-
-jsonify
-David Cooley
+jsonify
+David +Cooley
-2019-01-10
- +2024-01-18
+ Source:vignettes/jsonify.Rmd
jsonify.RmdThere are two types of R objects we need to handle when converting to JSON, simple and complex.
+
+
To JSON +
+There are two types of R objects we need to handle when converting to +JSON, simple and complex.
- Simple - scalars, vectors, matrices
- Complex - data.frames and lists
I’ve categorised them this way because ‘simple’ objects don’t include any form of recursion. That is, a vector can’t contain a data.frame or a list. But a list or data.frame can contain other data.frames, vectors, matrices, scalars, lists, and any combination thereof.
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+Authors • jsonify
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-Authors and Citation • jsonify
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-Simple
-Simple objects ( scalars, vectors and matrices ) get converted to JSON ARRAYS
-## scalar -> single array
-to_json( 1 )
-# [1.0]
-to_json( "a" )
-# ["a"]
-
-## scalar (unboxed) -> single value
-to_json( 1, unbox = TRUE )
-# 1.0
-to_json( "a", unbox = TRUE )
-# "a"
-
-## vector -> array
-to_json( 1:4 )
-# [1,2,3,4]
-to_json( letters[1:4] )
-# ["a","b","c","d"]
-
-## named vector - array (of the elements)
-to_json( c("a" = 1, "b" = 2) )
-# [1.0,2.0]
-
-## matrix -> array of arrays (by row)
-to_json( matrix(1:4, ncol = 2) )
-# [[1,3],[2,4]]
-to_json( matrix(letters[1:4], ncol = 2))
-# [["a","c"],["b","d"]]
-
-## matrix -> array of arrays (by column)
-to_json( matrix(1:4, ncol = 2), by = "column" )
-# [[1,2],[3,4]]
-to_json( matrix(letters[1:4], ncol = 2 ), by = "column" )
-# [["a","b"],["c","d"]]I’ve categorised them this way because ‘simple’ objects don’t include +any form of recursion. That is, a vector can’t contain a data.frame or a +list. But a list or data.frame can contain other data.frames, vectors, +matrices, scalars, lists, and any combination thereof.
+
+
-Simple +
+Simple objects ( scalars, vectors and matrices ) get converted to +JSON ARRAYS
+
+## scalar -> single array
+to_json( 1 )
+# [1.0]
+to_json( "a" )
+# ["a"]
+
+## scalar (unboxed) -> single value
+to_json( 1, unbox = TRUE )
+# 1.0
+to_json( "a", unbox = TRUE )
+# "a"
+
+## vector -> array
+to_json( 1:4 )
+# [1,2,3,4]
+to_json( letters[1:4] )
+# ["a","b","c","d"]
+
+## named vector - array (of the elements)
+to_json( c("a" = 1, "b" = 2) )
+# [1.0,2.0]
+
+## matrix -> array of arrays (by row)
+to_json( matrix(1:4, ncol = 2) )
+# [[1,3],[2,4]]
+to_json( matrix(letters[1:4], ncol = 2))
+# [["a","c"],["b","d"]]
+
+## matrix -> array of arrays (by column)
+to_json( matrix(1:4, ncol = 2), by = "column" )
+# [[1,2],[3,4]]
+to_json( matrix(letters[1:4], ncol = 2 ), by = "column" )
+# [["a","b"],["c","d"]]
-
+
+
+
diff --git a/docs/authors.html b/docs/authors.html
index 288c887..b32b056 100644
--- a/docs/authors.html
+++ b/docs/authors.html
@@ -1,55 +1,12 @@
-
-
-
-
-
-
-
--Complex - Lists
-List of unnamed vectors gives an ARRAY of ARRAYS (since a vector gets converted to an array)
- +
+
-Complex - Lists +
+List of unnamed vectors gives an ARRAY of ARRAYS (since a vector gets +converted to an array)
+A list with named elements gives an OBJECT with named ARRAYS
- +A combination of named and unnamed list elements gives both
- +
-
-
+
-
+
-Complex - Data Frames
-A data.frame will, by default, treat each row as an object (to maintain the relationship inherent in a row of data )
-## data.frame -> array of objects (by row)
-to_json( data.frame( x = 1:2, y = 3:4) )
-# [{"x":1,"y":3},{"x":2,"y":4}]
-to_json( data.frame( x = c("a","b"), y = c("c","d")))
-# [{"x":"a","y":"c"},{"x":"b","y":"d"}]You can set by = "column" to parse the data.frame by columns. And as each column (in this example) is a vector, each vector gets converted to an array. And since the vectors have names (the column names), we get an object of named arrays
## data.frame -> object of arrays (by column)
-to_json( data.frame( x = 1:2, y = 3:4), by = "column" )
-# {"x":[1,2],"y":[3,4]}
-to_json( data.frame( x = c("a","b"), y = c("c","d") ), by = "column" )
-# {"x":["a","b"],"y":["c","d"]}
+
+
-Complex - Data Frames +
+A data.frame will, by default, treat each row as an object (to +maintain the relationship inherent in a row of data )
+
+## data.frame -> array of objects (by row)
+to_json( data.frame( x = 1:2, y = 3:4) )
+# [{"x":1,"y":3},{"x":2,"y":4}]
+to_json( data.frame( x = c("a","b"), y = c("c","d")))
+# [{"x":"a","y":"c"},{"x":"b","y":"d"}]You can set by = "column" to parse the data.frame by
+columns. And as each column (in this example) is a vector, each vector
+gets converted to an array. And since the vectors have names (the column
+names), we get an object of named arrays
+## data.frame -> object of arrays (by column)
+to_json( data.frame( x = 1:2, y = 3:4), by = "column" )
+# {"x":[1,2],"y":[3,4]}
+to_json( data.frame( x = c("a","b"), y = c("c","d") ), by = "column" )
+# {"x":["a","b"],"y":["c","d"]}
-
+-Complex - Mixed objects
+
+
-
+
-
+
+
+
+
+Complex - Mixed objects +
A data.frame where one columns is ‘AsIs’ a list
-## data.frame where one colun is a list
-df <- data.frame( id = 1, val = I(list( x = 1:2 ) ) )
-to_json( df )
-# [{"id":1.0,"val":{"x":[1,2]}}]The data.frame is being parsed ‘by row’, so we get an array of objects. The second column is a list of a named vector, so the val column contains an object of a named array.
+## data.frame where one colun is a list
+df <- data.frame( id = 1, val = I(list( x = 1:2 ) ) )
+to_json( df )
+# [{"id":1.0,"val":{"x":[1,2]}}]The data.frame is being parsed ‘by row’, so we get an array of
+objects. The second column is a list of a named vector, so the
+val column contains an object of a named array.
Here are the individual components to show how it’s put together
-## which we see is made up of
-to_json( data.frame( id = 1 ) )
-# [{"id":1.0}]
-## and
-to_json( list( x = 1:2 ) )
-# {"x":[1,2]}If we take the same example and parse it ‘by column’ we get the id column treated as a vector, but the list column remains the same
We can build up a more complex example with nested lists inside columns of data.frames
-df <- data.frame( id = 1, val = I(list(c(0,0))))
-df
-# id val
-# 1 1 0, 0
-to_json( df )
-# [{"id":1.0,"val":[[0.0,0.0]]}]
-
-df <- data.frame( id = 1:2, val = I(list( x = 1:2, y = 3:4 ) ) )
-df
-# id val
-# x 1 1, 2
-# y 2 3, 4
-to_json( df )
-# [{"id":1,"val":{"x":[1,2]}},{"id":2,"val":{"y":[3,4]}}]
-
-df <- data.frame( id = 1:2, val = I(list( x = 1:2, y = 3:6 ) ), val2 = I(list( a = "a", b = c("b","c") ) ) )
-df
-# id val val2
-# x 1 1, 2 a
-# y 2 3, 4, 5, 6 b, c
-pretty_json( df )
-# [
-# {
-# "id": 1,
-# "val": {
-# "x": [
-# 1,
-# 2
-# ]
-# },
-# "val2": {
-# "a": [
-# "a"
-# ]
-# }
-# },
-# {
-# "id": 2,
-# "val": {
-# "y": [
-# 3,
-# 4,
-# 5,
-# 6
-# ]
-# },
-# "val2": {
-# "b": [
-# "b",
-# "c"
-# ]
-# }
-# }
-# ]
-
-df <- data.frame( id = 1:2, val = I(list( x = 1:2, y = 3:6 ) ), val2 = I(list( a = "a", b = c("b","c") ) ), val3 = I(list( l = list( 1:3, l2 = c("a","b")), 1)) )
-df
-# id val val2 val3
-# x 1 1, 2 a 1:3, c("....
-# y 2 3, 4, 5, 6 b, c 1
-pretty_json( df )
-# [
-# {
-# "id": 1,
-# "val": {
-# "x": [
-# 1,
-# 2
-# ]
-# },
-# "val2": {
-# "a": [
-# "a"
-# ]
-# },
-# "val3": {
-# "l": {
-# "1": [
-# 1,
-# 2,
-# 3
-# ],
-# "l2": [
-# "a",
-# "b"
-# ]
-# }
-# }
-# },
-# {
-# "id": 2,
-# "val": {
-# "y": [
-# 3,
-# 4,
-# 5,
-# 6
-# ]
-# },
-# "val2": {
-# "b": [
-# "b",
-# "c"
-# ]
-# },
-# "val3": {
-# "1": [
-# 1.0
-# ]
-# }
-# }
-# ]
+## which we see is made up of
+to_json( data.frame( id = 1 ) )
+# [{"id":1.0}]
+## and
+to_json( list( x = 1:2 ) )
+# {"x":[1,2]}If we take the same example and parse it ‘by column’ we get the
+id column treated as a vector, but the list column remains
+the same
+to_json( df, by = "column" )
+# {"id":[1.0],"val":{"x":[1,2]}}We can build up a more complex example with nested lists inside
+columns of data.frames
+
+df <- data.frame( id = 1, val = I(list(c(0,0))))
+df
+# id val
+# 1 1 0, 0
+to_json( df )
+# [{"id":1.0,"val":[0.0,0.0]}]
+
+df <- data.frame( id = 1:2, val = I(list( x = 1:2, y = 3:4 ) ) )
+df
+# id val
+# x 1 1, 2
+# y 2 3, 4
+to_json( df )
+# [{"id":1,"val":{"x":[1,2]}},{"id":2,"val":{"y":[3,4]}}]
+
+df <- data.frame( id = 1:2, val = I(list( x = 1:2, y = 3:6 ) ), val2 = I(list( a = "a", b = c("b","c") ) ) )
+df
+# id val val2
+# x 1 1, 2 a
+# y 2 3, 4, 5, 6 b, c
+pretty_json( df )
+# [
+# {
+# "id": 1,
+# "val": {
+# "x": [
+# 1,
+# 2
+# ]
+# },
+# "val2": {
+# "a": [
+# "a"
+# ]
+# }
+# },
+# {
+# "id": 2,
+# "val": {
+# "y": [
+# 3,
+# 4,
+# 5,
+# 6
+# ]
+# },
+# "val2": {
+# "b": [
+# "b",
+# "c"
+# ]
+# }
+# }
+# ]
+
+df <- data.frame( id = 1:2, val = I(list( x = 1:2, y = 3:6 ) ), val2 = I(list( a = "a", b = c("b","c") ) ), val3 = I(list( l = list( 1:3, l2 = c("a","b")), 1)) )
+df
+# id val val2 val3
+# x 1 1, 2 a 1:3, c("....
+# y 2 3, 4, 5, 6 b, c 1
+pretty_json( df )
+# [
+# {
+# "id": 1,
+# "val": {
+# "x": [
+# 1,
+# 2
+# ]
+# },
+# "val2": {
+# "a": [
+# "a"
+# ]
+# },
+# "val3": {
+# "l": {
+# "": [
+# 1,
+# 2,
+# 3
+# ],
+# "l2": [
+# "a",
+# "b"
+# ]
+# }
+# }
+# },
+# {
+# "id": 2,
+# "val": {
+# "y": [
+# 3,
+# 4,
+# 5,
+# 6
+# ]
+# },
+# "val2": {
+# "b": [
+# "b",
+# "c"
+# ]
+# },
+# "val3": {
+# "": [
+# 1.0
+# ]
+# }
+# }
+# ]
+
+
From JSON +
+Use from_json() to convert from JSON to an R object.
