - dar join com outras tabelas - - criar colunas extras (e.g. logs, proporções, etc.) - -Qualquer coluna definida aqui deve também existir em `table_config.yaml`. - -# Além disso, sinta-se à vontade para alterar alguns nomes obscuros -# para algo um pouco mais explícito. - -TIPOS: - - Para modificar tipos de colunas, basta substituir STRING por outro tipo válido. - - Exemplo: `SAFE_CAST(column_name AS NUMERIC) column_name` - - Mais detalhes: https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types - -*/ - -CREATE VIEW basedosdados-312117.br_denatran_frota.municipio_tipo AS -SELECT -SAFE_CAST(sigla_uf AS STRING) sigla_uf, -SAFE_CAST(id_municipio AS STRING) id_municipio, -SAFE_CAST(ano AS INT64) ano, -SAFE_CAST(mes AS INT64) mes, -SAFE_CAST(automovel AS INT64) automovel, -SAFE_CAST(bonde AS INT64) bonde, -SAFE_CAST(caminhao AS INT64) caminhao, -SAFE_CAST(caminhaotrator AS INT64) caminhaotrator, -SAFE_CAST(caminhonete AS INT64) caminhonete, -SAFE_CAST(camioneta AS INT64) camioneta, -SAFE_CAST(ciclomotor AS INT64) ciclomotor, -SAFE_CAST(microonibus AS INT64) microonibus, -SAFE_CAST(motocicleta AS INT64) motocicleta, -SAFE_CAST(motoneta AS INT64) motoneta, -SAFE_CAST(onibus AS INT64) onibus, -SAFE_CAST(quadriciclo AS INT64) quadriciclo, -SAFE_CAST(reboque AS INT64) reboque, -SAFE_CAST(semireboque AS INT64) semireboque, -SAFE_CAST(sidecar AS INT64) sidecar, -SAFE_CAST(outros AS INT64) outros, -SAFE_CAST(tratoresteira AS INT64) tratoresteira, -SAFE_CAST(tratorrodas AS INT64) tratorrodas, -SAFE_CAST(triciclo AS INT64) triciclo, -SAFE_CAST(utilitario AS INT64) utilitario, -SAFE_CAST(chassiplataforma AS INT64) chassiplataforma, -SAFE_CAST(total AS INT64) total -from basedosdados-312117.br_denatran_frota_staging.municipio_tipo as t \ No newline at end of file diff --git a/br_denatran_frota/municipio_tipo/schema-prod.json b/br_denatran_frota/municipio_tipo/schema-prod.json deleted file mode 100644 index ecd58455f..000000000 --- a/br_denatran_frota/municipio_tipo/schema-prod.json +++ /dev/null @@ -1 +0,0 @@ -[{"name": "sigla_uf", "description": "Sigla da Unidade da Federa\u00e7\u00e3o original da base", "is_in_staging": true, "is_partition": false, "type": "STRING", "mode": "NULLABLE"}, {"name": "id_municipio", "description": "ID Munic\u00edpio - IBGE 7 D\u00edgitos", "is_in_staging": true, "is_partition": false, "type": "STRING", "mode": "NULLABLE"}, {"name": "ano", "description": "Ano", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "mes", "description": "M\u00eas", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "automovel", "description": "Autom\u00f3vel", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "bonde", "description": "Bonde", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "caminhao", "description": "Caminh\u00e3o", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "caminhaotrator", "description": "Caminh\u00e3o Trator", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "caminhonete", "description": "Caminhonete", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "camioneta", "description": "Camioneta", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "chassiplataforma", "description": "Chassi Plataforma", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "ciclomotor", "description": "Ciclo Motor", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "microonibus", "description": "Micro\u00f4nibus", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "motocicleta", "description": "Motocicleta", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "motoneta", "description": "Motoneta", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "onibus", "description": "\u00d4nibus", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "quadriciclo", "description": "Quadriciclo", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "reboque", "description": "Reboque", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "semireboque", "description": "Semi-reboque", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "sidecar", "description": "Side-car", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "outros", "description": "Argumento que n\u00e3o se enquadra em nenhuma defini\u00e7\u00e3o estabelecida", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "tratoresteira", "description": "Trator esteira", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "tratorrodas", "description": "Trator rodas", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "triciclo", "description": "Triciclo", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "utilitario", "description": "Utilit\u00e1rio", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "total", "description": "Total", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}] \ No newline at end of file diff --git a/br_denatran_frota/municipio_tipo/schema-staging.json b/br_denatran_frota/municipio_tipo/schema-staging.json deleted file mode 100644 index 43cc3a6ef..000000000 --- a/br_denatran_frota/municipio_tipo/schema-staging.json +++ /dev/null @@ -1 +0,0 @@ -[{"name": "sigla_uf", "description": "Sigla da Unidade da Federa\u00e7\u00e3o", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "ano", "description": "Ano", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "mes", "description": "M\u00eas", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "automovel", "description": "Autom\u00f3vel", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "bonde", "description": "Bonde", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "caminhao", "description": "Caminh\u00e3o", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "caminhaotrator", "description": "Caminh\u00e3o Trator", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "caminhonete", "description": "Caminhonete", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "camioneta", "description": "Camioneta", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "chassiplataforma", "description": "Chassi Plataforma", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "ciclomotor", "description": "Ciclo Motor", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "microonibus", "description": "Micro\u00f4nibus", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "motocicleta", "description": "Motocicleta", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "motoneta", "description": "Motoneta", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "onibus", "description": "\u00d4nibus", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "quadriciclo", "description": "Quadriciclo", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "reboque", "description": "Reboque", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "semireboque", "description": "Semi-reboque", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "sidecar", "description": "Side-car", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "outros", "description": "Argumento que n\u00e3o se enquadra em nenhuma defini\u00e7\u00e3o estabelecida", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "tratoresteira", "description": "Trator esteira", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "tratorrodas", "description": "Trator rodas", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "triciclo", "description": "Triciclo", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "utilitario", "description": "Utilit\u00e1rio", "is_in_staging": true, "is_partition": false, "type": "STRING"}, {"name": "total", "description": "Total", "is_in_staging": true, "is_partition": false, "type": "STRING"}] \ No newline at end of file diff --git a/br_denatran_frota/municipio_tipo/table_config.yaml b/br_denatran_frota/municipio_tipo/table_config.yaml deleted file mode 100644 index 28af5cb70..000000000 --- a/br_denatran_frota/municipio_tipo/table_config.yaml +++ /dev/null @@ -1,268 +0,0 @@ -source_bucket_name: basedosdadosdev -project_id_staging: basedosdados-312117 -project_id_prod: basedosdados-312117 -table_id: municipio_tipo # AUTO GENERATED -dataset_id: br_denatran_frota # AUTO GENERATED - -url_ckan: https://basedosdados.org/dataset/br-denatran-frota # AUTO GENERATED -url_github: https://github.com/basedosdados/mais/tree/master/bases/br_denatran_frota # AUTO GENERATED - -version: v1.3 # REQUIRED - -last_updated: 2021-05-28 # AUTO GENERATED - -# Descreva a tabela. Essas são as primeiras frases que um usuário vai ver. -# Você não precisa ser muito conciso. Sinta-se a vontade para dar exemplos de -# como usar os dados. -# Se souber, liste também aplicações: pesquisa, apps, etc. que usem os dados. -description: | # REQUIRED - Frota de veículos por município e tipo - -# Quem está completando esse arquivo config? -published_by: - name: Pedro Castro # REQUIRED - code_url: https://github.com/basedosdados/mais/tree/master/bases/br_denatran_frota/code # REQUIRED - website: https://github.com/pedrocastroo - email: pdesacastro@gmail.com - -# Qual organização/departamento/pessoa tratou os dados? -# As vezes há um ponto intermediário entre os dados originais e subir na Base dos Dados. -# Se essa pessoa é você, preencha abaixo com suas informações. -treated_by: - name: Pedro Castro - code_url: https://github.com/basedosdados/mais/tree/master/bases/br_denatran_frota/code - website: https://basedosdados.org/ - email: pdesacastro@gmail.com - -# Se houve passos de tratamento, limpeza e manipulação de dados, descreva-os aqui. -treatment_description: | - Padronização das colunas. Nova coluna, id_municipio. Remoção das linhas "MUNICIPIO NAO INFORMADO". - -# Com qual frequência a base é atualizada? -# Opções: hora | dia | semana | mes | 1 ano | 2 anos | 5 anos | 10 anos | unico | recorrente -data_update_frequency: mes # REQUIRED - -# Nível da observação (qual é a granularidade de cada linha na tabela) -# Escolha todas as opções necessárias. -# Regras: -# - minúsculo, sem acento, singular. -# - em portugues (ou seja, não use os nomes de colunas abaixo) -# Exemplos: pais, estado, municipio, cidade, hora, dia, semana, mes, ano, etc. -observation_level: #REQUIRED - - municipio - - mes - -# Quais colunas identificam uma linha unicamente? -# Preencha com os nomes de colunas. Ex: id_municipio, ano. -# Pode ser vazio pois certas tabelas não possuem identificadores. -primary_keys: - - id_municipio - - ano - - mes - -# Qual é a cobertura espacial da tabela? -# Regras: -# - minúsculo, sem acento, singular -# - descer até o menor nível administrativo cuja cobertura abaixo seja 'todos' -# Exemplo 1: tabela que cubra todos os municípios nos estados de SP e GO -# - brasil -# - SP, GO -# Exemplo 2: tabela que cubra países inteiros na América Latina -# - brasil, argentina, peru, equador -coverage_geo: - - brasil - -# Qual é a cobertura temporal (em anos) da tabela? -# Opções: ..., 1990, 1991, ..., 1999, 2000, 2001, ..., 2019, 2020, ... -coverage_time: - - 2003 - - 2004 - - 2005 - - 2006 - - 2007 - - 2008 - - 2009 - - 2010 - - 2011 - - 2012 - - 2013 - - 2014 - - 2015 - - 2016 - - 2017 - - 2018 - - 2019 - - 2020 - - 2021 - -# Liste as colunas da tabela que representam partições. -# Não esqueça de deletar essas colunas nas tabelas .csv na hora de subir para o BigQuery. -# Isso poupará muito tempo e dinheiro às pessoas utilizando essa tabela. -# Se não houver partições, não modifique abaixo. -partitions: # REQUIRED - -# Quais são as colunas? Certifique-se de escrever uma boa descrição, as pessoas vão gostar -# para saber sobre o que é a coluna. -# Adicionar todas as colunas manualmente pode ser bastante cansativo, por isso, quando -# inicializando este arquivo de configuração, você pode apontar a função para uma amostra de dados que -# preencherá automaticamente as colunas. -# Algumas colunas existirão apenas na tabela final, você as construirá em `publish.sql`. -# Para esses, defina is_in_staging como False. -# Além disso, você deve adicionar as colunas de partição aqui e definir is_partition como True. -columns: # REQUIRED - - - - name: sigla_uf - description: Sigla da Unidade da Federação original da base - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: id_municipio - description: ID Município - IBGE 7 Dígitos - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: ano - description: Ano - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: mes - description: Mês - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: automovel - description: Automóvel - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: bonde - description: Bonde - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: caminhao - description: Caminhão - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: caminhaotrator - description: Caminhão Trator - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: caminhonete - description: Caminhonete - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: camioneta - description: Camioneta - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: chassiplataforma - description: Chassi Plataforma - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: ciclomotor - description: Ciclo Motor - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: microonibus - description: Microônibus - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: motocicleta - description: Motocicleta - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: motoneta - description: Motoneta - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: onibus - description: Ônibus - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: quadriciclo - description: Quadriciclo - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: reboque - description: Reboque - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: semireboque - description: Semi-reboque - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: sidecar - description: Side-car - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: outros - description: Argumento que não se enquadra em nenhuma definição estabelecida - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: tratoresteira - description: Trator esteira - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: tratorrodas - description: Trator rodas - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: triciclo - description: Triciclo - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: utilitario - description: Utilitário - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: total - description: Total - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. \ No newline at end of file diff --git a/br_denatran_frota/municipio_tipo/table_description.txt b/br_denatran_frota/municipio_tipo/table_description.txt deleted file mode 100644 index 7ca0fad1e..000000000 --- a/br_denatran_frota/municipio_tipo/table_description.txt +++ /dev/null @@ -1,67 +0,0 @@ -Frota de veículos por município e tipo - - -Para saber mais acesse: -Website: https://basedosdados.org/dataset/br-denatran-frota -Github: https://github.com/basedosdados/mais/tree/master/bases/br_denatran_frota - -Ajude a manter o projeto :) -Apoia-se: https://apoia.se/basedosdados - -Publicado por -------------- -Nome: Pedro Castro -Código: https://github.com/basedosdados/mais/tree/master/bases/br_denatran_frota/code -Website: https://github.com/pedrocastroo -Email: pdesacastro@gmail.comTratado por ------------ -Nome: Pedro Castro -Código: https://github.com/basedosdados/mais/tree/master/bases/br_denatran_frota/code -Website: https://basedosdados.org/ -Email: pdesacastro@gmail.com - -Nível da Observação (i.e. a granularidade da linha) -------------------- -- municipio -- mes - -Colunas identificando linhas unicamente -------------------- -- id_municipio -- ano -- mes - -Cobertura Temporal ------------------- -- 2003 -- 2004 -- 2005 -- 2006 -- 2007 -- 2008 -- 2009 -- 2010 -- 2011 -- 2012 -- 2013 -- 2014 -- 2015 -- 2016 -- 2017 -- 2018 -- 2019 -- 2020 -- 2021 - -Cobertura Espacial ------------------- -- brasil - -Tratamento ----------- -Padronização das colunas. Nova coluna, id_municipio. Remoção das linhas "MUNICIPIO NAO INFORMADO". - -Frequencia de Atualização -------------------------- -mes - diff --git a/br_denatran_frota/uf_tipo/publish.sql b/br_denatran_frota/uf_tipo/publish.sql deleted file mode 100644 index 0725b27d8..000000000 --- a/br_denatran_frota/uf_tipo/publish.sql +++ /dev/null @@ -1,49 +0,0 @@ -/* - -Query para publicar a tabela. - -Esse é o lugar para: - - modificar nomes, ordem e tipos de colunas - - dar join com outras tabelas - - criar colunas extras (e.g. logs, proporções, etc.) - -Qualquer coluna definida aqui deve também existir em `table_config.yaml`. - -# Além disso, sinta-se à vontade para alterar alguns nomes obscuros -# para algo um pouco mais explícito. - -TIPOS: - - Para modificar tipos de colunas, basta substituir STRING por outro tipo válido. - - Exemplo: `SAFE_CAST(column_name AS NUMERIC) column_name` - - Mais detalhes: https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types - -*/ - -CREATE VIEW basedosdados-312117.br_denatran_frota.uf_tipo AS -SELECT -SAFE_CAST(sigla_uf AS STRING) sigla_uf, -SAFE_CAST(ano AS INT64) ano, -SAFE_CAST(mes AS INT64) mes, -SAFE_CAST(automovel AS INT64) automovel, -SAFE_CAST(bonde AS INT64) bonde, -SAFE_CAST(caminhao AS INT64) caminhao, -SAFE_CAST(caminhaotrator AS INT64) caminhaotrator, -SAFE_CAST(caminhonete AS INT64) caminhonete, -SAFE_CAST(camioneta AS INT64) camioneta, -SAFE_CAST(chassiplataforma AS INT64) chassiplataforma, -SAFE_CAST(ciclomotor AS INT64) ciclomotor, -SAFE_CAST(microonibus AS INT64) microonibus, -SAFE_CAST(motocicleta AS INT64) motocicleta, -SAFE_CAST(motoneta AS INT64) motoneta, -SAFE_CAST(onibus AS INT64) onibus, -SAFE_CAST(quadriciclo AS INT64) quadriciclo, -SAFE_CAST(reboque AS INT64) reboque, -SAFE_CAST(semireboque AS INT64) semireboque, -SAFE_CAST(sidecar AS INT64) sidecar, -SAFE_CAST(outros AS INT64) outros, -SAFE_CAST(tratoresteira AS INT64) tratoresteira, -SAFE_CAST(tratorrodas AS INT64) tratorrodas, -SAFE_CAST(triciclo AS INT64) triciclo, -SAFE_CAST(utilitario AS INT64) utilitario, -SAFE_CAST(total AS INT64) total -from basedosdados-312117.br_denatran_frota_staging.uf_tipo as t diff --git a/br_denatran_frota/uf_tipo/schema-prod.json b/br_denatran_frota/uf_tipo/schema-prod.json deleted file mode 100644 index 9179eec10..000000000 --- a/br_denatran_frota/uf_tipo/schema-prod.json +++ /dev/null @@ -1 +0,0 @@ -[{"name": "sigla_uf", "description": "Sigla da Unidade da Federa\u00e7\u00e3o", "is_in_staging": true, "is_partition": false, "type": "STRING", "mode": "NULLABLE"}, {"name": "ano", "description": "Ano", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "mes", "description": "M\u00eas", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "automovel", "description": "Autom\u00f3vel", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "bonde", "description": "Bonde", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "caminhao", "description": "Caminh\u00e3o", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "caminhaotrator", "description": "Caminh\u00e3o Trator", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "caminhonete", "description": "Caminhonete", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "camioneta", "description": "Camioneta", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "chassiplataforma", "description": "Chassi Plataforma", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "ciclomotor", "description": "Ciclo Motor", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "microonibus", "description": "Micro\u00f4nibus", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "motocicleta", "description": "Motocicleta", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "motoneta", "description": "Motoneta", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "onibus", "description": "\u00d4nibus", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "quadriciclo", "description": "Quadriciclo", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "reboque", "description": "Reboque", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "semireboque", "description": "Semi-reboque", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "sidecar", "description": "Side-car", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "outros", "description": "Argumento que n\u00e3o se enquadra em nenhuma defini\u00e7\u00e3o estabelecida", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "tratoresteira", "description": "Trator esteira", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "tratorrodas", "description": "Trator rodas", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "triciclo", "description": "Triciclo", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "utilitario", "description": "Utilit\u00e1rio", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}, {"name": "total", "description": "Total", "is_in_staging": true, "is_partition": false, "type": "INTEGER", "mode": "NULLABLE"}] \ No newline at end of file diff --git a/br_denatran_frota/uf_tipo/table_config.yaml b/br_denatran_frota/uf_tipo/table_config.yaml deleted file mode 100644 index 66cb8f5bc..000000000 --- a/br_denatran_frota/uf_tipo/table_config.yaml +++ /dev/null @@ -1,263 +0,0 @@ -source_bucket_name: basedosdadosdev -project_id_staging: basedosdados-312117 -project_id_prod: basedosdados-312117 -table_id: uf_tipo # AUTO GENERATED -dataset_id: br_denatran_frota # AUTO GENERATED - - -url_ckan: https://basedosdados.org/dataset/br-denatran-frota # AUTO GENERATED -url_github: https://github.com/basedosdados/mais/tree/master/bases/br_denatran_frota # AUTO GENERATED - -version: v1.2 # REQUIRED - -last_updated: 2021-05-28 # AUTO GENERATED - -# Descreva a tabela. Essas são as primeiras frases que um usuário vai ver. -# Você não precisa ser muito conciso. Sinta-se a vontade para dar exemplos de -# como usar os dados. -# Se souber, liste também aplicações: pesquisa, apps, etc. que usem os dados. -description: | # REQUIRED - Frota veículos por estado e tipo - -# Quem está completando esse arquivo config? -published_by: - name: Pedro Castro # REQUIRED - code_url: https://github.com/basedosdados/mais/tree/master/bases/br_denatran_frota/code # REQUIRED - website: https://github.com/pedrocastroo - email: pdesacastro@gmail.com - -# Qual organização/departamento/pessoa tratou os dados? -# As vezes há um ponto intermediário entre os dados originais e subir na Base dos Dados. -# Se essa pessoa é você, preencha abaixo com suas informações. -treated_by: - name: Pedro Castro - code_url: https://github.com/basedosdados/mais/tree/master/bases/br_denatran_frota/code - website: https://basedosdados.org/ - email: pdesacastro@gmail.com - -# Se houve passos de tratamento, limpeza e manipulação de dados, descreva-os aqui. -treatment_description: | - Padronização dos nomes das colunas. Remoção das linhas do total dos estados. - -# Com qual frequência a base é atualizada? -# Opções: hora | dia | semana | mes | 1 ano | 2 anos | 5 anos | 10 anos | unico | recorrente -data_update_frequency: mes # REQUIRED - -# Nível da observação (qual é a granularidade de cada linha na tabela) -# Escolha todas as opções necessárias. -# Regras: - # - minúsculo, sem acento, singular. -# - em portugues (ou seja, não use os nomes de colunas abaixo) -# Exemplos: pais, estado, municipio, cidade, hora, dia, semana, mes, ano, etc. -observation_level: #REQUIRED - - unidade da federação - - mes - -# Quais colunas identificam uma linha unicamente? -# Preencha com os nomes de colunas. Ex: id_municipio, ano. -# Pode ser vazio pois certas tabelas não possuem identificadores. -primary_keys: - - ano - - mes - - sigla_uf - -# Qual é a cobertura espacial da tabela? -# Regras: - # - minúsculo, sem acento, singular -# - descer até o menor nível administrativo cuja cobertura abaixo seja 'todos' -# Exemplo 1: tabela que cubra todos os municípios nos estados de SP e GO -# - brasil -# - SP, GO -# Exemplo 2: tabela que cubra países inteiros na América Latina -# - brasil, argentina, peru, equador -coverage_geo: - - brasil - -# Qual é a cobertura temporal (em anos) da tabela? -# Opções: ..., 1990, 1991, ..., 1999, 2000, 2001, ..., 2019, 2020, ... -coverage_time: - - 2003 - - 2004 - - 2005 - - 2006 - - 2007 - - 2008 - - 2009 - - 2010 - - 2011 - - 2012 - - 2013 - - 2014 - - 2015 - - 2016 - - 2017 - - 2018 - - 2019 - - 2020 - - 2021 - -# Liste as colunas da tabela que representam partições. -# Não esqueça de deletar essas colunas nas tabelas .csv na hora de subir para o BigQuery. -# Isso poupará muito tempo e dinheiro às pessoas utilizando essa tabela. -# Se não houver partições, não modifique abaixo. -partitions: # REQUIRED - -# Quais são as colunas? Certifique-se de escrever uma boa descrição, as pessoas vão gostar -# para saber sobre o que é a coluna. -# Adicionar todas as colunas manualmente pode ser bastante cansativo, por isso, quando -# inicializando este arquivo de configuração, você pode apontar a função para uma amostra de dados que -# preencherá automaticamente as colunas. -# Algumas colunas existirão apenas na tabela final, você as construirá em `publish.sql`. -# Para esses, defina is_in_staging como False. -# Além disso, você deve adicionar as colunas de partição aqui e definir is_partition como True. -columns: # REQUIRED - - - - name: sigla_uf - description: Sigla da Unidade da Federação - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: ano - description: Ano - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: mes - description: Mês - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: automovel - description: Automóvel - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: bonde - description: Bonde - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: caminhao - description: Caminhão - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: caminhaotrator - description: Caminhão Trator - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: caminhonete - description: Caminhonete - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: camioneta - description: Camioneta - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: chassiplataforma - description: Chassi Plataforma - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: ciclomotor - description: Ciclo Motor - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: microonibus - description: Microônibus - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: motocicleta - description: Motocicleta - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: motoneta - description: Motoneta - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: onibus - description: Ônibus - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: quadriciclo - description: Quadriciclo - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: reboque - description: Reboque - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: semireboque - description: Semi-reboque - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: sidecar - description: Side-car - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: outros - description: Argumento que não se enquadra em nenhuma definição estabelecida - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: tratoresteira - description: Trator esteira - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: tratorrodas - description: Trator rodas - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: triciclo - description: Triciclo - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: utilitario - description: Utilitário - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partition. - - - - name: total - description: Total - is_in_staging: True # Bool [True, False], whether the column is in the staging table - is_partition: False # Bool [True, False], whether the column is a partitio \ No newline at end of file diff --git a/br_denatran_frota/uf_tipo/table_description.txt b/br_denatran_frota/uf_tipo/table_description.txt deleted file mode 100644 index 982522203..000000000 --- a/br_denatran_frota/uf_tipo/table_description.txt +++ /dev/null @@ -1,67 +0,0 @@ -Frota veículos por estado e tipo - - -Para saber mais acesse: -Website: https://basedosdados.org/dataset/br-denatran-frota -Github: https://github.com/basedosdados/mais/tree/master/bases/br_denatran_frota - -Ajude a manter o projeto :) -Apoia-se: https://apoia.se/basedosdados - -Publicado por -------------- -Nome: Pedro Castro -Código: https://github.com/basedosdados/mais/tree/master/bases/br_denatran_frota/code -Website: https://github.com/pedrocastroo -Email: pdesacastro@gmail.comTratado por ------------ -Nome: Pedro Castro -Código: https://github.com/basedosdados/mais/tree/master/bases/br_denatran_frota/code -Website: https://basedosdados.org/ -Email: pdesacastro@gmail.com - -Nível da Observação (i.e. a granularidade da linha) -------------------- -- unidade da federação -- mes - -Colunas identificando linhas unicamente -------------------- -- ano -- mes -- sigla_uf - -Cobertura Temporal ------------------- -- 2003 -- 2004 -- 2005 -- 2006 -- 2007 -- 2008 -- 2009 -- 2010 -- 2011 -- 2012 -- 2013 -- 2014 -- 2015 -- 2016 -- 2017 -- 2018 -- 2019 -- 2020 -- 2021 - -Cobertura Espacial ------------------- -- brasil - -Tratamento ----------- -Padronização dos nomes das colunas. Remoção das linhas do total dos estados. - -Frequencia de Atualização -------------------------- -mes - diff --git a/pipelines/datasets/br_denatran_frota/tasks.py b/pipelines/datasets/br_denatran_frota/tasks.py index fb0c94dfb..1f27c5bae 100644 --- a/pipelines/datasets/br_denatran_frota/tasks.py +++ b/pipelines/datasets/br_denatran_frota/tasks.py @@ -1,53 +1,4 @@ # -*- coding: utf-8 -*- -""" -Tasks for br_denatran_frota -""" - -############################################################################### -# -# Aqui é onde devem ser definidas as tasks para os flows do projeto. -# Cada task representa um passo da pipeline. Não é estritamente necessário -# tratar todas as exceções que podem ocorrer durante a execução de uma task, -# mas é recomendável, ainda que não vá implicar em uma quebra no sistema. -# Mais informações sobre tasks podem ser encontradas na documentação do -# Prefect: https://docs.prefect.io/core/concepts/tasks.html -# -# De modo a manter consistência na codebase, todo o código escrito passará -# pelo pylint. Todos os warnings e erros devem ser corrigidos. -# -# As tasks devem ser definidas como funções comuns ao Python, com o decorador -# @task acima. É recomendado inserir type hints para as variáveis. -# -# Um exemplo de task é o seguinte: -# -# ----------------------------------------------------------------------------- -# from prefect import task -# -# @task -# def my_task(param1: str, param2: int) -> str: -# """ -# My task description. -# """ -# return f'{param1} {param2}' -# ----------------------------------------------------------------------------- -# -# Você também pode usar pacotes Python arbitrários, como numpy, pandas, etc. -# -# ----------------------------------------------------------------------------- -# from prefect import task -# import numpy as np -# -# @task -# def my_task(a: np.ndarray, b: np.ndarray) -> str: -# """ -# My task description. -# """ -# return np.add(a, b) -# ----------------------------------------------------------------------------- -# -# Abaixo segue um código para exemplificação, que pode ser removido. -# -############################################################################### from prefect import task import glob diff --git a/poetry.lock b/poetry.lock index 5d927f5e0..bc53c1a8e 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,11 +1,9 @@ - -# This file is automatically @generated by Poetry 1.4.1 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand. [[package]] name = "appnope" version = "0.1.3" description = "Disable App Nap on macOS >= 10.9" -category = "dev" optional = false python-versions = "*" files = [ @@ -17,7 +15,6 @@ files = [ name = "arrow" version = "1.2.3" description = "Better dates & times for Python" -category = "dev" optional = false python-versions = ">=3.6" files = [ @@ -28,12 +25,10 @@ files = [ [package.dependencies] python-dateutil = ">=2.7.0" - [[package]] name = "asttokens" version = "2.2.1" description = "Annotate AST trees with source code positions" -category = "dev" optional = false python-versions = "*" files = [ @@ -49,17 +44,19 @@ test = ["astroid", "pytest"] [[package]] name = "async-timeout" -version = "4.0.2" +version = "4.0.3" description = "Timeout context manager for asyncio programs" -category = "main" optional = false -python-versions = ">=3.6" +python-versions = ">=3.7" +files = [ + {file = "async-timeout-4.0.3.tar.gz", hash = "sha256:4640d96be84d82d02ed59ea2b7105a0f7b33abe8703703cd0ab0bf87c427522f"}, + {file = "async_timeout-4.0.3-py3-none-any.whl", hash = "sha256:7405140ff1230c310e51dc27b3145b9092d659ce68ff733fb0cefe3ee42be028"}, +] [[package]] name = "backcall" version = "0.2.0" description = "Specifications for callback functions passed in to an API" -category = "dev" optional = false python-versions = "*" files = [ @@ -71,7 +68,6 @@ files = [ name = "backports-zoneinfo" version = "0.2.1" description = "Backport of the standard library zoneinfo module" -category = "main" optional = false python-versions = ">=3.6" files = [ @@ -100,9 +96,12 @@ tzdata = ["tzdata"] name = "basedosdados" version = "1.6.9" description = "Organizar e facilitar o acesso a dados brasileiros através de tabelas públicas no BigQuery." -category = "main" optional = false python-versions = ">=3.7.1,<3.11" +files = [ + {file = "basedosdados-1.6.9-py3-none-any.whl", hash = "sha256:9a73ad8a3667cca327d81c5d41ec809ed0675825dfc5d93d1efcf45f9bd1e867"}, + {file = "basedosdados-1.6.9.tar.gz", hash = "sha256:51783ea130944295dbc6b7dcbad8676ca0ff0234cdf2b4d212177bcd12db7921"}, +] [package.dependencies] ckanapi = "4.6" @@ -127,9 +126,12 @@ tqdm = "4.50.2" name = "beautifulsoup4" version = "4.11.1" description = "Screen-scraping library" -category = "main" optional = false python-versions = ">=3.6.0" +files = [ + {file = "beautifulsoup4-4.11.1-py3-none-any.whl", hash = "sha256:58d5c3d29f5a36ffeb94f02f0d786cd53014cf9b3b3951d42e0080d8a9498d30"}, + {file = "beautifulsoup4-4.11.1.tar.gz", hash = "sha256:ad9aa55b65ef2808eb405f46cf74df7fcb7044d5cbc26487f96eb2ef2e436693"}, +] [package.dependencies] soupsieve = ">1.2" @@ -138,12 +140,10 @@ soupsieve = ">1.2" html5lib = ["html5lib"] lxml = ["lxml"] - 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Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Wed, 30 Aug 2023 17:51:49 -0300 Subject: [PATCH 207/265] =?UTF-8?q?Corre=C3=A7=C3=A3o=20no=20TOML=20p?= =?UTF-8?q?=C3=B3s=20merge?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- pyproject.toml | 8 -------- 1 file changed, 8 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 8e1d50a4c..db1db5d85 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -102,19 +102,11 @@ urllib3 = "1.26.7" websocket-client = "1.2.1" wget = "^3.2" zict = "2.0.0" -pre-commit = "^2.20.0" -google-analytics-data = "0.12.1" -google-api-python-client = "^2.58.0" -oauth2client = "^4.1.3" -redis-pal = "^1.0.0" -fake-useragent = "^1.1.3" -python-Levenshtein = "^0.21.1" [tool.poetry.dev-dependencies] pytest_cov = "^3.0.0" - [build-system] build-backend = "poetry.core.masonry.api" requires = ["poetry-core>=1.0.0"] From 2f518d155445171cb9b21a4d10f3018b77e2bb3c Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Wed, 30 Aug 2023 17:51:55 -0300 Subject: [PATCH 208/265] Regera o .lock --- poetry.lock | 1669 +++++++++++++++++++++++++++++++++------------------ 1 file changed, 1099 insertions(+), 570 deletions(-) diff --git a/poetry.lock b/poetry.lock index ba9843e68..5171ac94f 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,17 +1,65 @@ +# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand. + [[package]] name = "async-timeout" version = "4.0.3" description = "Timeout context manager for asyncio programs" -category = "main" +optional = false +python-versions = ">=3.7" +files = [ + {file = "async-timeout-4.0.3.tar.gz", hash = "sha256:4640d96be84d82d02ed59ea2b7105a0f7b33abe8703703cd0ab0bf87c427522f"}, + {file = "async_timeout-4.0.3-py3-none-any.whl", hash = "sha256:7405140ff1230c310e51dc27b3145b9092d659ce68ff733fb0cefe3ee42be028"}, +] + +[[package]] +name = "backoff" +version = "2.2.1" +description = "Function decoration for backoff and retry" +optional = 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18:01:57 -0300 Subject: [PATCH 209/265] Por algum motivo, faltou Polars --- poetry.lock | 34 +++++++++++++++++++++++++++++++++- pyproject.toml | 1 + 2 files changed, 34 insertions(+), 1 deletion(-) diff --git a/poetry.lock b/poetry.lock index 5171ac94f..ce2b2d456 100644 --- a/poetry.lock +++ b/poetry.lock @@ -2350,6 +2350,38 @@ files = [ dev = ["pre-commit", "tox"] testing = ["pytest", "pytest-benchmark"] +[[package]] +name = "polars" +version = "0.19.0" +description = "Blazingly fast DataFrame library" +optional = false +python-versions = ">=3.8" +files = [ + {file = "polars-0.19.0-cp38-abi3-macosx_10_7_x86_64.whl", hash = "sha256:1c86783df27926580f215472a2760fc8a6c39554a4156a33ac789f54eedcde0a"}, + {file = "polars-0.19.0-cp38-abi3-macosx_11_0_arm64.whl", hash = "sha256:d67cb0f5f9a0a6d62b3a0bb3d48e6a49680bbcf0f144ebcaf4a9ffbabb7c8f06"}, + {file = "polars-0.19.0-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:652b7f911784b4f9c3f9115873e94610268f1e89297477f35898222ff2ccad45"}, + {file = "polars-0.19.0-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6bfebcd0fde831b749e8dc2dcb08913b7b1c0272f10af4e279933203c0635dbb"}, + {file = "polars-0.19.0-cp38-abi3-win_amd64.whl", hash = "sha256:1c194fe6722b5be1721b86f20ba5593ba31f8f04e7ba8e0219235e71e17eda3f"}, + {file = "polars-0.19.0.tar.gz", hash = "sha256:72c0306d2d39d7e24d4530d3977f5853c76efd48a341375ce1f37c62610cfc6a"}, +] + +[package.extras] +adbc = ["adbc_driver_sqlite"] +all = ["polars[adbc,cloudpickle,connectorx,deltalake,fsspec,matplotlib,numpy,pandas,pyarrow,pydantic,sqlalchemy,timezone,xlsx2csv,xlsxwriter]"] +cloudpickle = ["cloudpickle"] +connectorx = ["connectorx"] +deltalake = ["deltalake (>=0.10.0)"] +fsspec = ["fsspec"] +matplotlib = ["matplotlib"] +numpy = ["numpy (>=1.16.0)"] +pandas = ["pandas", "pyarrow (>=7.0.0)"] +pyarrow = ["pyarrow (>=7.0.0)"] +pydantic = ["pydantic"] +sqlalchemy = ["pandas", "sqlalchemy"] +timezone = ["backports.zoneinfo", "tzdata"] +xlsx2csv = ["xlsx2csv (>=0.8.0)"] +xlsxwriter = ["xlsxwriter"] + [[package]] name = "pre-commit" version = "2.21.0" @@ -3728,4 +3760,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p [metadata] lock-version = "2.0" python-versions = ">=3.8,<3.11" -content-hash = "9f20fce15e8fb35f26391eb45434566e64da81ac1b3229376228fe8e74dc10f8" +content-hash = "aedce939153d3e095531054eb14dd03347cda7b26a03737dd3ef55944c2cc5f5" diff --git a/pyproject.toml b/pyproject.toml index db1db5d85..840f268f2 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -102,6 +102,7 @@ urllib3 = "1.26.7" websocket-client = "1.2.1" wget = "^3.2" zict = "2.0.0" +polars = "^0.19.0" [tool.poetry.dev-dependencies] pytest_cov = "^3.0.0" From 5ae929f6374b41bca9a7c4103f307472bf3e2cbb Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Wed, 30 Aug 2023 21:16:01 +0000 Subject: [PATCH 210/265] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- pipelines/datasets/br_denatran_frota/handlers.py | 4 +++- pipelines/datasets/br_denatran_frota/tasks.py | 1 - 2 files changed, 3 insertions(+), 2 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 21c0f8ef5..850dd7254 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -127,7 +127,9 @@ def treat_uf_tipo(file: str) -> pl.DataFrame: def output_file_to_csv(df: pl.DataFrame, filename: str) -> None: make_dir_when_not_exists(OUTPUT_PATH) pd_df = df.to_pandas() - to_partitions(pd_df, partition_columns=["ano", "mes", "sigla_uf"], savepath=OUTPUT_PATH) + to_partitions( + pd_df, partition_columns=["ano", "mes", "sigla_uf"], savepath=OUTPUT_PATH + ) return OUTPUT_PATH diff --git a/pipelines/datasets/br_denatran_frota/tasks.py b/pipelines/datasets/br_denatran_frota/tasks.py index 1f27c5bae..4c348fc17 100644 --- a/pipelines/datasets/br_denatran_frota/tasks.py +++ b/pipelines/datasets/br_denatran_frota/tasks.py @@ -53,4 +53,3 @@ def treat_municipio_tipo_task(file: str) -> pl.DataFrame: @task() def get_latest_data_task(table_name: str) -> tuple[int, int]: return get_latest_data(table_name) - From 90b1cde744aa1b03c3e8156a86edf51d9fb6ec05 Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Wed, 30 Aug 2023 18:25:10 -0300 Subject: [PATCH 211/265] Flake8 --- pipelines/datasets/br_denatran_frota/handlers.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 850dd7254..3567b743c 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -152,7 +152,7 @@ def get_latest_data(table_name: str): denatran_data: pd.DataFrame = get_data_from_prod( table_id=table_name, dataset_id="br_denatran_frota" ) - except: + except Exception as e: return 2003, 1 if not denatran_data.empty: year = denatran_data["ano"].max() From ab07da7ee31f7805fa1076982c521a901ba95c20 Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Wed, 30 Aug 2023 18:25:57 -0300 Subject: [PATCH 212/265] Adiciona pacotes faltantes da master --- pyproject.toml | 3 +++ 1 file changed, 3 insertions(+) diff --git a/pyproject.toml b/pyproject.toml index 840f268f2..6d76655cd 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -103,6 +103,9 @@ websocket-client = "1.2.1" wget = "^3.2" zict = "2.0.0" polars = "^0.19.0" +selenium = "^4.11.2" +fastparquet = "^2023.7.0" + [tool.poetry.dev-dependencies] pytest_cov = "^3.0.0" From 0f39d8bcecd05e51a4f9c2e8b49eb9e18cd05bbf Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Wed, 30 Aug 2023 18:27:50 -0300 Subject: [PATCH 213/265] Flake8 dnv --- pipelines/datasets/br_denatran_frota/handlers.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 3567b743c..164725797 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -152,7 +152,7 @@ def get_latest_data(table_name: str): denatran_data: pd.DataFrame = get_data_from_prod( table_id=table_name, dataset_id="br_denatran_frota" ) - except Exception as e: + except Exception: return 2003, 1 if not denatran_data.empty: year = denatran_data["ano"].max() From 61cd61b2e01f3317f77b1048836af45cee57d6d4 Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Wed, 30 Aug 2023 18:30:00 -0300 Subject: [PATCH 214/265] tirei lixo do gitignore --- .gitignore | 4 ---- 1 file changed, 4 deletions(-) diff --git a/.gitignore b/.gitignore index 12b7b689b..cb0166608 100644 --- a/.gitignore +++ b/.gitignore @@ -141,10 +141,6 @@ dmypy.json notebooks/ /tests/ -poetry.lock -pipelines/datasets/br_denatran_frota/todo_list.txt -pipelines/datasets/br_denatran_frota/run_local.py -basedosdados-dev-ff644018223b.json From 809a41b334ff4c6bac7e4b44af6a7020636f690f Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Wed, 30 Aug 2023 18:36:52 -0300 Subject: [PATCH 215/265] Adiciona pacote faltante --- poetry.lock | 149 ++++++++++++++++++++++++++++++++++++++++++++++++- pyproject.toml | 1 + 2 files changed, 149 insertions(+), 1 deletion(-) diff --git a/poetry.lock b/poetry.lock index 6e5445abf..da38c9731 100644 --- a/poetry.lock +++ b/poetry.lock @@ -11,6 +11,24 @@ files = [ {file = "async_timeout-4.0.3-py3-none-any.whl", hash = "sha256:7405140ff1230c310e51dc27b3145b9092d659ce68ff733fb0cefe3ee42be028"}, ] +[[package]] +name = "attrs" +version = "23.1.0" +description = "Classes Without Boilerplate" +optional = false +python-versions = ">=3.7" +files = [ + {file = "attrs-23.1.0-py3-none-any.whl", hash = "sha256:1f28b4522cdc2fb4256ac1a020c78acf9cba2c6b461ccd2c126f3aa8e8335d04"}, + {file = "attrs-23.1.0.tar.gz", hash = "sha256:6279836d581513a26f1bf235f9acd333bc9115683f14f7e8fae46c98fc50e015"}, +] + +[package.extras] +cov = ["attrs[tests]", "coverage[toml] (>=5.3)"] +dev = ["attrs[docs,tests]", "pre-commit"] +docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier", "zope-interface"] +tests = ["attrs[tests-no-zope]", "zope-interface"] +tests-no-zope = ["cloudpickle", "hypothesis", "mypy (>=1.1.