Skip to content

pytablewriter is a Python library to write a table in various formats: CSV / Elasticsearch / HTML / JavaScript / JSON / LaTeX / LDJSON / LTSV / Markdown / MediaWiki / NumPy / Excel / Pandas / Python / reStructuredText / SQLite / TOML / TSV.

License

Notifications You must be signed in to change notification settings

sundarsrst/pytablewriter

 
 

Repository files navigation

pytablewriter is a Python library to write a table in various formats: CSV / Elasticsearch / HTML / JavaScript / JSON / LaTeX / LDJSON / LTSV / Markdown / MediaWiki / NumPy / Excel / Pandas / Python / reStructuredText / SQLite / TOML / TSV.

PyPI package version Supported Python versions Linux/macOS CI status Windows CI status Test coverage GitHub stars
  • Write a table in various formats:
  • Automatic tabular data formatting
    • Alignment
    • Padding
    • Decimal places of numbers
  • Configure cell styles:
    • Text alignment
    • Font size/weight
    • Thousand separator for numbers: e.g. 1,000/1 000
  • Configure ouput:
    • Write table to a stream such as a file/standard-output/string-buffer/Jupyter-Notebook
    • Get rendered tabular text
  • Data source
  • Multibyte character support
  • ANSI color support

Write a Markdown table

Sample Code:
from pytablewriter import MarkdownTableWriter

writer = MarkdownTableWriter()
writer.table_name = "example_table"
writer.headers = ["int", "float", "str", "bool", "mix", "time"]
writer.value_matrix = [
    [0,   0.1,      "hoge", True,   0,      "2017-01-01 03:04:05+0900"],
    [2,   "-2.23",  "foo",  False,  None,   "2017-12-23 45:01:23+0900"],
    [3,   0,        "bar",  "true",  "inf", "2017-03-03 33:44:55+0900"],
    [-10, -9.9,     "",     "FALSE", "nan", "2017-01-01 00:00:00+0900"],
]

writer.write_table()
Output:
# example_table
|int|float|str |bool |  mix   |          time          |
|--:|----:|----|-----|-------:|------------------------|
|  0| 0.10|hoge|True |       0|2017-01-01 03:04:05+0900|
|  2|-2.23|foo |False|        |2017-12-23 12:34:51+0900|
|  3| 0.00|bar |True |Infinity|2017-03-03 22:44:55+0900|
|-10|-9.90|    |False|     NaN|2017-01-01 00:00:00+0900|
Rendering Result:
markdown_ss

Rendered markdown at GitHub

Write a Markdown table with a margin
Sample Code:
from pytablewriter import MarkdownTableWriter

writer = MarkdownTableWriter()
writer.table_name = "write example with a margin"
writer.headers = ["int", "float", "str", "bool", "mix", "time"]
writer.value_matrix = [
    [0,   0.1,      "hoge", True,   0,      "2017-01-01 03:04:05+0900"],
    [2,   "-2.23",  "foo",  False,  None,   "2017-12-23 45:01:23+0900"],
    [3,   0,        "bar",  "true",  "inf", "2017-03-03 33:44:55+0900"],
    [-10, -9.9,     "",     "FALSE", "nan", "2017-01-01 00:00:00+0900"],
]
writer.margin = 1  # add a whitespace for both sides of each cell

writer.write_table()
Output:
# write example with a margin
| int | float | str  | bool  |   mix    |           time           |
|----:|------:|------|-------|---------:|--------------------------|
|   0 |  0.10 | hoge | True  |        0 | 2017-01-01 03:04:05+0900 |
|   2 | -2.23 | foo  | False |          | 2017-12-23 12:34:51+0900 |
|   3 |  0.00 | bar  | True  | Infinity | 2017-03-03 22:44:55+0900 |
| -10 | -9.90 |      | False |      NaN | 2017-01-01 00:00:00+0900 |

margin attribute can be available for all of the text format writer classes.