+## scalar / vector
+js <- '[1,2,3]'
+from_json( js )
+# [1] 1 2 3
+
+## matrix
+js <- '[[1,2],[3,4],[5,6]]'
+from_json( js )
+# [,1] [,2]
+# [1,] 1 2
+# [2,] 3 4
+# [3,] 5 6
+
+## data.frame
+js <- '[{"x":1,"y":"a"},{"x":2,"y":"b"}]'
+from_json( js )
+# x y
+# 1 1 a
+# 2 2 b
+
+
+
Simplifying and NAs +
+By default from_json() will try and simplify
-
+
- arrays to vectors +
- arrays of arrays to matrices +
- array of objects with consistent key-value pairs to data.frames +
If an array contains objects with different keys, for example
+'[{"x":1},{"y":2}]', from_json() will not
+simplify this to a data.frame, because it would have to assume and
+insert NAs in rows where data is missing.
+js <- '[{"x":1},{"y":2}]'
+from_json( js )
+# [[1]]
+# [[1]]$x
+# [1] 1
+#
+#
+# [[2]]
+# [[2]]$y
+# [1] 2You can override this default and use fill_na = TRUE to
+force it to a data.frame with NAs in place of missing
+values
+js <- '[{"x":1},{"y":2}]'
+from_json( js, fill_na = TRUE )
+# x y
+# 1 1 NA
+# 2 NA 2
-
-
+
-
-
+
+
+
+
-
-
+
diff --git a/docs/bootstrap-toc.css b/docs/bootstrap-toc.css
new file mode 100644
index 0000000..5a85941
--- /dev/null
+++ b/docs/bootstrap-toc.css
@@ -0,0 +1,60 @@
+/*!
+ * Bootstrap Table of Contents v0.4.1 (http://afeld.github.io/bootstrap-toc/)
+ * Copyright 2015 Aidan Feldman
+ * Licensed under MIT (https://github.com/afeld/bootstrap-toc/blob/gh-pages/LICENSE.md) */
+
+/* modified from https://github.com/twbs/bootstrap/blob/94b4076dd2efba9af71f0b18d4ee4b163aa9e0dd/docs/assets/css/src/docs.css#L548-L601 */
+
+/* All levels of nav */
+nav[data-toggle='toc'] .nav > li > a {
+ display: block;
+ padding: 4px 20px;
+ font-size: 13px;
+ font-weight: 500;
+ color: #767676;
+}
+nav[data-toggle='toc'] .nav > li > a:hover,
+nav[data-toggle='toc'] .nav > li > a:focus {
+ padding-left: 19px;
+ color: #563d7c;
+ text-decoration: none;
+ background-color: transparent;
+ border-left: 1px solid #563d7c;
+}
+nav[data-toggle='toc'] .nav > .active > a,
+nav[data-toggle='toc'] .nav > .active:hover > a,
+nav[data-toggle='toc'] .nav > .active:focus > a {
+ padding-left: 18px;
+ font-weight: bold;
+ color: #563d7c;
+ background-color: transparent;
+ border-left: 2px solid #563d7c;
+}
+
+/* Nav: second level (shown on .active) */
+nav[data-toggle='toc'] .nav .nav {
+ display: none; /* Hide by default, but at >768px, show it */
+ padding-bottom: 10px;
+}
+nav[data-toggle='toc'] .nav .nav > li > a {
+ padding-top: 1px;
+ padding-bottom: 1px;
+ padding-left: 30px;
+ font-size: 12px;
+ font-weight: normal;
+}
+nav[data-toggle='toc'] .nav .nav > li > a:hover,
+nav[data-toggle='toc'] .nav .nav > li > a:focus {
+ padding-left: 29px;
+}
+nav[data-toggle='toc'] .nav .nav > .active > a,
+nav[data-toggle='toc'] .nav .nav > .active:hover > a,
+nav[data-toggle='toc'] .nav .nav > .active:focus > a {
+ padding-left: 28px;
+ font-weight: 500;
+}
+
+/* from https://github.com/twbs/bootstrap/blob/e38f066d8c203c3e032da0ff23cd2d6098ee2dd6/docs/assets/css/src/docs.css#L631-L634 */
+nav[data-toggle='toc'] .nav > .active > ul {
+ display: block;
+}
diff --git a/docs/bootstrap-toc.js b/docs/bootstrap-toc.js
new file mode 100644
index 0000000..1cdd573
--- /dev/null
+++ b/docs/bootstrap-toc.js
@@ -0,0 +1,159 @@
+/*!
+ * Bootstrap Table of Contents v0.4.1 (http://afeld.github.io/bootstrap-toc/)
+ * Copyright 2015 Aidan Feldman
+ * Licensed under MIT (https://github.com/afeld/bootstrap-toc/blob/gh-pages/LICENSE.md) */
+(function() {
+ 'use strict';
+
+ window.Toc = {
+ helpers: {
+ // return all matching elements in the set, or their descendants
+ findOrFilter: function($el, selector) {
+ // http://danielnouri.org/notes/2011/03/14/a-jquery-find-that-also-finds-the-root-element/
+ // http://stackoverflow.com/a/12731439/358804
+ var $descendants = $el.find(selector);
+ return $el.filter(selector).add($descendants).filter(':not([data-toc-skip])');
+ },
+
+ generateUniqueIdBase: function(el) {
+ var text = $(el).text();
+ var anchor = text.trim().toLowerCase().replace(/[^A-Za-z0-9]+/g, '-');
+ return anchor || el.tagName.toLowerCase();
+ },
+
+ generateUniqueId: function(el) {
+ var anchorBase = this.generateUniqueIdBase(el);
+ for (var i = 0; ; i++) {
+ var anchor = anchorBase;
+ if (i > 0) {
+ // add suffix
+ anchor += '-' + i;
+ }
+ // check if ID already exists
+ if (!document.getElementById(anchor)) {
+ return anchor;
+ }
+ }
+ },
+
+ generateAnchor: function(el) {
+ if (el.id) {
+ return el.id;
+ } else {
+ var anchor = this.generateUniqueId(el);
+ el.id = anchor;
+ return anchor;
+ }
+ },
+
+ createNavList: function() {
+ return $('');
+ },
+
+ createChildNavList: function($parent) {
+ var $childList = this.createNavList();
+ $parent.append($childList);
+ return $childList;
+ },
+
+ generateNavEl: function(anchor, text) {
+ var $a = $('');
+ $a.attr('href', '#' + anchor);
+ $a.text(text);
+ var $li = $('');
+ $li.append($a);
+ return $li;
+ },
+
+ generateNavItem: function(headingEl) {
+ var anchor = this.generateAnchor(headingEl);
+ var $heading = $(headingEl);
+ var text = $heading.data('toc-text') || $heading.text();
+ return this.generateNavEl(anchor, text);
+ },
+
+ // Find the first heading level (``, then `
-
-
-
Authors
+ +
+
-
+
Citation
+ Source:DESCRIPTION
+ -
-
-
-
David Cooley. Author, maintainer. -
-
-
Cooley D (2024). +jsonify: Convert Between 'R' Objects and Javascript Object Notation (JSON). +https://symbolixau.github.io/jsonify/, https://github.com/SymbolixAU/jsonify. +
+@Manual{,
+ title = {jsonify: Convert Between 'R' Objects and Javascript Object Notation (JSON)},
+ author = {David Cooley},
+ year = {2024},
+ note = {https://symbolixau.github.io/jsonify/, https://github.com/SymbolixAU/jsonify},
+}
`, then ``, etc.) that has more than one element. Defaults to 1 (for ``).
+ getTopLevel: function($scope) {
+ for (var i = 1; i <= 6; i++) {
+ var $headings = this.findOrFilter($scope, 'h' + i);
+ if ($headings.length > 1) {
+ return i;
+ }
+ }
+
+ return 1;
+ },
+
+ // returns the elements for the top level, and the next below it
+ getHeadings: function($scope, topLevel) {
+ var topSelector = 'h' + topLevel;
+
+ var secondaryLevel = topLevel + 1;
+ var secondarySelector = 'h' + secondaryLevel;
+
+ return this.findOrFilter($scope, topSelector + ',' + secondarySelector);
+ },
+
+ getNavLevel: function(el) {
+ return parseInt(el.tagName.charAt(1), 10);
+ },
+
+ populateNav: function($topContext, topLevel, $headings) {
+ var $context = $topContext;
+ var $prevNav;
+
+ var helpers = this;
+ $headings.each(function(i, el) {
+ var $newNav = helpers.generateNavItem(el);
+ var navLevel = helpers.getNavLevel(el);
+
+ // determine the proper $context
+ if (navLevel === topLevel) {
+ // use top level
+ $context = $topContext;
+ } else if ($prevNav && $context === $topContext) {
+ // create a new level of the tree and switch to it
+ $context = helpers.createChildNavList($prevNav);
+ } // else use the current $context
+
+ $context.append($newNav);
+
+ $prevNav = $newNav;
+ });
+ },
+
+ parseOps: function(arg) {
+ var opts;
+ if (arg.jquery) {
+ opts = {
+ $nav: arg
+ };
+ } else {
+ opts = arg;
+ }
+ opts.$scope = opts.$scope || $(document.body);
+ return opts;
+ }
+ },
+
+ // accepts a jQuery object, or an options object
+ init: function(opts) {
+ opts = this.helpers.parseOps(opts);
+
+ // ensure that the data attribute is in place for styling
+ opts.$nav.attr('data-toggle', 'toc');
+
+ var $topContext = this.helpers.createChildNavList(opts.$nav);
+ var topLevel = this.helpers.getTopLevel(opts.$scope);
+ var $headings = this.helpers.getHeadings(opts.$scope, topLevel);
+ this.helpers.populateNav($topContext, topLevel, $headings);
+ }
+ };
+
+ $(function() {
+ $('nav[data-toggle="toc"]').each(function(i, el) {
+ var $nav = $(el);
+ Toc.init($nav);
+ });
+ });
+})();
diff --git a/docs/index.html b/docs/index.html
index 87158d3..92b61bb 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -5,21 +5,24 @@
-Converts 'R' Objects to Javascript Object Notation (JSON) • jsonify
-
-
-
-
-
-
+Convert Between R Objects and Javascript Object Notation (JSON) • jsonify
+
+
+
+
+
+
+
-
-
+
+
+
+
@@ -62,334 +66,281 @@
+
-
-
+
-
-
-
-
-
-jsonify converts R objects to JSON.
-
-
-There are already JSON converters, why did you build this one?
+
+
+
+Converts between R objects and JSON.
+
+js <- '[{"x":1,"y":"a"},{"x":2,"y":"b"}]'
+( df <- from_json( js ) )
+# x y
+# 1 1 a
+# 2 2 b
+( to_json( df ) )
+# [{"x":1,"y":"a"},{"x":2,"y":"b"}]
+
+There are already JSON converters, why did you build this one?
+
Because I wanted it available at the source ( C++ ) level for integrating into other packages.
-
-
-Is it fast?
-yeah it’s pretty good.
-
-library(microbenchmark)
-library(jsonlite)
-
-n <- 1e6
-df <- data.frame(
- id = 1:n
- , value = sample(letters, size = n, replace = T)
- , val2 = rnorm(n = n)
- , log = sample(c(T,F), size = n, replace = T)
- , stringsAsFactors = FALSE
-)
-
-microbenchmark(
- jsonlite = {
- js <- jsonlite::toJSON( df )
- },
- jsonify = {
- js <- jsonify::to_json( df )
- },
- times = 3
-)
-
-# Unit: seconds
-# expr min lq mean median uq max neval
-# jsonlite 2.017081 2.063732 2.540350 2.110383 2.801984 3.493585 3
-# jsonify 1.186239 1.202719 1.514067 1.219198 1.677981 2.136763 3
-
-n <- 1e4
-x <- list(
- x = rnorm(n = n)
- , y = list(x = rnorm(n = n))
- , z = list( list( x = rnorm(n = n)))
- , xx = rnorm(n = n)
- , yy = data.frame(
- id = 1:n
- , value = sample(letters, size = n, replace = T)
- , val2 = rnorm(n = n)
- , log = sample(c(T,F), size = n, replace = T)
- )
-)
-
-microbenchmark(
- jsonlite = {
- js <- jsonlite::toJSON( x )
- },
- jsonify = {
- js <- jsonify::to_json( x )
- },
- times = 5
-)
-
-# Unit: milliseconds
-# expr min lq mean median uq max neval
-# jsonlite 18.52028 18.82241 19.32112 18.99683 19.18103 21.08508 5
-# jsonify 17.72060 18.19092 19.58308 19.52457 21.14687 21.33241 5
-
+
+What do you mean by “available at the source” ?