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"] + [[package]] name = "backoff" version = "2.2.1" @@ -1305,6 +1323,17 @@ googleapis-common-protos = ">=1.5.5" grpcio = ">=1.56.2" protobuf = ">=4.21.6" +[[package]] +name = "h11" +version = "0.14.0" +description = "A pure-Python, bring-your-own-I/O implementation of HTTP/1.1" +optional = false +python-versions = ">=3.7" +files = [ + {file = "h11-0.14.0-py3-none-any.whl", hash = "sha256:e3fe4ac4b851c468cc8363d500db52c2ead036020723024a109d37346efaa761"}, + {file = "h11-0.14.0.tar.gz", hash = "sha256:8f19fbbe99e72420ff35c00b27a34cb9937e902a8b810e2c88300c6f0a3b699d"}, +] + [[package]] name = "heapdict" version = "1.0.1" @@ -2196,6 +2225,20 @@ files = [ [package.dependencies] et-xmlfile = "*" +[[package]] +name = "outcome" +version = "1.2.0" +description = "Capture the outcome of Python function calls." +optional = false +python-versions = ">=3.7" +files = [ + {file = "outcome-1.2.0-py2.py3-none-any.whl", hash = "sha256:c4ab89a56575d6d38a05aa16daeaa333109c1f96167aba8901ab18b6b5e0f7f5"}, + {file = "outcome-1.2.0.tar.gz", hash = "sha256:6f82bd3de45da303cf1f771ecafa1633750a358436a8bb60e06a1ceb745d2672"}, +] + +[package.dependencies] +attrs = ">=19.2.0" + [[package]] name = "packaging" version = "21.3" @@ -2866,6 +2909,18 @@ files = [ [package.extras] diagrams = ["jinja2", "railroad-diagrams"] +[[package]] +name = "pysocks" +version = "1.7.1" +description = "A Python SOCKS client module. See https://github.com/Anorov/PySocks for more information." +optional = false +python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" +files = [ + {file = "PySocks-1.7.1-py27-none-any.whl", hash = "sha256:08e69f092cc6dbe92a0fdd16eeb9b9ffbc13cadfe5ca4c7bd92ffb078b293299"}, + {file = "PySocks-1.7.1-py3-none-any.whl", hash = "sha256:2725bd0a9925919b9b51739eea5f9e2bae91e83288108a9ad338b2e3a4435ee5"}, + {file = "PySocks-1.7.1.tar.gz", hash = "sha256:3f8804571ebe159c380ac6de37643bb4685970655d3bba243530d6558b799aa0"}, +] + [[package]] name = "pytest" version = "7.4.0" @@ -3166,6 +3221,17 @@ files = [ [package.extras] full = ["numpy"] +[[package]] +name = "rarfile" +version = "4.0" +description = "RAR archive reader for Python" +optional = false +python-versions = "*" +files = [ + {file = "rarfile-4.0-py3-none-any.whl", hash = "sha256:1094869119012f95c31a6f22cc3a9edbdca61861b805241116adbe2d737b68f8"}, + {file = "rarfile-4.0.tar.gz", hash = "sha256:67548769229c5bda0827c1663dce3f54644f9dbfba4ae86d4da2b2afd3e602a1"}, +] + [[package]] name = "redis" version = "4.6.0" @@ -3407,6 +3473,23 @@ numpy = ">=1.15" pandas = ">=0.23" scipy = ">=1.0" +[[package]] +name = "selenium" +version = "4.11.2" +description = "" +optional = false +python-versions = ">=3.7" +files = [ + {file = "selenium-4.11.2-py3-none-any.whl", hash = "sha256:98e72117b194b3fa9c69b48998f44bf7dd4152c7bd98544911a1753b9f03cc7d"}, + {file = "selenium-4.11.2.tar.gz", hash = "sha256:9f9a5ed586280a3594f7461eb1d9dab3eac9d91e28572f365e9b98d9d03e02b5"}, +] + +[package.dependencies] +certifi = ">=2021.10.8" +trio = ">=0.17,<1.0" +trio-websocket = ">=0.9,<1.0" +urllib3 = {version = ">=1.26,<3", extras = ["socks"]} + [[package]] name = "setuptools" version = "68.1.2" @@ -3434,6 +3517,17 @@ files = [ {file = "six-1.16.0.tar.gz", hash = "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926"}, ] +[[package]] +name = "sniffio" +version = "1.3.0" +description = "Sniff out which async library your code is running under" +optional = false +python-versions = ">=3.7" +files = [ + {file = "sniffio-1.3.0-py3-none-any.whl", hash = "sha256:eecefdce1e5bbfb7ad2eeaabf7c1eeb404d7757c379bd1f7e5cce9d8bf425384"}, + {file = "sniffio-1.3.0.tar.gz", hash = "sha256:e60305c5e5d314f5389259b7f22aaa33d8f7dee49763119234af3755c55b9101"}, +] + [[package]] name = "sortedcontainers" version = "2.4.0" @@ -3606,6 +3700,42 @@ notebook = ["ipywidgets (>=6)"] slack = ["slack-sdk"] telegram = ["requests"] +[[package]] +name = "trio" +version = "0.22.2" +description = "A friendly Python library for async concurrency and I/O" +optional = false +python-versions = ">=3.7" +files = [ + {file = "trio-0.22.2-py3-none-any.whl", hash = "sha256:f43da357620e5872b3d940a2e3589aa251fd3f881b65a608d742e00809b1ec38"}, + {file = "trio-0.22.2.tar.gz", hash = "sha256:3887cf18c8bcc894433420305468388dac76932e9668afa1c49aa3806b6accb3"}, +] + +[package.dependencies] +attrs = ">=20.1.0" +cffi = {version = ">=1.14", markers = "os_name == \"nt\" and implementation_name != \"pypy\""} +exceptiongroup = {version = ">=1.0.0rc9", markers = "python_version < \"3.11\""} +idna = "*" +outcome = "*" +sniffio = "*" +sortedcontainers = "*" + +[[package]] +name = "trio-websocket" +version = "0.10.3" +description = "WebSocket library for Trio" +optional = false +python-versions = ">=3.7" +files = [ + {file = "trio-websocket-0.10.3.tar.gz", hash = "sha256:1a748604ad906a7dcab9a43c6eb5681e37de4793ba0847ef0bc9486933ed027b"}, + {file = "trio_websocket-0.10.3-py3-none-any.whl", hash = "sha256:a9937d48e8132ebf833019efde2a52ca82d223a30a7ea3e8d60a7d28f75a4e3a"}, +] + +[package.dependencies] +exceptiongroup = "*" +trio = ">=0.11" +wsproto = ">=0.14" + [[package]] name = "tweepy" version = "4.4.0" @@ -3700,6 +3830,9 @@ files = [ {file = "urllib3-1.26.7.tar.gz", hash = "sha256:4987c65554f7a2dbf30c18fd48778ef124af6fab771a377103da0585e2336ece"}, ] +[package.dependencies] +PySocks = {version = ">=1.5.6,<1.5.7 || >1.5.7,<2.0", optional = true, markers = "extra == \"socks\""} + [package.extras] brotli = ["brotlipy (>=0.6.0)"] secure = ["certifi", "cryptography (>=1.3.4)", "idna (>=2.0.0)", "ipaddress", "pyOpenSSL (>=0.14)"] @@ -3764,6 +3897,20 @@ files = [ [package.extras] dev = ["black (>=19.3b0)", "pytest (>=4.6.2)"] +[[package]] +name = "wsproto" +version = "1.2.0" +description = "WebSockets state-machine based protocol implementation" +optional = false +python-versions = ">=3.7.0" +files = [ + {file = "wsproto-1.2.0-py3-none-any.whl", hash = "sha256:b9acddd652b585d75b20477888c56642fdade28bdfd3579aa24a4d2c037dd736"}, + {file = "wsproto-1.2.0.tar.gz", hash = "sha256:ad565f26ecb92588a3e43bc3d96164de84cd9902482b130d0ddbaa9664a85065"}, +] + +[package.dependencies] +h11 = ">=0.9.0,<1" + [[package]] name = "yarl" version = "1.9.2" @@ -3883,4 +4030,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p [metadata] lock-version = "2.0" python-versions = ">=3.8,<3.11" -content-hash = "e74524a804c1511e29e1e54e2aa9a7ac981a3867ab29038f4629f906ccd0b98f" +content-hash = "08c3f1c0e73eb0dd90edbc76debb3ff18859414dfb5596b3dd032b7bb2cf07a4" diff --git a/pyproject.toml b/pyproject.toml index 6d76655cd..c201dfeff 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -105,6 +105,7 @@ zict = "2.0.0" polars = "^0.19.0" selenium = "^4.11.2" fastparquet = "^2023.7.0" +rarfile = "^4.0" [tool.poetry.dev-dependencies] From 3381dd1c582cdcca3247df11318e7689c77778a9 Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Wed, 30 Aug 2023 18:45:50 -0300 Subject: [PATCH 216/265] Mais pacotes faltantes --- poetry.lock | 13 ++++++++++++- pyproject.toml | 2 ++ 2 files changed, 14 insertions(+), 1 deletion(-) diff --git a/poetry.lock b/poetry.lock index da38c9731..3d2f93174 100644 --- a/poetry.lock +++ b/poetry.lock @@ -3025,6 +3025,17 @@ text-unidecode = ">=1.3" [package.extras] unidecode = ["Unidecode (>=1.1.1)"] +[[package]] +name = "python-string-utils" +version = "1.0.0" +description = "Utility functions for strings validation and manipulation." +optional = false +python-versions = ">=3.5" +files = [ + {file = "python-string-utils-1.0.0.tar.gz", hash = "sha256:dcf9060b03f07647c0a603408dc8b03f807f3b54a05c6e19eb14460256fac0cb"}, + {file = "python_string_utils-1.0.0-py3-none-any.whl", hash = "sha256:f1a88700baf99db1a9b6953f44181ad9ca56623c81e257e6009707e2e7851fa4"}, +] + [[package]] name = "pytz" version = "2021.3" @@ -4030,4 +4041,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p [metadata] lock-version = "2.0" python-versions = ">=3.8,<3.11" -content-hash = "08c3f1c0e73eb0dd90edbc76debb3ff18859414dfb5596b3dd032b7bb2cf07a4" +content-hash = "4725811605c391e09291644e87d927467b0404c841ebda99c80ae7479dc5e708" diff --git a/pyproject.toml b/pyproject.toml index c201dfeff..e3f4fe3e0 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -106,6 +106,8 @@ polars = "^0.19.0" selenium = "^4.11.2" fastparquet = "^2023.7.0" rarfile = "^4.0" +setuptools = "^68.1.2" +python-string-utils = "^1.0.0" [tool.poetry.dev-dependencies] From 99c494761edd79d493afbf9ca994e97022e8739c Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Wed, 30 Aug 2023 18:48:49 -0300 Subject: [PATCH 217/265] faltou --- pytest.ini | 9 +++++++++ 1 file changed, 9 insertions(+) create mode 100644 pytest.ini diff --git a/pytest.ini b/pytest.ini new file mode 100644 index 000000000..46ad85d66 --- /dev/null +++ b/pytest.ini @@ -0,0 +1,9 @@ +[pytest] +testpaths = + tests +norecursedirs=dist build .tox scripts +addopts = + --doctest-modules + --cov=pipelines + -r a + -v \ No newline at end of file From bcf4acd6c85edad20c7310c6f44bf0fa4b21de40 Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Wed, 30 Aug 2023 19:00:47 -0300 Subject: [PATCH 218/265] Isso agora funciona --- pipelines/datasets/br_denatran_frota/handlers.py | 9 ++++----- 1 file changed, 4 insertions(+), 5 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 164725797..318c059ab 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -148,11 +148,10 @@ def get_desired_file(year: int, download_directory: str, filetype: str) -> str: def get_latest_data(table_name: str): - try: - denatran_data: pd.DataFrame = get_data_from_prod( - table_id=table_name, dataset_id="br_denatran_frota" - ) - except Exception: + denatran_data: pd.DataFrame = get_data_from_prod( + table_id=table_name, dataset_id="br_denatran_frota" + ) + if not denatran_data: return 2003, 1 if not denatran_data.empty: year = denatran_data["ano"].max() From 7906b0f5f61271d3fe56e73105b637bd274f5627 Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Wed, 30 Aug 2023 19:10:01 -0300 Subject: [PATCH 219/265] xlrd --- poetry.lock | 18 +++++++++++++++++- pyproject.toml | 1 + 2 files changed, 18 insertions(+), 1 deletion(-) diff --git a/poetry.lock b/poetry.lock index 3d2f93174..f12d56df9 100644 --- a/poetry.lock +++ b/poetry.lock @@ -3922,6 +3922,22 @@ files = [ [package.dependencies] h11 = ">=0.9.0,<1" +[[package]] +name = "xlrd" +version = "2.0.1" +description = "Library for developers to extract data from Microsoft Excel (tm) .xls spreadsheet files" +optional = false +python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*" +files = [ + {file = "xlrd-2.0.1-py2.py3-none-any.whl", hash = "sha256:6a33ee89877bd9abc1158129f6e94be74e2679636b8a205b43b85206c3f0bbdd"}, + {file = "xlrd-2.0.1.tar.gz", hash = "sha256:f72f148f54442c6b056bf931dbc34f986fd0c3b0b6b5a58d013c9aef274d0c88"}, +] + +[package.extras] +build = ["twine", "wheel"] +docs = ["sphinx"] +test = ["pytest", "pytest-cov"] + [[package]] name = "yarl" version = "1.9.2" @@ -4041,4 +4057,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p [metadata] lock-version = "2.0" python-versions = ">=3.8,<3.11" -content-hash = "4725811605c391e09291644e87d927467b0404c841ebda99c80ae7479dc5e708" +content-hash = "be55ea7e2f7f43848079b0bb8afc6c49cb77e9ce3caa4dba1f45abc661fdf696" diff --git a/pyproject.toml b/pyproject.toml index e3f4fe3e0..09fefef0c 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -108,6 +108,7 @@ fastparquet = "^2023.7.0" rarfile = "^4.0" setuptools = "^68.1.2" python-string-utils = "^1.0.0" +xlrd = "^2.0.1" [tool.poetry.dev-dependencies] From 62187a03b0f270d31597b8b63e1ad81d13cb9aac Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Sat, 2 Sep 2023 00:22:10 -0300 Subject: [PATCH 220/265] Isso aqui era o erro --- pipelines/datasets/br_denatran_frota/utils.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index 5ed81e289..d6565b79c 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -160,7 +160,7 @@ def calculate_total(df): calculated_total = calculate_total(df) mask = df["TOTAL"] != calculated_total - if pl.sum(mask) != 0: + if sum(mask) != 0: # In some cases, the quadriciclo data is multiplied by 10, and this will correct it before you new_df = clean_quadriciclo_data(df) new_calculated_total = calculate_total(new_df) From 803ea5e749a9f1afaab8ef619bcc6778aced3c7e Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Sat, 2 Sep 2023 22:14:12 -0300 Subject: [PATCH 221/265] agr vai --- pipelines/datasets/br_denatran_frota/utils.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index d6565b79c..e8e591394 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -526,7 +526,7 @@ def treat_uf(denatran_df: pl.DataFrame, ibge_df: pl.DataFrame, uf: str) -> None: suggested_name_ibge.alias("suggested_nome_ibge") ) denatran_uf = denatran_uf.with_columns( - denatran_uf.apply(fix_suggested_nome_ibge)["apply"].alias("suggested_nome_ibge") + denatran_uf.apply(fix_suggested_nome_ibge)["map"].alias("suggested_nome_ibge") ) municipios_no_denatran = denatran_uf["suggested_nome_ibge"].to_list() d = set(municipios_no_denatran) - set(municipios_na_bd) From 6d255bc81b02a8dfe0b9c379f6b10044d9ecb20b Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Sun, 3 Sep 2023 19:08:27 -0300 Subject: [PATCH 222/265] Resolve problema 2 --- pipelines/datasets/br_denatran_frota/handlers.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 318c059ab..33dace631 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -151,7 +151,7 @@ def get_latest_data(table_name: str): denatran_data: pd.DataFrame = get_data_from_prod( table_id=table_name, dataset_id="br_denatran_frota" ) - if not denatran_data: + if not isinstance(denatran_data, pd.DataFrame): return 2003, 1 if not denatran_data.empty: year = denatran_data["ano"].max() From d5dc7c9c54d46731ec99ebfa104b8aebfaa64d97 Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Sat, 16 Sep 2023 05:43:34 -0300 Subject: [PATCH 223/265] kkkkkkkkkkkkkkkkk --- pipelines/datasets/br_denatran_frota/handlers.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 33dace631..8c1b55655 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -161,7 +161,7 @@ def get_latest_data(table_name: str): if month == 12: year += 1 month = 1 - log(f"Ano: {year}, mês: {month+1}") + log(f"Ano: {str(year)}, mês: {str(month+1)}") return year, month + 1 else: log("Não achei ano não mané") From d3e2e50a38db0f18a14288c4f9c4b469d6659e6a Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Sat, 16 Sep 2023 05:52:21 -0300 Subject: [PATCH 224/265] schedule fix --- pipelines/datasets/br_denatran_frota/schedules.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/schedules.py b/pipelines/datasets/br_denatran_frota/schedules.py index 792760590..7f39a37ac 100644 --- a/pipelines/datasets/br_denatran_frota/schedules.py +++ b/pipelines/datasets/br_denatran_frota/schedules.py @@ -15,7 +15,7 @@ interval=timedelta(weeks=2), start_date=datetime(2021, 1, 1), labels=[ - constants.DATASETS_AGENT_LABEL.value, + constants.BASEDOSDADOS_PROD_AGENT_LABEL.value, ], ), ] From 6323142e44e3fa39115cb4a58b339e37677d5a74 Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Sat, 16 Sep 2023 05:59:28 -0300 Subject: [PATCH 225/265] TODO MERGE ISSO --- pyproject.toml | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index 6d76655cd..87f6968c8 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -105,7 +105,10 @@ zict = "2.0.0" polars = "^0.19.0" selenium = "^4.11.2" fastparquet = "^2023.7.0" - +rarfile = "^4.0" +setuptools = "^68.1.2" +python-string-utils = "^1.0.0" +xlrd = "^2.0.1" [tool.poetry.dev-dependencies] pytest_cov = "^3.0.0" From db0dbea1fa382ea62f6953ac987c80e0c111cd0b Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Sat, 16 Sep 2023 06:06:38 -0300 Subject: [PATCH 226/265] . --- pyproject.toml | 2 ++ 1 file changed, 2 insertions(+) diff --git a/pyproject.toml b/pyproject.toml index 87f6968c8..7df98c036 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -109,6 +109,8 @@ rarfile = "^4.0" setuptools = "^68.1.2" python-string-utils = "^1.0.0" xlrd = "^2.0.1" +geopandas = "0.13.2" +shapely = "2.0.1" [tool.poetry.dev-dependencies] pytest_cov = "^3.0.0" From 7e97dc53f3cac143c65646991cc4f5f88282eaff Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Sat, 16 Sep 2023 06:22:20 -0300 Subject: [PATCH 227/265] Pronto --- pipelines/datasets/br_denatran_frota/handlers.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 8c1b55655..412c7bebf 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -161,8 +161,9 @@ def get_latest_data(table_name: str): if month == 12: year += 1 month = 1 - log(f"Ano: {str(year)}, mês: {str(month+1)}") - return year, month + 1 + else: + month += 1 + return year, month else: log("Não achei ano não mané") return 2003, 1 From ddaee64e30054dfbe0f3e64c65f20fcdc8f12a54 Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Sat, 16 Sep 2023 06:34:26 -0300 Subject: [PATCH 228/265] Isso era pra ser tao simples --- pipelines/datasets/br_denatran_frota/handlers.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 412c7bebf..5f8e4d534 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -154,8 +154,8 @@ def get_latest_data(table_name: str): if not isinstance(denatran_data, pd.DataFrame): return 2003, 1 if not denatran_data.empty: - year = denatran_data["ano"].max() - month = denatran_data.loc[denatran_data["ano"] == year]["mes"].max() + year = int(denatran_data["ano"].max()) + month = int(denatran_data.loc[denatran_data["ano"] == year]["mes"].max()) log(year) log(month) if month == 12: @@ -163,6 +163,7 @@ def get_latest_data(table_name: str): month = 1 else: month += 1 + log(f"Ano: {year}, mês: {month}") return year, month else: log("Não achei ano não mané") From 42f0e52216d66a152302e9d97e5ef5a005f94f94 Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Sat, 16 Sep 2023 06:44:59 -0300 Subject: [PATCH 229/265] Cara. --- pipelines/datasets/br_denatran_frota/handlers.py | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 5f8e4d534..64392fc45 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -154,10 +154,12 @@ def get_latest_data(table_name: str): if not isinstance(denatran_data, pd.DataFrame): return 2003, 1 if not denatran_data.empty: - year = int(denatran_data["ano"].max()) - month = int(denatran_data.loc[denatran_data["ano"] == year]["mes"].max()) + year = denatran_data["ano"].max() + month = denatran_data.loc[denatran_data["ano"] == year]["mes"].max() log(year) + log(type(year)) log(month) + log(type(month)) if month == 12: year += 1 month = 1 From 4d33dd2c8fbc550e5915cc0c3626c00c628e666d Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Sat, 16 Sep 2023 06:52:52 -0300 Subject: [PATCH 230/265] Cara --- .../datasets/br_denatran_frota/handlers.py | 1 + pipelines/datasets/br_denatran_frota/run.py | 4 +- poetry.lock | 942 +++++++++++------- 3 files changed, 602 insertions(+), 345 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 64392fc45..c5948dc72 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -154,6 +154,7 @@ def get_latest_data(table_name: str): if not isinstance(denatran_data, pd.DataFrame): return 2003, 1 if not denatran_data.empty: + log(denatran_data.head(2)) year = denatran_data["ano"].max() month = denatran_data.loc[denatran_data["ano"] == year]["mes"].max() log(year) diff --git a/pipelines/datasets/br_denatran_frota/run.py b/pipelines/datasets/br_denatran_frota/run.py index a0ead7920..47e6b3ca5 100644 --- a/pipelines/datasets/br_denatran_frota/run.py +++ b/pipelines/datasets/br_denatran_frota/run.py @@ -1,4 +1,4 @@ # -*- coding: utf-8 -*- -from flows import br_denatran_frota_uf_tipo +from flows import br_denatran_frota_municipio_tipo -br_denatran_frota_uf_tipo.run() +br_denatran_frota_municipio_tipo.run() diff --git a/poetry.lock b/poetry.lock index f12d56df9..946b5d48f 100644 --- a/poetry.lock +++ b/poetry.lock @@ -267,6 +267,40 @@ files = [ [package.dependencies] colorama = {version = "*", markers = "platform_system == \"Windows\""} +[[package]] +name = "click-plugins" +version = "1.1.1" +description = "An extension module for click to enable registering CLI commands via setuptools entry-points." +optional = false +python-versions = "*" +files = [ + {file = "click-plugins-1.1.1.tar.gz", hash = "sha256:46ab999744a9d831159c3411bb0c79346d94a444df9a3a3742e9ed63645f264b"}, + {file = "click_plugins-1.1.1-py2.py3-none-any.whl", hash = "sha256:5d262006d3222f5057fd81e1623d4443e41dcda5dc815c06b442aa3c02889fc8"}, +] + +[package.dependencies] 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104fb3bb673bc258aa8581ef064fd68f11036fd7 Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Sat, 16 Sep 2023 07:05:01 -0300 Subject: [PATCH 231/265] converte na hr certa --- pipelines/datasets/br_denatran_frota/handlers.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index c5948dc72..678922767 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -157,6 +157,8 @@ def get_latest_data(table_name: str): log(denatran_data.head(2)) year = denatran_data["ano"].max() month = denatran_data.loc[denatran_data["ano"] == year]["mes"].max() + year = int(year) + month = int(month) log(year) log(type(year)) log(month) From dafcdc8a17dc5f35e5dca86bb2aa8f1313e4cec4 Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Fri, 22 Sep 2023 02:50:56 -0300 Subject: [PATCH 232/265] Meu deus cara --- pipelines/datasets/br_denatran_frota/backfill.py | 10 ++++++++++ pipelines/datasets/br_denatran_frota/run.py | 4 ---- 2 files changed, 10 insertions(+), 4 deletions(-) create mode 100644 pipelines/datasets/br_denatran_frota/backfill.py delete mode 100644 pipelines/datasets/br_denatran_frota/run.py diff --git a/pipelines/datasets/br_denatran_frota/backfill.py b/pipelines/datasets/br_denatran_frota/backfill.py new file mode 100644 index 000000000..ad8739398 --- /dev/null +++ b/pipelines/datasets/br_denatran_frota/backfill.py @@ -0,0 +1,10 @@ +# -*- coding: utf-8 -*- +from pipelines.datasets.br_denatran_frota.handlers import crawl, get_desired_file +from pipelines.datasets.br_denatran_frota.constants import constants + +months = range(1, 13) +year = 2003 +for month in months: + print(month) + crawl(month=month, year=year, temp_dir="DENATRAN_FILES") + get_desired_file(year=year, download_directory=constants.DOWNLOAD_PATH.value) diff --git a/pipelines/datasets/br_denatran_frota/run.py b/pipelines/datasets/br_denatran_frota/run.py deleted file mode 100644 index 47e6b3ca5..000000000 --- a/pipelines/datasets/br_denatran_frota/run.py +++ /dev/null @@ -1,4 +0,0 @@ -# -*- coding: utf-8 -*- -from flows import br_denatran_frota_municipio_tipo - -br_denatran_frota_municipio_tipo.run() From e1014942936028ef623fd9bbed18ccdf7687b67f Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Fri, 22 Sep 2023 02:54:45 -0300 Subject: [PATCH 233/265] =?UTF-8?q?Eu=20s=C3=B3=20quero=20que=20isso=20n?= =?UTF-8?q?=C3=A3o=20rode=20agora=20como=20parece?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- pipelines/datasets/br_denatran_frota/flows.py | 436 +++++++++--------- 1 file changed, 218 insertions(+), 218 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index d23f80558..93b87405a 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -1,219 +1,219 @@ # -*- coding: utf-8 -*- -""" -Flows for br_denatran_frota -""" - - -from datetime import datetime, timedelta -from prefect.run_configs import KubernetesRun -from prefect.storage import GCS -from prefect import Parameter, case, unmapped -from prefect.tasks.prefect import ( - create_flow_run, - wait_for_flow_run, -) -import os -from pipelines.constants import constants as pipelines_constants -from pipelines.utils.constants import constants as utils_constants - -from pipelines.utils.decorators import Flow -from pipelines.utils.execute_dbt_model.constants import constants as dump_db_constants -from pipelines.utils.tasks import ( - create_table_and_upload_to_gcs, - rename_current_flow_run_dataset_table, - get_current_flow_labels, -) -from pipelines.datasets.br_denatran_frota.tasks import ( - crawl_task, - treat_uf_tipo_task, - output_file_to_csv_task, - get_desired_file_task, - treat_municipio_tipo_task, - get_latest_data_task, -) -from pipelines.datasets.br_denatran_frota.constants import constants -from itertools import product - -year_range = list(range(2003, 2023)) -month_range = list(range(1, 13)) -date_pairs = list(product(year_range, month_range)) - -date_pairs_param: list[tuple] = Parameter("date_pairs", default=date_pairs) - -# from pipelines.datasets.br_denatran_frota.schedules import every_two_weeks - -with Flow( - name="br_denatran_frota.uf_tipo", - code_owners=[ - "Tamir", - ], -) as br_denatran_frota_uf_tipo: - dataset_id = Parameter("dataset_id", default="br_denatran_frota") - table_id = Parameter("table_id", default="uf_tipo") - - # Materialization mode - materialization_mode = Parameter( - "materialization_mode", default="dev", required=False - ) - - materialize_after_dump = Parameter( - "materialize after dump", default=False, required=False - ) - - dbt_alias = Parameter("dbt_alias", default=True, required=False) - rename_flow_run = rename_current_flow_run_dataset_table( - prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id - ) - - year_to_fetch = get_latest_data_task("uf_tipo") - crawled = crawl_task( - month=year_to_fetch[1], - year=year_to_fetch[0], - temp_dir=constants.DOWNLOAD_PATH.value, - upstream_tasks=[year_to_fetch], - ) - # Now get the downloaded file: - municipio_tipo_file = get_desired_file_task( - year=year_to_fetch[0], - download_directory=constants.DOWNLOAD_PATH.value, - filetype=constants.UF_TIPO_BASIC_FILENAME.value, - upstream_tasks=[crawled], - ) - df = treat_uf_tipo_task( - file=municipio_tipo_file, upstream_tasks=[crawled, municipio_tipo_file] - ) - csv_output = output_file_to_csv_task( - df, constants.UF_TIPO_BASIC_FILENAME.value, upstream_tasks=[df] - ) - wait_upload_table = create_table_and_upload_to_gcs( - data_path=csv_output, - dataset_id=dataset_id, - table_id=table_id, - dump_mode="append", - wait=csv_output, - ) - - with case(materialize_after_dump, True): - # Trigger DBT flow run - current_flow_labels = get_current_flow_labels() - materialization_flow = create_flow_run( - flow_name=utils_constants.FLOW_EXECUTE_DBT_MODEL_NAME.value, - project_name=pipelines_constants.PREFECT_DEFAULT_PROJECT.value, - parameters={ - "dataset_id": dataset_id, - "table_id": table_id, - "mode": materialization_mode, - "dbt_alias": dbt_alias, - }, - labels=current_flow_labels, - run_name=f"Materialize {dataset_id}.{table_id}", - ) - wait_for_materialization = wait_for_flow_run( - materialization_flow, - stream_states=True, - stream_logs=True, - raise_final_state=True, - ) - wait_for_materialization.max_retries = ( - dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_ATTEMPTS.value - ) - wait_for_materialization.retry_delay = timedelta( - seconds=dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_INTERVAL.value - ) - - -br_denatran_frota_uf_tipo.storage = GCS(pipelines_constants.GCS_FLOWS_BUCKET.value) -br_denatran_frota_uf_tipo.run_config = KubernetesRun( - image=pipelines_constants.DOCKER_IMAGE.value -) -# flow.schedule = every_two_weeks - - -with Flow( - name="br_denatran_frota.municipio_tipo", - code_owners=[ - "Tamir", - ], -) as br_denatran_frota_municipio_tipo: - dataset_id = Parameter("dataset_id", default="br_denatran_frota") - table_id = Parameter("table_id", default="municipio_tipo") - - # Materialization mode - materialization_mode = Parameter( - "materialization_mode", default="dev", required=False - ) - - materialize_after_dump = Parameter( - "materialize after dump", default=False, required=False - ) - - dbt_alias = Parameter("dbt_alias", default=True, required=False) - - rename_flow_run = rename_current_flow_run_dataset_table( - prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id - ) - year_to_fetch = get_latest_data_task("municipio_tipo") - crawled = crawl_task( - month=year_to_fetch[1], - year=year_to_fetch[0], - temp_dir=constants.DOWNLOAD_PATH.value, - upstream_tasks=[year_to_fetch], - ) - # Now get the downloaded file: - municipio_tipo_file = get_desired_file_task( - year=year_to_fetch[0], - download_directory=constants.DOWNLOAD_PATH.value, - filetype=constants.MUNIC_TIPO_BASIC_FILENAME.value, - upstream_tasks=[crawled], - ) - df = treat_municipio_tipo_task( - file=municipio_tipo_file, upstream_tasks=[crawled, municipio_tipo_file] - ) - csv_output = output_file_to_csv_task( - df, constants.MUNIC_TIPO_BASIC_FILENAME.value, upstream_tasks=[df] - ) - wait_upload_table = create_table_and_upload_to_gcs( - data_path=csv_output, - dataset_id=dataset_id, - table_id=table_id, - dump_mode="append", - wait=csv_output, - ) - - with case(materialize_after_dump, True): - # Trigger DBT flow run - current_flow_labels = get_current_flow_labels() - materialization_flow = create_flow_run( - flow_name=utils_constants.FLOW_EXECUTE_DBT_MODEL_NAME.value, - project_name=pipelines_constants.PREFECT_DEFAULT_PROJECT.value, - parameters={ - "dataset_id": dataset_id, - "table_id": table_id, - "mode": materialization_mode, - "dbt_alias": dbt_alias, - }, - labels=current_flow_labels, - run_name=f"Materialize {dataset_id}.{table_id}", - ) - - wait_for_materialization = wait_for_flow_run( - materialization_flow, - stream_states=True, - stream_logs=True, - raise_final_state=True, - ) - wait_for_materialization.max_retries = ( - dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_ATTEMPTS.value - ) - wait_for_materialization.retry_delay = timedelta( - seconds=dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_INTERVAL.value - ) - - -br_denatran_frota_municipio_tipo.storage = GCS( - pipelines_constants.GCS_FLOWS_BUCKET.value -) -br_denatran_frota_municipio_tipo.run_config = KubernetesRun( - image=pipelines_constants.DOCKER_IMAGE.value -) -# flow.schedule = every_two_weeks +# """ +# Flows for br_denatran_frota +# """ + + +# from datetime import datetime, timedelta +# from prefect.run_configs import KubernetesRun +# from prefect.storage import GCS +# from prefect import Parameter, case, unmapped +# from prefect.tasks.prefect import ( +# create_flow_run, +# wait_for_flow_run, +# ) +# import os +# from pipelines.constants import constants as pipelines_constants +# from pipelines.utils.constants import constants as utils_constants + +# from pipelines.utils.decorators import Flow +# from pipelines.utils.execute_dbt_model.constants import constants as dump_db_constants +# from pipelines.utils.tasks import ( +# create_table_and_upload_to_gcs, +# rename_current_flow_run_dataset_table, +# get_current_flow_labels, +# ) +# from pipelines.datasets.br_denatran_frota.tasks import ( +# crawl_task, +# treat_uf_tipo_task, +# output_file_to_csv_task, +# get_desired_file_task, +# treat_municipio_tipo_task, +# get_latest_data_task, +# ) +# from pipelines.datasets.br_denatran_frota.constants import constants +# from itertools import product + +# year_range = list(range(2003, 2023)) +# month_range = list(range(1, 13)) +# date_pairs = list(product(year_range, month_range)) + +# date_pairs_param: list[tuple] = Parameter("date_pairs", default=date_pairs) + +# # from pipelines.datasets.br_denatran_frota.schedules import every_two_weeks + +# with Flow( +# name="br_denatran_frota.uf_tipo", +# code_owners=[ +# "Tamir", +# ], +# ) as br_denatran_frota_uf_tipo: +# dataset_id = Parameter("dataset_id", default="br_denatran_frota") +# table_id = Parameter("table_id", default="uf_tipo") + +# # Materialization mode +# materialization_mode = Parameter( +# "materialization_mode", default="dev", required=False +# ) + +# materialize_after_dump = Parameter( +# "materialize after dump", default=False, required=False +# ) + +# dbt_alias = Parameter("dbt_alias", default=True, required=False) +# rename_flow_run = rename_current_flow_run_dataset_table( +# prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id +# ) + +# year_to_fetch = get_latest_data_task("uf_tipo") +# crawled = crawl_task( +# month=year_to_fetch[1], +# year=year_to_fetch[0], +# temp_dir=constants.DOWNLOAD_PATH.value, +# upstream_tasks=[year_to_fetch], +# ) +# # Now get the downloaded file: +# municipio_tipo_file = get_desired_file_task( +# year=year_to_fetch[0], +# download_directory=constants.DOWNLOAD_PATH.value, +# filetype=constants.UF_TIPO_BASIC_FILENAME.value, +# upstream_tasks=[crawled], +# ) +# df = treat_uf_tipo_task( +# file=municipio_tipo_file, upstream_tasks=[crawled, municipio_tipo_file] +# ) +# csv_output = output_file_to_csv_task( +# df, constants.UF_TIPO_BASIC_FILENAME.value, upstream_tasks=[df] +# ) +# wait_upload_table = create_table_and_upload_to_gcs( +# data_path=csv_output, +# dataset_id=dataset_id, +# table_id=table_id, +# dump_mode="append", +# wait=csv_output, +# ) + +# with case(materialize_after_dump, True): +# # Trigger DBT flow run +# current_flow_labels = get_current_flow_labels() +# materialization_flow = create_flow_run( +# flow_name=utils_constants.FLOW_EXECUTE_DBT_MODEL_NAME.value, +# project_name=pipelines_constants.PREFECT_DEFAULT_PROJECT.value, +# parameters={ +# "dataset_id": dataset_id, +# "table_id": table_id, +# "mode": materialization_mode, +# "dbt_alias": dbt_alias, +# }, +# labels=current_flow_labels, +# run_name=f"Materialize {dataset_id}.{table_id}", +# ) +# wait_for_materialization = wait_for_flow_run( +# materialization_flow, +# stream_states=True, +# stream_logs=True, +# raise_final_state=True, +# ) +# wait_for_materialization.max_retries = ( +# dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_ATTEMPTS.value +# ) +# wait_for_materialization.retry_delay = timedelta( +# seconds=dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_INTERVAL.value +# ) + + +# br_denatran_frota_uf_tipo.storage = GCS(pipelines_constants.GCS_FLOWS_BUCKET.value) +# br_denatran_frota_uf_tipo.run_config = KubernetesRun( +# image=pipelines_constants.DOCKER_IMAGE.value +# ) +# # flow.schedule = every_two_weeks + + +# with Flow( +# name="br_denatran_frota.municipio_tipo", +# code_owners=[ +# "Tamir", +# ], +# ) as br_denatran_frota_municipio_tipo: +# dataset_id = Parameter("dataset_id", default="br_denatran_frota") +# table_id = Parameter("table_id", default="municipio_tipo") + +# # Materialization mode +# materialization_mode = Parameter( +# "materialization_mode", default="dev", required=False +# ) + +# materialize_after_dump = Parameter( +# "materialize after dump", default=False, required=False +# ) + +# dbt_alias = Parameter("dbt_alias", default=True, required=False) + +# rename_flow_run = rename_current_flow_run_dataset_table( +# prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id +# ) +# year_to_fetch = get_latest_data_task("municipio_tipo") +# crawled = crawl_task( +# month=year_to_fetch[1], +# year=year_to_fetch[0], +# temp_dir=constants.DOWNLOAD_PATH.value, +# upstream_tasks=[year_to_fetch], +# ) +# # Now get the downloaded file: +# municipio_tipo_file = get_desired_file_task( +# year=year_to_fetch[0], +# download_directory=constants.DOWNLOAD_PATH.value, +# filetype=constants.MUNIC_TIPO_BASIC_FILENAME.value, +# upstream_tasks=[crawled], +# ) +# df = treat_municipio_tipo_task( +# file=municipio_tipo_file, upstream_tasks=[crawled, municipio_tipo_file] +# ) +# csv_output = output_file_to_csv_task( +# df, constants.MUNIC_TIPO_BASIC_FILENAME.value, upstream_tasks=[df] +# ) +# wait_upload_table = create_table_and_upload_to_gcs( +# data_path=csv_output, +# dataset_id=dataset_id, +# table_id=table_id, +# dump_mode="append", +# wait=csv_output, +# ) + +# with case(materialize_after_dump, True): +# # Trigger DBT flow run +# current_flow_labels = get_current_flow_labels() +# materialization_flow = create_flow_run( +# flow_name=utils_constants.FLOW_EXECUTE_DBT_MODEL_NAME.value, +# project_name=pipelines_constants.PREFECT_DEFAULT_PROJECT.value, +# parameters={ +# "dataset_id": dataset_id, +# "table_id": table_id, +# "mode": materialization_mode, +# "dbt_alias": dbt_alias, +# }, +# labels=current_flow_labels, +# run_name=f"Materialize {dataset_id}.{table_id}", +# ) + +# wait_for_materialization = wait_for_flow_run( +# materialization_flow, +# stream_states=True, +# stream_logs=True, +# raise_final_state=True, +# ) +# wait_for_materialization.max_retries = ( +# dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_ATTEMPTS.value +# ) +# wait_for_materialization.retry_delay = timedelta( +# seconds=dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_INTERVAL.value +# ) + + +# br_denatran_frota_municipio_tipo.storage = GCS( +# pipelines_constants.GCS_FLOWS_BUCKET.value +# ) +# br_denatran_frota_municipio_tipo.run_config = KubernetesRun( +# image=pipelines_constants.DOCKER_IMAGE.value +# ) +# # flow.schedule = every_two_weeks From 0cfa89a6bab2f2680b21211b3f61d66cb666211b Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Fri, 22 Sep 2023 02:59:33 -0300 Subject: [PATCH 234/265] =?UTF-8?q?Tem=20algo=20rodando=20autom=C3=A1tico?= =?UTF-8?q?=20e=20eu=20cansei?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- pipelines/datasets/br_denatran_frota/backfill.py | 7 ++++++- pipelines/datasets/br_denatran_frota/handlers.py | 2 +- 2 files changed, 7 insertions(+), 2 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/backfill.py b/pipelines/datasets/br_denatran_frota/backfill.py index ad8739398..b574ef739 100644 --- a/pipelines/datasets/br_denatran_frota/backfill.py +++ b/pipelines/datasets/br_denatran_frota/backfill.py @@ -2,9 +2,14 @@ from pipelines.datasets.br_denatran_frota.handlers import crawl, get_desired_file from pipelines.datasets.br_denatran_frota.constants import constants +# Fill for UF TIPO months = range(1, 13) year = 2003 for month in months: print(month) crawl(month=month, year=year, temp_dir="DENATRAN_FILES") - get_desired_file(year=year, download_directory=constants.DOWNLOAD_PATH.value) + file = get_desired_file( + year=year, + download_directory=constants.DOWNLOAD_PATH.value, + filetype=constants.UF_TIPO_BASIC_FILENAME.value, + ) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 678922767..b7627ce41 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -58,7 +58,7 @@ def crawl(month: int, year: int, temp_dir: str = "") -> None: log("Downloading file") files_dir = os.path.join(temp_dir, "files") make_dir_when_not_exists(files_dir) - year_dir_name = os.path.join(files_dir, f"{year}") + year_dir_name = os.path.join(files_dir, f"{year}/{month}") make_dir_when_not_exists(year_dir_name) if year > 2012: files_to_download = extract_links_post_2012(month, year, year_dir_name) From af9bebc0c902b4492c621a91734200cd86dfc726 Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Fri, 22 Sep 2023 03:24:14 -0300 Subject: [PATCH 235/265] Seguro morreu de velho --- pipelines/datasets/br_denatran_frota/backfill.py | 3 ++- pipelines/datasets/br_denatran_frota/utils.py | 2 ++ 2 files changed, 4 insertions(+), 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/backfill.py b/pipelines/datasets/br_denatran_frota/backfill.py index b574ef739..9a4856720 100644 --- a/pipelines/datasets/br_denatran_frota/backfill.py +++ b/pipelines/datasets/br_denatran_frota/backfill.py @@ -10,6 +10,7 @@ crawl(month=month, year=year, temp_dir="DENATRAN_FILES") file = get_desired_file( year=year, - download_directory=constants.DOWNLOAD_PATH.value, + download_directory=f"DENATRAN_FILES/{year}/{month}", filetype=constants.UF_TIPO_BASIC_FILENAME.value, ) + print(file) diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index e8e591394..65f8c3a74 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -433,6 +433,8 @@ def extraction_pre_2012(month: int, year: int, year_dir_name: str, zip_file: str zip_file (str): _description_ """ # Aí depois eu preciso andar pelo zip: + if not zip_file.endswith(".zip"): + return with ZipFile(zip_file, "r") as g: compressed_files = [file for file in g.infolist() if not file.is_dir()] new_filename = None From 5bd07ec722d8d7f4c7cb435808c00ebeff9b3ac8 Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Fri, 22 Sep 2023 03:28:55 -0300 Subject: [PATCH 236/265] Acho que isso segura --- pipelines/datasets/br_denatran_frota/backfill.py | 2 +- pipelines/datasets/br_denatran_frota/handlers.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/backfill.py b/pipelines/datasets/br_denatran_frota/backfill.py index 9a4856720..7c0f23a63 100644 --- a/pipelines/datasets/br_denatran_frota/backfill.py +++ b/pipelines/datasets/br_denatran_frota/backfill.py @@ -10,7 +10,7 @@ crawl(month=month, year=year, temp_dir="DENATRAN_FILES") file = get_desired_file( year=year, - download_directory=f"DENATRAN_FILES/{year}/{month}", + download_directory="DENATRAN_FILES", filetype=constants.UF_TIPO_BASIC_FILENAME.value, ) print(file) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index b7627ce41..678922767 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -58,7 +58,7 @@ def crawl(month: int, year: int, temp_dir: str = "") -> None: log("Downloading file") files_dir = os.path.join(temp_dir, "files") make_dir_when_not_exists(files_dir) - year_dir_name = os.path.join(files_dir, f"{year}/{month}") + year_dir_name = os.path.join(files_dir, f"{year}") make_dir_when_not_exists(year_dir_name) if year > 2012: files_to_download = extract_links_post_2012(month, year, year_dir_name) From 06561f3bcd95f22dde3e0a82d6458ed72cea7400 Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Tue, 26 Sep 2023 17:49:16 -0300 Subject: [PATCH 237/265] OK --- .../datasets/br_denatran_frota/backfill.py | 33 ++++++++++++------- .../datasets/br_denatran_frota/handlers.py | 3 +- pipelines/datasets/br_denatran_frota/utils.py | 19 ++++++++--- 3 files changed, 38 insertions(+), 17 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/backfill.py b/pipelines/datasets/br_denatran_frota/backfill.py index 7c0f23a63..3f2175169 100644 --- a/pipelines/datasets/br_denatran_frota/backfill.py +++ b/pipelines/datasets/br_denatran_frota/backfill.py @@ -1,16 +1,27 @@ # -*- coding: utf-8 -*- -from pipelines.datasets.br_denatran_frota.handlers import crawl, get_desired_file +from pipelines.datasets.br_denatran_frota.handlers import ( + crawl, + treat_uf_tipo, + get_desired_file, + output_file_to_csv, +) from pipelines.datasets.br_denatran_frota.constants import constants # Fill for UF TIPO months = range(1, 13) -year = 2003 -for month in months: - print(month) - crawl(month=month, year=year, temp_dir="DENATRAN_FILES") - file = get_desired_file( - year=year, - download_directory="DENATRAN_FILES", - filetype=constants.UF_TIPO_BASIC_FILENAME.value, - ) - print(file) +years = range(2003, 2023) +for year in years: + for month in months: + print(month) + crawl(month=month, year=year, temp_dir="DENATRAN_FILES") + file = get_desired_file( + year=year, + download_directory="DENATRAN_FILES", + filetype=f"{constants.UF_TIPO_BASIC_FILENAME.value}_{month}", + ) + if year == 2004 and month == 3: + breakpoint() + df = treat_uf_tipo(file=file) + path = output_file_to_csv( + df=df, filename=constants.UF_TIPO_BASIC_FILENAME.value + ) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 678922767..edac9a51e 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -24,6 +24,7 @@ get_data_from_prod, DenatranType, ) + import pandas as pd import polars as pl from string_utils import asciify @@ -37,7 +38,7 @@ MONTHS = constants.MONTHS.value DATASET = constants.DATASET.value DICT_UFS = constants.DICT_UFS.value -OUTPUT_PATH = constants.OUTPUT_PATH.value +OUTPUT_PATH = "DENATRAN_FILES" MONTHS_SHORT = constants.MONTHS_SHORT.value UF_TIPO_BASIC_FILENAME = constants.UF_TIPO_BASIC_FILENAME.value MUNIC_TIPO_BASIC_FILENAME = constants.MUNIC_TIPO_BASIC_FILENAME.value diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index 65f8c3a74..9522c82ca 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -61,6 +61,12 @@ def guess_header( expected_header = MUNICIPIO_TIPO_HEADER else: raise ValueError("Unrecognized type of dataframe.") + current_header = [c for c in df.columns] + equal_column_names = [ + (x, y) for x, y in zip(expected_header, current_header) if x == y + ] + if len(equal_column_names) / len(expected_header) >= 0.6: + return -1 header_guess = 0 while header_guess < max_header_guess: if len(df) - 1 < header_guess: @@ -90,6 +96,8 @@ def change_df_header(df: pd.DataFrame, header_row: int) -> pd.DataFrame: Returns: pd.DataFrame: Returns the same dataframe but with the corrected header """ + if header_row == -1: + return df new_header = df.iloc[header_row] new_df = df[(header_row + 1) :].reset_index(drop=True) new_df.rename(columns=new_header, inplace=True) @@ -480,11 +488,11 @@ def call_r_to_read_excel(file: str) -> pd.DataFrame: """ if not os.path.isfile(file): raise ValueError("Invalid file") - packages = ("readxl",) - r_utils = rpackages.importr("utils", suppress_messages=True) - r_utils.chooseCRANmirror(ind=1) - r_utils.install_packages(StrVector(packages)) - rpackages.importr("readxl", suppress_messages=True) + # packages = ("readxl",) + # r_utils = rpackages.importr("utils", suppress_messages=True) + # r_utils.chooseCRANmirror(ind=1) + # r_utils.install_packages(StrVector(packages)) + # rpackages.importr("readxl", lib_loc="usr/lib/R/library", suppress_messages=True) # Read the Excel file robjects.r( @@ -499,6 +507,7 @@ def call_r_to_read_excel(file: str) -> pd.DataFrame: ) # Convert the R dataframe to a pandas dataframe df = robjects.r["df"] + df = pd.DataFrame(dict(zip(df.names, list(df)))) return df From b7f00abfb7180a296f48d0d24f5ef61fe5c6bfc9 Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Wed, 27 Sep 2023 13:57:30 -0300 Subject: [PATCH 238/265] pronto --- .gitignore | 1 + 1 file changed, 1 insertion(+) diff --git a/.gitignore b/.gitignore index 7665019ad..0c847e57d 100644 --- a/.gitignore +++ b/.gitignore @@ -155,3 +155,4 @@ notebooks/ .DS_Store +/DENATRAN_FILES \ No newline at end of file From 736722a821adac906cdb12bbbaefe39ea756b02b Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Fri, 29 Sep 2023 01:29:48 -0300 Subject: [PATCH 239/265] solucao --- pipelines/datasets/br_denatran_frota/utils.