Write a reStructuredText table (Grid Tables)

Sample Code:
import pytablewriter

writer = pytablewriter.RstGridTableWriter()
writer.table_name = "example_table"
writer.headers = ["int", "float", "str", "bool", "mix", "time"]
writer.value_matrix = [
    [0,   0.1,      "hoge", True,   0,      "2017-01-01 03:04:05+0900"],
    [2,   "-2.23",  "foo",  False,  None,   "2017-12-23 45:01:23+0900"],
    [3,   0,        "bar",  "true",  "inf", "2017-03-03 33:44:55+0900"],
    [-10, -9.9,     "",     "FALSE", "nan", "2017-01-01 00:00:00+0900"],
]

writer.write_table()
Output:
.. table:: example_table

    +---+-----+----+-----+--------+------------------------+
    |int|float|str |bool |  mix   |          time          |
    +===+=====+====+=====+========+========================+
    |  0| 0.10|hoge|True |       0|2017-01-01 03:04:05+0900|
    +---+-----+----+-----+--------+------------------------+
    |  2|-2.23|foo |False|        |2017-12-23 12:34:51+0900|
    +---+-----+----+-----+--------+------------------------+
    |  3| 0.00|bar |True |Infinity|2017-03-03 22:44:55+0900|
    +---+-----+----+-----+--------+------------------------+
    |-10|-9.90|    |False|     NaN|2017-01-01 00:00:00+0900|
    +---+-----+----+-----+--------+------------------------+
Rendering Result: example_table

int

float

str

bool

mix

time

0

0.10

hoge

True

0

2017-01-01 03:04:05+0900

2

-2.23

foo

False

 

2017-12-23 12:34:51+0900

3

0.00

bar

True

Infinity

2017-03-03 22:44:55+0900

-10

-9.90

 

False

NaN

2017-01-01 00:00:00+0900

Write a table with JavaScript format (as a nested list variable definition)

Sample Code:
import pytablewriter

writer = pytablewriter.JavaScriptTableWriter()
writer.table_name = "example_table"
writer.headers = ["int", "float", "str", "bool", "mix", "time"]
writer.value_matrix = [
    [0,   0.1,      "hoge", True,   0,      "2017-01-01 03:04:05+0900"],
    [2,   "-2.23",  "foo",  False,  None,   "2017-12-23 45:01:23+0900"],
    [3,   0,        "bar",  "true",  "inf", "2017-03-03 33:44:55+0900"],
    [-10, -9.9,     "",     "FALSE", "nan", "2017-01-01 00:00:00+0900"],
]

writer.write_table()
Output:
const example_table = [
    ["int", "float", "str", "bool", "mix", "time"],
    [0, 0.10, "hoge", true, 0, "2017-01-01 03:04:05+0900"],
    [2, -2.23, "foo", false, null, "2017-12-23 12:34:51+0900"],
    [3, 0.00, "bar", true, Infinity, "2017-03-03 22:44:55+0900"],
    [-10, -9.90, "", false, NaN, "2017-01-01 00:00:00+0900"]
];

Write a table to an Excel sheet

Sample Code:
from pytablewriter import ExcelXlsxTableWriter

writer = ExcelXlsxTableWriter()
writer.table_name = "example"
writer.headers = ["int", "float", "str", "bool", "mix", "time"]
writer.value_matrix = [
    [0,   0.1,      "hoge", True,   0,      "2017-01-01 03:04:05+0900"],
    [2,   "-2.23",  "foo",  False,  None,   "2017-12-23 12:34:51+0900"],
    [3,   0,        "bar",  "true",  "inf", "2017-03-03 22:44:55+0900"],
    [-10, -9.9,     "",     "FALSE", "nan", "2017-01-01 00:00:00+0900"],
]
writer.dump("sample.xlsx")
Output:
excel_single

Output excel file (sample_single.xlsx)

Write a Unicode table

Sample Code:
from pytablewriter import UnicodeTableWriter

writer = UnicodeTableWriter()
writer.table_name = "example_table"
writer.headers = ["int", "float", "str", "bool", "mix", "time"]
writer.value_matrix = [
    [0,   0.1,      "hoge", True,   0,      "2017-01-01 03:04:05+0900"],
    [2,   "-2.23",  "foo",  False,  None,   "2017-12-23 45:01:23+0900"],
    [3,   0,        "bar",  "true",  "inf", "2017-03-03 33:44:55+0900"],
    [-10, -9.9,     "",     "FALSE", "nan", "2017-01-01 00:00:00+0900"],
]