+
+I want to be able to call the C++ code from another package, without going to & from R. Therefore, the C++ code is implemented in headers, so you can “link to” it in your own package.
+For example, the LinkingTo section in DESCRIPTION will look something like
+
+And in a c++ source file you can #include the header and use the available functions
+#include "jsonify/jsonify.hpp"
+
+Rcpp::StringVector my_json( Rcpp::DataFrame df ) {
+ return jsonify::api::to_json( df );
+}
+You can see an example of this in my geojsonsf package
+
+- Description
+- #include
+
-
-
-I thought you had an example of it being MUCH quicker than jsonlite ?
-Yeah, but I realised it was comparing two different methods. When jsonify was parsing nested lists, it was parsing data.frames column-wise, whereas jsonlite was row-wise. Which is a slower operation
+
+Can I call it from R if I want to?
+
+Yes. Just like the examples in this readme use to_json()
+
+df <- data.frame(
+ id = 1:3
+ , val = letters[1:3]
+ )
+jsonify::to_json( df )
+# [{"id":1,"val":"a"},{"id":2,"val":"b"},{"id":3,"val":"c"}]
-
-
-Oh right. So it wasn’t a fair test then.
-Correct.
-Here’s a more suitable comparison
-n <- 1e4
-x <- list(
- x = rnorm(n = n)
- , y = list(x = rnorm(n = n))
- , z = list( list( x = rnorm(n = n)))
- , xx = rnorm(n = n)
- , yy = data.frame(
- id = 1:n
- , value = sample(letters, size = n, replace = T)
- , val2 = rnorm(n = n)
- , log = sample(c(T,F), size = n, replace = T)
- )
-)
-
-microbenchmark(
- jsonlite_row = {
- js <- jsonlite::toJSON( x )
- },
- jsonlite_col = {
- js <- jsonlite::toJSON( x, dataframe = "columns" )
- },
- jsonify_row = {
- js <- jsonify::to_json( x )
- },
- jsonify_col = {
- js <- jsonify::to_json( x, by = "column" )
- },
- times = 5
-)
-
-# Unit: milliseconds
-# expr min lq mean median uq max neval
-# jsonlite_row 20.533642 20.717894 27.294220 21.122860 21.426250 52.670456 5
-# jsonlite_col 13.691643 13.812459 15.683795 14.293177 15.655705 20.965993 5
-# jsonify_row 17.506507 17.951948 20.929641 19.827791 21.161389 28.200572 5
-# jsonify_col 7.262305 7.382238 7.409085 7.434759 7.435476 7.530645 5
+
+Is it fast?
+
+yeah it’s pretty good.
+
+
+library(microbenchmark)
+library(jsonlite)
+
+n <- 1e6
+df <- data.frame(
+ id = 1:n
+ , value = sample(letters, size = n, replace = T)
+ , val2 = rnorm(n = n)
+ , log = sample(c(T,F), size = n, replace = T)
+ , stringsAsFactors = FALSE
+)
+
+microbenchmark(
+ jsonlite = {
+ jlt <- jsonlite::toJSON( df )
+ },
+ jsonify = {
+ jfy <- jsonify::to_json( df )
+ },
+ times = 3
+)
+
+# Unit: seconds
+# expr min lq mean median uq max neval
+# jsonlite 2.017081 2.063732 2.540350 2.110383 2.801984 3.493585 3
+# jsonify 1.186239 1.202719 1.514067 1.219198 1.677981 2.136763 3
+
+
+microbenchmark(
+ jsonlite = {
+ df_jlt <- jsonlite::fromJSON( jlt )
+ },
+ jsonify = {
+ df_jfy <- jsonify::from_json( jfy )
+ },
+ times = 3
+)
+
+# Unit: seconds
+# expr min lq mean median uq max neval
+# jsonlite 5.034888 5.149688 5.229363 5.264489 5.326601 5.388713 3
+# jsonify 4.551434 4.629683 4.678198 4.707932 4.741579 4.775227 3
+
+n <- 1e4
+x <- list(
+ x = rnorm(n = n)
+ , y = list(x = rnorm(n = n))
+ , z = list( list( x = rnorm(n = n)))
+ , xx = rnorm(n = n)
+ , yy = data.frame(
+ id = 1:n
+ , value = sample(letters, size = n, replace = T)
+ , val2 = rnorm(n = n)
+ , log = sample(c(T,F), size = n, replace = T)
+ )
+)
+
+microbenchmark(
+ jsonlite = {
+ jlt <- jsonlite::toJSON( x )
+ },
+ jsonify = {
+ jfy <- jsonify::to_json( x )
+ },
+ times = 5
+)
+
+# Unit: milliseconds
+# expr min lq mean median uq max neval
+# jsonlite 18.52028 18.82241 19.32112 18.99683 19.18103 21.08508 5
+# jsonify 17.72060 18.19092 19.58308 19.52457 21.14687 21.33241 5
+
+
+microbenchmark(
+ jsonlite = {
+ df_jlt <- jsonlite::fromJSON( jlt )
+ },
+ jsonify = {
+ df_jfy <- jsonify::from_json( jfy )
+ },
+ times = 3
+)
+
+# Unit: milliseconds
+# expr min lq mean median uq max neval
+# jsonlite 62.53554 62.96435 63.12574 63.39316 63.42084 63.44853 3
+# jsonify 42.47449 42.53826 43.38475 42.60204 43.83988 45.07773 3
-
-
-There’s no Date type in JSON, how have you handled this?
+
+There’s no Date type in JSON, how have you handled this?
+
At its core Dates in R are numeric, so they are treated as numbers when converted to JSON. However, the user can coerce to character through the numeric_dates argument.
-df <- data.frame(dte = as.Date("2018-01-01"))
-jsonify::to_json( df )
-# [{"dte":17532.0}]
-
-df <- data.frame(dte = as.Date("2018-01-01"))
-jsonify::to_json( df, numeric_dates = FALSE )
-# [{"dte":"2018-01-01"}]
+
+df <- data.frame(dte = as.Date("2018-01-01"))
+jsonify::to_json( df )
+# [{"dte":17532.0}]
+
+df <- data.frame(dte = as.Date("2018-01-01"))
+jsonify::to_json( df, numeric_dates = FALSE )
+# [{"dte":"2018-01-01"}]
-
-
-And POSIXct and POSIXlt?
+
+And POSIXct and POSIXlt?
+
The same
-
-jsonify::to_json( as.POSIXct("2018-01-01 10:00:00") )
-# [1514761200.0]
-jsonify::to_json( as.POSIXct("2018-01-01 10:00:00"), numeric_dates = FALSE)
-# ["2017-12-31T23:00:00"]
+
+
+jsonify::to_json( as.POSIXct("2018-01-01 10:00:00") )
+# [1514761200.0]
+jsonify::to_json( as.POSIXct("2018-01-01 10:00:00"), numeric_dates = FALSE)
+# ["2017-12-31T23:00:00"]
However, here the POSIXct values are returned in UTC timezone. This is by design.
POSIXlt will return each component of the date-time
-x <- as.POSIXlt("2018-01-01 01:00:00", tz = "GMT")
-jsonify::to_json( x )
-# {"sec":[0.0],"min":[0],"hour":[1],"mday":[1],"mon":[0],"year":[118],"wday":[1],"yday":[0],"isdst":[0]}
-
-jsonify::to_json( x, numeric_dates = FALSE)
-# {"sec":[0.0],"min":[0],"hour":[1],"mday":[1],"mon":[0],"year":[118],"wday":[1],"yday":[0],"isdst":[0]}
-
-
-
-What about lists?
-The purpose of this library is speed. A lot of overhead is incurred iterating over a list to find and convert objects from one type to another.
-For v0.2.0 I’ve managed to get the date handling at the c++ level, so there’s no penalty for recursing through the list to coerce to character.
-Therefore, lists will work too
-l <- list(
- dte = as.Date("2018-01-01")
- , psx = seq(as.POSIXct("2018-01-01 13:00:00"), as.POSIXct("2018-01-05 13:00:00"), length.out = 5)
- , df = data.frame(psx = seq(as.POSIXct("2018-01-01 13:00:00"), as.POSIXct("2018-01-05 13:00:00"), length.out = 5))
-)
-jsonify::to_json( l )
-# {"dte":[17532.0],"psx":[1514772000,1514858400,1514944800,1515031200,1515117600],"df":[{"psx":1514772000},{"psx":1514858400},{"psx":1514944800},{"psx":1515031200},{"psx":1515117600}]}
-js <- jsonify::to_json( l, numeric_dates = FALSE )
-jsonify::pretty_json( js )
-# {
-# "dte": [
-# "2018-01-01"
-# ],
-# "psx": [
-# "2018-01-01T02:00:00",
-# "2018-01-02T02:00:00",
-# "2018-01-03T02:00:00",
-# "2018-01-04T02:00:00",
-# "2018-01-05T02:00:00"
-# ],
-# "df": [
-# {
-# "psx": "2018-01-01T02:00:00"
-# },
-# {
-# "psx": "2018-01-02T02:00:00"
-# },
-# {
-# "psx": "2018-01-03T02:00:00"
-# },
-# {
-# "psx": "2018-01-04T02:00:00"
-# },
-# {
-# "psx": "2018-01-05T02:00:00"
-# }
-# ]
-# }
-And it’s still fast because of the design choice to coerce dates to UTC. All the date handling is done at the C++ leve, not R. So it’s faster.
-dtes <- seq(as.Date("2018-01-01"), as.Date("2019-01-01"), length.out = 365)
-psx <- seq(as.POSIXct("2018-01-01"), as.POSIXct("2019-01-01"), length.out = 365)
-n <- 1e5
-
-lst <- list(
- x = sample(dtes, size = n, replace = T)
- , y = list(
- ya = sample(dtes, size = n, replace = TRUE)
- , yb = rnorm(n = n)
- , yx = list( sample(dtes, size = n, replace = T ) )
- )
- , p = psx
-)
-
-library( microbenchmark )
-
-microbenchmark(
- jsonify1 = {
- jsonify::to_json( lst, numeric_dates = TRUE )
- },
- jsonify2 = {
- jsonify::to_json( lst, numeric_dates = FALSE )
- },
- jsonlite = {
- jsonlite::toJSON( lst )
- },
- times = 3
-)
-# Unit: milliseconds
-# expr min lq mean median uq max neval
-# jsonify1 60.26762 62.9191 70.36983 65.57057 75.42093 85.2713 3
-# jsonify2 314.75788 315.3369 331.71612 315.91598 340.19524 364.4745 3
-# jsonlite 674.26576 709.8997 737.83201 745.53362 769.61514 793.6967 3
+
+x <- as.POSIXlt("2018-01-01 01:00:00", tz = "GMT")
+jsonify::to_json( x )
+# {"sec":[0.0],"min":[0],"hour":[1],"mday":[1],"mon":[0],"year":[118],"wday":[1],"yday":[0],"isdst":[0]}
+
+jsonify::to_json( x, numeric_dates = FALSE)
+# {"sec":[0.0],"min":[0],"hour":[1],"mday":[1],"mon":[0],"year":[118],"wday":[1],"yday":[0],"isdst":[0]}
-
-
-That output looks nice, is that pretty_json() function new?
-Yep, it’s a new feature in v0.2.0
+
+I see factors are converted to strings
+
+Yep. Even though I constructed a data.frame() without setting stringsAsFactros = FALSE, jsonify automatically treats factors as strings.