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index 9522c82ca..a93c29b54 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -445,8 +445,9 @@ def extraction_pre_2012(month: int, year: int, year_dir_name: str, zip_file: str return with ZipFile(zip_file, "r") as g: compressed_files = [file for file in g.infolist() if not file.is_dir()] - new_filename = None + for file in compressed_files: + new_filename = None filename = file.filename.split("/")[-1] if re.search("Tipo", filename, re.IGNORECASE) or re.search( r"Tipo[-\s]UF", zip_file.split("/")[-1] From 87ee5632a5818641c609aa2693ad05e17eac15a4 Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Sun, 29 Oct 2023 18:27:37 -0300 Subject: [PATCH 240/265] Bugged data --- pipelines/datasets/br_denatran_frota/handlers.py | 1 + 1 file changed, 1 insertion(+) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index edac9a51e..aea2aa290 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -106,6 +106,7 @@ def treat_uf_tipo(file: str) -> pl.DataFrame: ) # Now we get all the actual RELEVANT uf data. month, year = get_year_month_from_filename(filename) # If the df is all strings, try to get numbers where it makes sense. + clean_df.replace(" - ", 0, inplace=True) if all(clean_df.dtypes == "object"): clean_df = clean_df.apply(pd.to_numeric, errors="ignore") clean_pl_df = pl.from_pandas(clean_df).lazy() From 83704962f013bf7f8cc6eaa693a08932e324f9bd Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Mon, 6 Nov 2023 17:53:49 -0300 Subject: [PATCH 241/265] Escaneia e resolve colunas multiplicadas por 10 --- .../datasets/br_denatran_frota/handlers.py | 4 +-- pipelines/datasets/br_denatran_frota/utils.py | 34 ++++++++++++------- 2 files changed, 24 insertions(+), 14 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index aea2aa290..f0723216f 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -110,7 +110,7 @@ def treat_uf_tipo(file: str) -> pl.DataFrame: if all(clean_df.dtypes == "object"): clean_df = clean_df.apply(pd.to_numeric, errors="ignore") clean_pl_df = pl.from_pandas(clean_df).lazy() - verify_total(clean_pl_df.collect()) + clean_pl_df = verify_total(clean_pl_df.collect()) # Add year and month clean_pl_df = clean_pl_df.with_columns( pl.lit(year, dtype=pl.Int64).alias("ano"), @@ -200,7 +200,7 @@ def treat_municipio_tipo(file: str) -> pl.DataFrame: ) # Rename for ease of use. new_df.sigla_uf = new_df.sigla_uf.str.strip() # Remove whitespace. new_pl_df = pl.from_pandas(new_df) - verify_total(new_pl_df) + new_pl_df = verify_total(new_pl_df) new_pl_df = new_pl_df.with_columns( pl.col("nome_denatran").apply(asciify).str.to_lowercase(), pl.lit(year, dtype=pl.Int64).alias("ano"), diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index a93c29b54..9b064b530 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -140,7 +140,7 @@ def get_year_month_from_filename(filename: str) -> tuple[int, int]: raise ValueError("No match found") -def verify_total(df: pl.DataFrame) -> None: +def verify_total(df: pl.DataFrame) -> pl.DataFrame: """Verify that we can pivot from wide to long. Essentially, gets a Wide dataframe, excludes all string columns and the TOTAL column and sums it all row wise. @@ -169,28 +169,38 @@ def calculate_total(df): mask = df["TOTAL"] != calculated_total if sum(mask) != 0: - # In some cases, the quadriciclo data is multiplied by 10, and this will correct it before you - new_df = clean_quadriciclo_data(df) - new_calculated_total = calculate_total(new_df) - mask = new_df["TOTAL"] != new_calculated_total + # In some cases, one of the columsn in the data is multiplied by 10, and this will correct it before you + columns_to_try = df.select(pl.exclude("TOTAL")).select( + pl.exclude([pl.col(pl.Utf8)]) + ) + for col in columns_to_try.columns: + new_df = clean_dirty_data(df=df, column_name=col) + new_calculated_total = calculate_total(new_df) + mask = new_df["TOTAL"] != new_calculated_total + if pl.sum(mask) == 0: + return new_df if pl.sum(mask) != 0: raise ValueError( "A coluna de TOTAL da base original tem inconsistências e é diferente da soma das demais colunas." ) + else: + return df -def clean_quadriciclo_data(df: pl.DataFrame) -> pl.DataFrame: - """Divide the quadriciclo column by 10 when the data is dirty. +def clean_dirty_data( + df: pl.DataFrame, column_name: str = "QUADRICICLO" +) -> pl.DataFrame: + """Divide the column_name column by 10 when the data is dirty. Args: df (pl.DataFrame): Denatran data to be cleaned Returns: - pl.DataFrame: Cleaned Denatran data with the quadriciclo column altered. + pl.DataFrame: Cleaned Denatran data with the column_name column altered. """ - old_quadriciclo = df["QUADRICICLO"] - new_quadriciclo = old_quadriciclo / 10 - return df.with_columns(new_quadriciclo.cast(pl.Int32).alias("QUADRICICLO")) + old_column = df[column_name] + new_column = old_column / 10 + return df.with_columns(new_column.cast(pl.Int32).alias(column_name)) def fix_suggested_nome_ibge(row: tuple[str, ...]) -> str: @@ -413,7 +423,7 @@ def extract_links_post_2012(month: int, year: int, directory: str) -> list[dict] match = re.search( r"(?i)\/([\w-]+)\/(\d{4})\/(\w+)\/([\w-]+)\.(?:xls|xlsx|rar|zip)$", href ) - if match: + if match and re.search("tipo", txt, flags=re.IGNORECASE): matched_month = match.group(3) matched_year = match.group(2) if MONTHS.get(matched_month) == month and matched_year == str(year): From e411b8a6de8bdd250fb710f7cf76024cf14aad58 Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Mon, 6 Nov 2023 18:55:05 -0300 Subject: [PATCH 242/265] Pronto --- pipelines/datasets/br_denatran_frota/utils.py | 17 ++++++++++------- 1 file changed, 10 insertions(+), 7 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index 9b064b530..9b0ef7dcf 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -157,7 +157,9 @@ def verify_total(df: pl.DataFrame) -> pl.DataFrame: """ def calculate_total(df): - columns_for_total = df.select(pl.exclude("TOTAL")).select(pl.exclude([pl.Utf8])) + columns_for_total = df.select( + [col for col in df.columns if df[col].dtype != pl.Utf8] + ).select(pl.exclude("TOTAL")) calculated_total = columns_for_total.select( pl.fold( acc=pl.lit(0), function=lambda acc, x: acc + x, exprs=pl.col("*") @@ -168,18 +170,19 @@ def calculate_total(df): calculated_total = calculate_total(df) mask = df["TOTAL"] != calculated_total - if sum(mask) != 0: + if mask.sum() != 0: # In some cases, one of the columsn in the data is multiplied by 10, and this will correct it before you - columns_to_try = df.select(pl.exclude("TOTAL")).select( - pl.exclude([pl.col(pl.Utf8)]) - ) + columns_to_try = df.select( + [col for col in df.columns if df[col].dtype != pl.Utf8] + ).select(pl.exclude("TOTAL")) + for col in columns_to_try.columns: new_df = clean_dirty_data(df=df, column_name=col) new_calculated_total = calculate_total(new_df) mask = new_df["TOTAL"] != new_calculated_total - if pl.sum(mask) == 0: + if mask.sum() == 0: return new_df - if pl.sum(mask) != 0: + if mask.sum() != 0: raise ValueError( "A coluna de TOTAL da base original tem inconsistências e é diferente da soma das demais colunas." ) From 57385dc5f429daa444fdf5148bf3a2fd91d48389 Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Sun, 19 Nov 2023 19:10:11 -0300 Subject: [PATCH 243/265] All is good --- pipelines/datasets/br_denatran_frota/flows.py | 444 +++++++++--------- .../datasets/br_denatran_frota/handlers.py | 20 + pipelines/datasets/br_denatran_frota/tasks.py | 6 + pipelines/datasets/br_denatran_frota/utils.py | 4 +- 4 files changed, 254 insertions(+), 220 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index 93b87405a..879895d30 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -1,219 +1,227 @@ # -*- coding: utf-8 -*- -# """ -# Flows for br_denatran_frota -# """ - - -# from datetime import datetime, timedelta -# from prefect.run_configs import KubernetesRun -# from prefect.storage import GCS -# from prefect import Parameter, case, unmapped -# from prefect.tasks.prefect import ( -# create_flow_run, -# wait_for_flow_run, -# ) -# import os -# from pipelines.constants import constants as pipelines_constants -# from pipelines.utils.constants import constants as utils_constants - -# from pipelines.utils.decorators import Flow -# from pipelines.utils.execute_dbt_model.constants import constants as dump_db_constants -# from pipelines.utils.tasks import ( -# create_table_and_upload_to_gcs, -# rename_current_flow_run_dataset_table, -# get_current_flow_labels, -# ) -# from pipelines.datasets.br_denatran_frota.tasks import ( -# crawl_task, -# treat_uf_tipo_task, -# output_file_to_csv_task, -# get_desired_file_task, -# treat_municipio_tipo_task, -# get_latest_data_task, -# ) -# from pipelines.datasets.br_denatran_frota.constants import constants -# from itertools import product - -# year_range = list(range(2003, 2023)) -# month_range = list(range(1, 13)) -# date_pairs = list(product(year_range, month_range)) - -# date_pairs_param: list[tuple] = Parameter("date_pairs", default=date_pairs) - -# # from pipelines.datasets.br_denatran_frota.schedules import every_two_weeks - -# with Flow( -# name="br_denatran_frota.uf_tipo", -# code_owners=[ -# "Tamir", -# ], -# ) as br_denatran_frota_uf_tipo: -# dataset_id = Parameter("dataset_id", default="br_denatran_frota") -# table_id = Parameter("table_id", default="uf_tipo") - -# # Materialization mode -# materialization_mode = Parameter( -# "materialization_mode", default="dev", required=False -# ) - -# materialize_after_dump = Parameter( -# "materialize after dump", default=False, required=False -# ) - -# dbt_alias = Parameter("dbt_alias", default=True, required=False) -# rename_flow_run = rename_current_flow_run_dataset_table( -# prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id -# ) - -# year_to_fetch = get_latest_data_task("uf_tipo") -# crawled = crawl_task( -# month=year_to_fetch[1], -# year=year_to_fetch[0], -# temp_dir=constants.DOWNLOAD_PATH.value, -# upstream_tasks=[year_to_fetch], -# ) -# # Now get the downloaded file: -# municipio_tipo_file = get_desired_file_task( -# year=year_to_fetch[0], -# download_directory=constants.DOWNLOAD_PATH.value, -# filetype=constants.UF_TIPO_BASIC_FILENAME.value, -# upstream_tasks=[crawled], -# ) -# df = treat_uf_tipo_task( -# file=municipio_tipo_file, upstream_tasks=[crawled, municipio_tipo_file] -# ) -# csv_output = output_file_to_csv_task( -# df, constants.UF_TIPO_BASIC_FILENAME.value, upstream_tasks=[df] -# ) -# wait_upload_table = create_table_and_upload_to_gcs( -# data_path=csv_output, -# dataset_id=dataset_id, -# table_id=table_id, -# dump_mode="append", -# wait=csv_output, -# ) - -# with case(materialize_after_dump, True): -# # Trigger DBT flow run -# current_flow_labels = get_current_flow_labels() -# materialization_flow = create_flow_run( -# flow_name=utils_constants.FLOW_EXECUTE_DBT_MODEL_NAME.value, -# project_name=pipelines_constants.PREFECT_DEFAULT_PROJECT.value, -# parameters={ -# "dataset_id": dataset_id, -# "table_id": table_id, -# "mode": materialization_mode, -# "dbt_alias": dbt_alias, -# }, -# labels=current_flow_labels, -# run_name=f"Materialize {dataset_id}.{table_id}", -# ) -# wait_for_materialization = wait_for_flow_run( -# materialization_flow, -# stream_states=True, -# stream_logs=True, -# raise_final_state=True, -# ) -# wait_for_materialization.max_retries = ( -# dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_ATTEMPTS.value -# ) -# wait_for_materialization.retry_delay = timedelta( -# seconds=dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_INTERVAL.value -# ) - - -# br_denatran_frota_uf_tipo.storage = GCS(pipelines_constants.GCS_FLOWS_BUCKET.value) -# br_denatran_frota_uf_tipo.run_config = KubernetesRun( -# image=pipelines_constants.DOCKER_IMAGE.value -# ) -# # flow.schedule = every_two_weeks - - -# with Flow( -# name="br_denatran_frota.municipio_tipo", -# code_owners=[ -# "Tamir", -# ], -# ) as br_denatran_frota_municipio_tipo: -# dataset_id = Parameter("dataset_id", default="br_denatran_frota") -# table_id = Parameter("table_id", default="municipio_tipo") - -# # Materialization mode -# materialization_mode = Parameter( -# "materialization_mode", default="dev", required=False -# ) - -# materialize_after_dump = Parameter( -# "materialize after dump", default=False, required=False -# ) - -# dbt_alias = Parameter("dbt_alias", default=True, required=False) - -# rename_flow_run = rename_current_flow_run_dataset_table( -# prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id -# ) -# year_to_fetch = get_latest_data_task("municipio_tipo") -# crawled = crawl_task( -# month=year_to_fetch[1], -# year=year_to_fetch[0], -# temp_dir=constants.DOWNLOAD_PATH.value, -# upstream_tasks=[year_to_fetch], -# ) -# # Now get the downloaded file: -# municipio_tipo_file = get_desired_file_task( -# year=year_to_fetch[0], -# download_directory=constants.DOWNLOAD_PATH.value, -# filetype=constants.MUNIC_TIPO_BASIC_FILENAME.value, -# upstream_tasks=[crawled], -# ) -# df = treat_municipio_tipo_task( -# file=municipio_tipo_file, upstream_tasks=[crawled, municipio_tipo_file] -# ) -# csv_output = output_file_to_csv_task( -# df, constants.MUNIC_TIPO_BASIC_FILENAME.value, upstream_tasks=[df] -# ) -# wait_upload_table = create_table_and_upload_to_gcs( -# data_path=csv_output, -# dataset_id=dataset_id, -# table_id=table_id, -# dump_mode="append", -# wait=csv_output, -# ) - -# with case(materialize_after_dump, True): -# # Trigger DBT flow run -# current_flow_labels = get_current_flow_labels() -# materialization_flow = create_flow_run( -# flow_name=utils_constants.FLOW_EXECUTE_DBT_MODEL_NAME.value, -# project_name=pipelines_constants.PREFECT_DEFAULT_PROJECT.value, -# parameters={ -# "dataset_id": dataset_id, -# "table_id": table_id, -# "mode": materialization_mode, -# "dbt_alias": dbt_alias, -# }, -# labels=current_flow_labels, -# run_name=f"Materialize {dataset_id}.{table_id}", -# ) - -# wait_for_materialization = wait_for_flow_run( -# materialization_flow, -# stream_states=True, -# stream_logs=True, -# raise_final_state=True, -# ) -# wait_for_materialization.max_retries = ( -# dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_ATTEMPTS.value -# ) -# wait_for_materialization.retry_delay = timedelta( -# seconds=dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_INTERVAL.value -# ) - - -# br_denatran_frota_municipio_tipo.storage = GCS( -# pipelines_constants.GCS_FLOWS_BUCKET.value -# ) -# br_denatran_frota_municipio_tipo.run_config = KubernetesRun( -# image=pipelines_constants.DOCKER_IMAGE.value -# ) -# # flow.schedule = every_two_weeks +from datetime import datetime, timedelta +from prefect.run_configs import KubernetesRun +from prefect.storage import GCS +from prefect import Parameter, case, unmapped +from prefect.tasks.prefect import ( + create_flow_run, + wait_for_flow_run, +) +from pipelines.constants import constants as pipelines_constants +from pipelines.utils.constants import constants as utils_constants + +from pipelines.utils.decorators import Flow +from pipelines.utils.execute_dbt_model.constants import constants as dump_db_constants +from pipelines.utils.tasks import ( + create_table_and_upload_to_gcs, + rename_current_flow_run_dataset_table, + get_current_flow_labels, +) +from pipelines.datasets.br_denatran_frota.tasks import ( + crawl_task, + treat_uf_tipo_task, + output_file_to_csv_task, + get_desired_file_task, + treat_municipio_tipo_task, + get_latest_data_task, + should_process_data_task, +) +from pipelines.datasets.br_denatran_frota.constants import constants +from itertools import product + +year_range = list(range(2003, 2023)) +month_range = list(range(1, 13)) +date_pairs = list(product(year_range, month_range)) + +date_pairs_param: list[tuple] = Parameter("date_pairs", default=date_pairs) + +# from pipelines.datasets.br_denatran_frota.schedules import every_two_weeks + +with Flow( + name="br_denatran_frota.uf_tipo", + code_owners=[ + "Tamir", + ], +) as br_denatran_frota_uf_tipo: + dataset_id = Parameter("dataset_id", default="br_denatran_frota") + table_id = Parameter("table_id", default="uf_tipo") + + # Materialization mode + materialization_mode = Parameter( + "materialization_mode", default="dev", required=False + ) + + materialize_after_dump = Parameter( + "materialize after dump", default=False, required=False + ) + + dbt_alias = Parameter("dbt_alias", default=True, required=False) + rename_flow_run = rename_current_flow_run_dataset_table( + prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id + ) + + year_to_fetch = get_latest_data_task("uf_tipo") + crawled = crawl_task( + month=year_to_fetch[1], + year=year_to_fetch[0], + temp_dir=constants.DOWNLOAD_PATH.value, + upstream_tasks=[year_to_fetch], + ) + # Now get the downloaded file: + desired_file = get_desired_file_task( + year=year_to_fetch[0], + download_directory=constants.DOWNLOAD_PATH.value, + filetype=constants.UF_TIPO_BASIC_FILENAME.value, + upstream_tasks=[crawled], + ) + decision = should_process_data_task( + bq_year=year_to_fetch[0], + bq_month=year_to_fetch[1], + filename=desired_file, + upstream_tasks=[crawled, desired_file], + ) + with case(decision, True): + df = treat_uf_tipo_task( + file=desired_file, upstream_tasks=[crawled, desired_file] + ) + csv_output = output_file_to_csv_task( + df, constants.UF_TIPO_BASIC_FILENAME.value, upstream_tasks=[df] + ) + wait_upload_table = create_table_and_upload_to_gcs( + data_path=csv_output, + dataset_id=dataset_id, + table_id=table_id, + dump_mode="append", + wait=csv_output, + ) + + with case(materialize_after_dump, True): + # Trigger DBT flow run + current_flow_labels = get_current_flow_labels() + materialization_flow = create_flow_run( + flow_name=utils_constants.FLOW_EXECUTE_DBT_MODEL_NAME.value, + project_name=pipelines_constants.PREFECT_DEFAULT_PROJECT.value, + parameters={ + "dataset_id": dataset_id, + "table_id": table_id, + "mode": materialization_mode, + "dbt_alias": dbt_alias, + }, + labels=current_flow_labels, + run_name=f"Materialize {dataset_id}.{table_id}", + ) + wait_for_materialization = wait_for_flow_run( + materialization_flow, + stream_states=True, + stream_logs=True, + raise_final_state=True, + ) + wait_for_materialization.max_retries = ( + dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_ATTEMPTS.value + ) + wait_for_materialization.retry_delay = timedelta( + seconds=dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_INTERVAL.value + ) + + +br_denatran_frota_uf_tipo.storage = GCS(pipelines_constants.GCS_FLOWS_BUCKET.value) +br_denatran_frota_uf_tipo.run_config = KubernetesRun( + image=pipelines_constants.DOCKER_IMAGE.value +) +# flow.schedule = every_two_weeks + + +with Flow( + name="br_denatran_frota.municipio_tipo", + code_owners=[ + "Tamir", + ], +) as br_denatran_frota_municipio_tipo: + dataset_id = Parameter("dataset_id", default="br_denatran_frota") + table_id = Parameter("table_id", default="municipio_tipo") + + # Materialization mode + materialization_mode = Parameter( + "materialization_mode", default="dev", required=False + ) + + materialize_after_dump = Parameter( + "materialize after dump", default=False, required=False + ) + + dbt_alias = Parameter("dbt_alias", default=True, required=False) + + rename_flow_run = rename_current_flow_run_dataset_table( + prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id + ) + year_to_fetch = get_latest_data_task("municipio_tipo") + crawled = crawl_task( + month=year_to_fetch[1], + year=year_to_fetch[0], + temp_dir=constants.DOWNLOAD_PATH.value, + upstream_tasks=[year_to_fetch], + ) + # Now get the downloaded file: + desired_file = get_desired_file_task( + year=year_to_fetch[0], + download_directory=constants.DOWNLOAD_PATH.value, + filetype=constants.MUNIC_TIPO_BASIC_FILENAME.value, + upstream_tasks=[crawled], + ) + + decision = should_process_data_task( + bq_year=year_to_fetch[0], + bq_month=year_to_fetch[1], + filename=desired_file, + upstream_tasks=[crawled, desired_file], + ) + with case(decision, True): + df = treat_municipio_tipo_task(file=desired_file, upstream_tasks=[decision]) + csv_output = output_file_to_csv_task( + df, constants.MUNIC_TIPO_BASIC_FILENAME.value, upstream_tasks=[df] + ) + wait_upload_table = create_table_and_upload_to_gcs( + data_path=csv_output, + dataset_id=dataset_id, + table_id=table_id, + dump_mode="append", + wait=csv_output, + ) + + with case(materialize_after_dump, True): + # Trigger DBT flow run + current_flow_labels = get_current_flow_labels() + materialization_flow = create_flow_run( + flow_name=utils_constants.FLOW_EXECUTE_DBT_MODEL_NAME.value, + project_name=pipelines_constants.PREFECT_DEFAULT_PROJECT.value, + parameters={ + "dataset_id": dataset_id, + "table_id": table_id, + "mode": materialization_mode, + "dbt_alias": dbt_alias, + }, + labels=current_flow_labels, + run_name=f"Materialize {dataset_id}.{table_id}", + ) + + wait_for_materialization = wait_for_flow_run( + materialization_flow, + stream_states=True, + stream_logs=True, + raise_final_state=True, + ) + wait_for_materialization.max_retries = ( + dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_ATTEMPTS.value + ) + wait_for_materialization.retry_delay = timedelta( + seconds=dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_INTERVAL.value + ) + + +br_denatran_frota_municipio_tipo.storage = GCS( + pipelines_constants.GCS_FLOWS_BUCKET.value +) +br_denatran_frota_municipio_tipo.run_config = KubernetesRun( + image=pipelines_constants.DOCKER_IMAGE.value +) +# flow.schedule = every_two_weeks diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index f0723216f..41383390b 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -224,3 +224,23 @@ def treat_municipio_tipo(file: str) -> pl.DataFrame: value_name="quantidade", ) # Long format. return full_pl_df + + +def should_process_data(bq_year: int, bq_month: int, filename: str) -> bool: + """Verify if the crawled data is new enough to be uploaded. + + Args: + bq_year (int): Year gotten from get_latest_data, comes from BQ data. + bq_month (int): Month gotten from get_latest_data, comes from BQ data. + filename (str): Name of the DENATRAN data file downloaded. + + Returns: + bool: Whether or not the data obtained from the website is recent enough to be updated. + """ + crawled_year, crawled_month = get_year_month_from_filename(filename) + if crawled_year > bq_year or ( + crawled_year == bq_year and crawled_month >= bq_month + ): + return True + else: + return False diff --git a/pipelines/datasets/br_denatran_frota/tasks.py b/pipelines/datasets/br_denatran_frota/tasks.py index 4c348fc17..c217941b9 100644 --- a/pipelines/datasets/br_denatran_frota/tasks.py +++ b/pipelines/datasets/br_denatran_frota/tasks.py @@ -13,6 +13,7 @@ get_desired_file, treat_municipio_tipo, get_latest_data, + should_process_data, ) from pipelines.utils.utils import ( log, @@ -53,3 +54,8 @@ def treat_municipio_tipo_task(file: str) -> pl.DataFrame: @task() def get_latest_data_task(table_name: str) -> tuple[int, int]: return get_latest_data(table_name) + + +@task() +def should_process_data_task(bq_year: int, bq_month: int, filename: str) -> bool: + return should_process_data(bq_year, bq_month, filename) diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index 9b0ef7dcf..64f342f50 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -20,7 +20,7 @@ from rpy2.robjects.vectors import StrVector import basedosdados as bd from enum import Enum - +from datetime import datetime DICT_UFS = constants.DICT_UFS.value SUBSTITUTIONS = constants.SUBSTITUTIONS.value @@ -426,7 +426,7 @@ def extract_links_post_2012(month: int, year: int, directory: str) -> list[dict] match = re.search( r"(?i)\/([\w-]+)\/(\d{4})\/(\w+)\/([\w-]+)\.(?:xls|xlsx|rar|zip)$", href ) - if match and re.search("tipo", txt, flags=re.IGNORECASE): + if match and re.search("tipo|município", txt, flags=re.IGNORECASE): matched_month = match.group(3) matched_year = match.group(2) if MONTHS.get(matched_month) == month and matched_year == str(year): From abb6614ea2bd36fd0033dd434a32b0d70e0902ab Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Thu, 23 Nov 2023 19:49:33 -0300 Subject: [PATCH 244/265] =?UTF-8?q?Refaz=20o=20pre=20commit,=20que=20N?= =?UTF-8?q?=C3=83O=20funciona=20aqui.?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .pre-commit-config.yaml | 34 ++++++++++++++++++++++++++++++++++ 1 file changed, 34 insertions(+) create mode 100644 .pre-commit-config.yaml diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml new file mode 100644 index 000000000..776fb49e4 --- /dev/null +++ b/.pre-commit-config.yaml @@ -0,0 +1,34 @@ +repos: + - repo: https://github.com/pre-commit/pre-commit-hooks + rev: v4.5.0 + hooks: + - id: check-added-large-files # prevents adding large files + - id: detect-private-key # detects private keys + - id: fix-byte-order-marker # fixes BOM + - id: fix-encoding-pragma # fixes encoding pragma + - id: no-commit-to-branch # prevents committing to protected branches + - id: trailing-whitespace # prevents trailing whitespace + - repo: https://github.com/python-poetry/poetry + rev: 1.7.0 + hooks: + - id: poetry-check + - repo: https://github.com/psf/black + rev: 23.11.0 + hooks: + - id: black + exclude: 'pipelines\/\{\{cookiecutter\.project_name\}\}.*' + - repo: https://github.com/pycqa/isort + rev: 5.12.0 + hooks: + - id: isort + args: [--profile, black, --skip, "pipelines/{{cookiecutter.project_name}}"] + - repo: https://github.com/PyCQA/autoflake + rev: v2.2.1 + hooks: + - id: autoflake + exclude: 'pipelines\/\{\{cookiecutter\.project_name\}\}.*' + - repo: https://github.com/PyCQA/flake8 + rev: 6.1.0 + hooks: + - id: flake8 + exclude: 'pipelines\/\{\{cookiecutter\.project_name\}\}.*' \ No newline at end of file From f81b5871ae90b4c6b140c7fcb39db52309dd6736 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Thu, 23 Nov 2023 22:49:55 +0000 Subject: [PATCH 245/265] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- pipelines/datasets/__init__.py | 14 +------- .../datasets/br_denatran_frota/backfill.py | 4 +-- pipelines/datasets/br_denatran_frota/flows.py | 36 +++++++++---------- .../br_denatran_frota/functions_test.py | 11 +++--- .../datasets/br_denatran_frota/handlers.py | 35 +++++++++--------- .../datasets/br_denatran_frota/schedules.py | 4 ++- pipelines/datasets/br_denatran_frota/tasks.py | 18 +++++----- .../datasets/br_denatran_frota/tasks_test.py | 11 +++--- pipelines/datasets/br_denatran_frota/utils.py | 25 ++++++------- 9 files changed, 72 insertions(+), 86 deletions(-) diff --git a/pipelines/datasets/__init__.py b/pipelines/datasets/__init__.py index 6d608d615..1441b7df4 100644 --- a/pipelines/datasets/__init__.py +++ b/pipelines/datasets/__init__.py @@ -7,19 +7,6 @@ ############################################################################### from pipelines.datasets.botdosdados.flows import * -from pipelines.datasets.br_cgu_pessoal_executivo_federal.flows import * -from pipelines.datasets.fundacao_lemann.flows import * -from pipelines.datasets.br_tse_eleicoes.flows import * -from pipelines.datasets.delete_flows.flows import * -from pipelines.datasets.br_jota.flows import * -from pipelines.datasets.br_fgv_igp.flows import * -from pipelines.datasets.br_me_caged.flows import * -from pipelines.datasets.br_ibge_pnadc.flows import * -from pipelines.datasets.cross_update.flows import * -from pipelines.datasets.br_denatran_frota.flows import * -from pipelines.datasets.br_bcb_estban.flows import * -from pipelines.datasets.br_ms_cnes.flows import * -from pipelines.datasets.br_rj_isp_estatisticas_seguranca.flows import * from pipelines.datasets.br_anatel_banda_larga_fixa.flows import * from pipelines.datasets.br_anatel_telefonia_movel.flows import * from pipelines.datasets.br_anp_precos_combustiveis.flows import * @@ -37,6 +24,7 @@ from pipelines.datasets.br_cvm_administradores_carteira.flows import * from pipelines.datasets.br_cvm_fi.flows import * from pipelines.datasets.br_cvm_oferta_publica_distribuicao.flows import * +from pipelines.datasets.br_denatran_frota.flows import * from pipelines.datasets.br_fgv_igp.flows import * from pipelines.datasets.br_ibge_inpc.flows import * from pipelines.datasets.br_ibge_ipca15.flows import * diff --git a/pipelines/datasets/br_denatran_frota/backfill.py b/pipelines/datasets/br_denatran_frota/backfill.py index 3f2175169..75805a585 100644 --- a/pipelines/datasets/br_denatran_frota/backfill.py +++ b/pipelines/datasets/br_denatran_frota/backfill.py @@ -1,11 +1,11 @@ # -*- coding: utf-8 -*- +from pipelines.datasets.br_denatran_frota.constants import constants from pipelines.datasets.br_denatran_frota.handlers import ( crawl, - treat_uf_tipo, get_desired_file, output_file_to_csv, + treat_uf_tipo, ) -from pipelines.datasets.br_denatran_frota.constants import constants # Fill for UF TIPO months = range(1, 13) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index 879895d30..1613e1a27 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -1,33 +1,31 @@ # -*- coding: utf-8 -*- -from datetime import datetime, timedelta +from datetime import timedelta +from itertools import product + +from prefect import Parameter, case, unmapped from prefect.run_configs import KubernetesRun from prefect.storage import GCS -from prefect import Parameter, case, unmapped -from prefect.tasks.prefect import ( - create_flow_run, - wait_for_flow_run, -) +from prefect.tasks.prefect import create_flow_run, wait_for_flow_run + from pipelines.constants import constants as pipelines_constants +from pipelines.datasets.br_denatran_frota.constants import constants +from pipelines.datasets.br_denatran_frota.tasks import ( + crawl_task, + get_desired_file_task, + get_latest_data_task, + output_file_to_csv_task, + should_process_data_task, + treat_municipio_tipo_task, + treat_uf_tipo_task, +) from pipelines.utils.constants import constants as utils_constants - from pipelines.utils.decorators import Flow from pipelines.utils.execute_dbt_model.constants import constants as dump_db_constants from pipelines.utils.tasks import ( create_table_and_upload_to_gcs, - rename_current_flow_run_dataset_table, get_current_flow_labels, + rename_current_flow_run_dataset_table, ) -from pipelines.datasets.br_denatran_frota.tasks import ( - crawl_task, - treat_uf_tipo_task, - output_file_to_csv_task, - get_desired_file_task, - treat_municipio_tipo_task, - get_latest_data_task, - should_process_data_task, -) -from pipelines.datasets.br_denatran_frota.constants import constants -from itertools import product year_range = list(range(2003, 2023)) month_range = list(range(1, 13)) diff --git a/pipelines/datasets/br_denatran_frota/functions_test.py b/pipelines/datasets/br_denatran_frota/functions_test.py index 11657cdd2..c104b8b5c 100644 --- a/pipelines/datasets/br_denatran_frota/functions_test.py +++ b/pipelines/datasets/br_denatran_frota/functions_test.py @@ -3,16 +3,17 @@ import shutil import tempfile import unittest + import pandas as pd +from pipelines.datasets.br_denatran_frota.constants import constants +from pipelines.datasets.br_denatran_frota.tasks import crawl from pipelines.datasets.br_denatran_frota.utils import ( - make_filename, - make_dir_when_not_exists, - guess_header, get_year_month_from_filename, + guess_header, + make_dir_when_not_exists, + make_filename, ) -from pipelines.datasets.br_denatran_frota.constants import constants -from pipelines.datasets.br_denatran_frota.tasks import crawl DOWNLOAD_PATH = constants.DOWNLOAD_PATH.value diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 41383390b..501fbdc82 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -7,33 +7,30 @@ import os import re +from zipfile import ZipFile + import basedosdados as bd +import pandas as pd +import polars as pl +from string_utils import asciify + from pipelines.datasets.br_denatran_frota.constants import constants from pipelines.datasets.br_denatran_frota.utils import ( - make_dir_when_not_exists, - extract_links_post_2012, - verify_total, - change_df_header, - guess_header, - get_year_month_from_filename, + DenatranType, call_downloader, + call_r_to_read_excel, + change_df_header, download_file, + extract_links_post_2012, extraction_pre_2012, - call_r_to_read_excel, - treat_uf, get_data_from_prod, - DenatranType, -) - -import pandas as pd -import polars as pl -from string_utils import asciify -from zipfile import ZipFile -from pipelines.utils.utils import ( - clean_dataframe, - to_partitions, - log, + get_year_month_from_filename, + guess_header, + make_dir_when_not_exists, + treat_uf, + verify_total, ) +from pipelines.utils.utils import clean_dataframe, log, to_partitions MONTHS = constants.MONTHS.value DATASET = constants.DATASET.value diff --git a/pipelines/datasets/br_denatran_frota/schedules.py b/pipelines/datasets/br_denatran_frota/schedules.py index 7f39a37ac..5ae6b53bc 100644 --- a/pipelines/datasets/br_denatran_frota/schedules.py +++ b/pipelines/datasets/br_denatran_frota/schedules.py @@ -4,9 +4,11 @@ """ -from datetime import timedelta, datetime +from datetime import datetime, timedelta + from prefect.schedules import Schedule from prefect.schedules.clocks import IntervalClock + from pipelines.constants import constants every_two_weeks = Schedule( diff --git a/pipelines/datasets/br_denatran_frota/tasks.py b/pipelines/datasets/br_denatran_frota/tasks.py index c217941b9..e21845ef2 100644 --- a/pipelines/datasets/br_denatran_frota/tasks.py +++ b/pipelines/datasets/br_denatran_frota/tasks.py @@ -1,23 +1,21 @@ # -*- coding: utf-8 -*- -from prefect import task -import glob -import os -from pipelines.datasets.br_denatran_frota.constants import constants + import pandas as pd import polars as pl +from prefect import task + +from pipelines.datasets.br_denatran_frota.constants import constants from pipelines.datasets.br_denatran_frota.handlers import ( crawl, - treat_uf_tipo, - output_file_to_csv, get_desired_file, - treat_municipio_tipo, get_latest_data, + output_file_to_csv, should_process_data, + treat_municipio_tipo, + treat_uf_tipo, ) -from pipelines.utils.utils import ( - log, -) +from pipelines.utils.utils import log MONTHS = constants.MONTHS.value DATASET = constants.DATASET.value diff --git a/pipelines/datasets/br_denatran_frota/tasks_test.py b/pipelines/datasets/br_denatran_frota/tasks_test.py index a434ed96d..a2d73c50a 100644 --- a/pipelines/datasets/br_denatran_frota/tasks_test.py +++ b/pipelines/datasets/br_denatran_frota/tasks_test.py @@ -1,20 +1,21 @@ # -*- coding: utf-8 -*- import os +import re import shutil import tempfile import unittest -import re -import polars as pl +import polars as pl from parameterized import parameterized + +from pipelines.datasets.br_denatran_frota.constants import constants from pipelines.datasets.br_denatran_frota.handlers import ( crawl, - treat_uf_tipo, get_desired_file, - treat_municipio_tipo, get_latest_data, + treat_municipio_tipo, + treat_uf_tipo, ) -from pipelines.datasets.br_denatran_frota.constants import constants DATASET = constants.DATASET.value DOWNLOAD_PATH = constants.DOWNLOAD_PATH.value diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index 64f342f50..d320567ca 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -3,24 +3,25 @@ General purpose functions for the br_denatran_frota project. """ -import pandas as pd -import polars as pl import difflib -import re import os +import re +from enum import Enum +from urllib.request import urlopen from zipfile import ZipFile -from rarfile import RarFile + +import basedosdados as bd +import pandas as pd +import polars as pl import requests -from string_utils import asciify -from pipelines.datasets.br_denatran_frota.constants import constants -from bs4 import BeautifulSoup -from urllib.request import urlopen -import rpy2.robjects.packages as rpackages import rpy2.robjects as robjects +import rpy2.robjects.packages as rpackages +from bs4 import BeautifulSoup +from rarfile import RarFile from rpy2.robjects.vectors import StrVector -import basedosdados as bd -from enum import Enum -from datetime import datetime +from string_utils import asciify + +from pipelines.datasets.br_denatran_frota.constants import constants DICT_UFS = constants.DICT_UFS.value SUBSTITUTIONS = constants.SUBSTITUTIONS.value From 863fc057dc7c2fb8e2fa37143d2c1acbad78ffd7 Mon Sep 17 00:00:00 2001 From: Tamir Einhorn Salem Date: Thu, 23 Nov 2023 23:07:50 -0300 Subject: [PATCH 246/265] Usa a task pra decidir --- pipelines/datasets/br_denatran_frota/flows.py | 29 ++++++++++++------- pipelines/datasets/br_denatran_frota/tasks.py | 8 +++++ 2 files changed, 26 insertions(+), 11 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index 1613e1a27..625dc996f 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -17,10 +17,12 @@ should_process_data_task, treat_municipio_tipo_task, treat_uf_tipo_task, + get_denatran_date, ) from pipelines.utils.constants import constants as utils_constants from pipelines.utils.decorators import Flow from pipelines.utils.execute_dbt_model.constants import constants as dump_db_constants +from pipelines.utils.metadata.tasks import check_if_data_is_outdated from pipelines.utils.tasks import ( create_table_and_upload_to_gcs, get_current_flow_labels, @@ -72,11 +74,14 @@ filetype=constants.UF_TIPO_BASIC_FILENAME.value, upstream_tasks=[crawled], ) - decision = should_process_data_task( - bq_year=year_to_fetch[0], - bq_month=year_to_fetch[1], - filename=desired_file, - upstream_tasks=[crawled, desired_file], + # We need to see the year, month from the file to decide on updating + extracted_date = get_denatran_date(desired_file, upstream_tasks=[desired_file]) + decision = check_if_data_is_outdated( + dataset_id=dataset_id, + table_id=table_id, + data_source_max_date=extracted_date, + date_format="%Y-%m", + upstream_tasks=[extracted_date], ) with case(decision, True): df = treat_uf_tipo_task( @@ -166,12 +171,14 @@ filetype=constants.MUNIC_TIPO_BASIC_FILENAME.value, upstream_tasks=[crawled], ) - - decision = should_process_data_task( - bq_year=year_to_fetch[0], - bq_month=year_to_fetch[1], - filename=desired_file, - upstream_tasks=[crawled, desired_file], + # We need to see the year, month from the file to decide on updating + extracted_date = get_denatran_date(desired_file, upstream_tasks=[desired_file]) + decision = check_if_data_is_outdated( + dataset_id=dataset_id, + table_id=table_id, + data_source_max_date=extracted_date, + date_format="%Y-%m", + upstream_tasks=[extracted_date], ) with case(decision, True): df = treat_municipio_tipo_task(file=desired_file, upstream_tasks=[decision]) diff --git a/pipelines/datasets/br_denatran_frota/tasks.py b/pipelines/datasets/br_denatran_frota/tasks.py index e21845ef2..19af17c5c 100644 --- a/pipelines/datasets/br_denatran_frota/tasks.py +++ b/pipelines/datasets/br_denatran_frota/tasks.py @@ -4,6 +4,7 @@ import pandas as pd import polars as pl from prefect import task +import datetime from pipelines.datasets.br_denatran_frota.constants import constants from pipelines.datasets.br_denatran_frota.handlers import ( @@ -14,6 +15,7 @@ should_process_data, treat_municipio_tipo, treat_uf_tipo, + get_year_month_from_filename, ) from pipelines.utils.utils import log @@ -57,3 +59,9 @@ def get_latest_data_task(table_name: str) -> tuple[int, int]: @task() def should_process_data_task(bq_year: int, bq_month: int, filename: str) -> bool: return should_process_data(bq_year, bq_month, filename) + + +@task() +def get_denatran_date(filename: str) -> datetime.date: + year, month = get_year_month_from_filename(filename) + return datetime.date(year, month, 1) From 7d0bd15ebc4035e1624f3d207672964191b95e82 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Fri, 24 Nov 2023 02:08:12 +0000 Subject: [PATCH 247/265] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- pipelines/datasets/br_denatran_frota/flows.py | 2 +- pipelines/datasets/br_denatran_frota/tasks.py | 5 +++-- 2 files changed, 4 insertions(+), 3 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index 625dc996f..75137b1a8 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -11,13 +11,13 @@ from pipelines.datasets.br_denatran_frota.constants import constants from pipelines.datasets.br_denatran_frota.tasks import ( crawl_task, + get_denatran_date, get_desired_file_task, get_latest_data_task, output_file_to_csv_task, should_process_data_task, treat_municipio_tipo_task, treat_uf_tipo_task, - get_denatran_date, ) from pipelines.utils.constants import constants as utils_constants from pipelines.utils.decorators import Flow diff --git a/pipelines/datasets/br_denatran_frota/tasks.py b/pipelines/datasets/br_denatran_frota/tasks.py index 19af17c5c..9d97203df 100644 --- a/pipelines/datasets/br_denatran_frota/tasks.py +++ b/pipelines/datasets/br_denatran_frota/tasks.py @@ -1,21 +1,22 @@ # -*- coding: utf-8 -*- +import datetime + import pandas as pd import polars as pl from prefect import task -import datetime from pipelines.datasets.br_denatran_frota.constants import constants from pipelines.datasets.br_denatran_frota.handlers import ( crawl, get_desired_file, get_latest_data, + get_year_month_from_filename, output_file_to_csv, should_process_data, treat_municipio_tipo, treat_uf_tipo, - get_year_month_from_filename, ) from pipelines.utils.utils import log From 136da7b659aae36d2acf45678ae57aafa489dd59 Mon Sep 17 00:00:00 2001 From: folhesgabriel Date: Tue, 12 Dec 2023 12:38:56 -0300 Subject: [PATCH 248/265] feat: add update_django_metadata task --- pipelines/datasets/br_denatran_frota/flows.py | 39 +- .../datasets/br_denatran_frota/handlers.py | 3 + poetry.lock | 5053 +++++++---------- 3 files changed, 2009 insertions(+), 3086 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index 75137b1a8..b3a9282d4 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -22,7 +22,10 @@ from pipelines.utils.constants import constants as utils_constants from pipelines.utils.decorators import Flow from pipelines.utils.execute_dbt_model.constants import constants as dump_db_constants -from pipelines.utils.metadata.tasks import check_if_data_is_outdated +from pipelines.utils.metadata.tasks import ( + check_if_data_is_outdated, + update_django_metadata, +) from pipelines.utils.tasks import ( create_table_and_upload_to_gcs, get_current_flow_labels, @@ -55,6 +58,8 @@ "materialize after dump", default=False, required=False ) + update_metadata = Parameter("update_metadata", default=False, required=False) + dbt_alias = Parameter("dbt_alias", default=True, required=False) rename_flow_run = rename_current_flow_run_dataset_table( prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id @@ -126,6 +131,19 @@ seconds=dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_INTERVAL.value ) + with case(update_metadata, True): + update_django_metadata( + dataset_id=dataset_id, + table_id=table_id, + date_column_name={"year": "ano", "month": "mes"}, + date_format="%Y-%m", + coverage_type="all_free", + # time_delta={"months": 6}, + prefect_mode=materialization_mode, + bq_project="basedosdados", + upstream_tasks=[wait_for_materialization], + ) + br_denatran_frota_uf_tipo.storage = GCS(pipelines_constants.GCS_FLOWS_BUCKET.value) br_denatran_frota_uf_tipo.run_config = KubernetesRun( @@ -152,12 +170,18 @@ "materialize after dump", default=False, required=False ) + update_metadata = Parameter("update_metadata", default=False, required=False) + dbt_alias = Parameter("dbt_alias", default=True, required=False) rename_flow_run = rename_current_flow_run_dataset_table( prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id ) + + # inserir get_api_most_recente_date + # na função get_latest_data year_to_fetch = get_latest_data_task("municipio_tipo") + crawled = crawl_task( month=year_to_fetch[1], year=year_to_fetch[0], @@ -222,6 +246,19 @@ seconds=dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_INTERVAL.value ) + with case(update_metadata, True): + update_django_metadata( + dataset_id=dataset_id, + table_id=table_id, + date_column_name={"year": "ano", "month": "mes"}, + date_format="%Y-%m", + coverage_type="all_free", + # time_delta={"months": 6}, + prefect_mode=materialization_mode, + bq_project="basedosdados", + upstream_tasks=[wait_for_materialization], + ) + br_denatran_frota_municipio_tipo.storage = GCS( pipelines_constants.GCS_FLOWS_BUCKET.value diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 501fbdc82..ab8eaa6fb 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -150,6 +150,9 @@ def get_latest_data(table_name: str): denatran_data: 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pipelines/datasets/br_denatran_frota/utils.py | 4 +- 4 files changed, 56 insertions(+), 34 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index b3a9282d4..90b25fd7e 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -47,7 +47,7 @@ ], ) as br_denatran_frota_uf_tipo: dataset_id = Parameter("dataset_id", default="br_denatran_frota") - table_id = Parameter("table_id", default="uf_tipo") + table_id = Parameter("table_id", default="uf_tipo2") # Materialization mode materialization_mode = Parameter( @@ -65,7 +65,7 @@ prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id ) - year_to_fetch = get_latest_data_task("uf_tipo") + year_to_fetch = get_latest_data_task(table_id=table_id, dataset_id=dataset_id) crawled = crawl_task( month=year_to_fetch[1], year=year_to_fetch[0], @@ -159,7 +159,7 @@ ], ) as br_denatran_frota_municipio_tipo: dataset_id = Parameter("dataset_id", default="br_denatran_frota") - table_id = Parameter("table_id", default="municipio_tipo") + table_id = Parameter("table_id", default="municipio_tipo2") # Materialization mode materialization_mode = Parameter( @@ -180,7 +180,7 @@ # inserir get_api_most_recente_date # na função get_latest_data - year_to_fetch = get_latest_data_task("municipio_tipo") + year_to_fetch = get_latest_data_task(table_id=table_id, dataset_id=dataset_id) crawled = crawl_task( month=year_to_fetch[1], @@ -197,6 +197,7 @@ ) # We need to see the year, month from the file to decide on updating extracted_date = get_denatran_date(desired_file, upstream_tasks=[desired_file]) + decision = check_if_data_is_outdated( dataset_id=dataset_id, table_id=table_id, diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index ab8eaa6fb..1dbd34625 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -30,6 +30,7 @@ treat_uf, verify_total, ) +from pipelines.utils.metadata.utils import get_api_most_recent_date from pipelines.utils.utils import clean_dataframe, log, to_partitions MONTHS = constants.MONTHS.value @@ -146,40 +147,58 @@ def get_desired_file(year: int, download_directory: str, filetype: str) -> str: raise ValueError("No files found buckaroo") -def get_latest_data(table_name: str): - denatran_data: pd.DataFrame = get_data_from_prod( - table_id=table_name, dataset_id="br_denatran_frota" - ) +def get_latest_data(table_id: str, dataset_id: str): + # denatran_data: pd.DataFrame = get_data_from_prod( + # table_id=table_name, dataset_id="br_denatran_frota" + # ) # substituir por get_api_most_recente_date aqui # pipelines.utils.metadata.utils.get_api_most_recente_date # ela vai retonar a data mais recente da tabela extraida da api - if not isinstance(denatran_data, pd.DataFrame): - return 2003, 1 - if not denatran_data.empty: - log(denatran_data.head(2)) - year = denatran_data["ano"].max() - month = denatran_data.loc[denatran_data["ano"] == year]["mes"].max() - year = int(year) - month = int(month) - log(year) - log(type(year)) - log(month) - log(type(month)) - if month == 12: - year += 1 - month = 1 - else: - month += 1 - log(f"Ano: {year}, mês: {month}") - return year, month + denatran_data = get_api_most_recent_date( + table_id=table_id, dataset_id=dataset_id, date_format="%Y-%m" + ) + + log(f"{denatran_data}") + year = denatran_data.year + month = denatran_data.month + log(f"Ano: {year}, mês: {month}") + if month == 12: + year += 1 + month = 1 else: - log("Não achei ano não mané") - return 2003, 1 + month += 1 + log(f"Ano: {year}, mês: {month}") + return year, month + + # if not isinstance(denatran_data, pd.DataFrame): + # return 2003, 1 + # if not denatran_data.empty: + # log(denatran_data.head(2)) + # year = denatran_data["ano"].max() + # month = denatran_data.loc[denatran_data["ano"] == year]["mes"].max() + # year = int(year) + # month = int(month) + # log(year) + # log(type(year)) + # log(month) + # log(type(month)) + # if month == 12: + # year += 1 + # month = 1 + # else: + # month += 1 + # log(f"Ano: {year}, mês: {month}") + # return year, month + # else: + # log("Não achei ano não mané") + # return 2003, 1 def treat_municipio_tipo(file: str) -> pl.DataFrame: - bd_municipios = get_data_from_prod( - table_id="municipio", dataset_id="br_bd_diretorios_brasil" + bd_municipios = bd.read_sql( + "select * from `basedosdados.br_bd_diretorios_brasil.municipio`", + billing_project_id="basedosdados-dev", + # from_file=True, ) bd_municipios = pl.from_pandas(bd_municipios) diff --git a/pipelines/datasets/br_denatran_frota/tasks.py b/pipelines/datasets/br_denatran_frota/tasks.py index 9d97203df..1ace90099 100644 --- a/pipelines/datasets/br_denatran_frota/tasks.py +++ b/pipelines/datasets/br_denatran_frota/tasks.py @@ -53,8 +53,8 @@ def treat_municipio_tipo_task(file: str) -> pl.DataFrame: @task() -def get_latest_data_task(table_name: str) -> tuple[int, int]: - return get_latest_data(table_name) +def get_latest_data_task(table_id: str, dataset_id: str) -> tuple[int, int]: + return get_latest_data(table_id=table_id, dataset_id=dataset_id) @task() diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index d320567ca..c83e84642 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -22,6 +22,7 @@ from string_utils import asciify from pipelines.datasets.br_denatran_frota.constants import constants +from pipelines.utils.utils import log DICT_UFS = constants.DICT_UFS.value SUBSTITUTIONS = constants.SUBSTITUTIONS.value @@ -136,7 +137,8 @@ def get_year_month_from_filename(filename: str) -> tuple[int, int]: if match: month = match.group(2) year = match.group(3) - return month, year + log(f"{year} && {month}") + return int(year), int(month) else: raise ValueError("No match found") From f5685b6b7e1421be590bba943c5b5b525c042b73 Mon Sep 17 00:00:00 2001 From: folhesgabriel Date: Thu, 14 Dec 2023 14:41:53 -0300 Subject: [PATCH 250/265] feat: update branch --- .github/workflows/ci.yaml | 4 + .gitignore | 1 + .pre-commit-config.yaml | 2 +- pipelines/datasets/__init__.py | 1 + .../br_anp_precos_combustiveis/flows.py | 25 +- .../br_anp_precos_combustiveis/tasks.py | 43 +- .../br_anp_precos_combustiveis/utils.py | 6 +- pipelines/datasets/br_bcb_agencia/flows.py | 7 +- .../datasets/br_bcb_agencia/schedules.py | 2 +- pipelines/datasets/br_bcb_agencia/tasks.py | 33 +- pipelines/datasets/br_bcb_agencia/utils.py | 105 +--- pipelines/datasets/br_bcb_estban/constants.py | 24 +- pipelines/datasets/br_bcb_estban/flows.py | 40 +- pipelines/datasets/br_bcb_estban/tasks.py | 302 +++++++-- pipelines/datasets/br_bcb_estban/utils.py | 149 +---- .../br_camara_dados_abertos/__init__.py | 0 .../br_camara_dados_abertos/constants.py | 55 ++ .../datasets/br_camara_dados_abertos/flows.py | 586 ++++++++++++++++++ .../br_camara_dados_abertos/schedules.py | 54 ++ .../datasets/br_camara_dados_abertos/tasks.py | 89 +++ .../datasets/br_camara_dados_abertos/utils.py | 157 +++++ .../br_cgu_beneficios_cidadao/flows.py | 22 +- .../br_cgu_beneficios_cidadao/tasks.py | 48 +- .../br_cgu_beneficios_cidadao/utils.py | 74 +-- .../flows.py | 2 +- .../tasks.py | 16 +- .../br_cvm_administradores_carteira/tasks.py | 44 -- pipelines/datasets/br_me_cnpj/tasks.py | 5 +- .../br_mg_belohorizonte_smfa_iptu/flows.py | 28 +- .../schedules.py | 2 +- .../br_mg_belohorizonte_smfa_iptu/tasks.py | 24 +- .../br_mp_pep_cargos_funcoes/tasks.py | 12 +- pipelines/datasets/br_ms_cnes/flows.py | 15 +- pipelines/datasets/br_ms_cnes/tasks.py | 13 +- pipelines/datasets/br_ms_cnes/utils.py | 37 -- .../br_ons_avaliacao_operacao/flows.py | 42 +- .../br_ons_avaliacao_operacao/tasks.py | 89 +-- .../br_ons_avaliacao_operacao/utils.py | 4 +- .../br_ons_estimativa_custos/flows.py | 39 +- .../br_ons_estimativa_custos/tasks.py | 89 +-- .../br_ons_estimativa_custos/utils.py | 7 +- pipelines/datasets/br_rf_cafir/tasks.py | 2 - pipelines/datasets/br_rf_cafir/utils.py | 42 -- .../br_rj_isp_estatisticas_seguranca/flows.py | 16 +- .../schedules.py | 16 +- .../br_rj_isp_estatisticas_seguranca/tasks.py | 14 +- .../datasets/br_stf_corte_aberta/flows.py | 25 +- .../datasets/br_stf_corte_aberta/tasks.py | 21 +- .../datasets/br_stf_corte_aberta/utils.py | 63 -- pipelines/datasets/cross_update/flows.py | 134 +++- pipelines/datasets/cross_update/schedules.py | 18 +- pipelines/datasets/cross_update/tasks.py | 306 ++++----- pipelines/datasets/cross_update/utils.py | 180 +++++- .../constants.py | 24 + .../mundo_transfermarkt_competicoes/utils.py | 128 ++-- .../flows.py | 19 +- .../tasks.py | 30 +- .../apply_architecture_to_dataframe/utils.py | 2 + .../utils/crawler_ibge_inflacao/tasks.py | 24 +- .../utils/crawler_ibge_inflacao/utils.py | 40 -- pipelines/utils/dump_to_gcs/flows.py | 2 +- pipelines/utils/dump_to_gcs/tasks.py | 53 +- pipelines/utils/execute_dbt_model/tasks.py | 6 +- pipelines/utils/metadata/tasks.py | 13 +- pipelines/utils/metadata/utils.py | 25 +- poetry.lock | 146 ++--- pyproject.toml | 1 + 67 files changed, 2121 insertions(+), 1526 deletions(-) create mode 100644 pipelines/datasets/br_camara_dados_abertos/__init__.py create mode 100644 pipelines/datasets/br_camara_dados_abertos/constants.py create mode 100644 pipelines/datasets/br_camara_dados_abertos/flows.py create mode 100644 pipelines/datasets/br_camara_dados_abertos/schedules.py create mode 100644 pipelines/datasets/br_camara_dados_abertos/tasks.py create mode 100644 pipelines/datasets/br_camara_dados_abertos/utils.py diff --git a/.github/workflows/ci.yaml b/.github/workflows/ci.yaml index 9963281e4..d5bd3cb3b 100644 --- a/.github/workflows/ci.yaml +++ b/.github/workflows/ci.yaml @@ -2,6 +2,10 @@ name: CI on: pull_request: + types: + - opened + - synchronize + - reopened jobs: test: diff --git a/.gitignore b/.gitignore index 0c847e57d..789b6851a 100644 --- a/.gitignore +++ b/.gitignore @@ -1,6 +1,7 @@ # User defined **/data/ test.py +test.ipynb test_local.py pylint.txt diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 776fb49e4..293896665 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -18,7 +18,7 @@ repos: - id: black exclude: 'pipelines\/\{\{cookiecutter\.project_name\}\}.*' - repo: https://github.com/pycqa/isort - rev: 5.12.0 + rev: 5.13.0 hooks: - id: isort args: [--profile, black, --skip, "pipelines/{{cookiecutter.project_name}}"] diff --git a/pipelines/datasets/__init__.py b/pipelines/datasets/__init__.py index 1441b7df4..85816ef03 100644 --- a/pipelines/datasets/__init__.py +++ b/pipelines/datasets/__init__.py @@ -18,6 +18,7 @@ from pipelines.datasets.br_bcb_taxa_selic.flows import * from pipelines.datasets.br_bd_indicadores.flows import * from pipelines.datasets.br_bd_metadados.flows import * +from pipelines.datasets.br_camara_dados_abertos.flows import * from pipelines.datasets.br_cgu_beneficios_cidadao.flows import * from pipelines.datasets.br_cgu_pessoal_executivo_federal.flows import * from pipelines.datasets.br_cgu_servidores_executivo_federal.flows import * diff --git a/pipelines/datasets/br_anp_precos_combustiveis/flows.py b/pipelines/datasets/br_anp_precos_combustiveis/flows.py index 886a8661d..d5cc2a0c8 100644 --- a/pipelines/datasets/br_anp_precos_combustiveis/flows.py +++ b/pipelines/datasets/br_anp_precos_combustiveis/flows.py @@ -15,19 +15,20 @@ every_week_anp_microdados, ) from pipelines.datasets.br_anp_precos_combustiveis.tasks import ( - check_for_updates, download_and_transform, + get_data_source_anp_max_date, make_partitions, ) -from pipelines.datasets.br_anp_precos_combustiveis.utils import download_files from pipelines.utils.constants import constants as utils_constants from pipelines.utils.decorators import Flow from pipelines.utils.execute_dbt_model.constants import constants as dump_db_constants -from pipelines.utils.metadata.tasks import update_django_metadata +from pipelines.utils.metadata.tasks import ( + check_if_data_is_outdated, + update_django_metadata, +) from pipelines.utils.tasks import ( create_table_and_upload_to_gcs, get_current_flow_labels, - log_task, rename_current_flow_run_dataset_table, ) @@ -54,13 +55,15 @@ ) update_metadata = Parameter("update_metadata", default=True, required=False) - dados_desatualizados = check_for_updates(dataset_id=dataset_id, table_id=table_id) - log_task(f"Checando se os dados estão desatualizados: {dados_desatualizados}") - with case(dados_desatualizados, False): - log_task( - "Dados atualizados, não é necessário fazer o download", - upstream_tasks=[dados_desatualizados], - ) + data_source_max_date = get_data_source_anp_max_date() + + dados_desatualizados = check_if_data_is_outdated( + dataset_id=dataset_id, + table_id=table_id, + data_source_max_date=data_source_max_date, + date_format="%Y-%m-%d", + upstream_tasks=[data_source_max_date], + ) with case(dados_desatualizados, True): df = download_and_transform(upstream_tasks=[rename_flow_run]) diff --git a/pipelines/datasets/br_anp_precos_combustiveis/tasks.py b/pipelines/datasets/br_anp_precos_combustiveis/tasks.py index bdaed6213..fd6a403a2 100644 --- a/pipelines/datasets/br_anp_precos_combustiveis/tasks.py +++ b/pipelines/datasets/br_anp_precos_combustiveis/tasks.py @@ -5,13 +5,12 @@ from datetime import timedelta -import numpy as np import pandas as pd from prefect import task from pipelines.constants import constants from pipelines.datasets.br_anp_precos_combustiveis.constants import ( - constants as anatel_constants, + constants as anp_constants, ) from pipelines.datasets.br_anp_precos_combustiveis.utils import ( creating_column_ano, @@ -26,20 +25,13 @@ rename_and_to_create_endereco, rename_columns, ) -from pipelines.utils.utils import extract_last_date, log @task -def check_for_updates(dataset_id, table_id): - """ - Checks if there are available updates for a specific dataset and table. - - Returns: - bool: Returns True if updates are available, otherwise returns False. - """ +def get_data_source_anp_max_date(): # Obtém a data mais recente do site - download_files(anatel_constants.URLS_DATA.value, anatel_constants.PATH_INPUT.value) - df = pd.read_csv(anatel_constants.URL_GLP.value, sep=";", encoding="utf-8") + download_files(anp_constants.URLS_DATA.value, anp_constants.PATH_INPUT.value) + df = pd.read_csv(anp_constants.URL_GLP.value, sep=";", encoding="utf-8") data_obj = ( df["Data da Coleta"].str[6:10] + "-" @@ -50,20 +42,7 @@ def check_for_updates(dataset_id, table_id): data_obj = data_obj.apply(lambda x: pd.to_datetime(x).strftime("%Y-%m-%d")) data_obj = pd.to_datetime(data_obj, format="%Y-%m-%d").dt.date data_obj = data_obj.max() - # Obtém a última data no site BD - data_bq_obj = extract_last_date( - dataset_id, table_id, "yy-mm-dd", "basedosdados", data="data_coleta" - ) - - # Registra a data mais recente do site - log(f"Última data no site do ANP: {data_obj}") - log(f"Última data no site da BD: {data_bq_obj}") - - # Compara as datas para verificar se há atualizações - if data_obj > data_bq_obj: - return True # Há atualizações disponíveis - else: - return False # Não há novas atualizações disponíveis + return data_obj @task( @@ -71,12 +50,12 @@ def check_for_updates(dataset_id, table_id): retry_delay=timedelta(seconds=constants.TASK_RETRY_DELAY.value), ) def download_and_transform(): - download_files(anatel_constants.URLS.value, anatel_constants.PATH_INPUT.value) + download_files(anp_constants.URLS.value, anp_constants.PATH_INPUT.value) precos_combustiveis = open_csvs( - anatel_constants.URL_DIESEL_GNV.value, - anatel_constants.URL_GASOLINA_ETANOL.value, - anatel_constants.URL_GLP.value, + anp_constants.URL_DIESEL_GNV.value, + anp_constants.URL_GASOLINA_ETANOL.value, + anp_constants.URL_GLP.value, ) df = get_id_municipio(id_municipio=precos_combustiveis) @@ -108,6 +87,6 @@ def make_partitions(df): partition_data( df, column_name="data_coleta", - output_directory=anatel_constants.PATH_OUTPUT.value, + output_directory=anp_constants.PATH_OUTPUT.value, ) - return anatel_constants.PATH_OUTPUT.value + return anp_constants.PATH_OUTPUT.value diff --git a/pipelines/datasets/br_anp_precos_combustiveis/utils.py b/pipelines/datasets/br_anp_precos_combustiveis/utils.py index 7a4b2a970..00ab47d88 100644 --- a/pipelines/datasets/br_anp_precos_combustiveis/utils.py +++ b/pipelines/datasets/br_anp_precos_combustiveis/utils.py @@ -12,7 +12,7 @@ import unidecode from pipelines.datasets.br_anp_precos_combustiveis.constants import ( - constants as anatel_constants, + constants as anp_constants, ) from pipelines.utils.utils import log @@ -190,8 +190,8 @@ def creating_column_ano(precos_combustiveis: pd.DataFrame): def rename_and_reordening(precos_combustiveis: pd.DataFrame): - precos_combustiveis.rename(columns=anatel_constants.RENAME.value, inplace=True) - precos_combustiveis = precos_combustiveis[anatel_constants.ORDEM.value] + precos_combustiveis.rename(columns=anp_constants.RENAME.value, inplace=True) + precos_combustiveis = precos_combustiveis[anp_constants.ORDEM.value] return precos_combustiveis diff --git a/pipelines/datasets/br_bcb_agencia/flows.py b/pipelines/datasets/br_bcb_agencia/flows.py index bc0bbc94a..fa3c1d226 100644 --- a/pipelines/datasets/br_bcb_agencia/flows.py +++ b/pipelines/datasets/br_bcb_agencia/flows.py @@ -73,12 +73,13 @@ with case(check_if_outdated, True): log_task("Existem atualizações! A run será inciada") - temxpes = download_data( - link=agencia_constants.AGENCIA_URL.value, upstream_tasks=[check_if_outdated] + donwload_files = download_data( + dowload_url=data_source_max_date[0], + upstream_tasks=[check_if_outdated], ) filepath = clean_data( - upstream_tasks=[temxpes], + upstream_tasks=[donwload_files], ) wait_upload_table = create_table_and_upload_to_gcs( diff --git a/pipelines/datasets/br_bcb_agencia/schedules.py b/pipelines/datasets/br_bcb_agencia/schedules.py index adefec15b..9c4c19ebd 100644 --- a/pipelines/datasets/br_bcb_agencia/schedules.py +++ b/pipelines/datasets/br_bcb_agencia/schedules.py @@ -14,7 +14,7 @@ clocks=[ CronClock( cron="45 23 10-30 * *", # At 23:45 on every day-of-month from 10 through 30. - start_date=datetime(2023, 11, 28, 0, 0), + start_date=datetime(2023, 11, 30, 0, 0), labels=[ constants.BASEDOSDADOS_PROD_AGENT_LABEL.value, ], diff --git a/pipelines/datasets/br_bcb_agencia/tasks.py b/pipelines/datasets/br_bcb_agencia/tasks.py index 31aaaf76c..7f48126fe 100644 --- a/pipelines/datasets/br_bcb_agencia/tasks.py +++ b/pipelines/datasets/br_bcb_agencia/tasks.py @@ -5,6 +5,7 @@ import os +import time as tm from datetime import timedelta import basedosdados as bd @@ -45,19 +46,23 @@ def extract_most_recent_date(xpath, url): dicionario_data_url = {parse_date(url): url for url in url_list} tupla_data_maxima_url = max(dicionario_data_url.items(), key=lambda x: x[0]) data_maxima = tupla_data_maxima_url[0] - link_data_maxima = tupla_data_maxima_url[1] + url = tupla_data_maxima_url[1] + log(f"---- the most recent date is ->> {data_maxima}") + log(f"---- the select URL is ->> {url}") - return link_data_maxima, data_maxima + return url, data_maxima @task( max_retries=constants.TASK_MAX_RETRIES.value, retry_delay=timedelta(seconds=constants.TASK_RETRY_DELAY.value), ) -def download_data(link: str): +def download_data(dowload_url: str): # select the most recent link - current_link = "https://www.bcb.gov.br" + link + base_url = "https://www.bcb.gov.br" + + current_link = base_url + dowload_url log(f"Downloading file from: {current_link} ") download_and_unzip( @@ -67,6 +72,7 @@ def download_data(link: str): log( f"The file: {os.listdir(agencia_constants.DOWNLOAD_PATH_AGENCIA.value)} was downloaded" ) + tm.sleep(1.5) @task( @@ -84,7 +90,6 @@ def clean_data(): files = os.listdir(path) log(f"file is: {files}") # file = file[1] - log(f"file is: {files}") for file in files: # the files format change across the year @@ -95,7 +100,7 @@ def clean_data(): df = clean_column_names(df) # rename columns df.rename(columns=rename_cols(), inplace=True) - log(df.columns) + # fill left zeros with field range df["id_compe_bcb_agencia"] = ( df["id_compe_bcb_agencia"].astype(str).str.zfill(4) @@ -116,12 +121,12 @@ def clean_data(): # drop ddd column thats going to be added later df.drop(columns=["ddd"], inplace=True) log("ddd removed") - log(df.columns) + # some files doesnt have 'id_municipio', just 'nome'. # to add new ids is necessary to join by name # clean nome municipio - - df = clean_nome_municipio(df) + log("limpando nome muncipio") + df = clean_nome_municipio(df, "nome") municipio = bd.read_sql( query="select * from `basedosdados.br_bd_diretorios_brasil.municipio`", @@ -129,14 +134,12 @@ def clean_data(): ) municipio = municipio[["nome", "sigla_uf", "id_municipio", "ddd"]] - log("municipio dataset successfully downloaded!") - - municipio = clean_nome_municipio(municipio) + municipio = clean_nome_municipio(municipio, "nome") # check if id_municipio already exists + df["sigla_uf"] = df["sigla_uf"].str.strip() if "id_municipio" not in df.columns: # read municipio from bd datalake - # join id_municipio to df df = pd.merge( df, @@ -148,9 +151,6 @@ def clean_data(): # check if ddd already exists, if it doesnt, add it if "ddd" not in df.columns: - # - # read municipio from bd datalake - df = pd.merge( df, municipio[["id_municipio", "ddd"]], @@ -162,7 +162,6 @@ def clean_data(): # clean cep column df["cep"] = df["cep"].astype(str) df["cep"] = df["cep"].apply(remove_non_numeric_chars) - log("cep ok") # cnpj cleaning working df = create_cnpj_col(df) diff --git a/pipelines/datasets/br_bcb_agencia/utils.py b/pipelines/datasets/br_bcb_agencia/utils.py index 67bdcfaa3..65f74cd7a 100644 --- a/pipelines/datasets/br_bcb_agencia/utils.py +++ b/pipelines/datasets/br_bcb_agencia/utils.py @@ -21,8 +21,16 @@ # ---- functions to download data -# todo:colocar check no ano e mes def parse_date(url: str) -> datetime: + """This function parse the date of a br_bcb_agencia url + + Args: + url (str): URL of br_bcb_agencia extracted from https://www.bcb.gov.br/fis/info/agencias.asp?frame=1 + + Returns: + datetime: a date object + """ + padrao = re.compile(r"\d+") numeros = padrao.findall(url) @@ -91,10 +99,6 @@ def find_cnpj_row_number(file_path: str) -> int: return cnpj_row_number -# ! get_column_names deleted; -# ! count_list_values - - def get_conv_names(file_path: str, skiprows: str) -> dict: """get column names from a file to be used as a converter @@ -146,14 +150,14 @@ def read_file(file_path: str, file_name: str) -> pd.DataFrame: skiprows = find_cnpj_row_number(file_path=file_path) + 1 conv = get_conv_names(file_path=file_path, skiprows=skiprows) - df = pd.read_excel(file_path, skiprows=skiprows, converters=conv, skipfooter=1) + df = pd.read_excel(file_path, skiprows=skiprows, converters=conv, skipfooter=2) # todo: rethink logic. file_name param feeds another function create_year_month_cols df = create_year_month_cols(df=df, file=file_name) except Exception as e: log(e) conv = get_conv_names(file_path=file_path, skiprows=9) - df = pd.read_excel(file_path, skiprows=9, converters=conv) + df = pd.read_excel(file_path, skiprows=9, converters=conv, skipfooter=2) df = create_year_month_cols(df=df, file=file_name) return df @@ -169,21 +173,20 @@ def clean_column_names(df: pd.DataFrame) -> pd.DataFrame: DataFrame: a dataframe with cleaned columns """ # Remove leading and trailing whitespaces from column names + log("---- cleaning col names ----") df.columns = df.columns.str.strip() - print("colnames striped") + # Remove accents and special characters from column names df.columns = df.columns.map( lambda x: unicodedata.normalize("NFKD", x) .encode("ascii", "ignore") .decode("utf-8") ) - print("colnames cleaned 1") # Replace remaining special characters with underscores df.columns = df.columns.str.replace(r"[^\w\s]+", "_", regex=True) - print("colnames cleaned 2") # Lowercase all column names df.columns = df.columns.str.lower() - print("colnames to lower") + return df @@ -201,10 +204,12 @@ def create_year_month_cols(df: pd.DataFrame, file: str) -> pd.DataFrame: Returns: pd.DataFrame: a dataframe with month and year columns """ - print(f"{file}") + df["ano"] = file[0:4] df["mes"] = file[4:6] - print(f"year {file[0:4]} and month {file[4:6]} cols created") + log( + f" ---- creating ano and mes columns ----- ano {file[0:4]} mes {file[4:6]} cols created" + ) return df @@ -268,6 +273,7 @@ def order_cols(): "ano", "mes", "sigla_uf", + "nome", "id_municipio", "data_inicio", "cnpj", @@ -287,7 +293,7 @@ def order_cols(): return cols_order -def clean_nome_municipio(df: pd.DataFrame) -> pd.DataFrame: +def clean_nome_municipio(df: pd.DataFrame, col_name: str) -> pd.DataFrame: """perform cleaning operations on the municipio column Args: @@ -296,36 +302,17 @@ def clean_nome_municipio(df: pd.DataFrame) -> pd.DataFrame: Returns: pd.DataFrame: dataframe with municipio cleaned column """ - df["nome"] = df["nome"].apply( + df[col_name] = df[col_name].apply( lambda x: unicodedata.normalize("NFKD", str(x)) .encode("ascii", "ignore") .decode("utf-8") ) - df["nome"] = df["nome"].apply(lambda x: re.sub(r"[^\w\s]", "", x)) - df["nome"] = df["nome"].str.lower() - df["nome"] = df["nome"].str.strip() + df[col_name] = df[col_name].apply(lambda x: re.sub(r"[^\w\s]", "", x)) + df[col_name] = df[col_name].str.lower() + df[col_name] = df[col_name].str.strip() return df -def read_brazilian_municipallity_ids_from_base_dos_dados( - billing_id: str, -) -> pd.DataFrame: - """Download municipio table from base dos dados - - Args: - billing_id (str): BQ billing project id - - Returns: - pd.DataFrame: municipio table from base dos dados - """ - municipio = bd.read_table( - dataset_id="br_bd_diretorios_brasil", - table_id="municipio", - billing_project_id=billing_id, - ) - return municipio - - def remove_latin1_accents_from_df(df): for col in df.columns: df[col] = df[col].apply( @@ -414,51 +401,9 @@ def replace_nan_with_empty_set_coltypes_str(df: pd.DataFrame) -> pd.DataFrame: df (pd.DataFrame): a dataframe Returns: - pd.DataFrame: a datrafaame with all columns as strings and nan values as empty cels + pd.DataFrame: a datrafaame with all columns as strings and nan values representing null values """ for col in df.columns: df[col] = df[col].astype(str) df[col] = df[col].replace("nan", "") return df - - -# function copied from datasets.br_tse_eleicoes.utils -def get_data_from_prod(dataset_id: str, table_id: str, columns: list) -> list: - """ - Get select columns from a table in prod. - """ - - storage = bd.Storage(dataset_id=dataset_id, table_id=table_id) - blobs = list( - storage.client["storage_staging"] - .bucket("basedosdados-dev") - .list_blobs(prefix=f"staging/{storage.dataset_id}/{storage.table_id}/") - ) - - dfs = [] - - for blob in blobs: - partitions = re.findall(r"\w+(?==)", blob.name) - if len(set(partitions) & set(columns)) == 0: - df = pd.read_csv( - blob.public_url, - usecols=columns, - dtype={"id_municipio": str, "id_municipio_bcb": str, "ddd": str}, - ) - dfs.append(df) - else: - columns2add = list(set(partitions) & set(columns)) - for column in columns2add: - columns.remove(column) - df = pd.read_csv( - blob.public_url, - usecols=columns, - dtype={"id_municipio": str, "id_municipio_bcb": str}, - ) - for column in columns2add: - df[column] = blob.name.split(column + "=")[1].split("/")[0] - dfs.append(df) - - df = pd.concat(dfs) - - return df diff --git a/pipelines/datasets/br_bcb_estban/constants.py b/pipelines/datasets/br_bcb_estban/constants.py index 91a4585a7..6ede61f1e 100644 --- a/pipelines/datasets/br_bcb_estban/constants.py +++ b/pipelines/datasets/br_bcb_estban/constants.py @@ -8,9 +8,21 @@ class constants(Enum): # pylint: disable=c0103 ESTBAN_URL = "https://www4.bcb.gov.br/fis/cosif/estban.asp?frame=1" - AGENCIA_XPATH = '//*[@id="ESTBAN_AGENCIA"]' - MUNICIPIO_XPATH = '//*[@id="ESTBAN_MUNICIPIO"]' - DOWNLOAD_PATH_MUNICIPIO = "/tmp/input/municipio/" - DOWNLOAD_PATH_AGENCIA = "/tmp/input/agencia/" - CLEANED_FILES_PATH_MUNICIPIO = "/tmp/output/municipio/" - CLEANED_FILES_PATH_AGENCIA = "/tmp/output/agencia/" + ESTBAN_NEW_URL = "https://www.bcb.gov.br/estatisticas/estatisticabancariamunicipios" + + CSS_INPUT_FIELD_DICT = { + "municipio": "body > app-root > app-root > div > div > main > dynamic-comp > div > div:nth-child(5) > div:nth-child(1) > div > bcb-download-filter > div > ng-select > div > div > div.ng-input > input[type=text]", + "agencia": "body > app-root > app-root > div > div > main > dynamic-comp > div > div:nth-child(5) > div:nth-child(2) > div > bcb-download-filter > div > ng-select > div > div > div.ng-input > input[type=text]", + } + + CSS_DOWNLOAD_BUTTON = { + "municipio": "body > app-root > app-root > div > div > main > dynamic-comp > div > div:nth-child(5) > div:nth-child(1) > div > bcb-download-filter > div > button", + "agencia": "body > app-root > app-root > div > div > main > dynamic-comp > div > div:nth-child(5) > div:nth-child(2) > div > bcb-download-filter > div > button", + } + + ZIPFILE_PATH_MUNICIPIO = "/tmp/br_bcb_estban/municipio/zipfile" + ZIPFILE_PATH_AGENCIA = "/tmp/br_bcb_estban/agencia/zipfile" + INPUT_PATH_MUNICIPIO = "/tmp/br_bcb_estban/municipio/input" + INPUT_PATH_AGENCIA = "/tmp/br_bcb_estban/agencia/input" + OUTPUT_PATH_MUNICIPIO = "/tmp/br_bcb_estban/municipio/output/" + OUTPUT_PATH_AGENCIA = "/tmp/br_bcb_estban/agencia/output/" diff --git a/pipelines/datasets/br_bcb_estban/flows.py b/pipelines/datasets/br_bcb_estban/flows.py index d03ec06f4..692dc426b 100644 --- a/pipelines/datasets/br_bcb_estban/flows.py +++ b/pipelines/datasets/br_bcb_estban/flows.py @@ -21,8 +21,8 @@ from pipelines.datasets.br_bcb_estban.tasks import ( cleaning_agencias_data, cleaning_municipios_data, - download_estban_files, - extract_most_recent_date, + download_estban_selenium, + extract_last_date, get_id_municipio, ) from pipelines.utils.constants import constants as utils_constants @@ -64,16 +64,12 @@ prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id ) - data_source_max_date = extract_most_recent_date( - url=br_bcb_estban_constants.ESTBAN_URL.value, - xpath=br_bcb_estban_constants.MUNICIPIO_XPATH.value, - ) + data_source_max_date = extract_last_date(table_id=table_id) - # task check if is outdated check_if_outdated = check_if_data_is_outdated( dataset_id=dataset_id, table_id=table_id, - data_source_max_date=data_source_max_date[1], + data_source_max_date=data_source_max_date[0], date_format="%Y-%m", upstream_tasks=[data_source_max_date], ) @@ -83,15 +79,16 @@ with case(check_if_outdated, True): log_task("Existem atualizações! A run será inciada") - donwload_files = download_estban_files( - link=data_source_max_date[0], - save_path=br_bcb_estban_constants.DOWNLOAD_PATH_MUNICIPIO.value, + + donwload_files = download_estban_selenium( + save_path=br_bcb_estban_constants.ZIPFILE_PATH_MUNICIPIO.value, + table_id=table_id, + date=data_source_max_date[1], ) - municipio = get_id_municipio() + municipio = get_id_municipio(upstream_tasks=[donwload_files]) filepath = cleaning_municipios_data( - path=br_bcb_estban_constants.DOWNLOAD_PATH_MUNICIPIO.value, municipio=municipio, upstream_tasks=[donwload_files, municipio], ) @@ -177,16 +174,13 @@ prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id ) - data_source_max_date = extract_most_recent_date( - url=br_bcb_estban_constants.ESTBAN_URL.value, - xpath=br_bcb_estban_constants.AGENCIA_XPATH.value, - ) + data_source_max_date = extract_last_date(table_id=table_id) # task check if is outdated check_if_outdated = check_if_data_is_outdated( dataset_id=dataset_id, table_id=table_id, - data_source_max_date=data_source_max_date[1], + data_source_max_date=data_source_max_date[0], date_format="%Y-%m", upstream_tasks=[data_source_max_date], ) @@ -197,20 +191,20 @@ with case(check_if_outdated, True): log_task("Existem atualizações! A run será inciada") - donwload_files = download_estban_files( - link=data_source_max_date[0], - save_path=br_bcb_estban_constants.DOWNLOAD_PATH_MUNICIPIO.value, + donwload_files = download_estban_selenium( + save_path=br_bcb_estban_constants.ZIPFILE_PATH_AGENCIA.value, + table_id=table_id, + date=data_source_max_date[1], ) # read_file municipio = get_id_municipio() filepath = cleaning_agencias_data( - path=br_bcb_estban_constants.DOWNLOAD_PATH_AGENCIA.value, municipio=municipio, upstream_tasks=[donwload_files, municipio], ) - # 15/16/19/20 sao files problematicos + wait_upload_table = create_table_and_upload_to_gcs( data_path=filepath, dataset_id=dataset_id, diff --git a/pipelines/datasets/br_bcb_estban/tasks.py b/pipelines/datasets/br_bcb_estban/tasks.py index 1c5c0d287..b34d7950d 100644 --- a/pipelines/datasets/br_bcb_estban/tasks.py +++ b/pipelines/datasets/br_bcb_estban/tasks.py @@ -3,12 +3,23 @@ Tasks for br_bcb_estban """ +import datetime as dt import os +import zipfile from datetime import timedelta +from time import sleep import basedosdados as bd import pandas as pd +from bs4 import BeautifulSoup from prefect import task +from selenium import webdriver +from selenium.webdriver.chrome.service import Service as ChromeService +from selenium.webdriver.common.by import By +from selenium.webdriver.common.keys import Keys +from selenium.webdriver.support import expected_conditions as EC +from selenium.webdriver.support.ui import WebDriverWait +from webdriver_manager.chrome import ChromeDriverManager from pipelines.constants import constants from pipelines.datasets.br_bcb_estban.constants import ( @@ -19,14 +30,9 @@ create_id_municipio, create_id_verbete_column, create_month_year_columns, - download_and_unzip, - extract_download_links, - get_data_from_prod, order_cols_municipio, - parse_date, pre_cleaning_for_pivot_long_agencia, pre_cleaning_for_pivot_long_municipio, - read_files, rename_columns_agencia, rename_columns_municipio, standardize_monetary_units, @@ -36,29 +42,94 @@ from pipelines.utils.utils import clean_dataframe, log, to_partitions -@task( - max_retries=constants.TASK_MAX_RETRIES.value, - retry_delay=timedelta(seconds=constants.TASK_RETRY_DELAY.value), -) -def extract_most_recent_date(xpath, url): - # table date - url_list = extract_download_links(url=url, xpath=xpath) +@task +def extract_last_date(table_id: str) -> str: + """This task will extract the last date of agencias or municipios ESTBAN table from + BACEN website using selenium webdriver - dicionario_data_url = {parse_date(url): url for url in url_list} - tupla_data_maxima_url = max(dicionario_data_url.items(), key=lambda x: x[0]) - data_maxima = tupla_data_maxima_url[0] - link_data_maxima = tupla_data_maxima_url[1] + Args: + table_id (str): Table identifier (agencia or municipio) - return link_data_maxima, data_maxima + Returns: + str: The last release date of the table (Y%-m%) and the raw version (m%/%Y) + """ + options = webdriver.ChromeOptions() -@task( - max_retries=constants.TASK_MAX_RETRIES.value, - retry_delay=timedelta(seconds=constants.TASK_RETRY_DELAY.value), -) -def download_estban_files(save_path: str, link: str) -> str: - """This function downloads ESTBAN data from BACEN url, - unzip the csv files and return a path for the raw files + # https://github.com/SeleniumHQ/selenium/issues/11637 + prefs = { + "download.prompt_for_download": False, + "download.directory_upgrade": True, + "safebrowsing.enabled": True, + } + + options.add_experimental_option( + "prefs", + prefs, + ) + + options.add_argument("--headless=new") + # NOTE: The traditional --headless, and since version 96, Chrome has a new headless mode that allows users to get the full browser functionality (even run extensions). Between versions 96 to 108 it was --headless=chrome, after version 109 --headless=new + options.add_argument("--test-type") + options.add_argument("--disable-gpu") + options.add_argument("--no-first-run") + options.add_argument("--no-sandbox") + options.add_argument("--disable-dev-shm-usage") + options.add_argument("--no-default-browser-check") + options.add_argument("--ignore-certificate-errors") + options.add_argument("--start-maximized") + options.add_argument( + "user-agent=Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36" + ) + + driver = webdriver.Chrome( + service=ChromeService(ChromeDriverManager().install()), options=options + ) + + log("iniatilizing drivermanager") + log(f"using url {br_bcb_estban_constants.ESTBAN_NEW_URL.value}") + driver.get(br_bcb_estban_constants.ESTBAN_NEW_URL.value) + + # select input field and click on it + log( + f"searching for ---- {br_bcb_estban_constants.CSS_INPUT_FIELD_DICT.value[table_id]} to click on" + ) + input_field = WebDriverWait(driver, 20).until( + EC.element_to_be_clickable( + ( + By.CSS_SELECTOR, + br_bcb_estban_constants.CSS_INPUT_FIELD_DICT.value[table_id], + ) + ) + ) + + assert input_field.is_displayed() + + input_field.click() + + # parse source code + page_source = driver.page_source + + # find class ng-option ng-option-marked + soup = BeautifulSoup(page_source, "html.parser") + raw_date = soup.find("div", class_="ng-option ng-option-marked").get_text() + + # format it to %Y-%m + date = dt.datetime.strptime(raw_date, "%m/%Y").strftime("%Y-%m") + + log(f"The most recent file date is ->>>> {date}") + + # quit driver session + driver.quit() + + # return date, raw_date + return date, raw_date + + +@task +def download_estban_selenium(save_path: str, table_id: str, date: str) -> str: + """This function downloads ESTBAN data from BACEN url using selenium webdriver + and downloads it Args: @@ -68,12 +139,81 @@ def download_estban_files(save_path: str, link: str) -> str: str: The path to the estban files """ - file = "https://www4.bcb.gov.br" + link + if not os.path.exists(save_path): + os.makedirs(save_path, exist_ok=True) + + options = webdriver.ChromeOptions() - download_and_unzip(file, path=save_path) + # https://github.com/SeleniumHQ/selenium/issues/11637 + prefs = { + "download.default_directory": save_path, + "download.prompt_for_download": False, + "download.directory_upgrade": True, + "safebrowsing.enabled": True, + } + + options.add_experimental_option( + "prefs", + prefs, + ) + + options.add_argument("--headless=new") + options.add_argument("--test-type") + options.add_argument("--disable-gpu") + options.add_argument("--no-first-run") + options.add_argument("--no-sandbox") + options.add_argument("--disable-dev-shm-usage") + options.add_argument("--no-default-browser-check") + options.add_argument("--ignore-certificate-errors") + options.add_argument("--start-maximized") + options.add_argument( + "user-agent=Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36" + ) + log("iniatilizing drivermanager") + log(f"using url {br_bcb_estban_constants.ESTBAN_NEW_URL.value}") + + driver = webdriver.Chrome( + service=ChromeService(ChromeDriverManager().install()), options=options + ) + + driver.get(br_bcb_estban_constants.ESTBAN_NEW_URL.value) + driver.implicitly_wait(2) + + # select input field and send keys + log("looking for input field and sending keys") + input_field = WebDriverWait(driver, 20).until( + EC.element_to_be_clickable( + ( + By.CSS_SELECTOR, + br_bcb_estban_constants.CSS_INPUT_FIELD_DICT.value[table_id], + ) + ) + ) + + assert input_field.is_displayed() + + driver.execute_script("arguments[0].scrollIntoView();", input_field) + input_field.click() + input_field.send_keys(date) + input_field.send_keys(Keys.ENTER) + + log("looking for input field and sending keys") + # click button to download file + sleep(2) + download_button = WebDriverWait(driver, 20).until( + EC.element_to_be_clickable( + ( + By.CSS_SELECTOR, + br_bcb_estban_constants.CSS_DOWNLOAD_BUTTON.value[table_id], + ) + ) + ) + download_button.click() + # Sleep time to wait the download + sleep(12) log("download task successfully !") - log(f"files {os.listdir(save_path)} were downloaded and unzipped") + log(f"files {os.listdir(save_path)} were downloaded") return save_path @@ -98,30 +238,53 @@ def get_id_municipio() -> pd.DataFrame: # 2. clean data -@task( - max_retries=constants.TASK_MAX_RETRIES.value, - retry_delay=timedelta(seconds=constants.TASK_RETRY_DELAY.value), -) -def cleaning_municipios_data(path, municipio): +@task +def cleaning_municipios_data(municipio: pd.DataFrame) -> str: """Perform data cleaning operations with estban municipios data Args: df: a raw municipios estban dataset Returns: - df: a standardized partitioned estban dataset + str: file path to a standardized partitioned estban dataset """ + ZIP_PATH = br_bcb_estban_constants.ZIPFILE_PATH_MUNICIPIO.value + INPUT_PATH = br_bcb_estban_constants.INPUT_PATH_MUNICIPIO.value + OUTPUT_PATH = br_bcb_estban_constants.OUTPUT_PATH_MUNICIPIO.value + + log("building paths") + if not os.path.exists(INPUT_PATH): + os.makedirs(INPUT_PATH, exist_ok=True) - files = os.listdir(path) - log(f"the following files will be cleaned: {files}") + if not os.path.exists(OUTPUT_PATH): + os.makedirs(OUTPUT_PATH, exist_ok=True) - for file in files: + zip_files = os.listdir(ZIP_PATH) + log(f"unziping files ----> {zip_files}") + for file in zip_files: + if file.endswith(".csv.zip"): + log(f"Unziping file ----> : {file}") + with zipfile.ZipFile(os.path.join(ZIP_PATH, file), "r") as z: + z.extractall(INPUT_PATH) + + csv_files = os.listdir(INPUT_PATH) + + for file in csv_files: log(f"the file being cleaned is:{file}") - build_complete_file_path = os.path.join(path, file) + file_path = os.path.join(INPUT_PATH, file) - log(f"building {build_complete_file_path}") - df = read_files(build_complete_file_path) + log(f"building {file_path}") + + df = pd.read_csv( + file_path, + sep=";", + index_col=None, + encoding="latin-1", + skipfooter=2, + skiprows=2, + dtype={"CNPJ": str, "CODMUN": str}, + ) log("reading file") df = rename_columns_municipio(df) @@ -158,40 +321,61 @@ def cleaning_municipios_data(path, municipio): to_partitions( df, partition_columns=["ano", "mes", "sigla_uf"], - savepath=br_bcb_estban_constants.CLEANED_FILES_PATH_MUNICIPIO.value, + savepath=OUTPUT_PATH, ) del df - return br_bcb_estban_constants.CLEANED_FILES_PATH_MUNICIPIO.value + return OUTPUT_PATH -# 2. clean data -@task( - max_retries=constants.TASK_MAX_RETRIES.value, - retry_delay=timedelta(seconds=constants.TASK_RETRY_DELAY.value), -) -def cleaning_agencias_data(path, municipio): +@task +def cleaning_agencias_data(municipio: pd.DataFrame) -> str: """Perform data cleaning operations with estban municipios data Args: df: a raw municipios estban dataset Returns: - df: a standardized partitioned estban dataset + str: file path to a standardized partitioned estban dataset """ - # limit to 10 for testing purposes - # be aware, relie only in .csv files its not that good - # cause bacen can change file format - files = os.listdir(path) - log(f"the following files will be cleaned: {files}") + ZIP_PATH = br_bcb_estban_constants.ZIPFILE_PATH_AGENCIA.value + INPUT_PATH = br_bcb_estban_constants.INPUT_PATH_AGENCIA.value + OUTPUT_PATH = br_bcb_estban_constants.OUTPUT_PATH_AGENCIA.value + + log("building paths") + if not os.path.exists(INPUT_PATH): + os.makedirs(INPUT_PATH, exist_ok=True) + + if not os.path.exists(OUTPUT_PATH): + os.makedirs(OUTPUT_PATH, exist_ok=True) + + zip_files = os.listdir(ZIP_PATH) + log(f"unziping files ----> {zip_files}") + for file in zip_files: + if file.endswith(".csv.zip"): + log(f"Unziping file ----> : {file}") + with zipfile.ZipFile(os.path.join(ZIP_PATH, file), "r") as z: + z.extractall(INPUT_PATH) - for file in files: + csv_files = os.listdir(INPUT_PATH) + + for file in csv_files: log(f"the file being cleaned is:{file}") - build_complete_file_path = os.path.join(path, file) - log(f"building {build_complete_file_path}") - df = read_files(build_complete_file_path) + file_path = os.path.join(INPUT_PATH, file) + + log(f"building {file_path}") + + df = pd.read_csv( + file_path, + sep=";", + index_col=None, + encoding="latin-1", + skipfooter=2, + skiprows=2, + dtype={"CNPJ": str, "CODMUN": str}, + ) log("reading file") df = rename_columns_agencia(df) @@ -225,9 +409,9 @@ def cleaning_agencias_data(path, municipio): to_partitions( df, partition_columns=["ano", "mes", "sigla_uf"], - savepath=br_bcb_estban_constants.CLEANED_FILES_PATH_AGENCIA.value, + savepath=OUTPUT_PATH, ) del df - return br_bcb_estban_constants.CLEANED_FILES_PATH_AGENCIA.value + return OUTPUT_PATH diff --git a/pipelines/datasets/br_bcb_estban/utils.py b/pipelines/datasets/br_bcb_estban/utils.py index e8cb12b89..794d8a545 100644 --- a/pipelines/datasets/br_bcb_estban/utils.py +++ b/pipelines/datasets/br_bcb_estban/utils.py @@ -2,103 +2,13 @@ """ General purpose functions for the br_bcb_estban project """ -import os + import re -import unicodedata -from datetime import datetime -from io import BytesIO -from urllib.request import urlopen -from zipfile import ZipFile -import basedosdados as bd import numpy as np import pandas as pd -import requests -from lxml import html - -from pipelines.utils.utils import log - -# ------- macro etapa 1 download de dados -###### - - -# todo:colocar check no ano e mes -def parse_date(url: str) -> datetime: - padrao = re.compile(r"\d+") - - numeros = padrao.findall(url) - data = datetime(int(numeros[0][0:4]), int(numeros[0][4:6]), 1) - - return data - - -def extract_download_links(url, xpath): - """extract all download links from bcb agencias website - - Args: - url (str): bcb url https://www.bcb.gov.br/fis/info/agencias.asp?frame=1 - xpath (str): xpath which contais donwload links - - Returns: - list: a list of file links - """ - # Send a GET request to the URL - response = requests.get(url) - - # Parse the HTML content of the response using lxml - tree = html.fromstring(response.content) - - # Extract all the values from the given XPath - values = tree.xpath(xpath + "/option/@value") - - return values - - -def download_and_unzip(url, path): - """download and unzip a zip file - - Args: - url (str): a url - - - Returns: - list: unziped files in a given folder - """ - os.system(f"mkdir -p {path}") - http_response = urlopen(url) - zipfile = ZipFile(BytesIO(http_response.read())) - zipfile.extractall(path=path) - - return path - - -# ------- macro etapa 2 tratamento de dados -# --- read files -def read_files(path: str) -> pd.DataFrame: - """This function read a file from a given path - - Args: - path (str): a path to a file - - Returns: - pd.DataFrame: a dataframe with the file data - """ - df = pd.read_csv( - path, - sep=";", - index_col=None, - encoding="latin-1", - skipfooter=2, - skiprows=2, - dtype={"CNPJ": str, "CODMUN": str}, - ) - - return df - - -# ---1. rename columns def rename_columns_municipio(df: pd.DataFrame) -> pd.DataFrame: """this function rename columns from municipio dataframe @@ -138,12 +48,6 @@ def rename_columns_agencia(df: pd.DataFrame) -> pd.DataFrame: return df -# ---2 remove accents from a string -# clean_dataframe and remove_columns_accents from pipelines.utils.utils -# will be used -# change inputs - - def pre_cleaning_for_pivot_long_municipio(df: pd.DataFrame) -> pd.DataFrame: """This function drop and rename columns before the pivoting operation performed by the wide_to_long function. @@ -269,8 +173,7 @@ def wide_to_long_agencia(df: pd.DataFrame) -> pd.DataFrame: return df -# todo: to func:corrige unidades monetárias -def condicoes(database, valor) -> None: +def condicoes(database: str, valor: float) -> None: # cruzado if database <= 198812: return round(valor / (1000**2 * 2750), 6) @@ -288,7 +191,6 @@ def condicoes(database, valor) -> None: return round(valor, 0) -# todo: not str types. they're arrays i think def standardize_monetary_units( df: pd.DataFrame, date_column, value_column ) -> pd.DataFrame: @@ -308,7 +210,6 @@ def standardize_monetary_units( return df -# todo: to func:extrai os ids dos verbetes def create_id_verbete_column(df: pd.DataFrame, column_name: str) -> pd.DataFrame: """This function creates id_verbete column from a verbete column. It parses numeric digitis from the verbete column strings. @@ -327,13 +228,11 @@ def create_id_verbete_column(df: pd.DataFrame, column_name: str) -> pd.DataFrame return df -# todo: to func:criar ano e mes -# criar ano e mes def create_month_year_columns(df: pd.DataFrame, date_column: str) -> pd.DataFrame: """This function creates month and year columns from a date column. It Relies on the date column being a string in the format YYYYMM, where YYYY is the year and MM is the month. - # todo: introduce some kind of check to the date column from estban files + Args: df (pd.DataFrame): a ESTBAN municipios or agencia file @@ -393,45 +292,3 @@ def cols_order_agencia(df: pd.DataFrame) -> pd.DataFrame: df = df[order] return df - - -# function copied from datasets.br_tse_eleicoes.utils -def get_data_from_prod(dataset_id: str, table_id: str, columns: list) -> list: - """ - Get select columns from a table in prod. - """ - - storage = bd.Storage(dataset_id=dataset_id, table_id=table_id) - blobs = list( - storage.client["storage_staging"] - .bucket("basedosdados-dev") - .list_blobs(prefix=f"staging/{storage.dataset_id}/{storage.table_id}/") - ) - - dfs = [] - - for blob in blobs: - partitions = re.findall(r"\w+(?