writer.write_table()
Output:
┌───┬─────┬────┬─────┬────────┬────────────────────────┐
│int│float│str │bool │  mix   │          time          │
├───┼─────┼────┼─────┼────────┼────────────────────────┤
│  0│ 0.10│hoge│True │       0│2017-01-01 03:04:05+0900│
├───┼─────┼────┼─────┼────────┼────────────────────────┤
│  2│-2.23│foo │False│        │2017-12-23 12:34:51+0900│
├───┼─────┼────┼─────┼────────┼────────────────────────┤
│  3│ 0.00│bar │True │Infinity│2017-03-03 22:44:55+0900│
├───┼─────┼────┼─────┼────────┼────────────────────────┤
│-10│-9.90│    │False│     NaN│2017-01-01 00:00:00+0900│
└───┴─────┴────┴─────┴────────┴────────────────────────┘

Write a Markdown table from pandas.DataFrame instance

from_dataframe method of writer classes will set up tabular data from pandas.DataFrame:

Sample Code:
from textwrap import dedent
import pandas as pd
import six
from pytablewriter import MarkdownTableWriter

csv_data = six.StringIO(dedent("""\
    "i","f","c","if","ifc","bool","inf","nan","mix_num","time"
    1,1.10,"aa",1.0,"1",True,Infinity,NaN,1,"2017-01-01 00:00:00+09:00"
    2,2.20,"bbb",2.2,"2.2",False,Infinity,NaN,Infinity,"2017-01-02 03:04:05+09:00"
    3,3.33,"cccc",-3.0,"ccc",True,Infinity,NaN,NaN,"2017-01-01 00:00:00+09:00"
    """))
df = pd.read_csv(csv_data, sep=',')

writer = MarkdownTableWriter()
writer.from_dataframe(df)
writer.write_table()
Output:
| i | f  | c  | if |ifc|bool |  inf   |nan|mix_num |          time           |
|--:|---:|----|---:|---|-----|--------|---|-------:|-------------------------|
|  1|1.10|aa  | 1.0|  1|True |Infinity|NaN|       1|2017-01-01 00:00:00+09:00|
|  2|2.20|bbb | 2.2|2.2|False|Infinity|NaN|Infinity|2017-01-02 03:04:05+09:00|
|  3|3.33|cccc|-3.0|ccc|True |Infinity|NaN|     NaN|2017-01-01 00:00:00+09:00|

Adding a column of the DataFrame index if you specify add_index_column=True:

Sample Code:
import pandas as pd
from pytablewriter import MarkdownTableWriter

writer = MarkdownTableWriter()
writer.table_name = "add_index_column"
writer.from_dataframe(
    pd.DataFrame({"A": [1, 2], "B": [10, 11]}, index=["a", "b"]),
    add_index_column=True,
)
writer.write_table()
Output:
# add_index_column
|   | A | B |
|---|--:|--:|
|a  |  1| 10|
|b  |  2| 11|

Write a markdown table from a space-separated values

Sample Code:
from textwrap import dedent
import pytablewriter

writer = pytablewriter.MarkdownTableWriter()
writer.table_name = "ps"
writer.from_csv(
    dedent("""\
        USER       PID %CPU %MEM    VSZ   RSS TTY      STAT START   TIME COMMAND
        root         1  0.0  0.4  77664  8784 ?        Ss   May11   0:02 /sbin/init
        root         2  0.0  0.0      0     0 ?        S    May11   0:00 [kthreadd]
        root         4  0.0  0.0      0     0 ?        I<   May11   0:00 [kworker/0:0H]
        root         6  0.0  0.0      0     0 ?        I<   May11   0:00 [mm_percpu_wq]
        root         7  0.0  0.0      0     0 ?        S    May11   0:01 [ksoftirqd/0]
    """),
    delimiter=" ")
writer.write_table()
Output:
# ps
|USER|PID|%CPU|%MEM| VSZ |RSS |TTY|STAT|START|TIME|   COMMAND    |
|----|--:|---:|---:|----:|---:|---|----|-----|----|--------------|
|root|  1|   0| 0.4|77664|8784|?  |Ss  |May11|0:02|/sbin/init    |
|root|  2|   0| 0.0|    0|   0|?  |S   |May11|0:00|[kthreadd]    |
|root|  4|   0| 0.0|    0|   0|?  |I<  |May11|0:00|[kworker/0:0H]|
|root|  6|   0| 0.0|    0|   0|?  |I<  |May11|0:00|[mm_percpu_wq]|
|root|  7|   0| 0.0|    0|   0|?  |S   |May11|0:01|[ksoftirqd/0] |

dumps method returns rendered tabular text. dumps only available for text format writers.