-
-
-What do you mean by “available at the source” ?
-I want to be able to call the C++ code from another package, without going to & from R. Therefore, the C++ code is implemented in headers, so you can “link to” it in your own package.
-For example, the LinkingTo section in DESCRIPTION will look something like
-LinkingTo:
- Rcpp,
- jsonify
-And in a c++ source file you can #include the header and use the available functions
-
-
-
-
-Can I call it from R if I want to?
-Yes. Just like the examples in this readme use to_json()
-
-
-
-
-I see factors are converted to strings
-Yep. Even though I constructed a data.frame() without setting stringsAsFactros = FALSE, jsonify automatically treats factors as strings.
-
-
-
-Has this changed from v0.1?
+
+Has this changed from v0.1?
+
Yes. And it’s to keep the data more inline with modern concepts and design patterns.
If you want factors, use factors_as_string = FALSE in the to_json() call
-jsonify::to_json( df, factors_as_string = FALSE )
-# [{"id":1,"val":1},{"id":2,"val":2},{"id":3,"val":3}]
+
+jsonify::to_json( df, factors_as_string = FALSE )
+# [{"dte":17532.0}]
-
-
-How do I install it?
+
+How do I install it?
+
Get the latest release version from CRAN
-
-Or the development version from GitHub with:
-
+
+install.packages("jsonify")
+Or the development version from GitHub with:
+
+# install.packages("devtools")
+devtools::install_github("SymbolixAU/jsonify")
+
-
+
+
+
diff --git a/docs/news/index.html b/docs/news/index.html
index 2738134..55662fb 100644
--- a/docs/news/index.html
+++ b/docs/news/index.html
@@ -1,55 +1,12 @@
-
-
-
-
-
-
-
-Changelog • jsonify
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-Changelog • jsonify
-
+
+
-
-
-
-
-
-
-
+
-
+
-
+
+
+
-
-
+
diff --git a/docs/pkgdown.css b/docs/pkgdown.css
index c03fb08..80ea5b8 100644
--- a/docs/pkgdown.css
+++ b/docs/pkgdown.css
@@ -17,12 +17,14 @@ html, body {
height: 100%;
}
+body {
+ position: relative;
+}
+
body > .container {
display: flex;
height: 100%;
flex-direction: column;
-
- padding-top: 60px;
}
body > .container .row {
@@ -54,8 +56,10 @@ img.icon {
float: right;
}
-img {
+/* Ensure in-page images don't run outside their container */
+.contents img {
max-width: 100%;
+ height: auto;
}
/* Fix bug in bootstrap (only seen in firefox) */
@@ -69,14 +73,17 @@ summary {
margin-top: calc(-60px + 1em);
}
+dd {
+ margin-left: 3em;
+}
+
/* Section anchors ---------------------------------*/
a.anchor {
- margin-left: -30px;
- display:inline-block;
- width: 30px;
- height: 30px;
- visibility: hidden;
+ display: none;
+ margin-left: 5px;
+ width: 20px;
+ height: 20px;
background-image: url(./link.svg);
background-repeat: no-repeat;
@@ -84,17 +91,15 @@ a.anchor {
background-position: center center;
}
-.hasAnchor:hover a.anchor {
- visibility: visible;
-}
-
-@media (max-width: 767px) {
- .hasAnchor:hover a.anchor {
- visibility: hidden;
- }
+h1:hover .anchor,
+h2:hover .anchor,
+h3:hover .anchor,
+h4:hover .anchor,
+h5:hover .anchor,
+h6:hover .anchor {
+ display: inline-block;
}
-
/* Fixes for fixed navbar --------------------------*/
.contents h1, .contents h2, .contents h3, .contents h4 {
@@ -102,37 +107,135 @@ a.anchor {
margin-top: -40px;
}
-/* Static header placement on mobile devices */
-@media (max-width: 767px) {
- .navbar-fixed-top {
- position: absolute;
- }
- .navbar {
- padding: 0;
- }
+/* Navbar submenu --------------------------*/
+
+.dropdown-submenu {
+ position: relative;
+}
+
+.dropdown-submenu>.dropdown-menu {
+ top: 0;
+ left: 100%;
+ margin-top: -6px;
+ margin-left: -1px;
+ border-radius: 0 6px 6px 6px;
+}
+
+.dropdown-submenu:hover>.dropdown-menu {
+ display: block;
+}
+
+.dropdown-submenu>a:after {
+ display: block;
+ content: " ";
+ float: right;
+ width: 0;
+ height: 0;
+ border-color: transparent;
+ border-style: solid;
+ border-width: 5px 0 5px 5px;
+ border-left-color: #cccccc;
+ margin-top: 5px;
+ margin-right: -10px;
+}
+
+.dropdown-submenu:hover>a:after {
+ border-left-color: #ffffff;
}
+.dropdown-submenu.pull-left {
+ float: none;
+}
+
+.dropdown-submenu.pull-left>.dropdown-menu {
+ left: -100%;
+ margin-left: 10px;
+ border-radius: 6px 0 6px 6px;
+}
/* Sidebar --------------------------*/
-#sidebar {
+#pkgdown-sidebar {
margin-top: 30px;
+ position: -webkit-sticky;
+ position: sticky;
+ top: 70px;
}
-#sidebar h2 {
+
+#pkgdown-sidebar h2 {
font-size: 1.5em;
margin-top: 1em;
}
-#sidebar h2:first-child {
+#pkgdown-sidebar h2:first-child {
margin-top: 0;
}
-#sidebar .list-unstyled li {
+#pkgdown-sidebar .list-unstyled li {
margin-bottom: 0.5em;
}
+/* bootstrap-toc tweaks ------------------------------------------------------*/
+
+/* All levels of nav */
+
+nav[data-toggle='toc'] .nav > li > a {
+ padding: 4px 20px 4px 6px;
+ font-size: 1.5rem;
+ font-weight: 400;
+ color: inherit;
+}
+
+nav[data-toggle='toc'] .nav > li > a:hover,
+nav[data-toggle='toc'] .nav > li > a:focus {
+ padding-left: 5px;
+ color: inherit;
+ border-left: 1px solid #878787;
+}
+
+nav[data-toggle='toc'] .nav > .active > a,
+nav[data-toggle='toc'] .nav > .active:hover > a,
+nav[data-toggle='toc'] .nav > .active:focus > a {
+ padding-left: 5px;
+ font-size: 1.5rem;
+ font-weight: 400;
+ color: inherit;
+ border-left: 2px solid #878787;
+}
+
+/* Nav: second level (shown on .active) */
+
+nav[data-toggle='toc'] .nav .nav {
+ display: none; /* Hide by default, but at >768px, show it */
+ padding-bottom: 10px;
+}
+
+nav[data-toggle='toc'] .nav .nav > li > a {
+ padding-left: 16px;
+ font-size: 1.35rem;
+}
+
+nav[data-toggle='toc'] .nav .nav > li > a:hover,
+nav[data-toggle='toc'] .nav .nav > li > a:focus {
+ padding-left: 15px;
+}
+
+nav[data-toggle='toc'] .nav .nav > .active > a,
+nav[data-toggle='toc'] .nav .nav > .active:hover > a,
+nav[data-toggle='toc'] .nav .nav > .active:focus > a {
+ padding-left: 15px;
+ font-weight: 500;
+ font-size: 1.35rem;
+}
+
+/* orcid ------------------------------------------------------------------- */
+
.orcid {
- height: 16px;
+ font-size: 16px;
+ color: #A6CE39;
+ /* margins are required by official ORCID trademark and display guidelines */
+ margin-left:4px;
+ margin-right:4px;
vertical-align: middle;
}
@@ -140,14 +243,14 @@ a.anchor {
.ref-index th {font-weight: normal;}
-.ref-index td {vertical-align: top;}
+.ref-index td {vertical-align: top; min-width: 100px}
.ref-index .icon {width: 40px;}
.ref-index .alias {width: 40%;}
.ref-index-icons .alias {width: calc(40% - 40px);}
.ref-index .title {width: 60%;}
.ref-arguments th {text-align: right; padding-right: 10px;}
-.ref-arguments th, .ref-arguments td {vertical-align: top;}
+.ref-arguments th, .ref-arguments td {vertical-align: top; min-width: 100px}
.ref-arguments .name {width: 20%;}
.ref-arguments .desc {width: 80%;}
@@ -160,31 +263,26 @@ table {
/* Syntax highlighting ---------------------------------------------------- */
-pre {
- word-wrap: normal;
- word-break: normal;
- border: 1px solid #eee;
-}
-
-pre, code {
+pre, code, pre code {
background-color: #f8f8f8;
color: #333;
}
+pre, pre code {
+ white-space: pre-wrap;
+ word-break: break-all;
+ overflow-wrap: break-word;
+}
-pre code {
- overflow: auto;
- word-wrap: normal;
- white-space: pre;
+pre {
+ border: 1px solid #eee;
}
-pre .img {
+pre .img, pre .r-plt {
margin: 5px 0;
}
-pre .img img {
+pre .img img, pre .r-plt img {
background-color: #fff;
- display: block;
- height: auto;
}
code a, pre a {
@@ -201,9 +299,8 @@ a.sourceLine:hover {
.kw {color: #264D66;} /* keyword */
.co {color: #888888;} /* comment */
-.message { color: black; font-weight: bolder;}
-.error { color: orange; font-weight: bolder;}
-.warning { color: #6A0366; font-weight: bolder;}
+.error {font-weight: bolder;}
+.warning {font-weight: bolder;}
/* Clipboard --------------------------*/
@@ -222,6 +319,19 @@ a.sourceLine:hover {
visibility: visible;
}
+/* headroom.js ------------------------ */
+
+.headroom {
+ will-change: transform;
+ transition: transform 200ms linear;
+}
+.headroom--pinned {
+ transform: translateY(0%);
+}
+.headroom--unpinned {
+ transform: translateY(-100%);
+}
+
/* mark.js ----------------------------*/
mark {
@@ -234,3 +344,41 @@ mark {
.html-widget {
margin-bottom: 10px;
}
+
+/* fontawesome ------------------------ */
+
+.fab {
+ font-family: "Font Awesome 5 Brands" !important;
+}
+
+/* don't display links in code chunks when printing */
+/* source: https://stackoverflow.com/a/10781533 */
+@media print {
+ code a:link:after, code a:visited:after {
+ content: "";
+ }
+}
+
+/* Section anchors ---------------------------------
+ Added in pandoc 2.11: https://github.com/jgm/pandoc-templates/commit/9904bf71
+*/
+
+div.csl-bib-body { }
+div.csl-entry {
+ clear: both;
+}
+.hanging-indent div.csl-entry {
+ margin-left:2em;
+ text-indent:-2em;
+}
+div.csl-left-margin {
+ min-width:2em;
+ float:left;
+}
+div.csl-right-inline {
+ margin-left:2em;
+ padding-left:1em;
+}
+div.csl-indent {
+ margin-left: 2em;
+}
diff --git a/docs/pkgdown.js b/docs/pkgdown.js
index eb7e83d..6f0eee4 100644
--- a/docs/pkgdown.js
+++ b/docs/pkgdown.js
@@ -2,18 +2,11 @@
(function($) {
$(function() {
- $("#sidebar")
- .stick_in_parent({offset_top: 40})
- .on('sticky_kit:bottom', function(e) {
- $(this).parent().css('position', 'static');
- })
- .on('sticky_kit:unbottom', function(e) {
- $(this).parent().css('position', 'relative');
- });
+ $('.navbar-fixed-top').headroom();
- $('body').scrollspy({
- target: '#sidebar',
- offset: 60
+ $('body').css('padding-top', $('.navbar').height() + 10);
+ $(window).resize(function(){
+ $('body').css('padding-top', $('.navbar').height() + 10);
});
$('[data-toggle="tooltip"]').tooltip();
@@ -87,7 +80,7 @@
$(document).ready(function() {
var copyButton = "";
- $(".examples, div.sourceCode").addClass("hasCopyButton");
+ $("div.sourceCode").addClass("hasCopyButton");
// Insert copy buttons:
$(copyButton).prependTo(".hasCopyButton");
@@ -98,7 +91,7 @@
// Initialize clipboard:
var clipboardBtnCopies = new ClipboardJS('[data-clipboard-copy]', {
text: function(trigger) {
- return trigger.parentNode.textContent;
+ return trigger.parentNode.textContent.replace(/\n#>[^\n]*/g, "");
}
});
diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml
index 6a18080..619f050 100644
--- a/docs/pkgdown.yml
+++ b/docs/pkgdown.yml
@@ -1,6 +1,7 @@
-pandoc: 2.3.1
-pkgdown: 1.3.0
+pandoc: 3.1.1
+pkgdown: 2.0.7
pkgdown_sha: ~
articles:
jsonify: jsonify.html
+last_built: 2024-01-17T21:33Z
diff --git a/docs/reference/Rplot001.png b/docs/reference/Rplot001.png
new file mode 100644
index 0000000000000000000000000000000000000000..17a358060aed2a86950757bbd25c6f92c08c458f
GIT binary patch
literal 1011
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zVg?3oArNM~bhqvg0|WD9PZ!6KiaBo&GBN^{G%5UFpXcEKVvd5*5Eu=C0SJK)8A6*F
U7`aXvEC5;V>FVdQ&MBb@00SN#Z2$lO
literal 0
HcmV?d00001
diff --git a/docs/reference/as.json.html b/docs/reference/as.json.html
new file mode 100644
index 0000000..596a781
--- /dev/null
+++ b/docs/reference/as.json.html
@@ -0,0 +1,101 @@
+
+Coerce string to JSON — as.json • jsonify
+
+
+
+
+
+
+
+
+
+
+
+
+ Coerce string to JSON
+
+
+
+ as.json(x)
+
+
+
+ Arguments
+ - x
+string to coerce to JSON
+
+
+ Examples
+
+js <- '{"x":1,"y":2}'
+as.json(js)
+#> {"x":1,"y":2}
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/docs/reference/from_json.html b/docs/reference/from_json.html
new file mode 100644
index 0000000..5d183b6
--- /dev/null
+++ b/docs/reference/from_json.html
@@ -0,0 +1,239 @@
+
+From JSON — from_json • jsonify
+
+
+
+
+
+
+
+
+
+
+
+
+ Converts JSON to an R object.