==)", blob.name) - if len(set(partitions) & set(columns)) == 0: - df = pd.read_csv( - blob.public_url, - usecols=columns, - dtype={"id_municipio": str, "id_municipio_bcb": str}, - ) - dfs.append(df) - else: - columns2add = list(set(partitions) & set(columns)) - for column in columns2add: - columns.remove(column) - df = pd.read_csv( - blob.public_url, - usecols=columns, - dtype={"id_municipio": str, "id_municipio_bcb": str}, - ) - for column in columns2add: - df[column] = blob.name.split(column + "=")[1].split("/")[0] - dfs.append(df) - - df = pd.concat(dfs) - - return df diff --git a/pipelines/datasets/br_camara_dados_abertos/__init__.py b/pipelines/datasets/br_camara_dados_abertos/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/pipelines/datasets/br_camara_dados_abertos/constants.py b/pipelines/datasets/br_camara_dados_abertos/constants.py new file mode 100644 index 000000000..f83d71d73 --- /dev/null +++ b/pipelines/datasets/br_camara_dados_abertos/constants.py @@ -0,0 +1,55 @@ +# -*- coding: utf-8 -*- +from enum import Enum + + +class constants(Enum): + TABLE_NAME_ARCHITECTURE = { + "votacao_proposicao_afetada": "https://docs.google.com/spreadsheets/d/1sHBdS7dgGAWlegMs1rEy6OwUVDwTLcZy92pFX6U5rXM/edit#gid=0", + "voto_parlamentar": "https://docs.google.com/spreadsheets/d/171Mykmg5qz54Kp35XgSD_IshngQHYE3jfGZ8yL-wEpE/edit#gid=0", + "votacao_microdados": "https://docs.google.com/spreadsheets/d/1GZjzBqAQ5RqaB6kyOjD7iZeKSPxB07lAkZnvaGjREIY/edit#gid=0", + "votacao_objeto": "https://docs.google.com/spreadsheets/d/1w2r5eK8jx3SwMTo83LKiI-wK_UE26SlTrJFqe_GZw4E/edit#gid=0", + "votacao_orientacao_bancada": "https://docs.google.com/spreadsheets/d/1_gl5llaGw5Mr0A6Q8AUoHHiOiEGl7Ht8Yf3p2n4k8uA/edit#gid=0", + } + + INPUT_PATH = "/tmp/input/" + OUTPUT_PATH = "/tmp/output/" + + ANOS = [2023] + + TABLE_LIST = { + "votacao_microdados": "votacoes", + "votacao_orientacao_bancada": "votacoesOrientacoes", + "voto_parlamentar": "votacoesVotos", + "votacao_objeto": "votacoesObjetos", + "votacao_proposicao_afetada": "votacoesProposicoes", + } + + RENAME_COLUMNS_OBJETO = { + "ano": "ano", + "idVotacao": "id_votacao", + "uriVotacao": "uriVotacao", + "data": "data", + "descricao": "descricao", + "proposicao_id": "id_proposicao", + "proposicao_uri": "proposicao_uri", + "proposicao_ementa": "ementa", + "proposicao_codTipo": "codigo_tipo", + "proposicao_siglaTipo": "sigla_tipo", + "proposicao_numero": "numero", + "proposicao_ano": "ano_proposicao", + "proposicao_titulo": "titulo", + } + + # ------------------------------------------------------------> DEPUTADOS + + TABLE_LIST_DEPUTADOS = { + "deputados": "deputados", + "deputado_ocupacao": "deputadosOcupacoes", + "deputado_profissao": "deputadosProfissoes", + } + + TABLE_NAME_ARCHITECTURE_DEPUTADOS = { + "deputados": "https://docs.google.com/spreadsheets/d/1qfcR5CyUxwa4423mtA8q_XAbgDOEFcPHtKmsg7ZpgyU/edit#gid=0", + "deputado_ocupacao": "https://docs.google.com/spreadsheets/d/1Cj6WE3jk63p21IjrINeaYKoMSOGoDDf1XpY3UH8sct4/edit#gid=0", + "deputado_profissao": "https://docs.google.com/spreadsheets/d/12R2OY7eqUKxuojcpYYBsCiHyzUOLBBdObnkuv2JUMNI/edit#gid=0", + } diff --git a/pipelines/datasets/br_camara_dados_abertos/flows.py b/pipelines/datasets/br_camara_dados_abertos/flows.py new file mode 100644 index 000000000..09c9a2afd --- /dev/null +++ b/pipelines/datasets/br_camara_dados_abertos/flows.py @@ -0,0 +1,586 @@ +# -*- coding: utf-8 -*- + +# register flow in prefect + +from datetime import timedelta + +from prefect import Parameter, case +from prefect.run_configs import KubernetesRun +from prefect.storage import GCS +from prefect.tasks.prefect import create_flow_run, wait_for_flow_run + +from pipelines.constants import constants +from pipelines.datasets.br_camara_dados_abertos.schedules import ( + every_day_camara_dados_abertos, + every_day_camara_dados_abertos_deputados, +) +from pipelines.datasets.br_camara_dados_abertos.tasks import ( + download_files_and_get_max_date, + download_files_and_get_max_date_deputados, + make_partitions, + treat_and_save_table, +) +from pipelines.utils.constants import constants as utils_constants +from pipelines.utils.decorators import Flow +from pipelines.utils.execute_dbt_model.constants import constants as dump_db_constants +from pipelines.utils.metadata.tasks import ( + check_if_data_is_outdated, + update_django_metadata, +) +from pipelines.utils.tasks import ( + create_table_and_upload_to_gcs, + get_current_flow_labels, + log_task, + rename_current_flow_run_dataset_table, +) + +with Flow(name="br_camara_dados_abertos.votacao", code_owners=["trick"]) as br_camara: + # Parameters + dataset_id = Parameter( + "dataset_id", default="br_camara_dados_abertos", required=True + ) + table_id = Parameter( + "table_id", + default=[ + "votacao_microdados", + "votacao_objeto", + "votacao_orientacao_bancada", + "voto_parlamentar", + "votacao_proposicao_afetada", + ], + required=True, + ) + + materialization_mode = Parameter( + "materialization_mode", default="prod", required=False + ) + materialize_after_dump = Parameter( + "materialize_after_dump", default=True, required=False + ) + dbt_alias = Parameter("dbt_alias", default=True, required=False) + + rename_flow_run = rename_current_flow_run_dataset_table( + prefix="Dump: ", + dataset_id=dataset_id, + table_id=table_id[0], + wait=table_id[0], + ) + + update_metadata = Parameter("update_metadata", default=True, required=False) + data_source_max_date = download_files_and_get_max_date() + + dados_desatualizados = check_if_data_is_outdated( + dataset_id=dataset_id, + table_id=table_id[0], + data_source_max_date=data_source_max_date, + date_format="%Y-%m-%d", + upstream_tasks=[data_source_max_date], + ) + + with case(dados_desatualizados, False): + log_task("Não há atualizações!") + + with case(dados_desatualizados, True): + # ! ---------------------------------------- > Votacao - Microdados + + filepath_microdados = make_partitions( + table_id="votacao_microdados", + date_column="data", + upstream_tasks=[rename_flow_run], + ) + wait_upload_table = create_table_and_upload_to_gcs( + data_path=filepath_microdados, + dataset_id=dataset_id, + table_id=table_id[0], + dump_mode="append", + wait=filepath_microdados, + ) + with case(materialize_after_dump, True): + # Trigger DBT flow run + current_flow_labels = get_current_flow_labels() + materialization_flow = create_flow_run( + flow_name=utils_constants.FLOW_EXECUTE_DBT_MODEL_NAME.value, + project_name=constants.PREFECT_DEFAULT_PROJECT.value, + parameters={ + "dataset_id": dataset_id, + "table_id": table_id[0], + "mode": materialization_mode, + "dbt_alias": dbt_alias, + }, + labels=current_flow_labels, + run_name=f"Materialize {dataset_id}.{table_id[0]}", + ) + + wait_for_materialization = wait_for_flow_run( + materialization_flow, + stream_states=True, + stream_logs=True, + raise_final_state=True, + ) + wait_for_materialization.max_retries = ( + dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_ATTEMPTS.value + ) + wait_for_materialization.retry_delay = timedelta( + seconds=dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_INTERVAL.value + ) + + with case(update_metadata, True): + update_django_metadata( + dataset_id, + table_id[0], + date_column_name={"date": "data"}, + date_format="%Y-%m-%d", + coverage_type="part_bdpro", + time_delta={"months": 6}, + prefect_mode=materialization_mode, + bq_project="basedosdados", + upstream_tasks=[wait_for_materialization], + ) + + # ! ---------------------------------------- > Votacao - objeto + + filepath_objeto = make_partitions( + table_id="votacao_objeto", + date_column="data", + upstream_tasks=[rename_flow_run], + ) + wait_upload_table = create_table_and_upload_to_gcs( + data_path=filepath_objeto, + dataset_id=dataset_id, + table_id=table_id[1], + dump_mode="append", + wait=filepath_objeto, + ) + with case(materialize_after_dump, True): + # Trigger DBT flow run + current_flow_labels = get_current_flow_labels() + materialization_flow = create_flow_run( + flow_name=utils_constants.FLOW_EXECUTE_DBT_MODEL_NAME.value, + project_name=constants.PREFECT_DEFAULT_PROJECT.value, + parameters={ + "dataset_id": dataset_id, + "table_id": table_id[1], + "mode": materialization_mode, + "dbt_alias": dbt_alias, + }, + labels=current_flow_labels, + run_name=f"Materialize {dataset_id}.{table_id[1]}", + ) + + wait_for_materialization = wait_for_flow_run( + materialization_flow, + stream_states=True, + stream_logs=True, + raise_final_state=True, + ) + wait_for_materialization.max_retries = ( + dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_ATTEMPTS.value + ) + wait_for_materialization.retry_delay = timedelta( + seconds=dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_INTERVAL.value + ) + + with case(update_metadata, True): + update_django_metadata( + dataset_id, + table_id[1], + date_column_name={"date": "data"}, + date_format="%Y-%m-%d", + coverage_type="part_bdpro", + time_delta={"months": 6}, + prefect_mode=materialization_mode, + bq_project="basedosdados", + upstream_tasks=[wait_for_materialization], + ) + + # ! ---------------------------------------- > Votacao - Parlamentar + + filepath_parlamentar = make_partitions( + table_id="voto_parlamentar", + date_column="dataHoraVoto", + upstream_tasks=[rename_flow_run], + ) + wait_upload_table = create_table_and_upload_to_gcs( + data_path=filepath_parlamentar, + dataset_id=dataset_id, + table_id=table_id[3], + dump_mode="append", + wait=filepath_parlamentar, + ) + with case(materialize_after_dump, True): + # Trigger DBT flow run + current_flow_labels = get_current_flow_labels() + materialization_flow = create_flow_run( + flow_name=utils_constants.FLOW_EXECUTE_DBT_MODEL_NAME.value, + project_name=constants.PREFECT_DEFAULT_PROJECT.value, + parameters={ + "dataset_id": dataset_id, + "table_id": table_id[3], + "mode": materialization_mode, + "dbt_alias": dbt_alias, + }, + labels=current_flow_labels, + run_name=f"Materialize {dataset_id}.{table_id[3]}", + ) + + wait_for_materialization = wait_for_flow_run( + materialization_flow, + stream_states=True, + stream_logs=True, + raise_final_state=True, + ) + wait_for_materialization.max_retries = ( + dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_ATTEMPTS.value + ) + wait_for_materialization.retry_delay = timedelta( + seconds=dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_INTERVAL.value + ) + + with case(update_metadata, True): + update_django_metadata( + dataset_id, + table_id[3], + date_column_name={"date": "data"}, + date_format="%Y-%m-%d", + coverage_type="part_bdpro", + time_delta={"months": 6}, + prefect_mode=materialization_mode, + bq_project="basedosdados", + upstream_tasks=[wait_for_materialization], + ) + + # ! ---------------------------------------- > Votacao - Proposicao + + filepath_proposicao = make_partitions( + table_id="votacao_proposicao_afetada", + date_column="data", + upstream_tasks=[rename_flow_run], + ) + wait_upload_table = create_table_and_upload_to_gcs( + data_path=filepath_proposicao, + dataset_id=dataset_id, + table_id=table_id[4], + dump_mode="append", + wait=filepath_proposicao, + ) + with case(materialize_after_dump, True): + # Trigger DBT flow run + current_flow_labels = get_current_flow_labels() + materialization_flow = create_flow_run( + flow_name=utils_constants.FLOW_EXECUTE_DBT_MODEL_NAME.value, + project_name=constants.PREFECT_DEFAULT_PROJECT.value, + parameters={ + "dataset_id": dataset_id, + "table_id": table_id[4], + "mode": materialization_mode, + "dbt_alias": dbt_alias, + }, + labels=current_flow_labels, + run_name=f"Materialize {dataset_id}.{table_id[4]}", + ) + + wait_for_materialization = wait_for_flow_run( + materialization_flow, + stream_states=True, + stream_logs=True, + raise_final_state=True, + ) + wait_for_materialization.max_retries = ( + dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_ATTEMPTS.value + ) + wait_for_materialization.retry_delay = timedelta( + seconds=dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_INTERVAL.value + ) + + with case(update_metadata, True): + update_django_metadata( + dataset_id, + table_id[4], + date_column_name={"date": "data"}, + date_format="%Y-%m-%d", + coverage_type="part_bdpro", + time_delta={"months": 6}, + prefect_mode=materialization_mode, + bq_project="basedosdados", + upstream_tasks=[wait_for_materialization], + ) + + # ! ---------------------------------------- > Votacao - Orientacao -- Não tem data + + filepath_orientacao = make_partitions( + table_id="votacao_orientacao_bancada", + date_column="data", + upstream_tasks=[rename_flow_run], + ) + wait_upload_table = create_table_and_upload_to_gcs( + data_path=filepath_orientacao, + dataset_id=dataset_id, + table_id=table_id[2], + dump_mode="append", + wait=filepath_orientacao, + ) + with case(materialize_after_dump, True): + # Trigger DBT flow run + current_flow_labels = get_current_flow_labels() + materialization_flow = create_flow_run( + flow_name=utils_constants.FLOW_EXECUTE_DBT_MODEL_NAME.value, + project_name=constants.PREFECT_DEFAULT_PROJECT.value, + parameters={ + "dataset_id": dataset_id, + "table_id": table_id[2], + "mode": materialization_mode, + "dbt_alias": dbt_alias, + }, + labels=current_flow_labels, + run_name=f"Materialize {dataset_id}.{table_id[2]}", + ) + + wait_for_materialization = wait_for_flow_run( + materialization_flow, + stream_states=True, + stream_logs=True, + raise_final_state=True, + ) + wait_for_materialization.max_retries = ( + dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_ATTEMPTS.value + ) + wait_for_materialization.retry_delay = timedelta( + seconds=dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_INTERVAL.value + ) + + # ! ---------------------------------------------------> Não tem data. Precisaremos usar o historical_database + with case(update_metadata, True): + update_django_metadata( + dataset_id, + table_id[2], + date_format="%Y-%m", + coverage_type="all_free", + time_delta={"months": 6}, + prefect_mode=materialization_mode, + bq_project="basedosdados", + historical_database=False, + upstream_tasks=[wait_for_materialization], + ) + +br_camara.storage = GCS(constants.GCS_FLOWS_BUCKET.value) +br_camara.run_config = KubernetesRun(image=constants.DOCKER_IMAGE.value) +br_camara.schedule = every_day_camara_dados_abertos + + +# --------------------------------------------------------------------------------------- +# --------------------------------------------------------------------------------------- +# --------------------------------------------------------------------------------------- + +# ------------------------------ TABLES DEPUTADOS --------------------------------------- + +with Flow( + name="br_camara_dados_abertos.deputado", code_owners=["trick"] +) as br_camara_deputado: + # Parameters + dataset_id = Parameter( + "dataset_id", default="br_camara_dados_abertos", required=True + ) + table_id = Parameter( + "table_id", + default=[ + "deputado", + "deputado_ocupacao", + "deputado_profissao", + ], + required=True, + ) + + materialization_mode = Parameter( + "materialization_mode", default="prod", required=False + ) + materialize_after_dump = Parameter( + "materialize_after_dump", default=True, required=False + ) + dbt_alias = Parameter("dbt_alias", default=True, required=False) + + rename_flow_run = rename_current_flow_run_dataset_table( + prefix="Dump: ", + dataset_id=dataset_id, + table_id=table_id[0], + wait=table_id[0], + ) + + update_metadata = Parameter("update_metadata", default=True, required=False) + data_source_max_date_deputado = download_files_and_get_max_date_deputados() + + dados_desatualizados = check_if_data_is_outdated( + dataset_id=dataset_id, + table_id=table_id[2], + data_source_max_date=data_source_max_date_deputado, + date_format="%Y-%m-%d", + upstream_tasks=[data_source_max_date_deputado], + ) + + with case(dados_desatualizados, False): + log_task("Não há atualizações!") + + with case(dados_desatualizados, True): + # --------------------------------------- > Deputados + + filepath_deputados = treat_and_save_table( + table_id="deputados", upstream_tasks=[rename_flow_run] + ) + wait_upload_table = create_table_and_upload_to_gcs( + data_path=filepath_deputados, + dataset_id=dataset_id, + table_id=table_id[0], + dump_mode="append", + wait=filepath_deputados, + ) + + with case(materialize_after_dump, True): + # Trigger DBT flow run + current_flow_labels = get_current_flow_labels() + materialization_flow = create_flow_run( + flow_name=utils_constants.FLOW_EXECUTE_DBT_MODEL_NAME.value, + project_name=constants.PREFECT_DEFAULT_PROJECT.value, + parameters={ + "dataset_id": dataset_id, + "table_id": table_id[0], + "mode": materialization_mode, + "dbt_alias": dbt_alias, + }, + labels=current_flow_labels, + run_name=f"Materialize {dataset_id}.{table_id[0]}", + ) + + wait_for_materialization = wait_for_flow_run( + materialization_flow, + stream_states=True, + stream_logs=True, + raise_final_state=True, + ) + wait_for_materialization.max_retries = ( + dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_ATTEMPTS.value + ) + wait_for_materialization.retry_delay = timedelta( + seconds=dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_INTERVAL.value + ) + + with case(update_metadata, True): + update_django_metadata( + dataset_id, + table_id[0], + coverage_type="all_free", + prefect_mode=materialization_mode, + bq_project="basedosdados", + historical_database=False, + upstream_tasks=[wait_for_materialization], + ) + + # ----------------------------------------------> Deputados - Ocupacao + + filepath_deputados_ocupacao = treat_and_save_table( + table_id="deputado_ocupacao", upstream_tasks=[filepath_deputados] + ) + wait_upload_table = create_table_and_upload_to_gcs( + data_path=filepath_deputados_ocupacao, + dataset_id=dataset_id, + table_id=table_id[1], + dump_mode="append", + wait=filepath_deputados_ocupacao, + ) + + with case(materialize_after_dump, True): + # Trigger DBT flow run + current_flow_labels = get_current_flow_labels() + materialization_flow = create_flow_run( + flow_name=utils_constants.FLOW_EXECUTE_DBT_MODEL_NAME.value, + project_name=constants.PREFECT_DEFAULT_PROJECT.value, + parameters={ + "dataset_id": dataset_id, + "table_id": table_id[1], + "mode": materialization_mode, + "dbt_alias": dbt_alias, + }, + labels=current_flow_labels, + run_name=f"Materialize {dataset_id}.{table_id[1]}", + ) + + wait_for_materialization = wait_for_flow_run( + materialization_flow, + stream_states=True, + stream_logs=True, + raise_final_state=True, + ) + wait_for_materialization.max_retries = ( + dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_ATTEMPTS.value + ) + wait_for_materialization.retry_delay = timedelta( + seconds=dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_INTERVAL.value + ) + + with case(update_metadata, True): + update_django_metadata( + dataset_id, + table_id[1], + coverage_type="all_free", + prefect_mode=materialization_mode, + bq_project="basedosdados", + historical_database=False, + upstream_tasks=[wait_for_materialization], + ) + + # ----------------------------------------------> Deputados - Profissão + + filepath_deputados_profissao = treat_and_save_table( + table_id="deputado_profissao", upstream_tasks=[filepath_deputados_ocupacao] + ) + wait_upload_table = create_table_and_upload_to_gcs( + data_path=filepath_deputados_profissao, + dataset_id=dataset_id, + table_id=table_id[2], + dump_mode="append", + wait=filepath_deputados_profissao, + ) + + with case(materialize_after_dump, True): + # Trigger DBT flow run + current_flow_labels = get_current_flow_labels() + materialization_flow = create_flow_run( + flow_name=utils_constants.FLOW_EXECUTE_DBT_MODEL_NAME.value, + project_name=constants.PREFECT_DEFAULT_PROJECT.value, + parameters={ + "dataset_id": dataset_id, + "table_id": table_id[2], + "mode": materialization_mode, + "dbt_alias": dbt_alias, + }, + labels=current_flow_labels, + run_name=f"Materialize {dataset_id}.{table_id[2]}", + ) + + wait_for_materialization = wait_for_flow_run( + materialization_flow, + stream_states=True, + stream_logs=True, + raise_final_state=True, + ) + wait_for_materialization.max_retries = ( + dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_ATTEMPTS.value + ) + wait_for_materialization.retry_delay = timedelta( + seconds=dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_INTERVAL.value + ) + + with case(update_metadata, True): + update_django_metadata( + dataset_id, + table_id[2], + date_format="%Y-%m-%d", + date_column_name={"date": "data"}, + coverage_type="all_free", + prefect_mode=materialization_mode, + bq_project="basedosdados", + historical_database=True, + upstream_tasks=[wait_for_materialization], + ) + +br_camara_deputado.storage = GCS(constants.GCS_FLOWS_BUCKET.value) +br_camara_deputado.run_config = KubernetesRun(image=constants.DOCKER_IMAGE.value) +br_camara_deputado.schedule = every_day_camara_dados_abertos_deputados diff --git a/pipelines/datasets/br_camara_dados_abertos/schedules.py b/pipelines/datasets/br_camara_dados_abertos/schedules.py new file mode 100644 index 000000000..252544482 --- /dev/null +++ b/pipelines/datasets/br_camara_dados_abertos/schedules.py @@ -0,0 +1,54 @@ +# -*- coding: utf-8 -*- +from datetime import datetime + +from prefect.schedules import Schedule +from prefect.schedules.clocks import CronClock + +from pipelines.constants import constants + +every_day_camara_dados_abertos = Schedule( + clocks=[ + CronClock( + cron="0 9 * * *", # every day at 9:00 UTC + start_date=datetime(2021, 1, 1), + labels=[constants.BASEDOSDADOS_PROD_AGENT_LABEL.value], + parameter_defaults={ + "update_metadata": True, + "dbt_alias": True, + "materialize_after_dump": True, + "materialization_mode": "prod", + "table_id": [ + "votacao_microdados", + "votacao_objeto", + "votacao_orientacao_bancada", + "voto_parlamentar", + "votacao_proposicao_afetada", + ], + "dataset_id": "br_camara_dados_abertos", + }, + ), + ], +) + + +every_day_camara_dados_abertos_deputados = Schedule( + clocks=[ + CronClock( + cron="30 9 * * *", # every day at 9:00 UTC + start_date=datetime(2021, 1, 1), + labels=[constants.BASEDOSDADOS_PROD_AGENT_LABEL.value], + parameter_defaults={ + "update_metadata": True, + "dbt_alias": True, + "materialize_after_dump": True, + "materialization_mode": "prod", + "table_id": [ + "deputado", + "deputado_ocupacao", + "deputado_profissao", + ], + "dataset_id": "br_camara_dados_abertos", + }, + ), + ], +) diff --git a/pipelines/datasets/br_camara_dados_abertos/tasks.py b/pipelines/datasets/br_camara_dados_abertos/tasks.py new file mode 100644 index 000000000..f3502bcf6 --- /dev/null +++ b/pipelines/datasets/br_camara_dados_abertos/tasks.py @@ -0,0 +1,89 @@ +# -*- coding: utf-8 -*- +import os +from datetime import timedelta + +import pandas as pd +from prefect import task + +from pipelines.constants import constants +from pipelines.datasets.br_camara_dados_abertos.constants import ( + constants as constants_camara, +) +from pipelines.datasets.br_camara_dados_abertos.utils import ( + get_data, + get_data_deputados, + read_and_clean_camara_dados_abertos, + read_and_clean_data_deputados, +) +from pipelines.utils.utils import log, to_partitions + + +# ! Microdados +@task +def make_partitions(table_id, date_column) -> str: + """ + Make partitions for a given table based on a date column. + + Args: + table_id (str): The ID of the table. + date_column (str): The name of the date column. + + Returns: + str: The path where the partitions are saved. + """ + df = read_and_clean_camara_dados_abertos( + path=constants_camara.INPUT_PATH.value, + table_id=f"{table_id}", + date_column=date_column, + ) + log(f"particionando {table_id}") + to_partitions( + data=df, + partition_columns=["ano"], + savepath=f"{constants_camara.OUTPUT_PATH.value}/{table_id}/", + ) + + return f"{constants_camara.OUTPUT_PATH.value}/{table_id}/" + + +# ! Obtendo a data máxima. +@task +def download_files_and_get_max_date(): + df = get_data() + data_max = df["data"].max() + + return data_max + + +# -------------------------------------------------------------------> Deputados +@task +def download_files_and_get_max_date_deputados(): + df = get_data_deputados() + + df["dataHora"] = pd.to_datetime(df["dataHora"]) + + data_max = df["dataHora"].max() + + return data_max + + +@task( + max_retries=constants.TASK_MAX_RETRIES.value, + retry_delay=timedelta(seconds=constants.TASK_RETRY_DELAY.value), +) +def treat_and_save_table(table_id): + log(f"------------- TRATANDO {table_id} --------------") + df = read_and_clean_data_deputados(table_id=table_id) + + if not os.path.exists(f"{constants_camara.OUTPUT_PATH.value}{table_id}"): + os.makedirs(f"{constants_camara.OUTPUT_PATH.value}{table_id}") + + log(f"Saving {table_id} to {constants_camara.OUTPUT_PATH.value}{table_id}/data.csv") + + df.to_csv( + f"{constants_camara.OUTPUT_PATH.value}{table_id}/data.csv", sep=",", index=False + ) + + log(f"{constants_camara.OUTPUT_PATH.value}{table_id}/data.csv") + + return f"{constants_camara.OUTPUT_PATH.value}{table_id}/data.csv" diff --git a/pipelines/datasets/br_camara_dados_abertos/utils.py b/pipelines/datasets/br_camara_dados_abertos/utils.py new file mode 100644 index 000000000..6fb677dce --- /dev/null +++ b/pipelines/datasets/br_camara_dados_abertos/utils.py @@ -0,0 +1,157 @@ +# -*- coding: utf-8 -*- +import os + +import pandas as pd +import requests + +from pipelines.datasets.br_camara_dados_abertos.constants import constants +from pipelines.utils.apply_architecture_to_dataframe.utils import ( + apply_architecture_to_dataframe, +) +from pipelines.utils.utils import log + + +# -------------------------------------------------------------------------------------> VOTACAO +def download_csvs_camara() -> None: + """ + Docs: + This function does download all csvs from archives of camara dos deputados. + The csvs saved in conteiners of docker. + + return: + None + """ + log("Downloading csvs from camara dos deputados") + if not os.path.exists(constants.INPUT_PATH.value): + os.makedirs(constants.INPUT_PATH.value) + + for ano in constants.ANOS.value: + for chave, valor in constants.TABLE_LIST.value.items(): + url = f"http://dadosabertos.camara.leg.br/arquivos/{valor}/csv/{valor}-{ano}.csv" + + response = requests.get(url) + + if response.status_code == 200: + with open(f"{constants.INPUT_PATH.value}{valor}.csv", "wb") as f: + f.write(response.content) + elif response.status_code >= 400 and response.status_code <= 599: + raise Exception( + f"Erro de requisição: status code {response.status_code}" + ) + + log("------------- archive inside in container --------------") + log(os.listdir(constants.INPUT_PATH.value)) + + +def get_data(): + download_csvs_camara() + df = pd.read_csv( + f'{constants.INPUT_PATH.value}{constants.TABLE_LIST.value["votacao_microdados"]}.csv', + sep=";", + ) + + return df + + +def read_and_clean_camara_dados_abertos( + table_id=str, path=constants.INPUT_PATH.value, date_column=str +) -> pd.DataFrame: + """ + Lê e limpa os dados abertos da câmara. + + Esta função lê um arquivo CSV de um caminho específico, adiciona uma coluna "ano" ao DataFrame e aplica uma arquitetura específica ao DataFrame com base no ID da tabela. + + Parâmetros: + table_id (str): ID da tabela para determinar a arquitetura a ser aplicada. + path (str): Caminho para o arquivo CSV a ser lido. + date_column (str): Nome da coluna que contém a data. + + Retorna: + pd.DataFrame: DataFrame após a aplicação da arquitetura. + """ + df = pd.read_csv(f"{path}{constants.TABLE_LIST.value[table_id]}.csv", sep=";") + + if table_id == "votacao_orientacao_bancada": + df["ano"] = constants.ANOS.value[0] + else: + df["ano"] = df[date_column].str[0:4] + + log("------------- columns before apply architecture --------------") + log(f"------------- TABLE ---------------- {table_id} --------------") + log(df.columns) + if table_id == "votacao_objeto": + df.rename(columns=constants.RENAME_COLUMNS_OBJETO.value, inplace=True) + df = df[constants.RENAME_COLUMNS_OBJETO.value.values()] + + else: + df = apply_architecture_to_dataframe( + df, + url_architecture=constants.TABLE_NAME_ARCHITECTURE.value[table_id], + apply_include_missing_columns=False, + apply_column_order_and_selection=True, + apply_rename_columns=True, + ) + log("------------- columns after apply architecture --------------") + log(f"------------- TABLE ---------------- {table_id} ------------") + log(df.columns) + return df + + +# ------------------------------------------------------------> DEPUTADOS + + +def download_csvs_camara_deputado() -> None: + """ + Docs: + This function does download all csvs from archives of camara dos deputados. + The csvs saved in conteiners of docker. + + return: + None + """ + print("Downloading csvs from camara dos deputados") + if not os.path.exists(constants.INPUT_PATH.value): + os.makedirs(constants.INPUT_PATH.value) + + for key, valor in constants.TABLE_LIST_DEPUTADOS.value.items(): + url = f"http://dadosabertos.camara.leg.br/arquivos/{valor}/csv/{valor}.csv" + + response = requests.get(url) + + if response.status_code == 200: + with open(f"{constants.INPUT_PATH.value}{valor}.csv", "wb") as f: + f.write(response.content) + + elif response.status_code >= 400 and response.status_code <= 599: + raise Exception(f"Erro de requisição: status code {response.status_code}") + + log(os.listdir(constants.INPUT_PATH.value)) + + +def read_and_clean_data_deputados(table_id): + df = pd.read_csv( + f"{constants.INPUT_PATH.value}{constants.TABLE_LIST_DEPUTADOS.value[table_id]}.csv", + sep=";", + ) + + df = apply_architecture_to_dataframe( + df, + url_architecture=constants.TABLE_NAME_ARCHITECTURE_DEPUTADOS.value[table_id], + apply_include_missing_columns=False, + apply_rename_columns=True, + apply_column_order_and_selection=True, + ) + + log(df.columns) + + return df + + +def get_data_deputados(): + download_csvs_camara_deputado() + df = pd.read_csv( + f'{constants.INPUT_PATH.value}{constants.TABLE_LIST_DEPUTADOS.value["deputado_profissao"]}.csv', + sep=";", + ) + + return df diff --git a/pipelines/datasets/br_cgu_beneficios_cidadao/flows.py b/pipelines/datasets/br_cgu_beneficios_cidadao/flows.py index e0aa19ecb..14acb8421 100644 --- a/pipelines/datasets/br_cgu_beneficios_cidadao/flows.py +++ b/pipelines/datasets/br_cgu_beneficios_cidadao/flows.py @@ -16,7 +16,6 @@ every_day_novo_bolsa_familia, ) from pipelines.datasets.br_cgu_beneficios_cidadao.tasks import ( - check_for_updates, crawl_last_date, crawler_bolsa_familia, crawler_bpc, @@ -26,11 +25,13 @@ from pipelines.utils.constants import constants as utils_constants from pipelines.utils.decorators import Flow from pipelines.utils.execute_dbt_model.constants import constants as dump_db_constants -from pipelines.utils.metadata.flows import update_django_metadata +from pipelines.utils.metadata.tasks import ( + check_if_data_is_outdated, + update_django_metadata, +) from pipelines.utils.tasks import ( # update_django_metadata, create_table_and_upload_to_gcs, get_current_flow_labels, - log_task, rename_current_flow_run_dataset_table, ) @@ -63,10 +64,11 @@ ) data = crawl_last_date(table_id=table_id) - update = check_for_updates( + update = check_if_data_is_outdated( dataset_id=dataset_id, table_id=table_id, - max_date=data[0], + data_source_max_date=data[0], + date_format="%Y-%m", upstream_tasks=[data], ) @@ -166,10 +168,11 @@ ) data = crawl_last_date(table_id=table_id) - update = check_for_updates( + update = check_if_data_is_outdated( dataset_id=dataset_id, table_id=table_id, - max_date=data[0], + data_source_max_date=data[0], + date_format="%Y-%m", upstream_tasks=[data], ) with case(update, True): @@ -263,10 +266,11 @@ prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id ) data = crawl_last_date(table_id=table_id) - update = check_for_updates( + update = check_if_data_is_outdated( dataset_id=dataset_id, table_id=table_id, - max_date=data[0], + date_format="%Y-%m", + data_source_max_date=data[0], upstream_tasks=[data], ) with case(update, True): diff --git a/pipelines/datasets/br_cgu_beneficios_cidadao/tasks.py b/pipelines/datasets/br_cgu_beneficios_cidadao/tasks.py index 56782a134..154886feb 100644 --- a/pipelines/datasets/br_cgu_beneficios_cidadao/tasks.py +++ b/pipelines/datasets/br_cgu_beneficios_cidadao/tasks.py @@ -3,18 +3,15 @@ Tasks for br_cgu_beneficios_cidadao """ -from datetime import datetime, timedelta +from datetime import timedelta import pandas as pd -import requests from prefect import task -from pipelines.constants import constants as main_constants from pipelines.datasets.br_cgu_beneficios_cidadao.constants import constants from pipelines.datasets.br_cgu_beneficios_cidadao.utils import ( download_unzip_csv, extract_dates, - extract_last_date, parquet_partition, ) from pipelines.utils.utils import log @@ -53,49 +50,6 @@ def crawl_last_date(table_id: str) -> list: return [max_date, max_row["urls"].iloc[0]] -@task( - max_retries=constants.TASK_MAX_RETRIES.value, - retry_delay=timedelta(seconds=constants.TASK_RETRY_DELAY.value), -) -def check_for_updates(dataset_id: str, table_id: str, max_date: datetime) -> bool: - """ - Verifica se há atualizações disponíveis em um conjunto de dados (dataset). - - Parâmetros: - - dataset_id (str): O identificador do conjunto de dados no site. - - table_id (str): O identificador da tabela dentro do conjunto de dados. - - max_date (datetime): A data mais recente a ser comparada com a última data na BD. - - Retorna: - - True se houver atualizações disponíveis, False caso contrário. - - Exemplo de uso: - if check_for_updates("meu_dataset", "minha_tabela", datetime(2023, 11, 10)): - print("Há atualizações disponíveis.") - else: - print("Não há novas atualizações disponíveis.") - """ - - # Obtém a última data no site BD - bd_date = extract_last_date( - dataset_id, - table_id, - billing_project_id=main_constants.BASEDOSDADOS_PROD_AGENT_LABEL.value, - ) - bd_date = datetime.strptime(bd_date, "%Y-%m") - # Registra a data mais recente do site - log(f"Última data no Portal da Transferência: {max_date}") - log(f"Última data na BD: {bd_date}") - - # Compara as datas para verificar se há atualizações - if max_date > bd_date: - log("Há atualizações disponíveis") - return True # Há atualizações disponíveis - else: - log("Não há novas atualizações disponíveis") - return False # Não há novas atualizações disponíveis - - @task( max_retries=constants.TASK_MAX_RETRIES.value, retry_delay=timedelta(seconds=constants.TASK_RETRY_DELAY.value), diff --git a/pipelines/datasets/br_cgu_beneficios_cidadao/utils.py b/pipelines/datasets/br_cgu_beneficios_cidadao/utils.py index c69f09b9f..0c411db2a 100644 --- a/pipelines/datasets/br_cgu_beneficios_cidadao/utils.py +++ b/pipelines/datasets/br_cgu_beneficios_cidadao/utils.py @@ -1,15 +1,11 @@ # -*- coding: utf-8 -*- import os import zipfile -from datetime import datetime -import basedosdados as bd -import numpy as np import pandas as pd import requests from bs4 import BeautifulSoup from selenium import webdriver -from selenium.common.exceptions import ElementNotInteractableException from selenium.webdriver.chrome.service import Service as ChromeService from selenium.webdriver.common.by import By from selenium.webdriver.support.ui import Select @@ -17,7 +13,7 @@ from webdriver_manager.chrome import ChromeDriverManager from pipelines.datasets.br_cgu_beneficios_cidadao.constants import constants -from pipelines.utils.utils import get_credentials_from_secret, log, to_partitions +from pipelines.utils.utils import log, to_partitions def download_unzip_csv( @@ -389,71 +385,3 @@ def parquet_partition(path: str, table: str) -> str: log("Partição feita.") return output_directory - - -def extract_last_date( - dataset_id, table_id, billing_project_id: str, data: str = "data" -): - """ - Extracts the last update date of a given dataset table. - - Args: - dataset_id (str): The ID of the dataset. - table_id (str): The ID of the table. - - Returns: - str: The last update date in the format 'yyyy-mm' or 'yyyy-mm-dd'. - - Raises: - Exception: If an error occurs while extracting the last update date. - """ - if table_id == "garantia_safra": - try: - query_bd = f""" - SELECT - MAX(CONCAT(ano_referencia,"-",mes_referencia)) as max_date - FROM - `{billing_project_id}.{dataset_id}.{table_id}` - """ - - t = bd.read_sql( - query=query_bd, - billing_project_id=billing_project_id, - from_file=True, - ) - input_date_str = t["max_date"][0] - - date_obj = datetime.strptime(input_date_str, "%Y-%m") - - last_date = date_obj.strftime("%Y-%m") - log(f"Última data YYYY-MM: {last_date}") - - return last_date - except Exception as e: - log(f"An error occurred while extracting the last update date: {str(e)}") - raise - else: - try: - query_bd = f""" - SELECT - MAX(CONCAT(ano_competencia,"-",mes_competencia)) as max_date - FROM - `{billing_project_id}.{dataset_id}.{table_id}` - """ - - t = bd.read_sql( - query=query_bd, - billing_project_id=billing_project_id, - from_file=True, - ) - input_date_str = t["max_date"][0] - - date_obj = datetime.strptime(input_date_str, "%Y-%m") - - last_date = date_obj.strftime("%Y-%m") - log(f"Última data YYYY-MM: {last_date}") - - return last_date - except Exception as e: - log(f"An error occurred while extracting the last update date: {str(e)}") - raise diff --git a/pipelines/datasets/br_cgu_servidores_executivo_federal/flows.py b/pipelines/datasets/br_cgu_servidores_executivo_federal/flows.py index 673dca8a4..491869cea 100644 --- a/pipelines/datasets/br_cgu_servidores_executivo_federal/flows.py +++ b/pipelines/datasets/br_cgu_servidores_executivo_federal/flows.py @@ -53,7 +53,7 @@ "materialization_mode", default="prod", required=False ) materialize_after_dump = Parameter( - "materialize after dump", default=True, required=False + "materialize_after_dump", default=True, required=False ) dbt_alias = Parameter("dbt_alias", default=True, required=False) diff --git a/pipelines/datasets/br_cgu_servidores_executivo_federal/tasks.py b/pipelines/datasets/br_cgu_servidores_executivo_federal/tasks.py index a68f3fdc9..424fbb684 100644 --- a/pipelines/datasets/br_cgu_servidores_executivo_federal/tasks.py +++ b/pipelines/datasets/br_cgu_servidores_executivo_federal/tasks.py @@ -18,7 +18,8 @@ make_url, process_table, ) -from pipelines.utils.utils import extract_last_date, log, to_partitions +from pipelines.utils.metadata.utils import get_api_most_recent_date +from pipelines.utils.utils import log, to_partitions @task # noqa @@ -148,14 +149,11 @@ def is_up_to_date(next_date: datetime.date) -> bool: @task def get_next_date() -> datetime.date: - last_date_in_bq = extract_last_date( - "br_cgu_servidores_executivo_federal", - "cadastro_servidores", - "yy-mm", - "basedosdados", + last_date_in_api = get_api_most_recent_date( + dataset_id="br_cgu_servidores_executivo_federal", + table_id="cadastro_servidores", + date_format="%Y-%m", ) - year, month = last_date_in_bq.split("-") - - next_date = datetime.date(int(year), int(month), 1) + relativedelta(months=1) + next_date = last_date_in_api + relativedelta(months=1) return next_date diff --git a/pipelines/datasets/br_cvm_administradores_carteira/tasks.py b/pipelines/datasets/br_cvm_administradores_carteira/tasks.py index 62716e2af..8a3dc2cbf 100644 --- a/pipelines/datasets/br_cvm_administradores_carteira/tasks.py +++ b/pipelines/datasets/br_cvm_administradores_carteira/tasks.py @@ -7,15 +7,12 @@ import os import shutil -import basedosdados as bd import pandas as pd import requests from pandas.api.types import is_string_dtype from prefect import task from unidecode import unidecode -from pipelines.utils.utils import log - @task def crawl(root: str, url: str, chunk_size=128) -> None: @@ -153,44 +150,3 @@ def clean_table_pessoa_juridica(root: str) -> str: dataframe.to_csv(ou_filepath, index=False) return ou_filepath - - -@task -def extract_last_date( - dataset_id: str, - table_id: str, - billing_project_id: str, - var_name: str, -) -> str: - """ - Extracts the last update date of a given dataset table. - - Args: - dataset_id (str): The ID of the dataset. - table_id (str): The ID of the table. - billing_project_id (str): The billing project ID. - - Returns: - str: The last update date in the format 'yyyy-mm-dd'. - - Raises: - Exception: If an error occurs while extracting the last update date. - """ - - query_bd = f""" - SELECT MAX({var_name}) as max_date - FROM - `{billing_project_id}.{dataset_id}.