Sample Code:
import pytablewriter

writer = pytablewriter.MarkdownTableWriter()
writer.headers = ["int", "float", "str", "bool", "mix", "time"]
writer.value_matrix = [
    [0,   0.1,      "hoge", True,   0,      "2017-01-01 03:04:05+0900"],
    [2,   "-2.23",  "foo",  False,  None,   "2017-12-23 45:01:23+0900"],
    [3,   0,        "bar",  "true",  "inf", "2017-03-03 33:44:55+0900"],
    [-10, -9.9,     "",     "FALSE", "nan", "2017-01-01 00:00:00+0900"],
]

print(writer.dumps())
Output:
|int|float|str |bool |  mix   |          time          |
|--:|----:|----|-----|-------:|------------------------|
|  0| 0.10|hoge|True |       0|2017-01-01 03:04:05+0900|
|  2|-2.23|foo |False|        |2017-12-23 45:01:23+0900|
|  3| 0.00|bar |True |Infinity|2017-03-03 33:44:55+0900|
|-10|-9.90|    |False|     NaN|2017-01-01 00:00:00+0900|

Writers can specify cell Style for each column manually by styles attribute of writer classes.

Sample Code:
from pytablewriter import MarkdownTableWriter
from pytablewriter.style import Style

writer = MarkdownTableWriter()
writer.table_name = "set style by styles"
writer.headers = [
    "auto align",
    "left align",
    "center align",
    "bold",
    "italic",
    "bold italic ts",
]
writer.value_matrix = [
    [11, 11, 11, 11, 11, 11],
    [1234, 1234, 1234, 1234, 1234, 1234],
]

# specify styles for each column
writer.styles = [
    Style(),
    Style(align="left"),
    Style(align="center"),
    Style(font_weight="bold"),
    Style(font_style="italic"),
    Style(font_weight="bold", font_style="italic", thousand_separator=","),
]

writer.write_table()
Output:
# set style by styles
|auto align|left align|center align|  bold  |italic|bold italic ts|
|---------:|----------|:----------:|-------:|-----:|-------------:|
|        11|11        |     11     |  **11**|  _11_|      _**11**_|
|      1234|1234      |    1234    |**1234**|_1234_|   _**1,234**_|

Rendering result

You can also set Style to a specific column with index or header by using set_style method:

Sample Code:
from pytablewriter import MarkdownTableWriter
from pytablewriter.style import Style

writer = MarkdownTableWriter()
writer.headers = ["A", "B", "C",]
writer.value_matrix = [[11, 11, 11], [1234, 1234, 1234]]

writer.table_name = "set style by index"
writer.set_style(1, Style(align="center", font_weight="bold"))
writer.set_style(2, Style(thousand_separator=" "))
writer.write_table()
writer.write_null_line()

writer.table_name = "set style by header"
writer.set_style("B", Style(font_style="italic"))
writer.write_table()
Output:
# set style by index
| A  |   B    |  C  |
|---:|:------:|----:|
|  11| **11** |   11|
|1234|**1234**|1 234|

# set style by header
| A  |  B   |  C  |
|---:|-----:|----:|
|  11|  _11_|   11|
|1234|_1234_|1 234|

Create Elasticsearch index and put data

Sample Code:
import datetime
import json

from elasticsearch import Elasticsearch
import pytablewriter as ptw

es = Elasticsearch(hosts="localhost:9200")

writer = ptw.ElasticsearchWriter()
writer.stream = es
writer.index_name = "es writer example"
writer.headers = [
    "str", "byte", "short", "int", "long", "float", "date", "bool", "ip",
]
writer.value_matrix = [
    [
        "abc", 100, 10000, 2000000000, 200000000000, 0.1,
        datetime.datetime(2017, 1, 2, 3, 4, 5), True, "127.0.0.1",
    ],
    [
        "def", -10, -1000, -200000000, -20000000000, 100.1,
        datetime.datetime(2017, 6, 5, 4, 5, 2), False, "::1",
    ],
]