+
+
+
+ from_json(json, simplify = TRUE, fill_na = FALSE, buffer_size = 1024)
+
+
+
+ Arguments
+ - json
+JSON to convert to R object. Can be a string, url or link to a file.
- simplify
+logical, if TRUE, coerces JSON to the simplest R object possible. See Details
- fill_na
+logical, if TRUE and simplify is TRUE,
+data.frames will be na-filled if there are missing JSON keys.
+Ignored if simplify is FALSE. See details and examples.
- buffer_size
+size of buffer used when reading a file from disk. Defaults to 1024
+
+ Details
+ When simplify = TRUE
single arrays are coerced to vectors
array of arrays (all the same length) are coerced to matrices
objects with the same keys are coerced to data.frames
When simplify = TRUE and fill_na = TRUE
objects are coerced to data.frames, and any missing values are filled with NAs
+
+
+ Examples
+
+from_json('{"a":[1, 2, 3]}')
+#> $a
+#> [1] 1 2 3
+#>
+from_json('{"a":8, "b":99.5, "c":true, "d":"cats", "e":[1, "cats", 3]}')
+#> $a
+#> [1] 8
+#>
+#> $b
+#> [1] 99.5
+#>
+#> $c
+#> [1] TRUE
+#>
+#> $d
+#> [1] "cats"
+#>
+#> $e
+#> [1] "1" "cats" "3"
+#>
+from_json('{"a":8, "b":{"c":123, "d":{"e":456}}}')
+#> $a
+#> [1] 8
+#>
+#> $b
+#> $b$c
+#> [1] 123
+#>
+#> $b$d
+#> $b$d$e
+#> [1] 456
+#>
+#>
+#>
+
+lst <- list("a" = 5L, "b" = 1.43, "c" = "cats", "d" = FALSE)
+js <- jsonify::to_json(lst, unbox = TRUE)
+from_json( js )
+#> $a
+#> [1] 5
+#>
+#> $b
+#> [1] 1.43
+#>
+#> $c
+#> [1] "cats"
+#>
+#> $d
+#> [1] FALSE
+#>
+
+## Return a data frame
+from_json('[{"id":1,"val":"a"},{"id":2,"val":"b"}]')
+#> id val
+#> 1 1 a
+#> 2 2 b
+
+## Return a data frame with a list column
+from_json('[{"id":1,"val":"a"},{"id":2,"val":["b","c"]}]')
+#> id val
+#> 1 1 a
+#> 2 2 b, c
+
+## Without simplifying to a data.frame
+from_json('[{"id":1,"val":"a"},{"id":2,"val":["b","c"]}]', simplify = FALSE )
+#> [[1]]
+#> [[1]]$id
+#> [1] 1
+#>
+#> [[1]]$val
+#> [1] "a"
+#>
+#>
+#> [[2]]
+#> [[2]]$id
+#> [1] 2
+#>
+#> [[2]]$val
+#> [[2]]$val[[1]]
+#> [1] "b"
+#>
+#> [[2]]$val[[2]]
+#> [1] "c"
+#>
+#>
+#>
+
+## Missing JSON keys
+from_json('[{"x":1},{"x":2,"y":"hello"}]')
+#> [[1]]
+#> [[1]]$x
+#> [1] 1
+#>
+#>
+#> [[2]]
+#> [[2]]$x
+#> [1] 2
+#>
+#> [[2]]$y
+#> [1] "hello"
+#>
+#>
+
+## Missing JSON keys - filling with NAs
+from_json('[{"x":1},{"x":2,"y":"hello"}]', fill_na = TRUE )
+#> x y
+#> 1 1 <NA>
+#> 2 2 hello
+
+## Duplicate object keys
+from_json('[{"x":1,"x":"a"},{"x":2,"x":"b"}]')
+#> x
+#> 1 1
+#> 2 2
+
+from_json('[{"id":1,"val":"a","val":1},{"id":2,"val":"b"}]', fill_na = TRUE )
+#> id val
+#> 1 1 a
+#> 2 2 b
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/docs/reference/from_ndjson.html b/docs/reference/from_ndjson.html
new file mode 100644
index 0000000..e8151c5
--- /dev/null
+++ b/docs/reference/from_ndjson.html
@@ -0,0 +1,117 @@
+
+from ndjson — from_ndjson • jsonify
+
+
+
+
+
+
+
+
+
+
+
+
+ Converts ndjson into R objects
+
+
+
+ from_ndjson(ndjson, simplify = TRUE, fill_na = FALSE)
+
+
+
+ Arguments
+ - ndjson
+new-line delimited JSON to convert to R object. Can be a string, url or link to a file.
- simplify
+logical, if TRUE, coerces JSON to the simplest R object possible. See Details
- fill_na
+logical, if TRUE and simplify is TRUE,
+data.frames will be na-filled if there are missing JSON keys.
+Ignored if simplify is FALSE. See details and examples.
+
+
+ Examples
+
+js <- to_ndjson( data.frame( x = 1:5, y = 6:10 ) )
+from_ndjson( js )
+#> x y
+#> 1 1 6
+#> 2 2 7
+#> 3 3 8
+#> 4 4 9
+#> 5 5 10
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/docs/reference/index.html b/docs/reference/index.html
index 24c1c74..9406733 100644
--- a/docs/reference/index.html
+++ b/docs/reference/index.html
@@ -1,55 +1,12 @@
-
-
-
-
-
-
-
-Function reference • jsonify
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-Function reference • jsonify
-
+
+
-
-
-
-
-
-
-
+
-
+
+
+
-
-
+
diff --git a/docs/reference/jsondf-package.html b/docs/reference/jsondf-package.html
deleted file mode 100644
index c2c01f0..0000000
--- a/docs/reference/jsondf-package.html
+++ /dev/null
@@ -1,174 +0,0 @@
-
-
-
-
-
-
-
-
-A short title line describing what the package does — jsondf-package • jsonify
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
- A short title line describing what the package does
-
- jsondf-package.Rd
-
-
-
-
- A more detailed description of what the package does. A length
- of about one to five lines is recommended.
-
-
-
-
- Details
-
- This section should provide a more detailed overview of how to use the
- package, including the most important functions.
-
- References
-
- This optional section can contain literature or other references for
- background information.
-
- See also
-
- Optional links to other man pages
-
-
- Examples
- # NOT RUN {
- ## Optional simple examples of the most important functions
- ## These can be in \dontrun{} and \donttest{} blocks.
-
-# }
-
-
-
-
-
-
-
-
-
-
-
-
-
diff --git a/docs/reference/minify_json.html b/docs/reference/minify_json.html
index 43c8418..9056933 100644
--- a/docs/reference/minify_json.html
+++ b/docs/reference/minify_json.html
@@ -1,58 +1,12 @@
-
-
-
-
-
-
-
-Minify Json — minify_json • jsonify
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-Minify Json — minify_json • jsonify
-
-
-
+
+
-
-
-
-
-
+
-
Removes indentiation from a JSON string
-
- minify_json(json, ...)
-
- Arguments
-
-
- json
- string of JSON
-
- ...
- other argments passed to to_json
-
-
+
+ minify_json(json, ...)
+
- Examples
-
-df <- data.frame(id = 1:10, val = rnorm(10))
-js <- to_json( df )
-jsp <- pretty_json(js)
-minify_json( jsp )#> [{"id":1,"val":-1.4000435167217549},{"id":2,"val":0.2553170548452597},{"id":3,"val":-2.437263611219531},{"id":4,"val":-0.005571286746160735},{"id":5,"val":0.6215527214152141},{"id":6,"val":1.1484116060260608},{"id":7,"val":-1.821817660976626},{"id":8,"val":-0.24732530207352436},{"id":9,"val":-0.24419960677838332},{"id":10,"val":-0.2827054488144648}]
-
-
-
+
-
+
+
+
-
-
+
diff --git a/docs/reference/pretty_json.html b/docs/reference/pretty_json.html
index 2b50153..54a767d 100644
--- a/docs/reference/pretty_json.html
+++ b/docs/reference/pretty_json.html
@@ -1,58 +1,12 @@
-
-
-
-
-
-
-
-Pretty Json — pretty_json • jsonify
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-Pretty Json — pretty_json • jsonify
-
-
-
+
+
-
-
-
-
-
+
-
Adds indentiation to a JSON string
-
- pretty_json(json, ...)
-
- Arguments
-
-
- json
- string of JSON
-
- ...
- other argments passed to to_json
-
-
-
- Examples
- #> [
-#> {
-#> "id": 1,
-#> "val": -0.5536993836887205
-#> },
-#> {
-#> "id": 2,
-#> "val": 0.628982042036008
-#> },
-#> {
-#> "id": 3,
-#> "val": 2.065024895359223
-#> },
-#> {
-#> "id": 4,
-#> "val": -1.6309894020822316
-#> },
-#> {
-#> "id": 5,
-#> "val": 0.5124269498518048
-#> },
-#> {
-#> "id": 6,
-#> "val": -1.863011492068328
-#> },
-#> {
-#> "id": 7,
-#> "val": -0.5220125147454544
-#> },
-#> {
-#> "id": 8,
-#> "val": -0.05260190995387954
-#> },
-#> {
-#> "id": 9,
-#> "val": 0.5429963426611403
-#> },
-#> {
-#> "id": 10,
-#> "val": -0.9140748272599284
-#> }
-#> ]
-## can also use directly on an R object
-pretty_json( df )#> [
-#> {
-#> "id": 1,
-#> "val": -0.5536993836887205
-#> },
-#> {
-#> "id": 2,
-#> "val": 0.628982042036008
-#> },
-#> {
-#> "id": 3,
-#> "val": 2.065024895359223
-#> },
-#> {
-#> "id": 4,
-#> "val": -1.6309894020822316
-#> },
-#> {
-#> "id": 5,
-#> "val": 0.5124269498518048
-#> },
-#> {
-#> "id": 6,
-#> "val": -1.863011492068328
-#> },
-#> {
-#> "id": 7,
-#> "val": -0.5220125147454544
-#> },
-#> {
-#> "id": 8,
-#> "val": -0.05260190995387954
-#> },
-#> {
-#> "id": 9,
-#> "val": 0.5429963426611403
-#> },
-#> {
-#> "id": 10,
-#> "val": -0.9140748272599284
-#> }
-#> ]
-
-
-
+
-
+
+
+
-
-
+
diff --git a/docs/reference/to_json.html b/docs/reference/to_json.html
index 76eacee..fea2f01 100644
--- a/docs/reference/to_json.html
+++ b/docs/reference/to_json.html
@@ -1,58 +1,12 @@
-
-
-
-
-
-
-
-To JSON — to_json • jsonify
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-To JSON — to_json • jsonify
-
-
-
+
+
-
-
-
-
-
+
-
Converts R objects to JSON
-
- to_json(x, unbox = FALSE, digits = NULL, numeric_dates = TRUE,
- factors_as_string = TRUE, by = "row")
-
- Arguments
-
-
- x
- object to convert to JSON
-
- unbox
- logical indicating if single-value arrays should be 'unboxed',
-that is, not contained inside an array.