{table_id}` - """ - - t = bd.read_sql( - query=query_bd, - billing_project_id=billing_project_id, - from_file=True, - ) - - data = t["max_date"][0] - - log(f"A data mais recente da tabela é: {data}") - - return str(data) diff --git a/pipelines/datasets/br_me_cnpj/tasks.py b/pipelines/datasets/br_me_cnpj/tasks.py index c950fd20b..0d78bbb46 100644 --- a/pipelines/datasets/br_me_cnpj/tasks.py +++ b/pipelines/datasets/br_me_cnpj/tasks.py @@ -5,10 +5,7 @@ import os from datetime import datetime -import pandas as pd -import requests from prefect import task -from tqdm import tqdm from pipelines.datasets.br_me_cnpj.constants import constants as constants_cnpj from pipelines.datasets.br_me_cnpj.utils import ( @@ -20,7 +17,7 @@ process_csv_simples, process_csv_socios, ) -from pipelines.utils.utils import extract_last_date, log +from pipelines.utils.utils import log ufs = constants_cnpj.UFS.value url = constants_cnpj.URL.value diff --git a/pipelines/datasets/br_mg_belohorizonte_smfa_iptu/flows.py b/pipelines/datasets/br_mg_belohorizonte_smfa_iptu/flows.py index c8d446232..5416bd1d6 100644 --- a/pipelines/datasets/br_mg_belohorizonte_smfa_iptu/flows.py +++ b/pipelines/datasets/br_mg_belohorizonte_smfa_iptu/flows.py @@ -10,23 +10,22 @@ from prefect.tasks.prefect import create_flow_run, wait_for_flow_run from pipelines.constants import constants -from pipelines.datasets.br_mg_belohorizonte_smfa_iptu.constants import ( - constants as constants_iptu, -) from pipelines.datasets.br_mg_belohorizonte_smfa_iptu.schedules import every_weeks_iptu from pipelines.datasets.br_mg_belohorizonte_smfa_iptu.tasks import ( - check_for_updates, download_and_transform, + get_data_source_sfma_iptu_max_date, make_partitions, ) from pipelines.utils.constants import constants as utils_constants from pipelines.utils.decorators import Flow from pipelines.utils.execute_dbt_model.constants import constants as dump_db_constants -from pipelines.utils.metadata.tasks import update_django_metadata +from pipelines.utils.metadata.tasks import ( + check_if_data_is_outdated, + update_django_metadata, +) from pipelines.utils.tasks import ( create_table_and_upload_to_gcs, get_current_flow_labels, - log_task, rename_current_flow_run_dataset_table, ) @@ -50,13 +49,16 @@ rename_flow_run = rename_current_flow_run_dataset_table( prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id ) - dados_desatualizados = check_for_updates(dataset_id=dataset_id, table_id=table_id) - log_task(f"Checando se os dados estão desatualizados: {dados_desatualizados}") - with case(dados_desatualizados, False): - log_task( - "Dados atualizados, não é necessário fazer o download", - upstream_tasks=[dados_desatualizados], - ) + + data_source_max_date = get_data_source_sfma_iptu_max_date() + + dados_desatualizados = check_if_data_is_outdated( + dataset_id=dataset_id, + table_id=table_id, + data_source_max_date=data_source_max_date, + date_format="%Y-%m", + upstream_tasks=[data_source_max_date], + ) with case(dados_desatualizados, True): df = download_and_transform() diff --git a/pipelines/datasets/br_mg_belohorizonte_smfa_iptu/schedules.py b/pipelines/datasets/br_mg_belohorizonte_smfa_iptu/schedules.py index 34b841bd7..25cc7cbbc 100644 --- a/pipelines/datasets/br_mg_belohorizonte_smfa_iptu/schedules.py +++ b/pipelines/datasets/br_mg_belohorizonte_smfa_iptu/schedules.py @@ -22,7 +22,7 @@ "materialization_mode": "prod", "materialize_after_dump": True, "dbt_alias": True, - "update_metadata": "True", + "update_metadata": True, }, ), ] diff --git a/pipelines/datasets/br_mg_belohorizonte_smfa_iptu/tasks.py b/pipelines/datasets/br_mg_belohorizonte_smfa_iptu/tasks.py index 671de9245..c97683ff2 100644 --- a/pipelines/datasets/br_mg_belohorizonte_smfa_iptu/tasks.py +++ b/pipelines/datasets/br_mg_belohorizonte_smfa_iptu/tasks.py @@ -18,7 +18,7 @@ reorder_and_fix_nan, scrapping_download_csv, ) -from pipelines.utils.utils import extract_last_date, log, to_partitions +from pipelines.utils.utils import log, to_partitions @task # noqa @@ -76,25 +76,7 @@ def data_url(url, headers): @task -def check_for_updates(dataset_id, table_id): - """ - Checks if there are available updates for a specific dataset and table. - - Returns: - bool: Returns True if updates are available, otherwise returns False. - """ +def get_data_source_sfma_iptu_max_date(): # Obtém a data mais recente do site data_obj = data_url(constants.URLS.value[0], constants.HEADERS.value) - - # Obtém a última data no site BD - data_bq_obj = extract_last_date(dataset_id, table_id, "yy-mm", "basedosdados") - - # Registra a data mais recente do site - log(f"Última data no site do SMFA: {data_obj}") - log(f"Última data no site da BD: {data_bq_obj}") - - # Compara as datas para verificar se há atualizações - if data_obj > data_bq_obj: - return True # Há atualizações disponíveis - else: - return False # Não há novas atualizações disponíveis + return data_obj diff --git a/pipelines/datasets/br_mp_pep_cargos_funcoes/tasks.py b/pipelines/datasets/br_mp_pep_cargos_funcoes/tasks.py index 64f32dbc6..80cd1c7e8 100644 --- a/pipelines/datasets/br_mp_pep_cargos_funcoes/tasks.py +++ b/pipelines/datasets/br_mp_pep_cargos_funcoes/tasks.py @@ -22,7 +22,8 @@ move_from_tmp_dir, wait_file_download, ) -from pipelines.utils.utils import extract_last_date, log, to_partitions +from pipelines.utils.metadata.utils import get_api_most_recent_date +from pipelines.utils.utils import log, to_partitions @task @@ -399,11 +400,10 @@ def is_up_to_date() -> bool: log(f"Last date website: {text}, parsed as {date_website}") - last_date_in_bq = extract_last_date( - "br_mp_pep", "cargos_funcoes", "yy-mm", "basedosdados" + last_date_in_api = get_api_most_recent_date( + dataset_id="br_mp_pep", table_id="cargos_funcoes", date_format="%Y-%m" ) - date_in_bq = datetime.datetime.strptime(last_date_in_bq, "%Y-%m") - log(f"Last date BQ: {date_in_bq}") + log(f"Last date API: {last_date_in_api}") - return date_in_bq == date_website + return last_date_in_api == date_website diff --git a/pipelines/datasets/br_ms_cnes/flows.py b/pipelines/datasets/br_ms_cnes/flows.py index 980658e7f..63d3b4c1a 100644 --- a/pipelines/datasets/br_ms_cnes/flows.py +++ b/pipelines/datasets/br_ms_cnes/flows.py @@ -66,7 +66,6 @@ files_path = check_files_to_parse( dataset_id=dataset_id, table_id=table_id, - billing_project_id="basedosdados", cnes_database="CNES", cnes_group_file=br_ms_cnes_constants.DATABASE_GROUPS.value["CNES"][0], ) @@ -173,7 +172,6 @@ files_path = check_files_to_parse( dataset_id=dataset_id, table_id=table_id, - billing_project_id="basedosdados", cnes_database="CNES", cnes_group_file=br_ms_cnes_constants.DATABASE_GROUPS.value["CNES"][1], ) @@ -274,7 +272,6 @@ files_path = check_files_to_parse( dataset_id=dataset_id, table_id=table_id, - billing_project_id="basedosdados", cnes_database="CNES", cnes_group_file=br_ms_cnes_constants.DATABASE_GROUPS.value["CNES"][4], ) @@ -375,7 +372,6 @@ files_path = check_files_to_parse( dataset_id=dataset_id, table_id=table_id, - billing_project_id="basedosdados", cnes_database="CNES", cnes_group_file=br_ms_cnes_constants.DATABASE_GROUPS.value["CNES"][3], ) @@ -478,7 +474,6 @@ files_path = check_files_to_parse( dataset_id=dataset_id, table_id=table_id, - billing_project_id="basedosdados", cnes_database="CNES", # mudar no aqui pra 1 cnes_group_file=br_ms_cnes_constants.DATABASE_GROUPS.value["CNES"][2], @@ -582,7 +577,6 @@ files_path = check_files_to_parse( dataset_id=dataset_id, table_id=table_id, - billing_project_id="basedosdados", cnes_database="CNES", cnes_group_file=br_ms_cnes_constants.DATABASE_GROUPS.value["CNES"][5], ) @@ -684,7 +678,6 @@ files_path = check_files_to_parse( dataset_id=dataset_id, table_id=table_id, - billing_project_id="basedosdados", cnes_database="CNES", cnes_group_file=br_ms_cnes_constants.DATABASE_GROUPS.value["CNES"][6], ) @@ -788,7 +781,6 @@ files_path = check_files_to_parse( dataset_id=dataset_id, table_id=table_id, - billing_project_id="basedosdados", cnes_database="CNES", cnes_group_file=br_ms_cnes_constants.DATABASE_GROUPS.value["CNES"][7], ) @@ -894,7 +886,6 @@ files_path = check_files_to_parse( dataset_id=dataset_id, table_id=table_id, - billing_project_id="basedosdados", cnes_database="CNES", cnes_group_file=br_ms_cnes_constants.DATABASE_GROUPS.value["CNES"][8], ) @@ -995,7 +986,6 @@ files_path = check_files_to_parse( dataset_id=dataset_id, table_id=table_id, - billing_project_id="basedosdados", cnes_database="CNES", cnes_group_file=br_ms_cnes_constants.DATABASE_GROUPS.value["CNES"][9], ) @@ -1098,7 +1088,6 @@ files_path = check_files_to_parse( dataset_id=dataset_id, table_id=table_id, - billing_project_id="basedosdados", cnes_database="CNES", cnes_group_file=br_ms_cnes_constants.DATABASE_GROUPS.value["CNES"][10], ) @@ -1200,7 +1189,6 @@ files_path = check_files_to_parse( dataset_id=dataset_id, table_id=table_id, - billing_project_id="basedosdados", cnes_database="CNES", cnes_group_file=br_ms_cnes_constants.DATABASE_GROUPS.value["CNES"][11], ) @@ -1279,7 +1267,7 @@ br_ms_cnes_regra_contratual.run_config = KubernetesRun( image=constants.DOCKER_IMAGE.value ) -br_ms_cnes_regra_contratual.schedule = schedule_br_ms_cnes_regra_contratual +# br_ms_cnes_regra_contratual.schedule = schedule_br_ms_cnes_regra_contratual # regra_contratual with Flow( @@ -1304,7 +1292,6 @@ files_path = check_files_to_parse( dataset_id=dataset_id, table_id=table_id, - billing_project_id="basedosdados", cnes_database="CNES", cnes_group_file=br_ms_cnes_constants.DATABASE_GROUPS.value["CNES"][12], ) diff --git a/pipelines/datasets/br_ms_cnes/tasks.py b/pipelines/datasets/br_ms_cnes/tasks.py index 0a1a2a3c4..8428b8a9b 100644 --- a/pipelines/datasets/br_ms_cnes/tasks.py +++ b/pipelines/datasets/br_ms_cnes/tasks.py @@ -8,23 +8,21 @@ from datetime import timedelta import pandas as pd -import rpy2.robjects as ro import rpy2.robjects.packages as rpackages import wget from prefect import task -from rpy2.robjects import pandas2ri from rpy2.robjects.packages import importr from pipelines.constants import constants from pipelines.datasets.br_ms_cnes.constants import constants as cnes_constants from pipelines.datasets.br_ms_cnes.utils import ( check_and_create_column, - extract_last_date, if_column_exist_delete, list_all_cnes_dbc_files, pre_cleaning_to_utf8, year_month_sigla_uf_parser, ) +from pipelines.utils.metadata.utils import get_api_most_recent_date from pipelines.utils.utils import log @@ -32,16 +30,15 @@ def check_files_to_parse( dataset_id: str, table_id: str, - billing_project_id, cnes_database: str, cnes_group_file: str, ) -> list[str]: - log(f"extracting last date from bq for {dataset_id}.{table_id}") - # 1. extrair data mais atual do bq - last_date = extract_last_date( + log(f"extracting last date from api for {dataset_id}.{table_id}") + # 1. extrair data mais atual da api + last_date = get_api_most_recent_date( dataset_id=dataset_id, table_id=table_id, - billing_project_id=billing_project_id, + date_format="%Y-%m", ) log("building next year/month to parse") # 2. adicionar mais um no mes ou transformar pra 1 se for 12 diff --git a/pipelines/datasets/br_ms_cnes/utils.py b/pipelines/datasets/br_ms_cnes/utils.py index a07d3da9d..902da1d95 100644 --- a/pipelines/datasets/br_ms_cnes/utils.py +++ b/pipelines/datasets/br_ms_cnes/utils.py @@ -5,11 +5,8 @@ from ftplib import FTP -import basedosdados as bd import pandas as pd -from pipelines.utils.utils import log - def list_all_cnes_dbc_files( database: str, @@ -135,37 +132,3 @@ def if_column_exist_delete(df: pd.DataFrame, col_list: str): del df[col] return df - - -def extract_last_date(dataset_id, table_id, billing_project_id: str): - """ - Extracts the last update date of a given dataset table. - - Args: - dataset_id (str): The ID of the dataset. - table_id (str): The ID of the table. - billing_project_id (str): The billing project ID. - - Returns: - str: The last update date in the format 'yyyy-mm' or 'yyyy-mm-dd'. - - Raises: - Exception: If an error occurs while extracting the last update date. - """ - - query_bd = f""" - SELECT MAX(DATE(CAST(ano AS INT64),CAST(mes AS INT64),1)) as max_date - FROM - `{billing_project_id}.{dataset_id}.{table_id}` - """ - - t = bd.read_sql( - query=query_bd, - billing_project_id=billing_project_id, - from_file=True, - ) - year_month = t["max_date"][0] - - log(f"O Ano/Mês mais recente da tabela é: {year_month}") - - return year_month diff --git a/pipelines/datasets/br_ons_avaliacao_operacao/flows.py b/pipelines/datasets/br_ons_avaliacao_operacao/flows.py index dfee6fc08..e0e7f65e9 100644 --- a/pipelines/datasets/br_ons_avaliacao_operacao/flows.py +++ b/pipelines/datasets/br_ons_avaliacao_operacao/flows.py @@ -5,7 +5,6 @@ # pylint: disable=invalid-name from datetime import timedelta -# TODO: extract_last_date_from_bq colocar billing de prod antes de fechar PR from prefect import Parameter, case from prefect.run_configs import KubernetesRun from prefect.storage import GCS @@ -23,15 +22,14 @@ schedule_br_ons_avaliacao_operacao_reservatorio, schedule_br_ons_avaliacao_operacao_restricao_operacao_usinas_eolicas, ) -from pipelines.datasets.br_ons_avaliacao_operacao.tasks import ( - download_data, - extract_last_date_from_bq, - wrang_data, -) +from pipelines.datasets.br_ons_avaliacao_operacao.tasks import download_data, wrang_data from pipelines.utils.constants import constants as utils_constants from pipelines.utils.decorators import Flow from pipelines.utils.execute_dbt_model.constants import constants as dump_db_constants -from pipelines.utils.metadata.tasks import update_django_metadata +from pipelines.utils.metadata.tasks import ( + task_get_api_most_recent_date, + update_django_metadata, +) from pipelines.utils.tasks import ( create_table_and_upload_to_gcs, get_current_flow_labels, @@ -60,11 +58,10 @@ prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id ) - data_mais_recente_do_bq = extract_last_date_from_bq( + data_mais_recente_do_bq = task_get_api_most_recent_date( table_id=table_id, dataset_id=dataset_id, - # vai ser retirado virar from file - billing_project_id="basedosdados", + date_format="%Y-%m-%d", ) dow_data = download_data( @@ -157,11 +154,10 @@ prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id ) - data_mais_recente_do_bq = extract_last_date_from_bq( + data_mais_recente_do_bq = task_get_api_most_recent_date( table_id=table_id, dataset_id=dataset_id, - # vai ser retirado virar from file - billing_project_id="basedosdados", + date_format="%Y-%m-%d", ) dow_data = download_data( @@ -257,11 +253,10 @@ prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id ) - data_mais_recente_do_bq = extract_last_date_from_bq( + data_mais_recente_do_bq = task_get_api_most_recent_date( table_id=table_id, dataset_id=dataset_id, - # vai ser retirado virar from file - billing_project_id="basedosdados", + date_format="%Y-%m-%d", ) dow_data = download_data( @@ -358,11 +353,10 @@ prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id ) - data_mais_recente_do_bq = extract_last_date_from_bq( + data_mais_recente_do_bq = task_get_api_most_recent_date( table_id=table_id, dataset_id=dataset_id, - # vai ser retirado virar from file - billing_project_id="basedosdados", + date_format="%Y-%m-%d", ) dow_data = download_data( @@ -460,11 +454,10 @@ prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id ) - data_mais_recente_do_bq = extract_last_date_from_bq( + data_mais_recente_do_bq = task_get_api_most_recent_date( table_id=table_id, dataset_id=dataset_id, - # vai ser retirado virar from file - billing_project_id="basedosdados", + date_format="%Y-%m-%d", ) dow_data = download_data( @@ -560,11 +553,10 @@ prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id ) - data_mais_recente_do_bq = extract_last_date_from_bq( + data_mais_recente_do_bq = task_get_api_most_recent_date( table_id=table_id, dataset_id=dataset_id, - # vai ser retirado virar from file - billing_project_id="basedosdados", + date_format="%Y-%m-%d", ) dow_data = download_data( diff --git a/pipelines/datasets/br_ons_avaliacao_operacao/tasks.py b/pipelines/datasets/br_ons_avaliacao_operacao/tasks.py index bf551c387..be745e645 100644 --- a/pipelines/datasets/br_ons_avaliacao_operacao/tasks.py +++ b/pipelines/datasets/br_ons_avaliacao_operacao/tasks.py @@ -7,7 +7,6 @@ from datetime import date, datetime from typing import Union -import basedosdados as bd import pandas as pd from prefect import task @@ -30,91 +29,6 @@ from pipelines.utils.utils import log, to_partitions -@task -def extract_last_date_from_bq( - dataset_id, table_id, billing_project_id: str -) -> Union[datetime, date]: - """Extrai a data mais recente de uma dada tabela dos conjuntos br_ons_avaliacao_operacao e br_ons_estimativa_custos do BQ - Args: - dataset_id (str): The ID of the dataset. - table_id (str): The ID of the table. - billing_project_id (str): The billing project ID. - - Returns: - Union[datetime, date]: data máxima da tabela - """ - - date_dict = { - "reservatorio": "yyyy-mm-dd", - "geracao_usina": "yyyy-mm-dd hh:mm:ss", - "geracao_termica_motivo_despacho": "yyyy-mm-dd hh:mm:ss", - "energia_natural_afluente": "yyyy-mm-dd", - "energia_armazenada_reservatorio": "yyyy-mm-dd", - "restricao_operacao_usinas_eolicas": "yyyy-mm-dd hh:mm:ss", - "custo_marginal_operacao_semi_horario": "yyyy-mm-dd hh:mm:ss", - "custo_marginal_operacao_semanal": "yyyy-mm-dd", - "balanco_energia_subsistemas": "yyyy-mm-dd hh:mm:ss", - "balanco_energia_subsistemas_dessem": "yyyy-mm-dd hh:mm:ss", - "custo_variavel_unitario_usinas_termicas": "yyyy-mm-dd", - } - - if date_dict[table_id] == "yyyy-mm-dd hh:mm:ss": - query_bd = f""" SELECT - MAX(FORMAT_TIMESTAMP('%F %T', TIMESTAMP(CONCAT(data, ' ', hora)))) AS max_data_hora - FROM - `{billing_project_id}.{dataset_id}.{table_id}` - """ - - t = bd.read_sql( - query=query_bd, - billing_project_id=billing_project_id, - from_file=True, - ) - - data = t["max_data_hora"][0] - data = pd.to_datetime(data, format="%Y-%m-%d %H:%M:%S") - - if ( - date_dict[table_id] == "yyyy-mm-dd" - and table_id != "custo_variavel_unitario_usinas_termicas" - ): - query_bd = f""" - SELECT MAX(data) as max_date - FROM - `{billing_project_id}.{dataset_id}.{table_id}` - """ - - t = bd.read_sql( - query=query_bd, - billing_project_id=billing_project_id, - from_file=True, - ) - - data = t["max_date"][0] - - print(f"A data mais recente da tabela no BQ é {data}") - - if ( - date_dict[table_id] == "yyyy-mm-dd" - and table_id == "custo_variavel_unitario_usinas_termicas" - ): - query_bd = f""" - SELECT MAX(data_inicio) as max_date - FROM - `{billing_project_id}.{dataset_id}.{table_id}` - """ - - t = bd.read_sql( - query=query_bd, - billing_project_id=billing_project_id, - from_file=True, - ) - - data = t["max_date"][0] - - return data - - @task def download_data( table_name: str, @@ -197,8 +111,7 @@ def wrang_data( Args: table_name (str): nome da tabela, equivale ao table_id - data_mais_recente_do_bq (Union[date,datetime]): Data mais recente da tabela no BQ extraida - com com a task extract_last_date_from_bq + data_mais_recente_do_bq (Union[date,datetime]): Data mais recente da tabela no BQ extraida da api Returns: tuple[bool,str,Union[date,datetime]]: Retorna uma Tupla com 3 elementos: diff --git a/pipelines/datasets/br_ons_avaliacao_operacao/utils.py b/pipelines/datasets/br_ons_avaliacao_operacao/utils.py index 907298ac5..3a1be58f4 100644 --- a/pipelines/datasets/br_ons_avaliacao_operacao/utils.py +++ b/pipelines/datasets/br_ons_avaliacao_operacao/utils.py @@ -53,7 +53,9 @@ def extrai_data_recente(df: pd.DataFrame, table_name: str) -> Union[datetime, da if date_dict[table_name] == "yyyy-mm-dd hh:mm:ss": df["data_hora"] = df["data"] + " " + df["hora"] - df["data_hora"] = pd.to_datetime(df["data_hora"], format="%Y-%m-%d %H:%M:%S") + df["data_hora"] = pd.to_datetime( + df["data_hora"], format="%Y-%m-%d %H:%M:%S" + ).dt.date data = df["data_hora"].max() if ( diff --git a/pipelines/datasets/br_ons_estimativa_custos/flows.py b/pipelines/datasets/br_ons_estimativa_custos/flows.py index d0dbdf762..0db0c3cbb 100644 --- a/pipelines/datasets/br_ons_estimativa_custos/flows.py +++ b/pipelines/datasets/br_ons_estimativa_custos/flows.py @@ -21,24 +21,20 @@ schedule_br_ons_estimativa_custos_custo_marginal_operacao_semi_horario, schedule_br_ons_estimativa_custos_custo_variavel_unitario_usinas_termicas, ) -from pipelines.datasets.br_ons_estimativa_custos.tasks import ( - download_data, - extract_last_date_from_bq, - wrang_data, -) +from pipelines.datasets.br_ons_estimativa_custos.tasks import download_data, wrang_data from pipelines.utils.constants import constants as utils_constants from pipelines.utils.decorators import Flow from pipelines.utils.execute_dbt_model.constants import constants as dump_db_constants -from pipelines.utils.metadata.tasks import update_django_metadata +from pipelines.utils.metadata.tasks import ( + task_get_api_most_recent_date, + update_django_metadata, +) from pipelines.utils.tasks import ( create_table_and_upload_to_gcs, get_current_flow_labels, rename_current_flow_run_dataset_table, ) -# TODO: extract_last_date_from_bq colocar billing de prod antes de fechar PR - - with Flow( name="br_ons_estimativa_custos.custo_marginal_operacao_semi_horario", code_owners=["Gabriel Pisa"], @@ -63,11 +59,10 @@ prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id ) - data_mais_recente_do_bq = extract_last_date_from_bq( + data_mais_recente_do_bq = task_get_api_most_recent_date( table_id=table_id, dataset_id=dataset_id, - # vai ser retirado virar from file - billing_project_id="basedosdados", + date_format="%Y-%m-%d", ) dow_data = download_data( @@ -165,11 +160,10 @@ prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id ) - data_mais_recente_do_bq = extract_last_date_from_bq( + data_mais_recente_do_bq = task_get_api_most_recent_date( table_id=table_id, dataset_id=dataset_id, - # vai ser retirado virar from file - billing_project_id="basedosdados", + date_format="%Y-%m-%d", ) dow_data = download_data( @@ -268,11 +262,10 @@ prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id ) - data_mais_recente_do_bq = extract_last_date_from_bq( + data_mais_recente_do_bq = task_get_api_most_recent_date( table_id=table_id, dataset_id=dataset_id, - # vai ser retirado virar from file - billing_project_id="basedosdados", + date_format="%Y-%m-%d", ) dow_data = download_data( @@ -371,11 +364,10 @@ prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id ) - data_mais_recente_do_bq = extract_last_date_from_bq( + data_mais_recente_do_bq = task_get_api_most_recent_date( table_id=table_id, dataset_id=dataset_id, - # vai ser retirado virar from file - billing_project_id="basedosdados", + date_format="%Y-%m-%d", ) dow_data = download_data( @@ -474,11 +466,10 @@ prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id ) - data_mais_recente_do_bq = extract_last_date_from_bq( + data_mais_recente_do_bq = task_get_api_most_recent_date( table_id=table_id, dataset_id=dataset_id, - # vai ser retirado virar from file - billing_project_id="basedosdados", + date_format="%Y-%m-%d", ) dow_data = download_data( diff --git a/pipelines/datasets/br_ons_estimativa_custos/tasks.py b/pipelines/datasets/br_ons_estimativa_custos/tasks.py index c8fe38ed7..520446576 100644 --- a/pipelines/datasets/br_ons_estimativa_custos/tasks.py +++ b/pipelines/datasets/br_ons_estimativa_custos/tasks.py @@ -7,7 +7,6 @@ from datetime import date, datetime from typing import Union -import basedosdados as bd import pandas as pd from prefect import task @@ -29,91 +28,6 @@ from pipelines.utils.utils import log, to_partitions -@task -def extract_last_date_from_bq( - dataset_id, table_id, billing_project_id: str -) -> Union[datetime, date]: - """Extrai a data mais recente de uma dada tabela dos conjuntos br_ons_avaliacao_operacao e br_ons_estimativa_custos do BQ - Args: - dataset_id (str): The ID of the dataset. - table_id (str): The ID of the table. - billing_project_id (str): The billing project ID. - - Returns: - Union[datetime, date]: data máxima da tabela - """ - - date_dict = { - "reservatorio": "yyyy-mm-dd", - "geracao_usina": "yyyy-mm-dd hh:mm:ss", - "geracao_termica_motivo_despacho": "yyyy-mm-dd hh:mm:ss", - "energia_natural_afluente": "yyyy-mm-dd", - "energia_armazenada_reservatorio": "yyyy-mm-dd", - "restricao_operacao_usinas_eolicas": "yyyy-mm-dd hh:mm:ss", - "custo_marginal_operacao_semi_horario": "yyyy-mm-dd hh:mm:ss", - "custo_marginal_operacao_semanal": "yyyy-mm-dd", - "balanco_energia_subsistemas": "yyyy-mm-dd hh:mm:ss", - "balanco_energia_subsistemas_dessem": "yyyy-mm-dd hh:mm:ss", - "custo_variavel_unitario_usinas_termicas": "yyyy-mm-dd", - } - - if date_dict[table_id] == "yyyy-mm-dd hh:mm:ss": - query_bd = f""" SELECT - MAX(FORMAT_TIMESTAMP('%F %T', TIMESTAMP(CONCAT(data, ' ', hora)))) AS max_data_hora - FROM - `{billing_project_id}.{dataset_id}.{table_id}` - """ - - t = bd.read_sql( - query=query_bd, - billing_project_id=billing_project_id, - from_file=True, - ) - - data = t["max_data_hora"][0] - data = pd.to_datetime(data, format="%Y-%m-%d %H:%M:%S") - - if ( - date_dict[table_id] == "yyyy-mm-dd" - and table_id != "custo_variavel_unitario_usinas_termicas" - ): - query_bd = f""" - SELECT MAX(data) as max_date - FROM - `{billing_project_id}.{dataset_id}.{table_id}` - """ - - t = bd.read_sql( - query=query_bd, - billing_project_id=billing_project_id, - from_file=True, - ) - - data = t["max_date"][0] - - print(f"A data mais recente da tabela no BQ é {data}") - - if ( - date_dict[table_id] == "yyyy-mm-dd" - and table_id == "custo_variavel_unitario_usinas_termicas" - ): - query_bd = f""" - SELECT MAX(data_inicio) as max_date - FROM - `{billing_project_id}.{dataset_id}.{table_id}` - """ - - t = bd.read_sql( - query=query_bd, - billing_project_id=billing_project_id, - from_file=True, - ) - - data = t["max_date"][0] - - return data - - @task def download_data( table_name: str, @@ -189,8 +103,7 @@ def wrang_data( Args: table_name (str): nome da tabela, equivale ao table_id data_mais_recente_do_bq (Union[date,datetime]): Data mais recente da tabela no BQ extraida - com com a task extract_last_date_from_bq - + com com a task task_get_api_most_recent_date Returns: tuple[bool,str,Union[date,datetime]]: Retorna uma Tupla com 3 elementos: 1. um valor booleano -> usado para parar o flow caso não haja atualização. diff --git a/pipelines/datasets/br_ons_estimativa_custos/utils.py b/pipelines/datasets/br_ons_estimativa_custos/utils.py index 1bba2b3e2..81bbca7c8 100644 --- a/pipelines/datasets/br_ons_estimativa_custos/utils.py +++ b/pipelines/datasets/br_ons_estimativa_custos/utils.py @@ -54,7 +54,9 @@ def extrai_data_recente(df: pd.DataFrame, table_name: str) -> Union[datetime, da if date_dict[table_name] == "yyyy-mm-dd hh:mm:ss": df["data_hora"] = df["data"] + " " + df["hora"] - df["data_hora"] = pd.to_datetime(df["data_hora"], format="%Y-%m-%d %H:%M:%S") + df["data_hora"] = pd.to_datetime( + df["data_hora"], format="%Y-%m-%d %H:%M:%S" + ).dt.date data = df["data_hora"].max() if ( @@ -64,6 +66,9 @@ def extrai_data_recente(df: pd.DataFrame, table_name: str) -> Union[datetime, da df["data_inicio"] = pd.to_datetime(df["data_inicio"], format="%Y-%m-%d").dt.date data = df["data_inicio"].max() + if isinstance(data, pd.Timestamp): + data = data.date() + return data diff --git a/pipelines/datasets/br_rf_cafir/tasks.py b/pipelines/datasets/br_rf_cafir/tasks.py index e383bff59..092dab94a 100644 --- a/pipelines/datasets/br_rf_cafir/tasks.py +++ b/pipelines/datasets/br_rf_cafir/tasks.py @@ -10,11 +10,9 @@ import pandas as pd from prefect import task -from pipelines.constants import constants from pipelines.datasets.br_rf_cafir.constants import constants as br_rf_cafir_constants from pipelines.datasets.br_rf_cafir.utils import ( download_csv_files, - extract_last_date, parse_date_parse_files, preserve_zeros, remove_accent, diff --git a/pipelines/datasets/br_rf_cafir/utils.py b/pipelines/datasets/br_rf_cafir/utils.py index 397886be9..d6de29728 100644 --- a/pipelines/datasets/br_rf_cafir/utils.py +++ b/pipelines/datasets/br_rf_cafir/utils.py @@ -7,54 +7,12 @@ import unicodedata from datetime import datetime -import basedosdados as bd import pandas as pd import requests from bs4 import BeautifulSoup from pipelines.utils.utils import log -# função para extrair datas -# valor usado para o check de atualização do site além de ser usado para update do coverage -# tambem será usado para criar uma coluna - - -def extract_last_date( - dataset_id: str, table_id: str, billing_project_id: str -) -> datetime: - """ - Extracts the last update date of a given dataset table. - - Args: - dataset_id (str): The ID of the dataset. - table_id (str): The ID of the table. - billing_project_id (str): The billing project ID. - - Returns: - str: The last update date in the format 'yyyy-mm-dd'. - - Raises: - Exception: If an error occurs while extracting the last update date. - """ - - query_bd = f""" - SELECT MAX(data_referencia) as max_date - FROM - `{billing_project_id}.{dataset_id}.{table_id}` - """ - - t = bd.read_sql( - query=query_bd, - billing_project_id=billing_project_id, - from_file=True, - ) - - data = t["max_date"][0] - - log(f"A data mais recente da tabela é: {data}") - - return data - def strip_string(x: pd.DataFrame) -> pd.DataFrame: """Aplica o strip em uma coluna de um dataframe, caso seja string. diff --git a/pipelines/datasets/br_rj_isp_estatisticas_seguranca/flows.py b/pipelines/datasets/br_rj_isp_estatisticas_seguranca/flows.py index 893daeeae..3fe0abad5 100644 --- a/pipelines/datasets/br_rj_isp_estatisticas_seguranca/flows.py +++ b/pipelines/datasets/br_rj_isp_estatisticas_seguranca/flows.py @@ -57,7 +57,7 @@ "materialize_after_dump", default=True, required=False ) - dbt_alias = Parameter("dbt_alias", default=False, required=False) + dbt_alias = Parameter("dbt_alias", default=True, required=False) rename_flow_run = rename_current_flow_run_dataset_table( prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id @@ -148,7 +148,7 @@ materialize_after_dump = Parameter( "materialize_after_dump", default=True, required=False ) - dbt_alias = Parameter("dbt_alias", default=False, required=False) + dbt_alias = Parameter("dbt_alias", default=True, required=False) rename_flow_run = rename_current_flow_run_dataset_table( prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id @@ -241,7 +241,7 @@ materialize_after_dump = Parameter( "materialize_after_dump", default=True, required=False ) - dbt_alias = Parameter("dbt_alias", default=False, required=False) + dbt_alias = Parameter("dbt_alias", default=True, required=False) rename_flow_run = rename_current_flow_run_dataset_table( prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id @@ -334,7 +334,7 @@ materialize_after_dump = Parameter( "materialize_after_dump", default=True, required=False ) - dbt_alias = Parameter("dbt_alias", default=False, required=False) + dbt_alias = Parameter("dbt_alias", default=True, required=False) update_metadata = Parameter("update_metadata", default=True, required=False) @@ -428,7 +428,7 @@ materialize_after_dump = Parameter( "materialize_after_dump", default=True, required=False ) - dbt_alias = Parameter("dbt_alias", default=False, required=False) + dbt_alias = Parameter("dbt_alias", default=True, required=False) update_metadata = Parameter("update_metadata", default=True, required=False) @@ -523,7 +523,7 @@ materialize_after_dump = Parameter( "materialize_after_dump", default=True, required=False ) - dbt_alias = Parameter("dbt_alias", default=False, required=False) + dbt_alias = Parameter("dbt_alias", default=True, required=False) update_metadata = Parameter("update_metadata", default=True, required=False) @@ -614,7 +614,7 @@ materialize_after_dump = Parameter( "materialize_after_dump", default=True, required=False ) - dbt_alias = Parameter("dbt_alias", default=False, required=False) + dbt_alias = Parameter("dbt_alias", default=True, required=False) update_metadata = Parameter("update_metadata", default=True, required=False) @@ -705,7 +705,7 @@ materialize_after_dump = Parameter( "materialize_after_dump", default=True, required=False ) - dbt_alias = Parameter("dbt_alias", default=False, required=False) + dbt_alias = Parameter("dbt_alias", default=True, required=False) update_metadata = Parameter("update_metadata", default=True, required=False) diff --git a/pipelines/datasets/br_rj_isp_estatisticas_seguranca/schedules.py b/pipelines/datasets/br_rj_isp_estatisticas_seguranca/schedules.py index b52e281a4..a30e8d430 100644 --- a/pipelines/datasets/br_rj_isp_estatisticas_seguranca/schedules.py +++ b/pipelines/datasets/br_rj_isp_estatisticas_seguranca/schedules.py @@ -24,7 +24,7 @@ "table_id": "evolucao_mensal_cisp", # ! table_id do dataset que será executado "materialization_mode": "prod", # ! Aonde o dataset será materializado (dev, prod ou prod-staging) "materialize_after_dump": True, # ! Se o dataset será materializado após o dump - "dbt_alias": False, + "dbt_alias": True, }, ), ] @@ -44,7 +44,7 @@ "table_id": "taxa_evolucao_mensal_uf", # ! table_id do dataset que será executado "materialization_mode": "prod", # ! Aonde o dataset será materializado (dev, prod ou prod-staging) "materialize_after_dump": True, # ! Se o dataset será materializado após o dump - "dbt_alias": False, + "dbt_alias": True, }, ), ] @@ -64,7 +64,7 @@ "table_id": "taxa_evolucao_mensal_municipio", # ! table_id do dataset que será executado "materialization_mode": "prod", # ! Aonde o dataset será materializado (dev, prod ou prod-staging) "materialize_after_dump": True, # ! Se o dataset será materializado após o dump - "dbt_alias": False, + "dbt_alias": True, }, ), ] @@ -84,7 +84,7 @@ "table_id": "feminicidio_mensal_cisp", # ! table_id do dataset que será executado "materialization_mode": "prod", # ! Aonde o dataset será materializado (dev, prod ou prod-staging) "materialize_after_dump": True, # ! Se o dataset será materializado após o dump - "dbt_alias": False, + "dbt_alias": True, }, ), ] @@ -104,7 +104,7 @@ "table_id": "evolucao_policial_morto_servico_mensal", # ! table_id do dataset que será executado "materialization_mode": "prod", # ! Aonde o dataset será materializado (dev, prod ou prod-staging) "materialize_after_dump": True, # ! Se o dataset será materializado após o dump - "dbt_alias": False, + "dbt_alias": True, }, ), ] @@ -125,7 +125,7 @@ "table_id": "armas_apreendidas_mensal", # ! table_id do dataset que será executado "materialization_mode": "prod", # ! Aonde o dataset será materializado (dev, prod ou prod-staging) "materialize_after_dump": True, # ! Se o dataset será materializado após o dump - "dbt_alias": False, + "dbt_alias": True, }, ), ] @@ -146,7 +146,7 @@ "table_id": "evolucao_mensal_municipio", # ! table_id do dataset que será executado "materialization_mode": "prod", # ! Aonde o dataset será materializado (dev, prod ou prod-staging) "materialize_after_dump": True, # ! Se o dataset será materializado após o dump - "dbt_alias": False, + "dbt_alias": True, }, ), ] @@ -166,7 +166,7 @@ "table_id": "evolucao_mensal_uf", # ! table_id do dataset que será executado "materialization_mode": "prod", # ! Aonde o dataset será materializado (dev, prod ou prod-staging) "materialize_after_dump": True, # ! Se o dataset será materializado após o dump - "dbt_alias": False, + "dbt_alias": True, }, ), ] diff --git a/pipelines/datasets/br_rj_isp_estatisticas_seguranca/tasks.py b/pipelines/datasets/br_rj_isp_estatisticas_seguranca/tasks.py index 629691445..568731f04 100644 --- a/pipelines/datasets/br_rj_isp_estatisticas_seguranca/tasks.py +++ b/pipelines/datasets/br_rj_isp_estatisticas_seguranca/tasks.py @@ -73,8 +73,15 @@ def clean_data( sep=";", thousands=".", decimal=",", + dtype=str, ) log(f"file -> {file_name} read") + if ( + file_name == isp_constants.TAXA_EVOLUCAO_MENSAL_UF.value + or file_name == isp_constants.TAXA_EVOLUCAO_MENSAL_MUNICIPIO.value + ): + df = df.apply(lambda x: x.str.replace(",", ".")) + log(df.head()) else: df = pd.read_excel( @@ -96,12 +103,13 @@ def clean_data( log("creating columns order") ordem_colunas = create_columns_order(nomes_colunas) - log("checking tipo_fase col") - df = check_tipo_fase(df) - log("ordering columns") df = df[ordem_colunas] + log(df.columns) + log("checking tipo_fase col") + df = check_tipo_fase(df) + log("building dir") os.system(f"mkdir -p {isp_constants.OUTPUT_PATH.value}") diff --git a/pipelines/datasets/br_stf_corte_aberta/flows.py b/pipelines/datasets/br_stf_corte_aberta/flows.py index 2e58c7333..256d04f4b 100644 --- a/pipelines/datasets/br_stf_corte_aberta/flows.py +++ b/pipelines/datasets/br_stf_corte_aberta/flows.py @@ -12,18 +12,20 @@ from pipelines.constants import constants from pipelines.datasets.br_stf_corte_aberta.schedules import every_day_stf from pipelines.datasets.br_stf_corte_aberta.tasks import ( - check_for_updates, download_and_transform, + get_data_source_stf_max_date, make_partitions, ) from pipelines.utils.constants import constants as utils_constants from pipelines.utils.decorators import Flow from pipelines.utils.execute_dbt_model.constants import constants as dump_db_constants -from pipelines.utils.metadata.tasks import update_django_metadata +from pipelines.utils.metadata.tasks import ( + check_if_data_is_outdated, + update_django_metadata, +) from pipelines.utils.tasks import ( create_table_and_upload_to_gcs, get_current_flow_labels, - log_task, rename_current_flow_run_dataset_table, ) @@ -44,15 +46,16 @@ prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id ) - dados_desatualizados = check_for_updates( - dataset_id=dataset_id, table_id=table_id, upstream_tasks=[rename_flow_run] + data_source_max_date = get_data_source_stf_max_date() + + dados_desatualizados = check_if_data_is_outdated( + dataset_id=dataset_id, + table_id=table_id, + data_source_max_date=data_source_max_date, + date_format="%Y-%m-%d", + upstream_tasks=[data_source_max_date], ) - log_task(f"Checando se os dados estão desatualizados: {dados_desatualizados}") - with case(dados_desatualizados, False): - log_task( - "Dados atualizados, não é necessário fazer o download", - upstream_tasks=[dados_desatualizados, rename_flow_run], - ) + with case(dados_desatualizados, True): df = download_and_transform(upstream_tasks=[rename_flow_run]) output_path = make_partitions(df=df, upstream_tasks=[df]) diff --git a/pipelines/datasets/br_stf_corte_aberta/tasks.py b/pipelines/datasets/br_stf_corte_aberta/tasks.py index f4c16542f..01eb5d585 100644 --- a/pipelines/datasets/br_stf_corte_aberta/tasks.py +++ b/pipelines/datasets/br_stf_corte_aberta/tasks.py @@ -4,7 +4,6 @@ """ from datetime import datetime, timedelta -import pandas as pd from prefect import task from pipelines.constants import constants @@ -12,7 +11,6 @@ from pipelines.datasets.br_stf_corte_aberta.utils import ( check_for_data, column_bool, - extract_last_date, fix_columns_data, partition_data, read_csv, @@ -26,25 +24,10 @@ max_retries=constants.TASK_MAX_RETRIES.value, retry_delay=timedelta(seconds=constants.TASK_RETRY_DELAY.value), ) -def check_for_updates(dataset_id, table_id): +def get_data_source_stf_max_date(): data_obj = check_for_data() data_obj = datetime.strptime(data_obj, "%Y-%m-%d").date() - # Obtém a última data no site BD - data_bq_obj = extract_last_date( - dataset_id=dataset_id, - table_id=table_id, - date_format="yy-mm-dd", - billing_project_id="basedosdados", - data="data_decisao", - ) - # Registra a data mais recente do site - log(f"Última data no site do STF: {data_obj}") - log(f"Última data no site da BD: {data_bq_obj}") - # Compara as datas para verificar se há atualizações - if data_obj > data_bq_obj: - return True # Há atualizações disponíveis - else: - return False # Não há novas atualizações disponíveis + return data_obj @task( diff --git a/pipelines/datasets/br_stf_corte_aberta/utils.py b/pipelines/datasets/br_stf_corte_aberta/utils.py index 941d03530..adac225c7 100644 --- a/pipelines/datasets/br_stf_corte_aberta/utils.py +++ b/pipelines/datasets/br_stf_corte_aberta/utils.py @@ -6,7 +6,6 @@ import time from datetime import datetime -import basedosdados as bd import numpy as np import pandas as pd from selenium import webdriver @@ -122,68 +121,6 @@ def partition_data(df: pd.DataFrame, column_name: list[str], output_directory: s ) -def extract_last_date( - dataset_id, table_id, date_format: str, billing_project_id: str, data: str = "data" -): - """ - Extracts the last update date of a given dataset table. - Args: - dataset_id (str): The ID of the dataset. - table_id (str): The ID of the table. - date_format (str): Date format ('yy-mm' or 'yy-mm-dd') - if set to 'yy-mm' the function will look for ano and mes named columns in the table_id - and return a concatenated string in the formar yyyy-mm. if set to 'yyyy-mm-dd' - the function will look for data named column in the format 'yyyy-mm-dd' and return it. - Returns: - str: The last update date in the format 'yyyy-mm' or 'yyyy-mm-dd'. - Raises: - Exception: If an error occurs while extracting the last update date. - """ - if date_format == "yy-mm": - try: - query_bd = f""" - SELECT - MAX(CONCAT(ano,"-",mes)) as max_date - FROM - `{billing_project_id}.{dataset_id}.{table_id}` - """ - t = bd.read_sql( - query=query_bd, - billing_project_id=billing_project_id, - from_file=True, - ) - input_date_str = t["max_date"][0] - date_obj = datetime.strptime(input_date_str, "%Y-%m") - last_date = date_obj.strftime("%Y-%m") - log(f"Última data YYYY-MM: {last_date}") - return last_date - except Exception as e: - log(f"An error occurred while extracting the last update date: {str(e)}") - raise - else: - try: - query_bd = f""" - SELECT - MAX({data}) as max_date - FROM - `{billing_project_id}.{dataset_id}.{table_id}` - """ - log(f"Query: {query_bd}") - t = bd.read_sql( - query=query_bd, - billing_project_id=billing_project_id, - from_file=True, - ) - # it infers that the data variable is already on basedosdados standart format - # yyyy-mm-dd - last_date = t["max_date"][0] - log(f"Última data YYYY-MM-DD: {last_date}") - return last_date - except Exception as e: - log(f"An error occurred while extracting the last update date: {str(e)}") - raise - - def check_for_data(): log("Iniciando web scrapping") web_scrapping() diff --git a/pipelines/datasets/cross_update/flows.py b/pipelines/datasets/cross_update/flows.py index 532478b24..7ac447763 100644 --- a/pipelines/datasets/cross_update/flows.py +++ b/pipelines/datasets/cross_update/flows.py @@ -4,6 +4,8 @@ """ # pylint: disable=invalid-name,line-too-long +from datetime import timedelta + from prefect import Parameter, case, unmapped from prefect.run_configs import KubernetesRun from prefect.storage import GCS @@ -12,30 +14,56 @@ from pipelines.constants import constants from pipelines.datasets.cross_update.schedules import schedule_nrows from pipelines.datasets.cross_update.tasks import ( - crawler_tables, - datasearch_json, - rename_blobs, - update_nrows, + filter_eligible_download_tables, + get_metadata_data, + query_tables, ) from pipelines.utils.constants import constants as utils_constants from pipelines.utils.decorators import Flow -from pipelines.utils.tasks import get_current_flow_labels +from pipelines.utils.execute_dbt_model.constants import constants as dump_db_constants +from pipelines.utils.metadata.tasks import update_django_metadata +from pipelines.utils.tasks import ( + create_table_and_upload_to_gcs, + get_current_flow_labels, + rename_current_flow_run_dataset_table, +) with Flow( - name="cross_update.update_nrows", code_owners=["lucas_cr"] + name="cross_update.update_nrows", code_owners=["lauris"] ) as crossupdate_nrows: dump_to_gcs = Parameter("dump_to_gcs", default=False, required=False) + update_metadata_table = Parameter( + "update_metadata_table", default=False, required=False + ) days = Parameter("days", default=7, required=False) mode = Parameter("mode", default="prod", required=False) - page_size = Parameter("page_size", default=100, required=False) + current_flow_labels = get_current_flow_labels() + + # Atualiza a tabela que contem os metadados do BQ + with case(update_metadata_table, True): + update_metadata_table_flow = create_flow_run( + flow_name="cross_update.update_metadata_table", + project_name=constants.PREFECT_DEFAULT_PROJECT.value, + parameters={"materialization_mode": mode}, + labels=current_flow_labels, + ) + + wait_for_create_table = wait_for_flow_run( + update_metadata_table_flow, + stream_states=True, + stream_logs=True, + raise_final_state=True, + ) + + # Consulta e seleciona apenas as tabelas que atendem os critérios de tamanho e abertura(bdpro) - json_response = datasearch_json(page_size=page_size, mode=mode) - updated_tables, tables_to_zip = crawler_tables(json_response, days=days) - updated_tables.set_upstream(json_response) - update_nrows.map(updated_tables, mode=unmapped(mode)) + eligible_to_zip_tables = query_tables(days=days, mode=mode) + tables_to_zip = filter_eligible_download_tables( + eligible_to_zip_tables, upstream_tasks=[eligible_to_zip_tables] + ) + # Para cada tabela selecionada cria um flow de dump para gcs with case(dump_to_gcs, True): - current_flow_labels = get_current_flow_labels() dump_to_gcs_flow = create_flow_run.map( flow_name=unmapped(utils_constants.FLOW_DUMP_TO_GCS_NAME.value), project_name=unmapped(constants.PREFECT_DEFAULT_PROJECT.value), @@ -51,9 +79,85 @@ raise_final_state=unmapped(True), ) - rename_blobs(upstream_tasks=[wait_for_dump_to_gcs]) - crossupdate_nrows.storage = GCS(str(constants.GCS_FLOWS_BUCKET.value)) crossupdate_nrows.run_config = KubernetesRun(image=str(constants.DOCKER_IMAGE.value)) -# crossupdate_nrows.schedule = schedule_nrows +crossupdate_nrows.schedule = schedule_nrows + +with Flow( + name="cross_update.update_metadata_table", code_owners=["lauris"] +) as crossupdate_update_metadata_table: + dataset_id = Parameter("dataset_id", default="br_bd_metadados", required=False) + table_id = Parameter("table_id", default="bigquery_tables", required=False) + update_metadata = Parameter("update_metadata", default=False, required=False) + materialization_mode = Parameter( + "materialization_mode", default="dev", required=False + ) + materialize_after_dump = Parameter( + "materialize_after_dump", default=True, required=False + ) + dbt_alias = Parameter("dbt_alias", default=True, required=False) + + rename_flow_run = rename_current_flow_run_dataset_table( + prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id + ) + + file_path = get_metadata_data( + mode=materialization_mode, upstream_tasks=[materialization_mode] + ) + + wait_upload_table = create_table_and_upload_to_gcs( + data_path=file_path, + dataset_id=dataset_id, + table_id=table_id, + dump_mode="append", + upstream_tasks=[file_path], + ) + + with case(materialize_after_dump, True): + # Trigger DBT flow run + current_flow_labels = get_current_flow_labels() + materialization_flow = create_flow_run( + flow_name=utils_constants.FLOW_EXECUTE_DBT_MODEL_NAME.value, + project_name=constants.PREFECT_DEFAULT_PROJECT.value, + parameters={ + "dataset_id": dataset_id, + "table_id": table_id, + "mode": materialization_mode, + "dbt_alias": dbt_alias, + }, + labels=current_flow_labels, + run_name=f"Materialize {dataset_id}.