# delete existing index ---
es.indices.delete(index=writer.index_name, ignore=404)

# create an index and put data ---
writer.write_table()

# display the result ---
es.indices.refresh(index=writer.index_name)

print("----- mappings -----")
response = es.indices.get_mapping(index=writer.index_name, doc_type="table")
print("{}\n".format(json.dumps(response, indent=4)))

print("----- documents -----")
response = es.search(
    index=writer.index_name,
    doc_type="table",
    body={
        "query": {"match_all": {}}
    }
)
for hit in response["hits"]["hits"]:
    print(json.dumps(hit["_source"], indent=4))
Output:
----- mappings -----
{
    "es_writer_example": {
        "mappings": {
            "table": {
                "properties": {
                    "bool": {
                        "type": "boolean"
                    },
                    "byte": {
                        "type": "byte"
                    },
                    "date": {
                        "type": "date",
                        "format": "date_optional_time"
                    },
                    "float": {
                        "type": "double"
                    },
                    "int": {
                        "type": "integer"
                    },
                    "ip": {
                        "type": "text"
                    },
                    "long": {
                        "type": "long"
                    },
                    "short": {
                        "type": "short"
                    },
                    "str": {
                        "type": "text"
                    }
                }
            }
        }
    }
}

----- documents -----
{
    "str": "def",
    "byte": -10,
    "short": -1000,
    "int": -200000000,
    "long": -20000000000,
    "float": 100.1,
    "date": "2017-06-05T04:05:02",
    "bool": false,
    "ip": "::1"
}
{
    "str": "abc",
    "byte": 100,
    "short": 10000,
    "int": 2000000000,
    "long": 200000000000,
    "float": 0.1,
    "date": "2017-01-02T03:04:05",
    "bool": true,
    "ip": "127.0.0.1"
}

Render a table on Jupyter Notebook

https://nbviewer.jupyter.org/github/thombashi/pytablewriter/blob/master/examples/ipynb/jupyter_notebook_example.ipynb

jupyter_notebook_table

Table formatting for Jupyter Notebook

Write a table using multibyte character

You can use multibyte characters as table data. Multibyte characters also properly padded and aligned.

Sample Code:
import pytablewriter

writer = pytablewriter.RstSimpleTableWriter()
writer.table_name = "生成に関するパターン"
writer.headers = ["パターン名", "概要", "GoF", "Code Complete[1]"]
writer.value_matrix = [
    ["Abstract Factory", "関連する一連のインスタンスを状況に応じて、適切に生成する方法を提供する。", "Yes", "Yes"],
    ["Builder", "複合化されたインスタンスの生成過程を隠蔽する。", "Yes", "No"],
    ["Factory Method", "実際に生成されるインスタンスに依存しない、インスタンスの生成方法を提供する。", "Yes", "Yes"],
    ["Prototype", "同様のインスタンスを生成するために、原型のインスタンスを複製する。", "Yes", "No"],
    ["Singleton", "あるクラスについて、インスタンスが単一であることを保証する。", "Yes", "Yes"],
]
writer.write_table()
Output:
multi_byte_char_table

Output of multi-byte character table

More examples are available at https://pytablewriter.rtfd.io/en/latest/pages/examples/index.html

pip install pytablewriter

Some of the formats require additional dependency packages, you can install the dependency packages as follows:

  • Elasticsearch
    • pip install pytablewriter[es6] or pip install pytablewriter[es5]
  • Excel
    • pip install pytablewriter[excel]
  • HTML
    • pip install pytablewriter[html]
  • SQLite
    • pip install pytablewriter[sqlite]
  • TOML
    • pip install pytablewriter[toml]
  • All of the extra dependencies
    • pip install pytablewriter[all]
sudo add-apt-repository ppa:thombashi/ppa
sudo apt update
sudo apt install python3-pytablewriter

Python 2.7+ or 3.5+

https://pytablewriter.rtfd.io/

  • pytablereader
    • Tabular data loaded by pytablereader can be written another tabular data format with pytablewriter.

https://trello.com/b/kE0XG34y

About

pytablewriter is a Python library to write a table in various formats: CSV / Elasticsearch / HTML / JavaScript / JSON / LaTeX / LDJSON / LTSV / Markdown / MediaWiki / NumPy / Excel / Pandas / Python / reStructuredText / SQLite / TOML / TSV.

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages

  • Python 99.6%
  • Other 0.4%