-
- digits
- integer specifying the number of decimal places to round numerics.
-Default is NULL - no rounding
-
- numeric_dates
- logical indicating if dates should be treated as numerics.
-Defaults to TRUE for speed. If FALSE, the dates will be coerced to character in UTC time zone
-
- factors_as_string
- logical indicating if factors should be treated as strings. Defaults to TRUE.
-
- by
- either "row" or "column" indicating if data.frames and matrices should be processed
-row-wise or column-wise. Defaults to "row"
-
-
-
- Examples
-
-to_json(1:3)#> [1,2,3]to_json(letters[1:3])#> ["a","b","c"]#> [{"x":1,"y":"a"},{"x":2,"y":"b"},{"x":3,"y":"c"}]#> {"x":[1,2,3],"y":{"z":["a","b","c"]}}#> [17532,17533,17534,17535,17536]#> ["2018-01-01","2018-01-02","2018-01-03","2018-01-04","2018-01-05"]
-psx <- seq(
- as.POSIXct("2018-01-01", tz = "Australia/Melbourne"),
- as.POSIXct("2018-02-01", tz = "Australia/Melbourne"),
- length.out = 5
- )
-to_json(psx)#> [1514725200,1515394800,1516064400,1516734000,1517403600]to_json(psx, numeric_dates = FALSE)#> ["2017-12-31T13:00:00","2018-01-08T07:00:00","2018-01-16T01:00:00","2018-01-23T19:00:00","2018-01-31T13:00:00"]#> {"x":1.0}#> {"x":1.0,"y":"a","z":{"x":2.0,"y":"b"}}
-## rounding numbers using the digits argument
-to_json(1.23456789, digits = 2)#> [1.23]#> [{"x":1,"y":0.0,"z":"a"},{"x":2,"y":0.0,"z":"b"},{"x":3,"y":-1.0,"z":"c"}]
-## keeping factors
-to_json(df, digits = 2, factors_as_string = FALSE )#> [{"x":1,"y":0.47,"z":1},{"x":2,"y":0.36,"z":2},{"x":3,"y":-1.3,"z":3}]
-
-
-
-
+
-
+
+
+
-
-
+
diff --git a/docs/reference/to_ndjson.html b/docs/reference/to_ndjson.html
new file mode 100644
index 0000000..78be0f5
--- /dev/null
+++ b/docs/reference/to_ndjson.html
@@ -0,0 +1,199 @@
+
+To ndjson — to_ndjson • jsonify
+
+
+
+
+
+
+
+
+
+
+
+
+ Converts R objects to ndjson
+
+
+
+ to_ndjson(
+ x,
+ unbox = FALSE,
+ digits = NULL,
+ numeric_dates = TRUE,
+ factors_as_string = TRUE,
+ by = "row"
+)
+
+
+
+ Arguments
+ - x
+object to convert to JSON
- unbox
+logical indicating if single-value arrays should be 'unboxed',
+that is, not contained inside an array.
- digits
+integer specifying the number of decimal places to round numerics.
+Default is NULL - no rounding
- numeric_dates
+logical indicating if dates should be treated as numerics.
+Defaults to TRUE for speed. If FALSE, the dates will be coerced to character in UTC time zone
- factors_as_string
+logical indicating if factors should be treated as strings. Defaults to TRUE.
- by
+either "row" or "column" indicating if data.frames and matrices should be processed
+row-wise or column-wise. Defaults to "row"
+
+ Details
+ Lists are converted to ndjson non-recursively. That is, each of the objects
+in the list at the top level are converted to a new-line JSON object. Any nested
+sub-elements are then contained within that JSON object. See examples
+
+
+
+ Examples
+
+to_ndjson( 1:5 )
+#> [1,2,3,4,5]
+to_ndjson( letters )
+#> ["a","b","c","d","e","f","g","h","i","j","k","l","m","n","o","p","q","r","s","t","u","v","w","x","y","z"]
+
+mat <- matrix(1:6, ncol = 2)
+
+to_ndjson( x = mat )
+#> [1,4]
+#> [2,5]
+#> [3,6]
+to_ndjson( x = mat, by = "col" )
+#> [1,2,3]
+#> [4,5,6]
+
+df <- data.frame(
+ x = 1:5
+ , y = letters[1:5]
+ , z = as.Date(seq(18262, 18262 + 4, by = 1 ), origin = "1970-01-01" )
+ )
+
+to_ndjson( x = df )
+#> {"x":1,"y":"a","z":18262.0}
+#> {"x":2,"y":"b","z":18263.0}
+#> {"x":3,"y":"c","z":18264.0}
+#> {"x":4,"y":"d","z":18265.0}
+#> {"x":5,"y":"e","z":18266.0}
+to_ndjson( x = df, numeric_dates = FALSE )
+#> {"x":1,"y":"a","z":"2020-01-01"}
+#> {"x":2,"y":"b","z":"2020-01-02"}
+#> {"x":3,"y":"c","z":"2020-01-03"}
+#> {"x":4,"y":"d","z":"2020-01-04"}
+#> {"x":5,"y":"e","z":"2020-01-05"}
+to_ndjson( x = df, factors_as_string = FALSE )
+#> {"x":1,"y":"a","z":18262.0}
+#> {"x":2,"y":"b","z":18263.0}
+#> {"x":3,"y":"c","z":18264.0}
+#> {"x":4,"y":"d","z":18265.0}
+#> {"x":5,"y":"e","z":18266.0}
+to_ndjson( x = df, by = "column" )
+#> {"x":[1,2,3,4,5]}
+#> {"y":["a","b","c","d","e"]}
+#> {"z":[18262.0,18263.0,18264.0,18265.0,18266.0]}
+to_ndjson( x = df, by = "column", numeric_dates = FALSE )
+#> {"x":[1,2,3,4,5]}
+#> {"y":["a","b","c","d","e"]}
+#> {"z":["2020-01-01","2020-01-02","2020-01-03","2020-01-04","2020-01-05"]}
+
+## Lists are non-recurisve; only elements `x` and `y` are converted to ndjson
+lst <- list(
+ x = 1:5
+ , y = list(
+ a = letters[1:5]
+ , b = data.frame(i = 10:15, j = 20:25)
+ )
+)
+
+to_ndjson( x = lst )
+#> {"x":[1,2,3,4,5]}
+#> {"y":{"a":["a","b","c","d","e"],"b":[{"i":10,"j":20},{"i":11,"j":21},{"i":12,"j":22},{"i":13,"j":23},{"i":14,"j":24},{"i":15,"j":25}]}}
+to_ndjson( x = lst, by = "column")
+#> {"x":[1,2,3,4,5]}
+#> {"y":{"a":["a","b","c","d","e"],"b":{"i":[10,11,12,13,14,15],"j":[20,21,22,23,24,25]}}}
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/docs/reference/validate_json.html b/docs/reference/validate_json.html
index 8d3e6d5..7a31dfa 100644
--- a/docs/reference/validate_json.html
+++ b/docs/reference/validate_json.html
@@ -1,58 +1,12 @@
-
-
-
-
-
-
-
-validate JSON — validate_json • jsonify
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-validate JSON — validate_json • jsonify
-
-
-
+
+
-
-
-
-
-
+
-
Validates JSON
-
- validate_json(json)
-
- Arguments
-
-
- json
- character or json object
-
-
- Value
+
+ validate_json(json)
+
- logical vector
+
+ Arguments
+ - json
+character or json object
+
+ Value
- Examples
-
-validate_json('[]')#> [1] TRUE#> [1] TRUE
-validate_json('{"x":1,"y":2,"z":"a"}')#> [1] TRUE#> [1] TRUE TRUE#> [1] FALSE TRUE
-
-
-
+
+ Examples
+
+validate_json('[]')
+#> [1] TRUE
+df <- data.frame(id = 1:5, val = letters[1:5])
+validate_json( to_json(df) )
+#> [1] TRUE
+
+validate_json('{"x":1,"y":2,"z":"a"}')
+#> [1] TRUE
+
+validate_json( c('{"x":1,"y":2,"z":"a"}', to_json(df) ) )
+#> [1] TRUE TRUE
+validate_json( c('{"x":1,"y":2,"z":a}', to_json(df) ) )
+#> [1] FALSE TRUE
+
+
+
+
-
+
+
+
-
-
+
diff --git a/docs/sitemap.xml b/docs/sitemap.xml
new file mode 100644
index 0000000..af36988
--- /dev/null
+++ b/docs/sitemap.xml
@@ -0,0 +1,54 @@
+
+
+
+ /404.html
+
+
+ /LICENSE-text.html
+
+
+ /LICENSE.html
+
+
+ /articles/index.html
+
+
+ /articles/jsonify.html
+
+
+ /authors.html
+
+
+ /index.html
+
+
+ /news/index.html
+
+
+ /reference/as.json.html
+
+
+ /reference/from_json.html
+
+
+ /reference/from_ndjson.html
+
+
+ /reference/index.html
+
+
+ /reference/minify_json.html
+
+
+ /reference/pretty_json.html
+
+
+ /reference/to_json.html
+
+
+ /reference/to_ndjson.html
+
+
+ /reference/validate_json.html
+
+
`).
+ getTopLevel: function($scope) {
+ for (var i = 1; i <= 6; i++) {
+ var $headings = this.findOrFilter($scope, 'h' + i);
+ if ($headings.length > 1) {
+ return i;
+ }
+ }
+
+ return 1;
+ },
+
+ // returns the elements for the top level, and the next below it
+ getHeadings: function($scope, topLevel) {
+ var topSelector = 'h' + topLevel;
+
+ var secondaryLevel = topLevel + 1;
+ var secondarySelector = 'h' + secondaryLevel;
+
+ return this.findOrFilter($scope, topSelector + ',' + secondarySelector);
+ },
+
+ getNavLevel: function(el) {
+ return parseInt(el.tagName.charAt(1), 10);
+ },
+
+ populateNav: function($topContext, topLevel, $headings) {
+ var $context = $topContext;
+ var $prevNav;
+
+ var helpers = this;
+ $headings.each(function(i, el) {
+ var $newNav = helpers.generateNavItem(el);
+ var navLevel = helpers.getNavLevel(el);
+
+ // determine the proper $context
+ if (navLevel === topLevel) {
+ // use top level
+ $context = $topContext;
+ } else if ($prevNav && $context === $topContext) {
+ // create a new level of the tree and switch to it
+ $context = helpers.createChildNavList($prevNav);
+ } // else use the current $context
+
+ $context.append($newNav);
+
+ $prevNav = $newNav;
+ });
+ },
+
+ parseOps: function(arg) {
+ var opts;
+ if (arg.jquery) {
+ opts = {
+ $nav: arg
+ };
+ } else {
+ opts = arg;
+ }
+ opts.$scope = opts.$scope || $(document.body);
+ return opts;
+ }
+ },
+
+ // accepts a jQuery object, or an options object
+ init: function(opts) {
+ opts = this.helpers.parseOps(opts);
+
+ // ensure that the data attribute is in place for styling
+ opts.$nav.attr('data-toggle', 'toc');
+
+ var $topContext = this.helpers.createChildNavList(opts.$nav);
+ var topLevel = this.helpers.getTopLevel(opts.$scope);
+ var $headings = this.helpers.getHeadings(opts.$scope, topLevel);
+ this.helpers.populateNav($topContext, topLevel, $headings);
+ }
+ };
+
+ $(function() {
+ $('nav[data-toggle="toc"]').each(function(i, el) {
+ var $nav = $(el);
+ Toc.init($nav);
+ });
+ });
+})();
diff --git a/docs/index.html b/docs/index.html
index 87158d3..92b61bb 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -5,21 +5,24 @@
-Converts 'R' Objects to Javascript Object Notation (JSON) • jsonify
-
-
-
-
-
-
+Convert Between R Objects and Javascript Object Notation (JSON) • jsonify
+
+
+
+
+
+
+
-
-
+
+
+
+
@@ -62,334 +66,281 @@
+
-
-
+
-
-
-
-
-
-jsonify converts R objects to JSON.