{table_id}", + upstream_tasks=[wait_upload_table], + ) + + wait_for_materialization = wait_for_flow_run( + materialization_flow, + stream_states=True, + stream_logs=True, + raise_final_state=True, + ) + + wait_for_materialization.max_retries = ( + dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_ATTEMPTS.value + ) + + wait_for_materialization.retry_delay = timedelta( + seconds=dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_INTERVAL.value + ) + + with case(update_metadata, True): + update_django_metadata( + dataset_id=dataset_id, + table_id=table_id, + coverage_type="all_free", + prefect_mode=materialization_mode, + bq_project="basedosdados", + historical_database=False, + ) + + +crossupdate_update_metadata_table.storage = GCS(str(constants.GCS_FLOWS_BUCKET.value)) +crossupdate_update_metadata_table.run_config = KubernetesRun( + image=str(constants.DOCKER_IMAGE.value) +) diff --git a/pipelines/datasets/cross_update/schedules.py b/pipelines/datasets/cross_update/schedules.py index 78374f2b5..62388aa3e 100644 --- a/pipelines/datasets/cross_update/schedules.py +++ b/pipelines/datasets/cross_update/schedules.py @@ -3,27 +3,27 @@ Schedules for br_tse_eleicoes """ -from datetime import datetime, timedelta +from datetime import datetime from prefect.schedules import Schedule -from prefect.schedules.clocks import IntervalClock +from prefect.schedules.clocks import CronClock from pipelines.constants import constants schedule_nrows = Schedule( clocks=[ - IntervalClock( - interval=timedelta(days=7), - start_date=datetime(2021, 1, 1, 9, 45), + CronClock( + cron="0 8 * * 2", + start_date=datetime(2023, 5, 1, 7, 30), labels=[ - str(constants.BASEDOSDADOS_PROD_AGENT_LABEL.value), + constants.BASEDOSDADOS_PROD_AGENT_LABEL.value, ], parameter_defaults={ "dump_to_gcs": True, - "days": 7, "mode": "prod", - "page_size": 100, + "days": 7, + "update_metadata_table": True, }, ), - ], + ] ) diff --git a/pipelines/datasets/cross_update/tasks.py b/pipelines/datasets/cross_update/tasks.py index ec63c54e1..257087731 100644 --- a/pipelines/datasets/cross_update/tasks.py +++ b/pipelines/datasets/cross_update/tasks.py @@ -2,213 +2,179 @@ """ Tasks for cross update of metadata. """ -import datetime import re -from datetime import timedelta # pylint: disable=invalid-name, too-many-locals -from typing import Dict, List, Tuple +from typing import Dict, List import basedosdados as bd -import ruamel.yaml as ryaml +import pandas as pd from google.cloud import storage from prefect import task from tqdm import tqdm -from pipelines.datasets.cross_update.utils import _safe_fetch -from pipelines.utils.dump_to_gcs.constants import constants as dump_to_gcs_constants +from pipelines.datasets.cross_update.utils import find_closed_tables, save_file from pipelines.utils.utils import log @task -def datasearch_json(page_size: int, mode: str) -> Dict: +def query_tables(days: int = 7, mode: str = "dev") -> List[Dict[str, str]]: """ - This task uses `bd_dataset_search` website API - enpoint to retrieve a list of tables updated in last 7 days. - Args: - page_size (int): Number of tables to be retrieved in each request. - mode (str): prod or staging - Returns: - dict with api response + Queries BigQuery Tables metadata to find elegible tables to zip. """ - if mode == "prod": - url = "https://basedosdados.org/api/3/action/bd_dataset_search" - elif mode == "dev": - url = "https://staging.basedosdados.org/api/3/action/bd_dataset_search" - else: - raise ValueError("mode must be prod or dev") - url = f"{url}?q=&resource_type=bdm_table&page=1&page_size={page_size}" # pylint: disable=C0301 - response = _safe_fetch(url) - json_response = response.json() - - return json_response - - -@task(nout=2) -def crawler_tables( - json_response: dict, days: int = 7 -) -> Tuple[List[Dict[str, str]], List[Dict[str, str]]]: - """Generate a list of dicts like {"dataset_id": "dataset_id", "table_id": "table_id"} - where all tables were update in the last 7 days + + if mode == "dev": + billing_project_id = "basedosdados-dev" + elif mode == "prod": + billing_project_id = "basedosdados" + + query = f""" + SELECT + dataset_id, + table_id, + row_count, + size_bytes + FROM `basedosdados.br_bd_metadados.bigquery_tables` + WHERE + dataset_id NOT IN ("analytics_295884852","logs") AND + DATE_DIFF(CURRENT_DATE(),last_modified_date,DAY) <= {days} """ - # the line below returns the full number of datasets, despite the page_size this approach - # leads to an IndexError when the number of datasets is greater than page_size (in the flow) - # n_datasets = json_response["result"]["count"] - - # changed n_datasets to the actual number of datasets, limited by page_size - n_datasets = len(json_response["result"]["datasets"]) - n_resources = [ - json_response["result"]["datasets"][k]["num_resources"] - for k in range(n_datasets) - ] - datasets = json_response["result"]["datasets"] - bdm_tables = [] - for i in range(n_datasets): - for j in range(n_resources[i]): - if datasets[i]["resources"][j]["resource_type"] == "bdm_table": - bdm_tables.append(datasets[i]["resources"][j]) - - log(f"Found {len(bdm_tables)} bdm tables") - log(bdm_tables[0].keys()) - to_update = [] - for bdm_table in bdm_tables: - # skip if dataset_id, table_id, last_updated, and number of rows are not in the bdm_table keys - if not all( - key in bdm_table.keys() - for key in ["dataset_id", "table_id", "metadata_modified", "number_rows"] - ): - continue - tmp_dict = { - "dataset_id": bdm_table["dataset_id"], - "table_id": bdm_table["table_id"], - "last_updated": bdm_table["metadata_modified"], - "number_rows": bdm_table["number_rows"], - } - to_update.append(tmp_dict) - - # filter list of dictionaries by last_updated and remove older than X days - today = datetime.datetime.today() - seven_days_ago = today - timedelta(days=days) - to_update = [ - x - for x in to_update - if datetime.datetime.strptime(x["last_updated"], "%Y-%m-%dT%H:%M:%S.%f") - > seven_days_ago - ] - log(f"Found {len(to_update)} tables updated in last {days} days") - - to_zip = [] - for bdm_table in to_update: - tmp_dict = { - "dataset_id": bdm_table["dataset_id"], - "table_id": bdm_table["table_id"], - "project_id": "basedosdados", - "maximum_bytes_processed": dump_to_gcs_constants.MAX_BYTES_PROCESSED_PER_TABLE.value, - "number_rows": bdm_table["number_rows"], - } - to_zip.append(tmp_dict) - - # remove tables where number of rows is None - to_zip = [x for x in to_zip if x["number_rows"] is not None] - # keep only tables with less than 200k lines - to_zip = [x for x in to_zip if x["number_rows"] <= 200000] - - log(f"Found {len(to_zip)} tables to zip") - for table in to_zip: - log( - f"Zipping: dataset_id: {table['dataset_id']}, table_id: {table['table_id']}" - ) + tables = bd.read_sql( + query=query, + billing_project_id=billing_project_id, + from_file=True, + ) - for x in to_zip: - del x["number_rows"] + log(f"Found {len(tables)} eligible tables to zip") - for x in to_update: - del x["number_rows"] - del x["last_updated"] + to_zip = tables.to_dict("records") - return (to_update, to_zip) + return to_zip @task -def update_nrows(table_dict: Dict[str, str], mode: str) -> None: - """Get number of rows in a table +def rename_blobs() -> None: + """Rename blobs in basedosdados-dev bucket""" + storage_client = storage.Client() - Args: - table_dict (Dict[str, str]): Dict with dataset_id and table_id - mode (str): prod or dev - Returns: - None - """ - dataset_id = table_dict["dataset_id"] - table_id = table_dict["table_id"] - config_map = {} - if mode == "prod": - config_map.update({"database": f"basedosdados.{dataset_id}.{table_id}"}) - config_map.update({"project_id": "basedosdados"}) - elif mode == "dev": - config_map.update( - {"database": f"basedosdados-dev.{dataset_id}_staging.{table_id}"} - ) - config_map.update({"project_id": "basedosdados-dev"}) - else: - raise ValueError("mode must be prod or dev") + bucket = storage_client.get_bucket("basedosdados-public") + blobs = bucket.list_blobs(prefix="one-click-download/") + + for blob in tqdm(list(blobs)): + table_id = blob.name.split("/")[-2] + new_name = re.sub(r"data0*\.csv\.gz", table_id + ".csv.gz", blob.name) + bucket.rename_blob(blob, new_name) - # ideally, we would consume the API to get the number of rows, - # but it is not available yet. - # See: https://stackoverflow.com/questions/69313542/num-rows-issue-for-views-in-big-query-python-library - query = f"SELECT COUNT(*) AS n_rows FROM `{config_map['database']}`" - n_rows = bd.read_sql( - query=query, billing_project_id=config_map["project_id"], from_file=True - )["n_rows"].to_list()[0] - fields_to_update = [{"number_rows": int(n_rows)}] +@task +def get_metadata_data(mode: str = "dev") -> str: + """ + Fetches metadata about BigQuery tables and saves it as a file. - # add credentials to config.toml - # TODO: remove this because bd 2.0 does not have Metadata class - handle = bd.Metadata(dataset_id=dataset_id, table_id=table_id) - handle.create(if_exists="replace") + Returns: + - str: The full file path where the metadata file is saved. - yaml = ryaml.YAML() - yaml.preserve_quotes = True - yaml.indent(mapping=4, sequence=6, offset=4) + This function retrieves metadata information for BigQuery tables. It queries the INFORMATION_SCHEMA + to obtain a list of schema names and then retrieves metadata about tables within those schemas. + The fetched metadata includes information such as table names, sizes, and other properties. + The data is then saved as a file. - config_file = handle.filepath.as_posix() + Note: + - The function uses the batch method to efficiently retrieve metadata for tables in batches + to avoid API limitations or timeouts. + """ - with open(config_file, encoding="utf-8") as fp: - data = yaml.load(fp) + if mode == "dev": + billing_project_id = "basedosdados-dev" + elif mode == "prod": + billing_project_id = "basedosdados" - # log(data) + schema_names_query = """ + SELECT schema_name FROM `basedosdados`.INFORMATION_SCHEMA.SCHEMATA + """ - for field in fields_to_update: - for k, v in field.items(): - if isinstance(v, dict): - for i, j in v.items(): - data[k][i] = j - else: - data[k] = v + log(schema_names_query) + schema_names_list = bd.read_sql( + query=schema_names_query, + billing_project_id=billing_project_id, + from_file=True, + )["schema_name"] + + def batch(lst, n): + for i in range(0, len(lst), n): + yield lst[i : i + n] + + df_list = [] + for schema_batch in batch(schema_names_list, 50): + query = "" + for schema_name in schema_batch: + query += f"SELECT * FROM `basedosdados.{schema_name}.__TABLES__` UNION ALL " + query = query[:-11] + batch_df = bd.read_sql( + query=query, + billing_project_id=billing_project_id, + from_file=True, + ) + df_list.append(batch_df) - with open(config_file, "w", encoding="utf-8") as fp: - yaml.dump(data, fp) + df = pd.concat(df_list, ignore_index=True) - # log(data) + full_filepath = save_file(df=df, table_id="bigquery_tables") - if handle.validate(): - handle.publish(if_exists="replace") - log(f"Metadata for {table_id} updated") - else: - log("Fail to validate metadata.") + return full_filepath @task -def rename_blobs() -> None: - """Rename blobs in basedosdados-dev bucket""" - storage_client = storage.Client() +def filter_eligible_download_tables(eligible_download_tables: List) -> List: + """ + Filters a list of tables to include only those that meet the following criteria: + - Registered in Django database + - Contains open rows (only rows marked as open are downloadable) + - Size is smaller than 5GB and has fewer than 200K rows + - Contains row information in BigQuery + """ - bucket = storage_client.get_bucket("basedosdados-public") - blobs = bucket.list_blobs(prefix="one-click-download/") + backend = bd.Backend(graphql_url="https://api.basedosdados.org/api/v1/graphql") + all_closed_tables = find_closed_tables(backend) + remove_from_eligible_download_table = [] - for blob in tqdm(list(blobs)): - table_id = blob.name.split("/")[-2] - new_name = re.sub(r"data0*\.csv\.gz", table_id + ".csv.gz", blob.name) - bucket.rename_blob(blob, new_name) + for table in eligible_download_tables: + table["table_django_id"] = backend._get_table_id_from_name( + gcp_dataset_id=table["dataset_id"], gcp_table_id=table["table_id"] + ) + + if table["table_django_id"] is None: + remove_from_eligible_download_table.append(table) + + elif table["row_count"] > 200000 or table["size_bytes"] > 5000000000: + remove_from_eligible_download_table.append(table) + log(f"{table['dataset_id']}.{table['table_id']} is too big to zip") + + elif table["table_django_id"] in all_closed_tables: + remove_from_eligible_download_table.append(table) + log(f"{table['dataset_id']}.{table['table_id']} is all closed") + + elif table["row_count"] == 0: + remove_from_eligible_download_table.append(table) + log( + f"{table['dataset_id']}.{table['table_id']} missing information about number of rows" + ) + + # etapa removida pq essa funçao foi desenvolvida no backend da BD, + # mantive aqui para caso seja necessario inclui-la novamente em outro momento + # if table["table_django_id"] is not None: + # modify_table_metadata(table, backend) + + log(f"Removed {len(remove_from_eligible_download_table)} tables") + eligible_download_tables = [ + table + for table in eligible_download_tables + if table not in remove_from_eligible_download_table + ] + + log(f"Found {len(eligible_download_tables)} tables to zip") + for table in eligible_download_tables: + log(f"{table['dataset_id']}.{table['table_id']}") + + return eligible_download_tables diff --git a/pipelines/datasets/cross_update/utils.py b/pipelines/datasets/cross_update/utils.py index 1db767be4..9191766b3 100644 --- a/pipelines/datasets/cross_update/utils.py +++ b/pipelines/datasets/cross_update/utils.py @@ -2,24 +2,170 @@ """ Utils for cross_update pipeline """ -import requests +import os +import pandas as pd +from pandas import json_normalize -def _safe_fetch(url: str): +from pipelines.utils.utils import get_credentials_from_secret, log + + +def save_file(df: pd.DataFrame, table_id: str) -> str: """ - Safely fetchs urls and, if somehting goes wrong, informs user what is the possible cause + Saves a DataFrame as a CSV file. + + Args: + df (pd.DataFrame): The DataFrame to be saved. + table_id (str): The identifier for the table. + + Returns: + str: The full file path of the saved CSV file. + """ - response = None - try: - response = requests.get(url, timeout=300) - response.raise_for_status() - except requests.exceptions.HTTPError as errh: - print("Http Error:", errh) - except requests.exceptions.ConnectionError as errc: - print("Error Connecting:", errc) - except requests.exceptions.Timeout as errt: - print("Timeout Error:", errt) - except requests.exceptions.RequestException as err: - print("This url doesn't appear to exists:", err) - - return response + + # Define the folder path for storing the file + folder = f"tmp/{table_id}" + # Create the folder if it doesn't exist + os.system(f"mkdir -p {folder}") + # Define the full file path for the CSV file + full_filepath = f"{folder}/{table_id}.csv" + # Save the DataFrame as a CSV file + df.to_csv(full_filepath, index=False) + log("save_input") + return full_filepath + + +def batch(lst, n): + for i in range(0, len(lst), n): + yield lst[i : i + n] + + +def find_closed_tables(backend): + query = """ + query { + allCoverage(isClosed: false, table_Id_Isnull:false, datetimeRanges_Id_Isnull:false) { + edges { + node { + table { + _id + name + isClosed + dataset { + name + } + } + datetimeRanges { + edges { + node { + id + startYear + startMonth + startDay + endYear + endMonth + endDay + } + } + } + } + } + } + }""" + + response = backend._execute_query(query=query) + response = backend._simplify_graphql_response(response)["allCoverage"] + data = json_normalize(response) + open_tables = data["table._id"].tolist() + + query = """ + query { + allCoverage(isClosed: true, table_Id_Isnull:false, datetimeRanges_Id_Isnull:false) { + edges { + node { + table { + _id + name + isClosed + dataset { + name + } + } + datetimeRanges { + edges { + node { + id + } + } + } + } + } + } + }""" + + response = backend._execute_query(query=query) + response = backend._simplify_graphql_response(response)["allCoverage"] + data = json_normalize(response) + closed_tables = data["table._id"].tolist() + + all_closed_tables = [table for table in closed_tables if table not in open_tables] + + return all_closed_tables + + +def modify_table_metadata(table, backend): + mutation = """ + mutation($input: CreateUpdateTableInput!) { + CreateUpdateTable(input: $input) { + errors { + field, + messages + }, + clientMutationId, + table { + id, + } + } + } + """ + + # colocando essa condição porque o graphql nao aceita valores maiores do que esse para os campos "uncompressedFileSize" e "numberRows" + if table["size_bytes"] > 2147483647: + table["size_bytes"] = None + + if table["row_count"] > 2147483647: + table["row_count"] = None + + mutation_parameters = { + "id": table["table_django_id"], + "numberRows": table["row_count"], + "uncompressedFileSize": table["size_bytes"], + } + + response = backend._execute_query( + query=mutation, + variables={"input": mutation_parameters}, + headers=get_headers(backend), + ) + + if response is None: + log(table) + + +def get_headers(backend): + credentials = get_credentials_from_secret(secret_path="api_user_prod") + + mutation = """ + mutation ($email: String!, $password: String!) { + tokenAuth(email: $email, password: $password) { + token + } + } + """ + variables = {"email": credentials["email"], "password": credentials["password"]} + + response = backend._execute_query(query=mutation, variables=variables) + token = response["tokenAuth"]["token"] + + header_for_mutation_query = {"Authorization": f"Bearer {token}"} + + return header_for_mutation_query diff --git a/pipelines/datasets/mundo_transfermarkt_competicoes/constants.py b/pipelines/datasets/mundo_transfermarkt_competicoes/constants.py index 2ef29374b..8149d1eeb 100644 --- a/pipelines/datasets/mundo_transfermarkt_competicoes/constants.py +++ b/pipelines/datasets/mundo_transfermarkt_competicoes/constants.py @@ -95,3 +95,27 @@ class constants(Enum): # pylint: disable=c0103 "chutes_fora_man", "chutes_fora_vis", ] + COLUMNS_MAPPING = { + "ht": "time_man", + "at": "time_vis", + "fthg": "gols_man", + "ftag": "gols_vis", + "col_home": "colocacao_man", + "col_away": "colocacao_vis", + "ac": "escanteios_vis", + "hc": "escanteios_man", + "adef": "defesas_vis", + "hdef": "defesas_man", + "af": "faltas_vis", + "afk": "chutes_bola_parada_vis", + "aimp": "impedimentos_vis", + "as": "chutes_vis", + "asofft": "chutes_fora_vis", + "hf": "faltas_man", + "hfk": "chutes_bola_parada_man", + "himp": "impedimentos_man", + "hs": "chutes_man", + "hsofft": "chutes_fora_man", + "htag": "gols_1_tempo_vis", + "hthg": "gols_1_tempo_man", + } diff --git a/pipelines/datasets/mundo_transfermarkt_competicoes/utils.py b/pipelines/datasets/mundo_transfermarkt_competicoes/utils.py index fa458d571..a00eef144 100644 --- a/pipelines/datasets/mundo_transfermarkt_competicoes/utils.py +++ b/pipelines/datasets/mundo_transfermarkt_competicoes/utils.py @@ -341,6 +341,33 @@ def valor_vazio(df): return df +def rename_columns(df): + df = df.rename(columns=mundo_constants.COLUMNS_MAPPING.value) + return df + + +def clean_column(column): + column = column.str.replace(r"['\":.mTh]", "", regex=True) + column = column.replace("", None) + return column + + +def extract_additional_columns(df_valor): + df_valor["idade_media_titular_vis"] = clean_column( + df_valor["idade_media_titular_vis"] + ) + df_valor["idade_media_titular_man"] = clean_column( + df_valor["idade_media_titular_man"] + ) + df_valor["valor_equipe_titular_man"] = clean_column( + df_valor["valor_equipe_titular_man"] + ) + df_valor["valor_equipe_titular_vis"] = clean_column( + df_valor["valor_equipe_titular_vis"] + ) + return df_valor + + # ! Código principal da coleta do Brasileirão async def execucao_coleta(): """ @@ -384,12 +411,16 @@ async def execucao_coleta(): site_data = requests.get(base_url.format(season=season), headers=headers) soup = BeautifulSoup(site_data.content, "html.parser") link_tags = soup.find_all("a", attrs={"class": "ergebnis-link"}) + link_tags2 = soup.find_all("a", attrs={"title": "Match preview"}) for tag in link_tags: links.append(re.sub(r"\s", "", tag["href"])) + for tag in link_tags2: + links.append(re.sub(r"\s", "", tag["href"])) if len(links) % 10 != 0: num_excess = len(links) % 10 del links[-num_excess:] tabela = soup.findAll("div", class_="box") + for i in range(1, int(len(links) / 10) + 1): for row in tabela[i].findAll("tr"): # para tudo que estiver em cells = row.findAll("td") # variável para encontrar @@ -400,28 +431,31 @@ async def execucao_coleta(): ) # iterando sobre cada linha at_tag.append(cells[6].findAll(text=True)) # iterando sobre cada linha - for time in range(len(links)): - ht.append(str(ht_tag[time][2])) - col_home.append(str(ht_tag[time][0])) - for time in range(len(links)): + for time in range(380): + try: + ht.append(str(ht_tag[time][2])) + col_home.append(str(ht_tag[time][0])) + except Exception: + ht.append(str(ht_tag[time][0])) + str_vazio = "" + col_home.append(str(str_vazio)) + for time in range(380): at.append(str(at_tag[time][0])) - col_away.append(str(at_tag[time][2])) + try: + col_away.append(str(at_tag[time][2])) + except Exception: + str_vazio = "" + col_away.append(str(str_vazio)) + for tag in result_tag: fthg.append(str(pattern_fthg.findall(str(tag)))) ftag.append(str(pattern_ftag.findall(str(tag)))) + # Gerando os links para coletar dados sobre estatística e dados gerais # links das estatísticas - links_esta = [] + links_esta = [link.replace("index", "statistik") for link in links] # links das escalações de cada partida - links_valor = [] - - # Gerando os links para coletar dados sobre estatística e dados gerais - for link in links: - esta = link.replace("index", "statistik") - links_esta.append(esta) - for link in links: - valor = link.replace("index", "aufstellung") - links_valor.append(valor) + links_valor = [link.replace("index", "aufstellung") for link in links] n_links = len(links) log(f"Encontrados {n_links} partidas.") @@ -430,6 +464,7 @@ async def execucao_coleta(): for n, link in enumerate(links_esta): # Tentativas de obter os links content = await get_content(base_link + link, wait_time=0.01) + # log(content) if content: try: df = process(df, content) @@ -441,10 +476,12 @@ async def execucao_coleta(): else: df = vazio(df) log(f"{n+1} dados de {n_links} extraídos.") + # Segundo loop: Dados gerais for n, link in enumerate(links_valor): # Tentativas de obter os links content = await get_content(base_link + link, wait_time=0.01) + # log(content) if content: try: df_valor = pegar_valor(df_valor, content) @@ -481,32 +518,7 @@ async def execucao_coleta(): df["htag"] = df["htag"].map(lambda x: str(x).replace(")", "")) df["hthg"] = df["hthg"].map(lambda x: str(x).replace("(", "")) - df_valor["idade_media_titular_vis"] = df_valor["idade_media_titular_vis"].map( - lambda x: str(x).replace(" ", "") - ) - df_valor["idade_media_titular_man"] = df_valor["idade_media_titular_man"].map( - lambda x: str(x).replace(" ", "") - ) - - df_valor["valor_equipe_titular_man"] = df_valor["valor_equipe_titular_man"].map( - lambda x: str(x).replace("m", "0000") - ) - df_valor["valor_equipe_titular_man"] = df_valor["valor_equipe_titular_man"].map( - lambda x: str(x).replace("Th.", "000") - ) - df_valor["valor_equipe_titular_man"] = df_valor["valor_equipe_titular_man"].map( - lambda x: str(x).replace(".", "") - ) - - df_valor["valor_equipe_titular_vis"] = df_valor["valor_equipe_titular_vis"].map( - lambda x: str(x).replace("m", "0000") - ) - df_valor["valor_equipe_titular_vis"] = df_valor["valor_equipe_titular_vis"].map( - lambda x: str(x).replace("Th.", "000") - ) - df_valor["valor_equipe_titular_vis"] = df_valor["valor_equipe_titular_vis"].map( - lambda x: str(x).replace(".", "") - ) + df_valor = extract_additional_columns(df_valor) df["publico_max"] = df["publico_max"].map(lambda x: str(x).replace(".", "")) df["publico"] = df["publico"].map(lambda x: str(x).replace(".", "")) @@ -524,39 +536,15 @@ def sem_info(x, y): del df["test"] df["data"] = pd.to_datetime(df["data"]).dt.date - df["horario"] = pd.to_datetime(df["horario"], format="%I:%M %p") - df["horario"] = df["horario"].dt.strftime("%H:%M") + # df["horario"] = pd.to_datetime(df["horario"], format="%I:%M %p") + # df["horario"] = df["horario"].dt.strftime("%H:%M") df.fillna("", inplace=True) - df["rodada"] = df["rodada"].astype(np.int64) + # df["rodada"] = df["rodada"].astype(np.int64) # renomear colunas - df = df.rename( - columns={ - "ht": "time_man", - "at": "time_vis", - "fthg": "gols_man", - "ftag": "gols_vis", - "col_home": "colocacao_man", - "col_away": "colocacao_vis", - "ac": "escanteios_vis", - "hc": "escanteios_man", - "adef": "defesas_vis", - "hdef": "defesas_man", - "af": "faltas_vis", - "afk": "chutes_bola_parada_vis", - "aimp": "impedimentos_vis", - "as": "chutes_vis", - "asofft": "chutes_fora_vis", - "hf": "faltas_man", - "hfk": "chutes_bola_parada_man", - "himp": "impedimentos_man", - "hs": "chutes_man", - "hsofft": "chutes_fora_man", - "htag": "gols_1_tempo_vis", - "hthg": "gols_1_tempo_man", - } - ) + df = rename_columns(df) + # Concatenando os valores dos dois loops df = pd.concat([df, df_valor], axis=1) df["data"] = pd.to_datetime(df["data"]) diff --git a/pipelines/datasets/mundo_transfermarkt_competicoes_internacionais/flows.py b/pipelines/datasets/mundo_transfermarkt_competicoes_internacionais/flows.py index 070253826..c740640a7 100644 --- a/pipelines/datasets/mundo_transfermarkt_competicoes_internacionais/flows.py +++ b/pipelines/datasets/mundo_transfermarkt_competicoes_internacionais/flows.py @@ -16,14 +16,17 @@ every_first_and_last_week, ) from pipelines.datasets.mundo_transfermarkt_competicoes_internacionais.tasks import ( - check_for_updates, execucao_coleta_sync, + get_data_source_transfermarkt_max_date, make_partitions, ) from pipelines.utils.constants import constants as utils_constants from pipelines.utils.decorators import Flow from pipelines.utils.execute_dbt_model.constants import constants as dump_db_constants -from pipelines.utils.metadata.tasks import update_django_metadata +from pipelines.utils.metadata.tasks import ( + check_if_data_is_outdated, + update_django_metadata, +) from pipelines.utils.tasks import ( create_table_and_upload_to_gcs, get_current_flow_labels, @@ -59,11 +62,15 @@ ) update_metadata = Parameter("update_metadata", default=True, required=False) - dados_desatualizados = check_for_updates(dataset_id, table_id) - log_task(f"Checando se os dados estão desatualizados: {dados_desatualizados}") + data_source_max_date = get_data_source_transfermarkt_max_date() - with case(dados_desatualizados, False): - log_task("Não há atualizações!") + dados_desatualizados = check_if_data_is_outdated( + dataset_id=dataset_id, + table_id=table_id, + data_source_max_date=data_source_max_date, + date_format="%Y-%m-%d", + upstream_tasks=[data_source_max_date], + ) with case(dados_desatualizados, True): df = execucao_coleta_sync() diff --git a/pipelines/datasets/mundo_transfermarkt_competicoes_internacionais/tasks.py b/pipelines/datasets/mundo_transfermarkt_competicoes_internacionais/tasks.py index db2f6f5ba..91b2b9124 100644 --- a/pipelines/datasets/mundo_transfermarkt_competicoes_internacionais/tasks.py +++ b/pipelines/datasets/mundo_transfermarkt_competicoes_internacionais/tasks.py @@ -6,46 +6,22 @@ ############################################################################### import asyncio -import numpy as np import pandas as pd from pandas import DataFrame from prefect import task -from pipelines.datasets.mundo_transfermarkt_competicoes_internacionais.constants import ( - constants as mundo_constants, -) from pipelines.datasets.mundo_transfermarkt_competicoes_internacionais.utils import ( data_url, execucao_coleta, ) -from pipelines.utils.utils import extract_last_date, log, to_partitions +from pipelines.utils.utils import log, to_partitions @task -def check_for_updates(dataset_id: str, table_id: str) -> bool: - """ - Verifica se existem atualizações disponíveis para um conjunto de dados e tabela específicos. - - Retorna: - bool: Retorna True se houverem atualizações disponíveis, caso contrário retorna False. - """ +def get_data_source_transfermarkt_max_date(): # Obtém a data mais recente do site data_obj = data_url().strftime("%Y-%m-%d") - - # Obtém a última data no site BD - data_bq_obj = extract_last_date( - dataset_id, table_id, "yy-mm-dd", "basedosdados" - ).strftime("%Y-%m-%d") - - # Registra a data mais recente do site - log(f"Última data no site da transfermarkt: {data_obj}") - log(f"Última data no site da BD: {data_bq_obj}") - - # Compara as datas para verificar se há atualizações - if data_obj > data_bq_obj: - return True # Há atualizações disponíveis - else: - return False # Não há novas atualizações disponíveis + return data_obj @task diff --git a/pipelines/utils/apply_architecture_to_dataframe/utils.py b/pipelines/utils/apply_architecture_to_dataframe/utils.py index 7c6532ab7..b8e16ff7a 100644 --- a/pipelines/utils/apply_architecture_to_dataframe/utils.py +++ b/pipelines/utils/apply_architecture_to_dataframe/utils.py @@ -65,6 +65,8 @@ def read_architecture_table(url_architecture: str) -> pd.DataFrame: StringIO(requests.get(url, timeout=10).content.decode("utf-8")) ) + df_architecture.query("name != '(excluido)'", inplace=True) + return df_architecture.replace(np.nan, "", regex=True) diff --git a/pipelines/utils/crawler_ibge_inflacao/tasks.py b/pipelines/utils/crawler_ibge_inflacao/tasks.py index c58ec1968..35a0e0917 100644 --- a/pipelines/utils/crawler_ibge_inflacao/tasks.py +++ b/pipelines/utils/crawler_ibge_inflacao/tasks.py @@ -11,16 +11,12 @@ from datetime import datetime as dt from time import sleep -import basedosdados as bd import pandas as pd -import wget from prefect import task from tqdm import tqdm -from pipelines.utils.crawler_ibge_inflacao.utils import ( - extract_last_date, - get_legacy_session, -) +from pipelines.utils.crawler_ibge_inflacao.utils import get_legacy_session +from pipelines.utils.metadata.utils import get_api_most_recent_date from pipelines.utils.utils import log # necessary for use wget, see: https://stackoverflow.com/questions/35569042/ssl-certificate-verify-failed-with-python3 @@ -127,13 +123,17 @@ def check_for_updates( max_date_ibge = dataframe.strftime("%Y-%m") - log(f"A data mais no site do ---IBGE--- para a tabela {indice} é : {max_date_ibge}") - # TROCAR PARA BSEDOSDADOS ANTES DE IR PRA PROD - max_date_bd = extract_last_date( - dataset_id=dataset_id, table_id=table_id, billing_project_id="basedosdados" + log( + f"A data mais no site do ---IBGE--- para a tabela {indice} é : {dataframe.date()}" ) - log(f"A data mais recente da tabela no --- Big Query --- é: {max_date_bd}") - if max_date_ibge > max_date_bd: + + max_date_bd = get_api_most_recent_date( + table_id=table_id, + dataset_id=dataset_id, + date_format="%Y-%m", + ) + log(f"A data mais recente da tabela no --- Site da BD --- é: {max_date_bd}") + if dataframe.date() > max_date_bd: log( f"A tabela {indice} foi atualizada no site do IBGE. O Flow de atualização será executado!" ) diff --git a/pipelines/utils/crawler_ibge_inflacao/utils.py b/pipelines/utils/crawler_ibge_inflacao/utils.py index 9bf040a8b..3e95f3393 100644 --- a/pipelines/utils/crawler_ibge_inflacao/utils.py +++ b/pipelines/utils/crawler_ibge_inflacao/utils.py @@ -6,14 +6,12 @@ import ssl from datetime import datetime -import basedosdados as bd import requests import urllib3 from prefect.schedules import Schedule, adjustments, filters from prefect.schedules.clocks import CronClock from pipelines.constants import constants -from pipelines.utils.utils import log def generate_inflacao_clocks(parameters: dict): @@ -62,41 +60,3 @@ def get_legacy_session(): session = requests.session() session.mount("https://", CustomHttpAdapter(ctx)) return session - - -def extract_last_date( - dataset_id: str, - table_id: str, - billing_project_id: str, -) -> str: - """ - Extracts the last update date of a given dataset table. - - Args: - dataset_id (str): The ID of the dataset. - table_id (str): The ID of the table. - billing_project_id (str): The billing project ID. - - Returns: - str: The last update date in the format 'yyyy-mm-dd'. - - Raises: - Exception: If an error occurs while extracting the last update date. - """ - - query_bd = f""" - SELECT MAX(DATE(CAST(ano AS INT64),CAST(mes AS INT64),1)) as max_date - FROM - `{billing_project_id}.{dataset_id}.{table_id}` - """ - - t = bd.read_sql( - query=query_bd, - billing_project_id=billing_project_id, - from_file=True, - ) - - data = t["max_date"][0] - data = data.strftime("%Y-%m") - - return data diff --git a/pipelines/utils/dump_to_gcs/flows.py b/pipelines/utils/dump_to_gcs/flows.py index 4bfccbb18..0a577b1c8 100644 --- a/pipelines/utils/dump_to_gcs/flows.py +++ b/pipelines/utils/dump_to_gcs/flows.py @@ -20,7 +20,7 @@ with Flow( name=utils_constants.FLOW_DUMP_TO_GCS_NAME.value, - code_owners=["lucas_cr"], + code_owners=["lauris"], ) as dump_to_gcs_flow: project_id = Parameter("project_id", required=False) dataset_id = Parameter("dataset_id") # dataset_id or dataset_id_staging diff --git a/pipelines/utils/dump_to_gcs/tasks.py b/pipelines/utils/dump_to_gcs/tasks.py index acc887780..8e1cc9788 100644 --- a/pipelines/utils/dump_to_gcs/tasks.py +++ b/pipelines/utils/dump_to_gcs/tasks.py @@ -9,6 +9,7 @@ import jinja2 from basedosdados.download.base import google_client from basedosdados.upload.base import Base +from google.api_core.exceptions import NotFound from google.cloud import bigquery from prefect import task @@ -17,6 +18,7 @@ determine_whether_to_execute_or_not, get_redis_client, human_readable, + list_blobs_with_prefix, log, ) @@ -103,32 +105,38 @@ def download_data_to_gcs( # pylint: disable=R0912,R0913,R0914,R0915 f"Billing project ID was inferred from environment variables: {billing_project_id}" ) - # Checking if data exceeds the maximum allowed size - log("Checking if data exceeds the maximum allowed size") # pylint: disable=E1124 client = google_client(billing_project_id, from_file=True, reauth=False) - job_config = bigquery.QueryJobConfig() - job_config.dry_run = True - job = client["bigquery"].query(query, job_config=job_config) - while not job.done(): - sleep(1) - table_size = job.total_bytes_processed - log(f'Table size: {human_readable(table_size, unit="B", unit_divider=1024)}') - if table_size > maximum_bytes_processed: - max_allowed_size = human_readable( - maximum_bytes_processed, - unit="B", - unit_divider=1024, - ) - raise ValueError( - f"Table size exceeds the maximum allowed size: {max_allowed_size}" + + # Try to remove bdpro access + log("Trying to remove BDpro filter") + try: + query_remove_bdpro = f"DROP ROW ACCESS POLICY bdpro_filter ON `{project_id}.{dataset_id}.{table_id}`" + log(query_remove_bdpro) + job = client["bigquery"].query(query_remove_bdpro) + while not job.done(): + sleep(1) + log(job.result()) + log( + "Table has BDpro filter and it was removed so direct download contains only open rows" ) + bdpro = True + except NotFound as e: + if "Not found: Row access policy bdpro_filter on table" in str(e): + log("It was not possible to find BDpro filter, all rows will be downloaded") + bdpro = False + else: + raise (e) + except Exception as e: + raise ValueError(e) - # Get data log("Querying data from BigQuery") job = client["bigquery"].query(query) while not job.done(): sleep(1) + + results = job.to_dataframe() + log(results.head(5)) # pylint: disable=protected-access dest_table = job._properties["configuration"]["query"]["destinationTable"] dest_project_id = dest_table["projectId"] @@ -138,7 +146,7 @@ def download_data_to_gcs( # pylint: disable=R0912,R0913,R0914,R0915 f"Query results were stored in {dest_project_id}.{dest_dataset_id}.{dest_table_id}" ) - blob_path = f"gs://basedosdados-public/one-click-download/{dataset_id}/{table_id}/data*.csv.gz" + blob_path = f"gs://basedosdados-public/one-click-download/{dataset_id}/{table_id}/{table_id}.csv.gz" log(f"Loading data to {blob_path}") dataset_ref = bigquery.DatasetReference(dest_project_id, dest_dataset_id) table_ref = dataset_ref.table(dest_table_id) @@ -152,6 +160,13 @@ def download_data_to_gcs( # pylint: disable=R0912,R0913,R0914,R0915 extract_job.result() log("Data was loaded successfully") + if bdpro: + query_restore_bdpro_access = f'CREATE OR REPLACE ROW ACCESS POLICY bdpro_filter ON `{project_id}.{dataset_id}.{table_id}` GRANT TO ("group:bd-pro@basedosdados.org", "group:sudo@basedosdados.org") FILTER USING (TRUE)' + job = client["bigquery"].query(query_restore_bdpro_access) + while not job.done(): + sleep(1) + log("BDpro filter was reestored") + @task def get_project_id( diff --git a/pipelines/utils/execute_dbt_model/tasks.py b/pipelines/utils/execute_dbt_model/tasks.py index 3faa09bb7..3f05278c4 100644 --- a/pipelines/utils/execute_dbt_model/tasks.py +++ b/pipelines/utils/execute_dbt_model/tasks.py @@ -72,7 +72,11 @@ def run_dbt_model( selected_table = dataset_id if "run" in dbt_command: - run_command = f"dbt run --select {selected_table}" + if flags == "--full-refresh": + run_command = f"dbt run --full-refresh --select {selected_table}" + flags = None + else: + run_command = f"dbt run --select {selected_table}" if _vars: if isinstance(_vars, list): diff --git a/pipelines/utils/metadata/tasks.py b/pipelines/utils/metadata/tasks.py index 4c36d1ec4..9d94407ba 100644 --- a/pipelines/utils/metadata/tasks.py +++ b/pipelines/utils/metadata/tasks.py @@ -5,6 +5,7 @@ from datetime import datetime +import pandas as pd from prefect import task from pipelines.utils.metadata.utils import ( @@ -164,8 +165,9 @@ def check_if_data_is_outdated( data_source_max_date = datetime.strptime( data_source_max_date, date_format ).date() + if type(data_source_max_date) is pd.Timestamp: + data_source_max_date = data_source_max_date.date() - # antigo parse_coverage data_api = get_api_most_recent_date( dataset_id=dataset_id, table_id=table_id, date_format=date_format ) @@ -175,6 +177,15 @@ def check_if_data_is_outdated( # Compara as datas para verificar se há atualizações if data_source_max_date > data_api: + log("Há atualizações disponíveis") return True # Há atualizações disponíveis else: + log("Não há novas atualizações disponíveis") return False + + +@task +def task_get_api_most_recent_date(dataset_id, table_id, date_format): + return get_api_most_recent_date( + dataset_id=dataset_id, table_id=table_id, date_format=date_format + ) diff --git a/pipelines/utils/metadata/utils.py b/pipelines/utils/metadata/utils.py index a182ff424..235fd53b3 100644 --- a/pipelines/utils/metadata/utils.py +++ b/pipelines/utils/metadata/utils.py @@ -57,7 +57,7 @@ def get_credentials_utils(secret_path: str) -> Tuple[str, str]: """ Returns the user and password for the given secret path. """ - log(f"Getting user and password for secret path: {secret_path}") + # log(f"Getting user and password for secret path: {secret_path}") tokens_dict = get_credentials_from_secret(secret_path) email = tokens_dict.get("email") password = tokens_dict.get("password") @@ -752,7 +752,7 @@ def parse_datetime_ranges(datetime_result: dict, date_format: str) -> dict: date_objects = {} - log(f"the chosen format to parse the coverage was {date_format}") + # log(f"the chosen format to parse the coverage was {date_format}") edges = datetime_result["data"]["allCoverage"]["edges"] @@ -774,7 +774,7 @@ def parse_datetime_ranges(datetime_result: dict, date_format: str) -> dict: date_values = (end_year, end_month, end_day) date_string = format_check_date(date_values, date_format) - log(f"The following coverage is being added {date_objects}") + # log(f"The following coverage is being added {date_objects}") date_objects[dt_node["id"]] = date_string return date_objects @@ -859,9 +859,8 @@ def get_api_most_recent_date( # if not, raise ValueError if date_format not in accepted_date_format: raise ValueError( - f"The date_format ->> ->> {date_format} is not supported. Please choose between {accepted_date_format}" + f"The date_format ->> ->> {date_format} is not supported. Please choose among {accepted_date_format}" ) - log(f"The chosen date_format is ->> {date_format}") # Collect credentials_utils (email, password) = get_credentials_utils(secret_path=f"api_user_{api_mode}") @@ -876,8 +875,8 @@ def get_api_most_recent_date( api_mode, ) - # parse coverages - log(f"For the table ->>{table_id} the parsed coverages were ->> {coverages}") + # # parse coverages + # log(f"For the table ->>{table_id} the parsed coverages were ->> {coverages}") # Convert the date strings to date objects date_objects = {} @@ -885,14 +884,14 @@ def get_api_most_recent_date( date_objects[key] = datetime.strptime(date_string, date_format) # Compare the date objects, return the most recent date and format it - log( - f"For this table ->> {table_id} there are these datetime end values->> {date_objects}" - ) + # log( + # f"For this table ->> {table_id} there are these datetime end values->> {date_objects}" + # ) max_date_key = max(date_objects, key=date_objects.get) max_date_value = date_objects[max_date_key].date() - log( - f"The Most recent date for the ->> {table_id} in the prod API is ->> {max_date_value}" - ) + # log( + # f"The Most recent date for the ->> {table_id} in the prod API is ->> {max_date_value}" + # ) return max_date_value diff --git a/poetry.lock b/poetry.lock index 916e2c0bb..596215bdf 100644 --- a/poetry.lock +++ b/poetry.lock @@ -384,63 +384,63 @@ test-no-images = ["pytest", "pytest-cov", "wurlitzer"] [[package]] name = "coverage" -version = "7.3.2" +version = "7.3.3" description = "Code coverage measurement for Python" optional = false python-versions = ">=3.8" files = [ - {file = "coverage-7.3.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:d872145f3a3231a5f20fd48500274d7df222e291d90baa2026cc5152b7ce86bf"}, - {file = "coverage-7.3.