-
-
-There are already JSON converters, why did you build this one?
+
+
+
+Converts between R objects and JSON.
+
+js <- '[{"x":1,"y":"a"},{"x":2,"y":"b"}]'
+( df <- from_json( js ) )
+# x y
+# 1 1 a
+# 2 2 b
+( to_json( df ) )
+# [{"x":1,"y":"a"},{"x":2,"y":"b"}]
+
+There are already JSON converters, why did you build this one?
+
Because I wanted it available at the source ( C++ ) level for integrating into other packages.
-
-
-Is it fast?
-yeah it’s pretty good.
-
-library(microbenchmark)
-library(jsonlite)
-
-n <- 1e6
-df <- data.frame(
- id = 1:n
- , value = sample(letters, size = n, replace = T)
- , val2 = rnorm(n = n)
- , log = sample(c(T,F), size = n, replace = T)
- , stringsAsFactors = FALSE
-)
-
-microbenchmark(
- jsonlite = {
- js <- jsonlite::toJSON( df )
- },
- jsonify = {
- js <- jsonify::to_json( df )
- },
- times = 3
-)
-
-# Unit: seconds
-# expr min lq mean median uq max neval
-# jsonlite 2.017081 2.063732 2.540350 2.110383 2.801984 3.493585 3
-# jsonify 1.186239 1.202719 1.514067 1.219198 1.677981 2.136763 3
-
-n <- 1e4
-x <- list(
- x = rnorm(n = n)
- , y = list(x = rnorm(n = n))
- , z = list( list( x = rnorm(n = n)))
- , xx = rnorm(n = n)
- , yy = data.frame(
- id = 1:n
- , value = sample(letters, size = n, replace = T)
- , val2 = rnorm(n = n)
- , log = sample(c(T,F), size = n, replace = T)
- )
-)
-
-microbenchmark(
- jsonlite = {
- js <- jsonlite::toJSON( x )
- },
- jsonify = {
- js <- jsonify::to_json( x )
- },
- times = 5
-)
-
-# Unit: milliseconds
-# expr min lq mean median uq max neval
-# jsonlite 18.52028 18.82241 19.32112 18.99683 19.18103 21.08508 5
-# jsonify 17.72060 18.19092 19.58308 19.52457 21.14687 21.33241 5
-
+
+What do you mean by “available at the source” ?
+
+I want to be able to call the C++ code from another package, without going to & from R. Therefore, the C++ code is implemented in headers, so you can “link to” it in your own package.
+For example, the LinkingTo section in DESCRIPTION will look something like
+
+And in a c++ source file you can #include the header and use the available functions
+#include "jsonify/jsonify.hpp"
+
+Rcpp::StringVector my_json( Rcpp::DataFrame df ) {
+ return jsonify::api::to_json( df );
+}
+You can see an example of this in my geojsonsf package
+
+- Description
+- #include
+
-
-
-I thought you had an example of it being MUCH quicker than jsonlite ?
-Yeah, but I realised it was comparing two different methods. When jsonify was parsing nested lists, it was parsing data.frames column-wise, whereas jsonlite was row-wise. Which is a slower operation
+
+Can I call it from R if I want to?
+
+Yes. Just like the examples in this readme use to_json()
+
+df <- data.frame(
+ id = 1:3
+ , val = letters[1:3]
+ )
+jsonify::to_json( df )
+# [{"id":1,"val":"a"},{"id":2,"val":"b"},{"id":3,"val":"c"}]
-
-
-Oh right. So it wasn’t a fair test then.
-Correct.
-Here’s a more suitable comparison
-n <- 1e4
-x <- list(
- x = rnorm(n = n)
- , y = list(x = rnorm(n = n))
- , z = list( list( x = rnorm(n = n)))
- , xx = rnorm(n = n)
- , yy = data.frame(
- id = 1:n
- , value = sample(letters, size = n, replace = T)
- , val2 = rnorm(n = n)
- , log = sample(c(T,F), size = n, replace = T)
- )
-)
-
-microbenchmark(
- jsonlite_row = {
- js <- jsonlite::toJSON( x )
- },
- jsonlite_col = {
- js <- jsonlite::toJSON( x, dataframe = "columns" )
- },
- jsonify_row = {
- js <- jsonify::to_json( x )
- },
- jsonify_col = {
- js <- jsonify::to_json( x, by = "column" )
- },
- times = 5
-)
-
-# Unit: milliseconds
-# expr min lq mean median uq max neval
-# jsonlite_row 20.533642 20.717894 27.294220 21.122860 21.426250 52.670456 5
-# jsonlite_col 13.691643 13.812459 15.683795 14.293177 15.655705 20.965993 5
-# jsonify_row 17.506507 17.951948 20.929641 19.827791 21.161389 28.200572 5
-# jsonify_col 7.262305 7.382238 7.409085 7.434759 7.435476 7.530645 5
+
+Is it fast?
+
+yeah it’s pretty good.
+
+
+library(microbenchmark)
+library(jsonlite)
+
+n <- 1e6
+df <- data.frame(
+ id = 1:n
+ , value = sample(letters, size = n, replace = T)
+ , val2 = rnorm(n = n)
+ , log = sample(c(T,F), size = n, replace = T)
+ , stringsAsFactors = FALSE
+)
+
+microbenchmark(
+ jsonlite = {
+ jlt <- jsonlite::toJSON( df )
+ },
+ jsonify = {
+ jfy <- jsonify::to_json( df )
+ },
+ times = 3
+)
+
+# Unit: seconds
+# expr min lq mean median uq max neval
+# jsonlite 2.017081 2.063732 2.540350 2.110383 2.801984 3.493585 3
+# jsonify 1.186239 1.202719 1.514067 1.219198 1.677981 2.136763 3
+
+
+microbenchmark(
+ jsonlite = {
+ df_jlt <- jsonlite::fromJSON( jlt )
+ },
+ jsonify = {
+ df_jfy <- jsonify::from_json( jfy )
+ },
+ times = 3
+)
+
+# Unit: seconds
+# expr min lq mean median uq max neval
+# jsonlite 5.034888 5.149688 5.229363 5.264489 5.326601 5.388713 3
+# jsonify 4.551434 4.629683 4.678198 4.707932 4.741579 4.775227 3
+
+n <- 1e4
+x <- list(
+ x = rnorm(n = n)
+ , y = list(x = rnorm(n = n))
+ , z = list( list( x = rnorm(n = n)))
+ , xx = rnorm(n = n)
+ , yy = data.frame(
+ id = 1:n
+ , value = sample(letters, size = n, replace = T)
+ , val2 = rnorm(n = n)
+ , log = sample(c(T,F), size = n, replace = T)
+ )
+)
+
+microbenchmark(
+ jsonlite = {
+ jlt <- jsonlite::toJSON( x )
+ },
+ jsonify = {
+ jfy <- jsonify::to_json( x )
+ },
+ times = 5
+)
+
+# Unit: milliseconds
+# expr min lq mean median uq max neval
+# jsonlite 18.52028 18.82241 19.32112 18.99683 19.18103 21.08508 5
+# jsonify 17.72060 18.19092 19.58308 19.52457 21.14687 21.33241 5
+
+
+microbenchmark(
+ jsonlite = {
+ df_jlt <- jsonlite::fromJSON( jlt )
+ },
+ jsonify = {
+ df_jfy <- jsonify::from_json( jfy )
+ },
+ times = 3
+)
+
+# Unit: milliseconds
+# expr min lq mean median uq max neval
+# jsonlite 62.53554 62.96435 63.12574 63.39316 63.42084 63.44853 3
+# jsonify 42.47449 42.53826 43.38475 42.60204 43.83988 45.07773 3
-
-
-There’s no Date type in JSON, how have you handled this?
+
+There’s no Date type in JSON, how have you handled this?
+
At its core Dates in R are numeric, so they are treated as numbers when converted to JSON. However, the user can coerce to character through the numeric_dates argument.
-df <- data.frame(dte = as.Date("2018-01-01"))
-jsonify::to_json( df )
-# [{"dte":17532.0}]
-
-df <- data.frame(dte = as.Date("2018-01-01"))
-jsonify::to_json( df, numeric_dates = FALSE )
-# [{"dte":"2018-01-01"}]
+
+df <- data.frame(dte = as.Date("2018-01-01"))
+jsonify::to_json( df )
+# [{"dte":17532.0}]
+
+df <- data.frame(dte = as.Date("2018-01-01"))
+jsonify::to_json( df, numeric_dates = FALSE )
+# [{"dte":"2018-01-01"}]
-
-
-And POSIXct and POSIXlt?
+
+And POSIXct and POSIXlt?
+
The same
-
-jsonify::to_json( as.POSIXct("2018-01-01 10:00:00") )
-# [1514761200.0]
-jsonify::to_json( as.POSIXct("2018-01-01 10:00:00"), numeric_dates = FALSE)
-# ["2017-12-31T23:00:00"]
+
+
+jsonify::to_json( as.POSIXct("2018-01-01 10:00:00") )
+# [1514761200.0]
+jsonify::to_json( as.POSIXct("2018-01-01 10:00:00"), numeric_dates = FALSE)
+# ["2017-12-31T23:00:00"]
However, here the POSIXct values are returned in UTC timezone. This is by design.
POSIXlt will return each component of the date-time
-x <- as.POSIXlt("2018-01-01 01:00:00", tz = "GMT")
-jsonify::to_json( x )
-# {"sec":[0.0],"min":[0],"hour":[1],"mday":[1],"mon":[0],"year":[118],"wday":[1],"yday":[0],"isdst":[0]}
-
-jsonify::to_json( x, numeric_dates = FALSE)
-# {"sec":[0.0],"min":[0],"hour":[1],"mday":[1],"mon":[0],"year":[118],"wday":[1],"yday":[0],"isdst":[0]}
-
-
-
-What about lists?
-The purpose of this library is speed. A lot of overhead is incurred iterating over a list to find and convert objects from one type to another.
-For v0.2.0 I’ve managed to get the date handling at the c++ level, so there’s no penalty for recursing through the list to coerce to character.
-Therefore, lists will work too
-l <- list(
- dte = as.Date("2018-01-01")
- , psx = seq(as.POSIXct("2018-01-01 13:00:00"), as.POSIXct("2018-01-05 13:00:00"), length.out = 5)
- , df = data.frame(psx = seq(as.POSIXct("2018-01-01 13:00:00"), as.POSIXct("2018-01-05 13:00:00"), length.out = 5))
-)
-jsonify::to_json( l )
-# {"dte":[17532.0],"psx":[1514772000,1514858400,1514944800,1515031200,1515117600],"df":[{"psx":1514772000},{"psx":1514858400},{"psx":1514944800},{"psx":1515031200},{"psx":1515117600}]}
-js <- jsonify::to_json( l, numeric_dates = FALSE )
-jsonify::pretty_json( js )
-# {
-# "dte": [
-# "2018-01-01"
-# ],
-# "psx": [
-# "2018-01-01T02:00:00",
-# "2018-01-02T02:00:00",
-# "2018-01-03T02:00:00",
-# "2018-01-04T02:00:00",
-# "2018-01-05T02:00:00"
-# ],
-# "df": [
-# {
-# "psx": "2018-01-01T02:00:00"
-# },
-# {
-# "psx": "2018-01-02T02:00:00"
-# },
-# {
-# "psx": "2018-01-03T02:00:00"
-# },
-# {
-# "psx": "2018-01-04T02:00:00"
-# },
-# {
-# "psx": "2018-01-05T02:00:00"
-# }
-# ]
-# }
-And it’s still fast because of the design choice to coerce dates to UTC. All the date handling is done at the C++ leve, not R. So it’s faster.