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:310b3bb9c91ea66d59c53fa4989f57d2436e08f18fb2f421a1b0b6b8cc7fffda"}, - {file = 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"sha256:292d2d3783349f2b0734a0a0207b1e1e322ac193c2c09d8f7c613fb7cc501ea8"}, + {file = "google_auth_oauthlib-1.2.0-py2.py3-none-any.whl", hash = "sha256:297c1ce4cb13a99b5834c74a1fe03252e1e499716718b190f56bcb9c4abc4faf"}, ] [package.dependencies] @@ -1129,13 +1129,13 @@ tool = ["click (>=6.0.0)"] [[package]] name = "google-cloud-bigquery" -version = "3.14.0" +version = "3.14.1" description = "Google BigQuery API client library" optional = false python-versions = ">=3.7" files = [ - {file = "google-cloud-bigquery-3.14.0.tar.gz", hash = "sha256:76c919f771ac82ba372f5a8d326c032229c5fdab738d03a2b6e73b412c22c9eb"}, - {file = "google_cloud_bigquery-3.14.0-py2.py3-none-any.whl", hash = "sha256:3304f4742546be70e531232f31bbf5b4b257aa63a508101ab7c4582c9503b636"}, + {file = "google-cloud-bigquery-3.14.1.tar.gz", hash = "sha256:aa15bd86f79ea76824c7d710f5ae532323c4b3ba01ef4abff42d4ee7a2e9b142"}, + {file = "google_cloud_bigquery-3.14.1-py2.py3-none-any.whl", hash = "sha256:a8ded18455da71508db222b7c06197bc12b6dbc6ed5b0b64e7007b76d7016957"}, ] [package.dependencies] @@ -1176,13 +1176,13 @@ protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4 [[package]] name = "google-cloud-bigquery-storage" -version = "2.23.0" +version = "2.24.0" description = "Google Cloud Bigquery Storage API client library" optional = false python-versions = ">=3.7" files = [ - {file = "google-cloud-bigquery-storage-2.23.0.tar.gz", hash = "sha256:8496c6d30575efb224c18940566f9ac006d3b120ae759002918697c3407997e6"}, - {file = "google_cloud_bigquery_storage-2.23.0-py2.py3-none-any.whl", hash = "sha256:371ff0a86d6166d7a935d6839474e5b5ab04ebd6598ea4b6c12b920719f2e0cb"}, + {file = "google-cloud-bigquery-storage-2.24.0.tar.gz", hash = "sha256:b4af5b9aacd8396b8407d1b877601a376d8eea6d192823a8a7881bd2fdc076ce"}, + {file = "google_cloud_bigquery_storage-2.24.0-py2.py3-none-any.whl", hash = "sha256:7981eb2758cba56603058d11bb1eeeebf2e1c18097a7118a894510a16e02be52"}, ] [package.dependencies] @@ -1192,7 +1192,7 @@ protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4 [package.extras] fastavro = ["fastavro (>=0.21.2)"] -pandas = ["pandas (>=0.21.1)"] +pandas = ["importlib-metadata (>=1.0.0)", "pandas (>=0.21.1)"] pyarrow = ["pyarrow (>=0.15.0)"] [[package]] @@ -3980,19 +3980,19 @@ telegram = ["requests"] [[package]] name = "trio" -version = "0.23.1" +version = "0.23.2" description = "A friendly Python library for async concurrency and I/O" optional = false python-versions = ">=3.8" files = [ - {file = "trio-0.23.1-py3-none-any.whl", hash = "sha256:bb4abb3f4af23f96679e7c8cdabb8b234520f2498550d2cf63ebfd95f2ce27fe"}, - {file = "trio-0.23.1.tar.gz", hash = "sha256:16f89f7dcc8f7b9dcdec1fcd863e0c039af6d0f9a22f8dfd56f75d75ec73fd48"}, + {file = "trio-0.23.2-py3-none-any.whl", hash = "sha256:5a0b566fa5d50cf231cfd6b08f3b03aa4179ff004b8f3144059587039e2b26d3"}, + {file = "trio-0.23.2.tar.gz", hash = "sha256:da1d35b9a2b17eb32cae2e763b16551f9aa6703634735024e32f325c9285069e"}, ] [package.dependencies] attrs = ">=20.1.0" cffi = {version = ">=1.14", markers = "os_name == \"nt\" and implementation_name != \"pypy\""} -exceptiongroup = {version = ">=1.0.0rc9", markers = "python_version < \"3.11\""} +exceptiongroup = {version = "*", markers = "python_version < \"3.11\""} idna = "*" outcome = "*" sniffio = ">=1.3.0" diff --git a/pyproject.toml b/pyproject.toml index d8a2acbee..77870521a 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -113,6 +113,7 @@ geopandas = "0.13.2" shapely = "2.0.1" webdriver-manager = "^4.0.1" + [tool.poetry.dev-dependencies] pytest_cov = "^3.0.0" From ff57ade2a1cd36fdc9e19d82cf30a19c40820909 Mon Sep 17 00:00:00 2001 From: folhesgabriel Date: Thu, 14 Dec 2023 14:55:55 -0300 Subject: [PATCH 251/265] fix: basedosdados read_sql input --- pipelines/datasets/br_denatran_frota/handlers.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 1dbd34625..c8161afd1 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -197,8 +197,8 @@ def get_latest_data(table_id: str, dataset_id: str): def treat_municipio_tipo(file: str) -> pl.DataFrame: bd_municipios = bd.read_sql( "select * from `basedosdados.br_bd_diretorios_brasil.municipio`", - billing_project_id="basedosdados-dev", - # from_file=True, + # billing_project_id="basedosdados-dev", + from_file=True, ) bd_municipios = pl.from_pandas(bd_municipios) From 4153283d200f1ebdb3b055b3f7eb7b739351ba73 Mon Sep 17 00:00:00 2001 From: folhesgabriel Date: Thu, 14 Dec 2023 15:56:29 -0300 Subject: [PATCH 252/265] fix: table_id name and handlers --- pipelines/datasets/br_denatran_frota/flows.py | 10 ++++++---- pipelines/datasets/br_denatran_frota/handlers.py | 4 ++-- 2 files changed, 8 insertions(+), 6 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index 90b25fd7e..ce5220df4 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -47,7 +47,7 @@ ], ) as br_denatran_frota_uf_tipo: dataset_id = Parameter("dataset_id", default="br_denatran_frota") - table_id = Parameter("table_id", default="uf_tipo2") + table_id = Parameter("table_id", default="uf_tipo") # Materialization mode materialization_mode = Parameter( @@ -65,7 +65,7 @@ prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id ) - year_to_fetch = get_latest_data_task(table_id=table_id, dataset_id=dataset_id) + year_to_fetch = get_latest_data_task(table_id="uf_tipo", dataset_id=dataset_id) crawled = crawl_task( month=year_to_fetch[1], year=year_to_fetch[0], @@ -159,7 +159,7 @@ ], ) as br_denatran_frota_municipio_tipo: dataset_id = Parameter("dataset_id", default="br_denatran_frota") - table_id = Parameter("table_id", default="municipio_tipo2") + table_id = Parameter("table_id", default="municipio_tipo") # Materialization mode materialization_mode = Parameter( @@ -180,7 +180,9 @@ # inserir get_api_most_recente_date # na função get_latest_data - year_to_fetch = get_latest_data_task(table_id=table_id, dataset_id=dataset_id) + year_to_fetch = get_latest_data_task( + table_id="municipio_tipo", dataset_id=dataset_id + ) crawled = crawl_task( month=year_to_fetch[1], diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index c8161afd1..9f77c2618 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -102,7 +102,7 @@ def treat_uf_tipo(file: str) -> pl.DataFrame: clean_df = new_df[new_df.sigla_uf.isin(valid_ufs)].reset_index( drop=True ) # Now we get all the actual RELEVANT uf data. - month, year = get_year_month_from_filename(filename) + year, month = get_year_month_from_filename(filename) # If the df is all strings, try to get numbers where it makes sense. clean_df.replace(" - ", 0, inplace=True) if all(clean_df.dtypes == "object"): @@ -203,7 +203,7 @@ def treat_municipio_tipo(file: str) -> pl.DataFrame: bd_municipios = pl.from_pandas(bd_municipios) filename = os.path.split(file)[1] - month, year = get_year_month_from_filename(filename) + year, month = get_year_month_from_filename(filename) correct_sheet = [ sheet for sheet in pd.ExcelFile(file).sheet_names if sheet != "Glossário" ][0] From d7c29edfeaa9b9cab0d20946fb6518c4c87a5b15 Mon Sep 17 00:00:00 2001 From: folhesgabriel Date: Tue, 19 Dec 2023 10:59:05 -0300 Subject: [PATCH 253/265] feat: add schedules --- pipelines/datasets/br_denatran_frota/flows.py | 10 ++-- .../datasets/br_denatran_frota/schedules.py | 51 +++++++++++++++---- 2 files changed, 47 insertions(+), 14 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index ce5220df4..1c01339f9 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -38,10 +38,13 @@ date_pairs_param: list[tuple] = Parameter("date_pairs", default=date_pairs) -# from pipelines.datasets.br_denatran_frota.schedules import every_two_weeks - +# from pipelines.datasets.br_denatran_frota.schedules import ( +# every_month_municipio, +# every_month_uf, +# ) with Flow( name="br_denatran_frota.uf_tipo", + # todo: substituir por equipe pipelines code_owners=[ "Tamir", ], @@ -66,6 +69,7 @@ ) year_to_fetch = get_latest_data_task(table_id="uf_tipo", dataset_id=dataset_id) + crawled = crawl_task( month=year_to_fetch[1], year=year_to_fetch[0], @@ -178,8 +182,6 @@ prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id ) - # inserir get_api_most_recente_date - # na função get_latest_data year_to_fetch = get_latest_data_task( table_id="municipio_tipo", dataset_id=dataset_id ) diff --git a/pipelines/datasets/br_denatran_frota/schedules.py b/pipelines/datasets/br_denatran_frota/schedules.py index 5ae6b53bc..67d07f59a 100644 --- a/pipelines/datasets/br_denatran_frota/schedules.py +++ b/pipelines/datasets/br_denatran_frota/schedules.py @@ -2,23 +2,54 @@ """ Schedules for br_denatran_frota """ +from datetime import datetime +from prefect.schedules import Schedule, adjustments, filters +from prefect.schedules.clocks import CronClock -from datetime import datetime, timedelta +from pipelines.constants import constants -from prefect.schedules import Schedule -from prefect.schedules.clocks import IntervalClock +every_month_municipio = Schedule( + clocks=[ + CronClock( + cron="20 21 10-30 * *", # At 21:20 on every day-of-month from 10 through 30. + start_date=datetime(2023, 11, 22, 0, 0), + labels=[ + constants.BASEDOSDADOS_PROD_AGENT_LABEL.value, + ], + parameter_defaults={ + "dataset_id": "br_denatran_frota", + "table_id": "municipio_tipo", + "materialization_mode": "prod", + "materialize_after_dump": True, + "dbt_alias": True, + "update_metadata": True, + }, + ) + ], + filters=[filters.is_weekday], + adjustments=[adjustments.next_weekday], +) -from pipelines.constants import constants -every_two_weeks = Schedule( +every_month_uf = Schedule( clocks=[ - IntervalClock( - interval=timedelta(weeks=2), - start_date=datetime(2021, 1, 1), + CronClock( + cron="0 21 10-30 * *", # At 21:00 on every day-of-month from 10 through 30. + start_date=datetime(2023, 11, 22, 0, 0), labels=[ constants.BASEDOSDADOS_PROD_AGENT_LABEL.value, ], - ), - ] + parameter_defaults={ + "dataset_id": "br_denatran_frota", + "table_id": "uf_tipo", + "materialization_mode": "prod", + "materialize after dump": True, + "dbt_alias": True, + "update_metadata": True, + }, + ) + ], + filters=[filters.is_weekday], + adjustments=[adjustments.next_weekday], ) From ac20eb5963ecfc6a0ab1ce95dfe1de228a7c5b9c Mon Sep 17 00:00:00 2001 From: folhesgabriel Date: Thu, 18 Jan 2024 11:16:53 -0300 Subject: [PATCH 254/265] feat: add final flows --- .../datasets/br_denatran_frota/constants.py | 2 - pipelines/datasets/br_denatran_frota/flows.py | 80 +++++++++---------- .../datasets/br_denatran_frota/handlers.py | 68 +++++++--------- 3 files changed, 69 insertions(+), 81 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/constants.py b/pipelines/datasets/br_denatran_frota/constants.py index 6f69d6200..c7abf4aa4 100644 --- a/pipelines/datasets/br_denatran_frota/constants.py +++ b/pipelines/datasets/br_denatran_frota/constants.py @@ -11,8 +11,6 @@ class constants(Enum): # pylint: disable=c0103 Constant values for the br_denatran_frota project """ - # -*- coding: utf-8 -*- - MONTHS = { "janeiro": 1, "fevereiro": 2, diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index 1c01339f9..d67864dff 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -29,6 +29,7 @@ from pipelines.utils.tasks import ( create_table_and_upload_to_gcs, get_current_flow_labels, + log_task, rename_current_flow_run_dataset_table, ) @@ -44,7 +45,6 @@ # ) with Flow( name="br_denatran_frota.uf_tipo", - # todo: substituir por equipe pipelines code_owners=[ "Tamir", ], @@ -58,17 +58,19 @@ ) materialize_after_dump = Parameter( - "materialize after dump", default=False, required=False + "materialize_after_dump", default=False, required=False ) update_metadata = Parameter("update_metadata", default=False, required=False) dbt_alias = Parameter("dbt_alias", default=True, required=False) + rename_flow_run = rename_current_flow_run_dataset_table( prefix="Dump: ", dataset_id=dataset_id, table_id=table_id, wait=table_id ) year_to_fetch = get_latest_data_task(table_id="uf_tipo", dataset_id=dataset_id) + # search for most recent year in the API crawled = crawl_task( month=year_to_fetch[1], @@ -76,29 +78,26 @@ temp_dir=constants.DOWNLOAD_PATH.value, upstream_tasks=[year_to_fetch], ) - # Now get the downloaded file: - desired_file = get_desired_file_task( - year=year_to_fetch[0], - download_directory=constants.DOWNLOAD_PATH.value, - filetype=constants.UF_TIPO_BASIC_FILENAME.value, - upstream_tasks=[crawled], - ) - # We need to see the year, month from the file to decide on updating - extracted_date = get_denatran_date(desired_file, upstream_tasks=[desired_file]) - decision = check_if_data_is_outdated( - dataset_id=dataset_id, - table_id=table_id, - data_source_max_date=extracted_date, - date_format="%Y-%m", - upstream_tasks=[extracted_date], - ) - with case(decision, True): - df = treat_uf_tipo_task( - file=desired_file, upstream_tasks=[crawled, desired_file] + + with case(crawled, False): + log_task("No new data to be downloaded") + + with case(crawled, True): + # Now get the downloaded file: + # Used primarly to backfill data + desired_file = get_desired_file_task( + year=year_to_fetch[0], + download_directory=constants.DOWNLOAD_PATH.value, + filetype=constants.UF_TIPO_BASIC_FILENAME.value, + upstream_tasks=[crawled], ) + + df = treat_uf_tipo_task(file=desired_file, upstream_tasks=[desired_file]) + csv_output = output_file_to_csv_task( df, constants.UF_TIPO_BASIC_FILENAME.value, upstream_tasks=[df] ) + wait_upload_table = create_table_and_upload_to_gcs( data_path=csv_output, dataset_id=dataset_id, @@ -122,15 +121,18 @@ labels=current_flow_labels, run_name=f"Materialize {dataset_id}.{table_id}", ) + wait_for_materialization = wait_for_flow_run( materialization_flow, stream_states=True, stream_logs=True, raise_final_state=True, ) + wait_for_materialization.max_retries = ( dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_ATTEMPTS.value ) + wait_for_materialization.retry_delay = timedelta( seconds=dump_db_constants.WAIT_FOR_MATERIALIZATION_RETRY_INTERVAL.value ) @@ -171,7 +173,7 @@ ) materialize_after_dump = Parameter( - "materialize after dump", default=False, required=False + "materialize_after_dump", default=False, required=False ) update_metadata = Parameter("update_metadata", default=False, required=False) @@ -192,25 +194,21 @@ temp_dir=constants.DOWNLOAD_PATH.value, upstream_tasks=[year_to_fetch], ) - # Now get the downloaded file: - desired_file = get_desired_file_task( - year=year_to_fetch[0], - download_directory=constants.DOWNLOAD_PATH.value, - filetype=constants.MUNIC_TIPO_BASIC_FILENAME.value, - upstream_tasks=[crawled], - ) - # We need to see the year, month from the file to decide on updating - extracted_date = get_denatran_date(desired_file, upstream_tasks=[desired_file]) - - decision = check_if_data_is_outdated( - dataset_id=dataset_id, - table_id=table_id, - data_source_max_date=extracted_date, - date_format="%Y-%m", - upstream_tasks=[extracted_date], - ) - with case(decision, True): - df = treat_municipio_tipo_task(file=desired_file, upstream_tasks=[decision]) + + with case(crawled, False): + log_task("No new data to be downloaded") + + with case(crawled, True): + # Now get the downloaded file: + desired_file = get_desired_file_task( + year=year_to_fetch[0], + download_directory=constants.DOWNLOAD_PATH.value, + filetype=constants.MUNIC_TIPO_BASIC_FILENAME.value, + upstream_tasks=[crawled], + ) + + df = treat_municipio_tipo_task(file=desired_file, upstream_tasks=[desired_file]) + csv_output = output_file_to_csv_task( df, constants.MUNIC_TIPO_BASIC_FILENAME.value, upstream_tasks=[df] ) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 9f77c2618..7d0466f9c 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -31,18 +31,18 @@ verify_total, ) from pipelines.utils.metadata.utils import get_api_most_recent_date -from pipelines.utils.utils import clean_dataframe, log, to_partitions +from pipelines.utils.utils import log, to_partitions MONTHS = constants.MONTHS.value DATASET = constants.DATASET.value DICT_UFS = constants.DICT_UFS.value -OUTPUT_PATH = "DENATRAN_FILES" +OUTPUT_PATH = constants.OUTPUT_PATH.value MONTHS_SHORT = constants.MONTHS_SHORT.value UF_TIPO_BASIC_FILENAME = constants.UF_TIPO_BASIC_FILENAME.value MUNIC_TIPO_BASIC_FILENAME = constants.MUNIC_TIPO_BASIC_FILENAME.value -def crawl(month: int, year: int, temp_dir: str = "") -> None: +def crawl(month: int, year: int, temp_dir: str = "") -> bool: """Função principal para baixar os dados de frota por município e tipo e também por UF e tipo. Args: @@ -60,9 +60,18 @@ def crawl(month: int, year: int, temp_dir: str = "") -> None: year_dir_name = os.path.join(files_dir, f"{year}") make_dir_when_not_exists(year_dir_name) if year > 2012: - files_to_download = extract_links_post_2012(month, year, year_dir_name) - for file_dict in files_to_download: - call_downloader(file_dict) + try: + files_to_download = extract_links_post_2012(month, year, year_dir_name) + for file_dict in files_to_download: + call_downloader(file_dict) + except Exception as e: + log(e) + log( + "The above error indicates that the next month denatran file was not released yet." + ) + + return False + else: url = f"https://www.gov.br/infraestrutura/pt-br/assuntos/transito/arquivos-senatran/estatisticas/renavam/{year}/frota{'_' if year > 2008 else ''}{year}.zip" filename = f"{year_dir_name}/dados_anuais.zip" @@ -81,6 +90,8 @@ def crawl(month: int, year: int, temp_dir: str = "") -> None: else: extraction_pre_2012(month, year, year_dir_name, filename) + return True + def treat_uf_tipo(file: str) -> pl.DataFrame: valid_ufs = list(DICT_UFS.keys()) + list(DICT_UFS.values()) @@ -105,6 +116,12 @@ def treat_uf_tipo(file: str) -> pl.DataFrame: year, month = get_year_month_from_filename(filename) # If the df is all strings, try to get numbers where it makes sense. clean_df.replace(" - ", 0, inplace=True) + + # Create a reverse dictionary to replace uf names with uf sigla + reverse_dict = {v: k for k, v in DICT_UFS.items()} + clean_df["sigla_uf"] = clean_df["sigla_uf"].map(reverse_dict) + + # clean_df.replace() if all(clean_df.dtypes == "object"): clean_df = clean_df.apply(pd.to_numeric, errors="ignore") clean_pl_df = pl.from_pandas(clean_df).lazy() @@ -120,13 +137,15 @@ def treat_uf_tipo(file: str) -> pl.DataFrame: variable_name="tipo_veiculo", value_name="quantidade", ) # Long format. - clean_pl_df = clean_pl_df.collect() + return clean_pl_df def output_file_to_csv(df: pl.DataFrame, filename: str) -> None: make_dir_when_not_exists(OUTPUT_PATH) + pd_df = df.to_pandas() + log(pd_df.head(10)) to_partitions( pd_df, partition_columns=["ano", "mes", "sigla_uf"], savepath=OUTPUT_PATH ) @@ -148,12 +167,6 @@ def get_desired_file(year: int, download_directory: str, filetype: str) -> str: def get_latest_data(table_id: str, dataset_id: str): - # denatran_data: pd.DataFrame = get_data_from_prod( - # table_id=table_name, dataset_id="br_denatran_frota" - # ) - # substituir por get_api_most_recente_date aqui - # pipelines.utils.metadata.utils.get_api_most_recente_date - # ela vai retonar a data mais recente da tabela extraida da api denatran_data = get_api_most_recent_date( table_id=table_id, dataset_id=dataset_id, date_format="%Y-%m" ) @@ -168,38 +181,17 @@ def get_latest_data(table_id: str, dataset_id: str): else: month += 1 log(f"Ano: {year}, mês: {month}") - return year, month - - # if not isinstance(denatran_data, pd.DataFrame): - # return 2003, 1 - # if not denatran_data.empty: - # log(denatran_data.head(2)) - # year = denatran_data["ano"].max() - # month = denatran_data.loc[denatran_data["ano"] == year]["mes"].max() - # year = int(year) - # month = int(month) - # log(year) - # log(type(year)) - # log(month) - # log(type(month)) - # if month == 12: - # year += 1 - # month = 1 - # else: - # month += 1 - # log(f"Ano: {year}, mês: {month}") - # return year, month - # else: - # log("Não achei ano não mané") - # return 2003, 1 + # return year, month + return 2023, 12 def treat_municipio_tipo(file: str) -> pl.DataFrame: bd_municipios = bd.read_sql( - "select * from `basedosdados.br_bd_diretorios_brasil.municipio`", + "select nome, id_municipio, sigla_uf from `basedosdados.br_bd_diretorios_brasil.municipio`", # billing_project_id="basedosdados-dev", from_file=True, ) + bd_municipios = pl.from_pandas(bd_municipios) filename = os.path.split(file)[1] From 3ea44a9b7795c4f9df7848a58cdbffe61a286565 Mon Sep 17 00:00:00 2001 From: folhesgabriel Date: Thu, 18 Jan 2024 16:07:23 -0300 Subject: [PATCH 255/265] fix: crawler error to downloand october onwards files --- pipelines/datasets/br_denatran_frota/constants.py | 7 ++++--- pipelines/datasets/br_denatran_frota/handlers.py | 4 ++-- pipelines/datasets/br_denatran_frota/utils.py | 9 +++++++++ 3 files changed, 15 insertions(+), 5 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/constants.py b/pipelines/datasets/br_denatran_frota/constants.py index c7abf4aa4..b0e1de0db 100644 --- a/pipelines/datasets/br_denatran_frota/constants.py +++ b/pipelines/datasets/br_denatran_frota/constants.py @@ -21,9 +21,10 @@ class constants(Enum): # pylint: disable=c0103 "julho": 7, "agosto": 8, "setembro": 9, - "outubro": 10, - "novembro": 11, - "dezembro": 12, + # months + "Outubro": 10, + "Novembro": 11, + "Dezembro": 12, } DATASET = "br_denatran_frota" diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 7d0466f9c..71441988d 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -145,7 +145,7 @@ def output_file_to_csv(df: pl.DataFrame, filename: str) -> None: make_dir_when_not_exists(OUTPUT_PATH) pd_df = df.to_pandas() - log(pd_df.head(10)) + to_partitions( pd_df, partition_columns=["ano", "mes", "sigla_uf"], savepath=OUTPUT_PATH ) @@ -182,7 +182,7 @@ def get_latest_data(table_id: str, dataset_id: str): month += 1 log(f"Ano: {year}, mês: {month}") # return year, month - return 2023, 12 + return 2023, 10 def treat_municipio_tipo(file: str) -> pl.DataFrame: diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index c83e84642..3815229ed 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -421,6 +421,7 @@ def extract_links_post_2012(month: int, year: int, directory: str) -> list[dict] soup = BeautifulSoup(urlopen(url), "html.parser") # Só queremos os dados de frota nacional. nodes = soup.select("p:contains('rota por ') > a") + valid_links = [] for node in nodes: txt = node.text @@ -429,11 +430,16 @@ def extract_links_post_2012(month: int, year: int, directory: str) -> list[dict] match = re.search( r"(?i)\/([\w-]+)\/(\d{4})\/(\w+)\/([\w-]+)\.(?:xls|xlsx|rar|zip)$", href ) + if match and re.search("tipo|município", txt, flags=re.IGNORECASE): matched_month = match.group(3) matched_year = match.group(2) + log(f"------match_month {matched_month}") + # log(f'------matched_get{MONTHS.get(matched_month)}') + # log(f'------matched_year{matched_year}') if MONTHS.get(matched_month) == month and matched_year == str(year): filetype = match.group(0).split(".")[-1].lower() + log(f"------filetype {filetype}") info = { "txt": txt, "href": href, @@ -443,7 +449,10 @@ def extract_links_post_2012(month: int, year: int, directory: str) -> list[dict] "filetype": filetype, "destination_dir": directory, } + # log(f'------info {info}') valid_links.append(info) + + log(valid_links) return valid_links From d0f6b58a21229e710b38a71698df3c91bce617bc Mon Sep 17 00:00:00 2001 From: folhesgabriel Date: Tue, 23 Jan 2024 17:03:10 -0300 Subject: [PATCH 256/265] feat: final modifications --- .../datasets/br_denatran_frota/constants.py | 14 ++++++++- pipelines/datasets/br_denatran_frota/flows.py | 29 ++++++++++--------- .../datasets/br_denatran_frota/handlers.py | 24 ++++++++++----- pipelines/datasets/br_denatran_frota/tasks.py | 6 ++-- pipelines/datasets/br_denatran_frota/utils.py | 18 +++++------- 5 files changed, 54 insertions(+), 37 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/constants.py b/pipelines/datasets/br_denatran_frota/constants.py index b0e1de0db..5199c2df9 100644 --- a/pipelines/datasets/br_denatran_frota/constants.py +++ b/pipelines/datasets/br_denatran_frota/constants.py @@ -21,7 +21,19 @@ class constants(Enum): # pylint: disable=c0103 "julho": 7, "agosto": 8, "setembro": 9, - # months + "outubro": 10, + "novembro": 11, + "dezembro": 12, + # some months have capital letters deppending on the year + "Janeiro": 1, + "Fevereiro": 2, + "Marco": 3, + "Abril": 4, + "Maio": 5, + "Junho": 6, + "Julho": 7, + "Agosto": 8, + "Setembro": 9, "Outubro": 10, "Novembro": 11, "Dezembro": 12, diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index d67864dff..3c31e1c40 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -2,19 +2,23 @@ from datetime import timedelta from itertools import product -from prefect import Parameter, case, unmapped +from prefect import Parameter, case from prefect.run_configs import KubernetesRun from prefect.storage import GCS from prefect.tasks.prefect import create_flow_run, wait_for_flow_run from pipelines.constants import constants as pipelines_constants from pipelines.datasets.br_denatran_frota.constants import constants +from pipelines.datasets.br_denatran_frota.schedules import ( + every_month_municipio, + every_month_uf, +) from pipelines.datasets.br_denatran_frota.tasks import ( crawl_task, get_denatran_date, get_desired_file_task, get_latest_data_task, - output_file_to_csv_task, + output_file_to_parquet_task, should_process_data_task, treat_municipio_tipo_task, treat_uf_tipo_task, @@ -39,10 +43,7 @@ date_pairs_param: list[tuple] = Parameter("date_pairs", default=date_pairs) -# from pipelines.datasets.br_denatran_frota.schedules import ( -# every_month_municipio, -# every_month_uf, -# ) + with Flow( name="br_denatran_frota.uf_tipo", code_owners=[ @@ -94,16 +95,16 @@ df = treat_uf_tipo_task(file=desired_file, upstream_tasks=[desired_file]) - csv_output = output_file_to_csv_task( + parquet_output = output_file_to_parquet_task( df, constants.UF_TIPO_BASIC_FILENAME.value, upstream_tasks=[df] ) wait_upload_table = create_table_and_upload_to_gcs( - data_path=csv_output, + data_path=parquet_output, dataset_id=dataset_id, table_id=table_id, dump_mode="append", - wait=csv_output, + wait=parquet_output, ) with case(materialize_after_dump, True): @@ -155,7 +156,7 @@ br_denatran_frota_uf_tipo.run_config = KubernetesRun( image=pipelines_constants.DOCKER_IMAGE.value ) -# flow.schedule = every_two_weeks +br_denatran_frota_uf_tipo.schedule = every_month_uf with Flow( @@ -209,15 +210,15 @@ df = treat_municipio_tipo_task(file=desired_file, upstream_tasks=[desired_file]) - csv_output = output_file_to_csv_task( + parquet_output = output_file_to_parquet_task( df, constants.MUNIC_TIPO_BASIC_FILENAME.value, upstream_tasks=[df] ) wait_upload_table = create_table_and_upload_to_gcs( - data_path=csv_output, + data_path=parquet_output, dataset_id=dataset_id, table_id=table_id, dump_mode="append", - wait=csv_output, + wait=parquet_output, ) with case(materialize_after_dump, True): @@ -269,4 +270,4 @@ br_denatran_frota_municipio_tipo.run_config = KubernetesRun( image=pipelines_constants.DOCKER_IMAGE.value ) -# flow.schedule = every_two_weeks +br_denatran_frota_municipio_tipo.schedule = every_month_municipio diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 71441988d..ffb2e40db 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -94,6 +94,7 @@ def crawl(month: int, year: int, temp_dir: str = "") -> bool: def treat_uf_tipo(file: str) -> pl.DataFrame: + log(f"------- Cleaning {file}") valid_ufs = list(DICT_UFS.keys()) + list(DICT_UFS.values()) filename = os.path.split(file)[1] try: @@ -106,6 +107,7 @@ def treat_uf_tipo(file: str) -> pl.DataFrame: new_df = change_df_header(df, guess_header(df=df, type_of_file=DenatranType.UF)) # This is ad hoc for UF_tipo. + new_df.rename( columns={new_df.columns[0]: "sigla_uf"}, inplace=True ) # Rename for ease of use. @@ -124,6 +126,7 @@ def treat_uf_tipo(file: str) -> pl.DataFrame: # clean_df.replace() if all(clean_df.dtypes == "object"): clean_df = clean_df.apply(pd.to_numeric, errors="ignore") + clean_pl_df = pl.from_pandas(clean_df).lazy() clean_pl_df = verify_total(clean_pl_df.collect()) # Add year and month @@ -141,27 +144,30 @@ def treat_uf_tipo(file: str) -> pl.DataFrame: return clean_pl_df -def output_file_to_csv(df: pl.DataFrame, filename: str) -> None: +def output_file_to_parquet(df: pl.DataFrame, filename: str) -> None: make_dir_when_not_exists(OUTPUT_PATH) pd_df = df.to_pandas() to_partitions( - pd_df, partition_columns=["ano", "mes", "sigla_uf"], savepath=OUTPUT_PATH + pd_df, + partition_columns=["ano", "mes"], + savepath=OUTPUT_PATH, + file_type="parquet", ) return OUTPUT_PATH def get_desired_file(year: int, download_directory: str, filetype: str) -> str: - log("Accessing downloaded file") + log(f"-------- Accessing download directory {download_directory}") directory_to_search = os.path.join(download_directory, "files", f"{year}") - log(f"Directory: {directory_to_search}") + for file in os.listdir(directory_to_search): if re.search(filetype, file) and file.split(".")[-1] in [ "xls", "xlsx", ]: - log(f"File: {file}") + log(f"-------- The file {file} was selected") return os.path.join(directory_to_search, file) raise ValueError("No files found buckaroo") @@ -174,7 +180,7 @@ def get_latest_data(table_id: str, dataset_id: str): log(f"{denatran_data}") year = denatran_data.year month = denatran_data.month - log(f"Ano: {year}, mês: {month}") + if month == 12: year += 1 month = 1 @@ -182,13 +188,15 @@ def get_latest_data(table_id: str, dataset_id: str): month += 1 log(f"Ano: {year}, mês: {month}") # return year, month - return 2023, 10 + + return 2023, 12 def treat_municipio_tipo(file: str) -> pl.DataFrame: + log(f"------- Cleaning {file}") + bd_municipios = bd.read_sql( "select nome, id_municipio, sigla_uf from `basedosdados.br_bd_diretorios_brasil.municipio`", - # billing_project_id="basedosdados-dev", from_file=True, ) diff --git a/pipelines/datasets/br_denatran_frota/tasks.py b/pipelines/datasets/br_denatran_frota/tasks.py index 1ace90099..61ca04e9d 100644 --- a/pipelines/datasets/br_denatran_frota/tasks.py +++ b/pipelines/datasets/br_denatran_frota/tasks.py @@ -13,7 +13,7 @@ get_desired_file, get_latest_data, get_year_month_from_filename, - output_file_to_csv, + output_file_to_parquet, should_process_data, treat_municipio_tipo, treat_uf_tipo, @@ -38,8 +38,8 @@ def treat_uf_tipo_task(file) -> pl.DataFrame: @task() -def output_file_to_csv_task(df: pl.DataFrame, filename: str) -> None: - return output_file_to_csv(df, filename) +def output_file_to_parquet_task(df: pl.DataFrame, filename: str) -> None: + return output_file_to_parquet(df, filename) @task() diff --git a/pipelines/datasets/br_denatran_frota/utils.py b/pipelines/datasets/br_denatran_frota/utils.py index 3815229ed..3af0018cf 100644 --- a/pipelines/datasets/br_denatran_frota/utils.py +++ b/pipelines/datasets/br_denatran_frota/utils.py @@ -434,12 +434,9 @@ def extract_links_post_2012(month: int, year: int, directory: str) -> list[dict] if match and re.search("tipo|município", txt, flags=re.IGNORECASE): matched_month = match.group(3) matched_year = match.group(2) - log(f"------match_month {matched_month}") - # log(f'------matched_get{MONTHS.get(matched_month)}') - # log(f'------matched_year{matched_year}') if MONTHS.get(matched_month) == month and matched_year == str(year): filetype = match.group(0).split(".")[-1].lower() - log(f"------filetype {filetype}") + info = { "txt": txt, "href": href, @@ -449,10 +446,9 @@ def extract_links_post_2012(month: int, year: int, directory: str) -> list[dict] "filetype": filetype, "destination_dir": directory, } - # log(f'------info {info}') + valid_links.append(info) - log(valid_links) return valid_links @@ -514,11 +510,11 @@ def call_r_to_read_excel(file: str) -> pd.DataFrame: """ if not os.path.isfile(file): raise ValueError("Invalid file") - # packages = ("readxl",) - # r_utils = rpackages.importr("utils", suppress_messages=True) - # r_utils.chooseCRANmirror(ind=1) - # r_utils.install_packages(StrVector(packages)) - # rpackages.importr("readxl", lib_loc="usr/lib/R/library", suppress_messages=True) + packages = "readxl" + r_utils = rpackages.importr("utils", suppress_messages=True) + r_utils.chooseCRANmirror(ind=1) + r_utils.install_packages(StrVector(packages)) + rpackages.importr("readxl", suppress_messages=True) # Read the Excel file robjects.r( From 19fe83f4320ee55bc83e55136970680a2b45b3fc Mon Sep 17 00:00:00 2001 From: folhesgabriel Date: Wed, 24 Jan 2024 11:21:22 -0300 Subject: [PATCH 257/265] feat: add logs and set df cols to str --- pipelines/datasets/br_denatran_frota/handlers.py | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index ffb2e40db..9811cb05f 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -141,6 +141,7 @@ def treat_uf_tipo(file: str) -> pl.DataFrame: value_name="quantidade", ) # Long format. + log("-------- Data Wrangling finished") return clean_pl_df @@ -148,6 +149,7 @@ def output_file_to_parquet(df: pl.DataFrame, filename: str) -> None: make_dir_when_not_exists(OUTPUT_PATH) pd_df = df.to_pandas() + pd_df = pd_df.astype(str) to_partitions( pd_df, @@ -189,7 +191,7 @@ def get_latest_data(table_id: str, dataset_id: str): log(f"Ano: {year}, mês: {month}") # return year, month - return 2023, 12 + return 2023, 8 def treat_municipio_tipo(file: str) -> pl.DataFrame: @@ -242,6 +244,8 @@ def treat_municipio_tipo(file: str) -> pl.DataFrame: variable_name="tipo_veiculo", value_name="quantidade", ) # Long format. + + log("-------- Data Wrangling finished") return full_pl_df From b3474a58f71074401d9dedec53638c2b8c74991a Mon Sep 17 00:00:00 2001 From: folhesgabriel Date: Wed, 24 Jan 2024 11:38:36 -0300 Subject: [PATCH 258/265] feat: fix get_latest_data return --- pipelines/datasets/br_denatran_frota/handlers.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 9811cb05f..08762f263 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -189,9 +189,8 @@ def get_latest_data(table_id: str, dataset_id: str): else: month += 1 log(f"Ano: {year}, mês: {month}") - # return year, month - return 2023, 8 + return year, month def treat_municipio_tipo(file: str) -> pl.DataFrame: From 658bf37a4c2353f598c0bbdb70286a857a341bae Mon Sep 17 00:00:00 2001 From: folhesgabriel Date: Thu, 25 Jan 2024 15:33:37 -0300 Subject: [PATCH 259/265] feat: delete backfill and add documentation --- .../datasets/br_denatran_frota/backfill.py | 27 -------- .../br_denatran_frota/functions_test.py | 18 ++++++ .../datasets/br_denatran_frota/handlers.py | 62 +++++++++++++++++-- .../datasets/br_denatran_frota/tasks_test.py | 19 ++++++ 4 files changed, 95 insertions(+), 31 deletions(-) delete mode 100644 pipelines/datasets/br_denatran_frota/backfill.py diff --git a/pipelines/datasets/br_denatran_frota/backfill.py b/pipelines/datasets/br_denatran_frota/backfill.py deleted file mode 100644 index 75805a585..000000000 --- a/pipelines/datasets/br_denatran_frota/backfill.py +++ /dev/null @@ -1,27 +0,0 @@ -# -*- coding: utf-8 -*- -from pipelines.datasets.br_denatran_frota.constants import constants -from pipelines.datasets.br_denatran_frota.handlers import ( - crawl, - get_desired_file, - output_file_to_csv, - treat_uf_tipo, -) - -# Fill for UF TIPO -months = range(1, 13) -years = range(2003, 2023) -for year in years: - for month in months: - print(month) - crawl(month=month, year=year, temp_dir="DENATRAN_FILES") - file = get_desired_file( - year=year, - download_directory="DENATRAN_FILES", - filetype=f"{constants.UF_TIPO_BASIC_FILENAME.value}_{month}", - ) - if year == 2004 and month == 3: - breakpoint() - df = treat_uf_tipo(file=file) - path = output_file_to_csv( - df=df, filename=constants.UF_TIPO_BASIC_FILENAME.value - ) diff --git a/pipelines/datasets/br_denatran_frota/functions_test.py b/pipelines/datasets/br_denatran_frota/functions_test.py index c104b8b5c..c853bda50 100644 --- a/pipelines/datasets/br_denatran_frota/functions_test.py +++ b/pipelines/datasets/br_denatran_frota/functions_test.py @@ -17,8 +17,14 @@ DOWNLOAD_PATH = constants.DOWNLOAD_PATH.value +# Classes to test br_denatran_frota functions with unnittest + class TestMakeFilename(unittest.TestCase): + """ + Class to test function make_filename + """ + def test_make_filename(self): month = 2 year = 2013 @@ -53,6 +59,10 @@ def test_make_filename_without_ext(self): class TestMakeDirWhenNotExists(unittest.TestCase): + """ + Class to test function + """ + def setUp(self): self.temp_dir = tempfile.mkdtemp() @@ -67,12 +77,20 @@ def test_make_dir_when_not_exists(self): class TestDownloadFrota(unittest.TestCase): + """ + Class to test function download_file + """ + def test_download_frota_with_invalid_month(self): with self.assertRaises(ValueError): crawl(13, 2013) class TestFilenameExtraction(unittest.TestCase): + """ + Class to test filename extraction + """ + def test_correct_file(self): filename = "indicator_2-2022.xlsx" self.assertEqual(get_year_month_from_filename(filename), ("2", "2022")) diff --git a/pipelines/datasets/br_denatran_frota/handlers.py b/pipelines/datasets/br_denatran_frota/handlers.py index 08762f263..444dcb542 100644 --- a/pipelines/datasets/br_denatran_frota/handlers.py +++ b/pipelines/datasets/br_denatran_frota/handlers.py @@ -43,11 +43,12 @@ def crawl(month: int, year: int, temp_dir: str = "") -> bool: - """Função principal para baixar os dados de frota por município e tipo e também por UF e tipo. + """ + Main function to extract data from *frota por município e tipo* and *frota por UF e tipo*. Args: - month (int): Mês desejado. - year (int): Ano desejado. + month (int): Desired month + year (int): Desired year Raises: ValueError: Errors if the month is not a valid one. @@ -94,6 +95,16 @@ def crawl(month: int, year: int, temp_dir: str = "") -> bool: def treat_uf_tipo(file: str) -> pl.DataFrame: + """Function to treat data from frota por UF e tipo. + + + Args: + file (str): path to the file to be treated + + Returns: + pl.DataFrame: final file + """ + log(f"------- Cleaning {file}") valid_ufs = list(DICT_UFS.keys()) + list(DICT_UFS.values()) filename = os.path.split(file)[1] @@ -145,7 +156,16 @@ def treat_uf_tipo(file: str) -> pl.DataFrame: return clean_pl_df -def output_file_to_parquet(df: pl.DataFrame, filename: str) -> None: +def output_file_to_parquet(df: pl.DataFrame) -> None: + """Function to save .parquet uf_tipo and municipio_tipo files + + Args: + df (pl.DataFrame): Polars DataFrame to be saved + + Returns: + _type_: None + """ + make_dir_when_not_exists(OUTPUT_PATH) pd_df = df.to_pandas() @@ -161,6 +181,20 @@ def output_file_to_parquet(df: pl.DataFrame, filename: str) -> None: def get_desired_file(year: int, download_directory: str, filetype: str) -> str: + """Função para pegar o arquivo desejado de uf_tipo ou municipio_tipo em um diretório + + Args: + year (int): file year + download_directory (str): donwload directory + filetype (str): filetype + + Raises: + ValueError: No files found + + Returns: + str: File path + """ + log(f"-------- Accessing download directory {download_directory}") directory_to_search = os.path.join(download_directory, "files", f"{year}") @@ -175,6 +209,16 @@ def get_desired_file(year: int, download_directory: str, filetype: str) -> str: def get_latest_data(table_id: str, dataset_id: str): + """Function to extract the latest data from GRAPHIQL API + + Args: + table_id (str): table_id from BQ + dataset_id (str): table_id from BQ + + Returns: + _type_: most recente date + """ + denatran_data = get_api_most_recent_date( table_id=table_id, dataset_id=dataset_id, date_format="%Y-%m" ) @@ -194,6 +238,16 @@ def get_latest_data(table_id: str, dataset_id: str): def treat_municipio_tipo(file: str) -> pl.DataFrame: + """Function to treat data from frota por UF e tipo. + + + Args: + file (str): path to the file to be treated + + Returns: + pl.DataFrame: final file + """ + log(f"------- Cleaning {file}") bd_municipios = bd.read_sql( diff --git a/pipelines/datasets/br_denatran_frota/tasks_test.py b/pipelines/datasets/br_denatran_frota/tasks_test.py index a2d73c50a..45a0311db 100644 --- a/pipelines/datasets/br_denatran_frota/tasks_test.py +++ b/pipelines/datasets/br_denatran_frota/tasks_test.py @@ -24,6 +24,9 @@ DICT_UFS = constants.DICT_UFS.value +# Classes to test br_denatran_frota tasks with unnittest + + def custom_name_func(testcase_func, param_num, param): return "%s_%s" % ( testcase_func.__name__, @@ -32,6 +35,10 @@ def custom_name_func(testcase_func, param_num, param): class TestExtractingAllPossibleYears(unittest.TestCase): + """ + Classe para testar se o crawler consegue extrair arquivos de todos os anos + """ + def setUp(self): self.temp_dir = tempfile.TemporaryDirectory( dir=os.path.join(f"{DOWNLOAD_PATH}") @@ -57,6 +64,10 @@ def test_extract_denatran_files(self, month, year): class TestUFTreatmentPostCrawl(unittest.TestCase): + """ + Classe para testar task treat_uf_tipo_task + """ + def setUp(self): self.temp_dir = tempfile.TemporaryDirectory( dir=os.path.join(f"{DOWNLOAD_PATH}") @@ -97,11 +108,19 @@ def test_flow(self): class TestGetLatestData(unittest.TestCase): + """ + Classe para testar task get_latest_data + """ + def test_year(self): self.assertEqual(2021, get_latest_data("municipio")) class TestMunicipioTreatmentPostCrawl(unittest.TestCase): + """ + Classe para testar task treat_municipio_tipo_task + """ + def setUp(self): self.temp_dir = tempfile.TemporaryDirectory( dir=os.path.join(f"{DOWNLOAD_PATH}") From 0c41c7d00c63d0441f6a9a2e1d835349db8ac74b Mon Sep 17 00:00:00 2001 From: folhesgabriel Date: Thu, 25 Jan 2024 16:16:17 -0300 Subject: [PATCH 260/265] feat: remove backfill parameters from flow --- pipelines/datasets/br_denatran_frota/flows.py | 7 ------- 1 file changed, 7 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index 3c31e1c40..3916607b8 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -37,13 +37,6 @@ rename_current_flow_run_dataset_table, ) -year_range = list(range(2003, 2023)) -month_range = list(range(1, 13)) -date_pairs = list(product(year_range, month_range)) - -date_pairs_param: list[tuple] = Parameter("date_pairs", default=date_pairs) - - with Flow( name="br_denatran_frota.uf_tipo", code_owners=[ From 869430cc2873fbdc8d49d8022e8ffa13a0d8d59c Mon Sep 17 00:00:00 2001 From: folhesgabriel Date: Fri, 26 Jan 2024 14:22:52 -0300 Subject: [PATCH 261/265] feat: schedules --- pipelines/datasets/br_denatran_frota/schedules.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/schedules.py b/pipelines/datasets/br_denatran_frota/schedules.py index 67d07f59a..5845efcb4 100644 --- a/pipelines/datasets/br_denatran_frota/schedules.py +++ b/pipelines/datasets/br_denatran_frota/schedules.py @@ -44,7 +44,7 @@ "dataset_id": "br_denatran_frota", "table_id": "uf_tipo", "materialization_mode": "prod", - "materialize after dump": True, + "materialize_after_dump": True, "dbt_alias": True, "update_metadata": True, }, From 32a7f327564d832c1c92444474f6f9e2e9c67e53 Mon Sep 17 00:00:00 2001 From: folhesgabriel Date: Fri, 26 Jan 2024 16:14:18 -0300 Subject: [PATCH 262/265] feat: add code owners --- pipelines/datasets/br_denatran_frota/flows.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index 3916607b8..26205d618 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -40,7 +40,7 @@ with Flow( name="br_denatran_frota.uf_tipo", code_owners=[ - "Tamir", + "Gabriel Pisa", ], ) as br_denatran_frota_uf_tipo: dataset_id = Parameter("dataset_id", default="br_denatran_frota") @@ -155,7 +155,7 @@ with Flow( name="br_denatran_frota.municipio_tipo", code_owners=[ - "Tamir", + "Gabriel Pisa", ], ) as br_denatran_frota_municipio_tipo: dataset_id = Parameter("dataset_id", default="br_denatran_frota") From 5d3d7936780d2fbf1d6576fecd68fed3531ea5aa Mon Sep 17 00:00:00 2001 From: folhesgabriel Date: Fri, 26 Jan 2024 16:36:34 -0300 Subject: [PATCH 263/265] fix: flow --- pipelines/datasets/br_denatran_frota/tasks.py | 1 - 1 file changed, 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/tasks.py b/pipelines/datasets/br_denatran_frota/tasks.py index 61ca04e9d..592e3623a 100644 --- a/pipelines/datasets/br_denatran_frota/tasks.py +++ b/pipelines/datasets/br_denatran_frota/tasks.py @@ -3,7 +3,6 @@ import datetime -import pandas as pd import polars as pl from prefect import task From ea8d3c9e2b033c235ab4372ac62f0ed23ac9be09 Mon Sep 17 00:00:00 2001 From: folhesgabriel Date: Mon, 29 Jan 2024 08:29:17 -0300 Subject: [PATCH 264/265] fix: lint code --- pipelines/datasets/br_denatran_frota/flows.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index 26205d618..3673aa324 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -190,7 +190,7 @@ ) with case(crawled, False): - log_task("No new data to be downloaded") + log_task("There's no new data to be downloaded") with case(crawled, True): # Now get the downloaded file: From 16e1977456e53b225af41ffbd369e05ee6b0195d Mon Sep 17 00:00:00 2001 From: folhesgabriel Date: Mon, 29 Jan 2024 08:41:22 -0300 Subject: [PATCH 265/265] feat: remove unnused imports --- pipelines/datasets/br_denatran_frota/flows.py | 9 ++------- 1 file changed, 2 insertions(+), 7 deletions(-) diff --git a/pipelines/datasets/br_denatran_frota/flows.py b/pipelines/datasets/br_denatran_frota/flows.py index 3673aa324..0d8b88eb4 100644 --- a/pipelines/datasets/br_denatran_frota/flows.py +++ b/pipelines/datasets/br_denatran_frota/flows.py @@ -1,6 +1,6 @@ # -*- coding: utf-8 -*- + from datetime import timedelta -from itertools import product from prefect import Parameter, case from prefect.run_configs import KubernetesRun @@ -15,21 +15,16 @@ ) from pipelines.datasets.br_denatran_frota.tasks import ( crawl_task, - get_denatran_date, get_desired_file_task, get_latest_data_task, output_file_to_parquet_task, - should_process_data_task, treat_municipio_tipo_task, treat_uf_tipo_task, ) from pipelines.utils.constants import constants as utils_constants from pipelines.utils.decorators import Flow from pipelines.utils.execute_dbt_model.constants import constants as dump_db_constants -from pipelines.utils.metadata.tasks import ( - check_if_data_is_outdated, - update_django_metadata, -) +from pipelines.utils.metadata.tasks import update_django_metadata from pipelines.utils.tasks import ( create_table_and_upload_to_gcs, get_current_flow_labels,

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