-dtes <- seq(as.Date("2018-01-01"), as.Date("2019-01-01"), length.out = 365)
-psx <- seq(as.POSIXct("2018-01-01"), as.POSIXct("2019-01-01"), length.out = 365)
-n <- 1e5
-
-lst <- list(
- x = sample(dtes, size = n, replace = T)
- , y = list(
- ya = sample(dtes, size = n, replace = TRUE)
- , yb = rnorm(n = n)
- , yx = list( sample(dtes, size = n, replace = T ) )
- )
- , p = psx
-)
-
-library( microbenchmark )
-
-microbenchmark(
- jsonify1 = {
- jsonify::to_json( lst, numeric_dates = TRUE )
- },
- jsonify2 = {
- jsonify::to_json( lst, numeric_dates = FALSE )
- },
- jsonlite = {
- jsonlite::toJSON( lst )
- },
- times = 3
-)
-# Unit: milliseconds
-# expr min lq mean median uq max neval
-# jsonify1 60.26762 62.9191 70.36983 65.57057 75.42093 85.2713 3
-# jsonify2 314.75788 315.3369 331.71612 315.91598 340.19524 364.4745 3
-# jsonlite 674.26576 709.8997 737.83201 745.53362 769.61514 793.6967 3
+
+x <- as.POSIXlt("2018-01-01 01:00:00", tz = "GMT")
+jsonify::to_json( x )
+# {"sec":[0.0],"min":[0],"hour":[1],"mday":[1],"mon":[0],"year":[118],"wday":[1],"yday":[0],"isdst":[0]}
+
+jsonify::to_json( x, numeric_dates = FALSE)
+# {"sec":[0.0],"min":[0],"hour":[1],"mday":[1],"mon":[0],"year":[118],"wday":[1],"yday":[0],"isdst":[0]}
-
-
-That output looks nice, is that pretty_json() function new?
-Yep, it’s a new feature in v0.2.0
+
+I see factors are converted to strings
+
+Yep. Even though I constructed a data.frame() without setting stringsAsFactros = FALSE, jsonify automatically treats factors as strings.
-
-
-What do you mean by “available at the source” ?
-I want to be able to call the C++ code from another package, without going to & from R. Therefore, the C++ code is implemented in headers, so you can “link to” it in your own package.
-For example, the LinkingTo section in DESCRIPTION will look something like
-LinkingTo:
- Rcpp,
- jsonify
-And in a c++ source file you can #include the header and use the available functions
-
-
-
-
-Can I call it from R if I want to?
-Yes. Just like the examples in this readme use to_json()
-
-
-
-
-I see factors are converted to strings
-Yep. Even though I constructed a data.frame() without setting stringsAsFactros = FALSE, jsonify automatically treats factors as strings.
-
-
-
-Has this changed from v0.1?
+
+Has this changed from v0.1?
+
Yes. And it’s to keep the data more inline with modern concepts and design patterns.
If you want factors, use factors_as_string = FALSE in the to_json() call
-jsonify::to_json( df, factors_as_string = FALSE )
-# [{"id":1,"val":1},{"id":2,"val":2},{"id":3,"val":3}]
+
+jsonify::to_json( df, factors_as_string = FALSE )
+# [{"dte":17532.0}]
-
-
-How do I install it?
+
+How do I install it?
+
Get the latest release version from CRAN
-
-Or the development version from GitHub with:
-
+
+install.packages("jsonify")
+Or the development version from GitHub with:
+
+# install.packages("devtools")
+devtools::install_github("SymbolixAU/jsonify")
+
-
+
+
+
diff --git a/docs/news/index.html b/docs/news/index.html
index 2738134..55662fb 100644
--- a/docs/news/index.html
+++ b/docs/news/index.html
@@ -1,55 +1,12 @@
-
-
-
-
-
-
-
-Changelog • jsonify
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-Changelog • jsonify
-
+
+
-
-
-
-
-
-
-
+
-
+
-
+
+
+
-
-
+
diff --git a/docs/pkgdown.css b/docs/pkgdown.css
index c03fb08..80ea5b8 100644
--- a/docs/pkgdown.css
+++ b/docs/pkgdown.css
@@ -17,12 +17,14 @@ html, body {
height: 100%;
}
+body {
+ position: relative;
+}
+
body > .container {
display: flex;
height: 100%;
flex-direction: column;
-
- padding-top: 60px;
}
body > .container .row {
@@ -54,8 +56,10 @@ img.icon {
float: right;
}
-img {
+/* Ensure in-page images don't run outside their container */
+.contents img {
max-width: 100%;
+ height: auto;
}
/* Fix bug in bootstrap (only seen in firefox) */
@@ -69,14 +73,17 @@ summary {
margin-top: calc(-60px + 1em);
}
+dd {
+ margin-left: 3em;
+}
+
/* Section anchors ---------------------------------*/
a.anchor {
- margin-left: -30px;
- display:inline-block;
- width: 30px;
- height: 30px;
- visibility: hidden;
+ display: none;
+ margin-left: 5px;
+ width: 20px;
+ height: 20px;
background-image: url(./link.svg);
background-repeat: no-repeat;
@@ -84,17 +91,15 @@ a.anchor {
background-position: center center;
}
-.hasAnchor:hover a.anchor {
- visibility: visible;
-}
-
-@media (max-width: 767px) {
- .hasAnchor:hover a.anchor {
- visibility: hidden;
- }
+h1:hover .anchor,
+h2:hover .anchor,
+h3:hover .anchor,
+h4:hover .anchor,
+h5:hover .anchor,
+h6:hover .anchor {
+ display: inline-block;
}
-
/* Fixes for fixed navbar --------------------------*/
.contents h1, .contents h2, .contents h3, .contents h4 {
@@ -102,37 +107,135 @@ a.anchor {
margin-top: -40px;
}
-/* Static header placement on mobile devices */
-@media (max-width: 767px) {
- .navbar-fixed-top {
- position: absolute;
- }
- .navbar {
- padding: 0;
- }
+/* Navbar submenu --------------------------*/
+
+.dropdown-submenu {
+ position: relative;
+}
+
+.dropdown-submenu>.dropdown-menu {
+ top: 0;
+ left: 100%;
+ margin-top: -6px;
+ margin-left: -1px;
+ border-radius: 0 6px 6px 6px;
+}
+
+.dropdown-submenu:hover>.dropdown-menu {
+ display: block;
+}
+
+.dropdown-submenu>a:after {
+ display: block;
+ content: " ";
+ float: right;
+ width: 0;
+ height: 0;
+ border-color: transparent;
+ border-style: solid;
+ border-width: 5px 0 5px 5px;
+ border-left-color: #cccccc;
+ margin-top: 5px;
+ margin-right: -10px;
+}
+
+.dropdown-submenu:hover>a:after {
+ border-left-color: #ffffff;
}
+.dropdown-submenu.pull-left {
+ float: none;
+}
+
+.dropdown-submenu.pull-left>.dropdown-menu {
+ left: -100%;
+ margin-left: 10px;
+ border-radius: 6px 0 6px 6px;
+}
/* Sidebar --------------------------*/
-#sidebar {
+#pkgdown-sidebar {
margin-top: 30px;
+ position: -webkit-sticky;
+ position: sticky;
+ top: 70px;
}
-#sidebar h2 {
+
+#pkgdown-sidebar h2 {
font-size: 1.5em;
margin-top: 1em;
}
-#sidebar h2:first-child {
+#pkgdown-sidebar h2:first-child {
margin-top: 0;
}
-#sidebar .list-unstyled li {
+#pkgdown-sidebar .list-unstyled li {
margin-bottom: 0.5em;
}
+/* bootstrap-toc tweaks ------------------------------------------------------*/
+
+/* All levels of nav */
+
+nav[data-toggle='toc'] .nav > li > a {
+ padding: 4px 20px 4px 6px;
+ font-size: 1.5rem;
+ font-weight: 400;
+ color: inherit;
+}
+
+nav[data-toggle='toc'] .nav > li > a:hover,
+nav[data-toggle='toc'] .nav > li > a:focus {
+ padding-left: 5px;
+ color: inherit;
+ border-left: 1px solid #878787;
+}
+
+nav[data-toggle='toc'] .nav > .active > a,
+nav[data-toggle='toc'] .nav > .active:hover > a,
+nav[data-toggle='toc'] .nav > .active:focus > a {
+ padding-left: 5px;
+ font-size: 1.5rem;
+ font-weight: 400;
+ color: inherit;
+ border-left: 2px solid #878787;
+}
+
+/* Nav: second level (shown on .active) */
+
+nav[data-toggle='toc'] .nav .nav {
+ display: none; /* Hide by default, but at >768px, show it */
+ padding-bottom: 10px;
+}
+
+nav[data-toggle='toc'] .nav .nav > li > a {
+ padding-left: 16px;
+ font-size: 1.35rem;
+}
+
+nav[data-toggle='toc'] .nav .nav > li > a:hover,
+nav[data-toggle='toc'] .nav .nav > li > a:focus {
+ padding-left: 15px;
+}
+
+nav[data-toggle='toc'] .nav .nav > .active > a,
+nav[data-toggle='toc'] .nav .nav > .active:hover > a,
+nav[data-toggle='toc'] .nav .nav > .active:focus > a {
+ padding-left: 15px;
+ font-weight: 500;
+ font-size: 1.35rem;
+}
+
+/* orcid ------------------------------------------------------------------- */
+
.orcid {
- height: 16px;
+ font-size: 16px;
+ color: #A6CE39;
+ /* margins are required by official ORCID trademark and display guidelines */
+ margin-left:4px;
+ margin-right:4px;
vertical-align: middle;
}
@@ -140,14 +243,14 @@ a.anchor {
.ref-index th {font-weight: normal;}
-.ref-index td {vertical-align: top;}
+.ref-index td {vertical-align: top; min-width: 100px}
.ref-index .icon {width: 40px;}
.ref-index .alias {width: 40%;}
.ref-index-icons .alias {width: calc(40% - 40px);}
.ref-index .title {width: 60%;}
.ref-arguments th {text-align: right; padding-right: 10px;}
-.ref-arguments th, .ref-arguments td {vertical-align: top;}
+.ref-arguments th, .ref-arguments td {vertical-align: top; min-width: 100px}
.ref-arguments .name {width: 20%;}
.ref-arguments .desc {width: 80%;}
@@ -160,31 +263,26 @@ table {
/* Syntax highlighting ---------------------------------------------------- */
-pre {
- word-wrap: normal;
- word-break: normal;
- border: 1px solid #eee;
-}
-
-pre, code {
+pre, code, pre code {
background-color: #f8f8f8;
color: #333;
}
+pre, pre code {
+ white-space: pre-wrap;
+ word-break: break-all;
+ overflow-wrap: break-word;
+}
-pre code {
- overflow: auto;
- word-wrap: normal;
- white-space: pre;
+pre {
+ border: 1px solid #eee;
}
-pre .img {
+pre .img, pre .r-plt {
margin: 5px 0;
}
-pre .img img {
+pre .img img, pre .r-plt img {
background-color: #fff;
- display: block;
- height: auto;
}
code a, pre a {
@@ -201,9 +299,8 @@ a.sourceLine:hover {
.kw {color: #264D66;} /* keyword */
.co {color: #888888;} /* comment */
-.message { color: black; font-weight: bolder;}
-.error { color: orange; font-weight: bolder;}
-.warning { color: #6A0366; font-weight: bolder;}
+.error {font-weight: bolder;}
+.warning {font-weight: bolder;}
/* Clipboard --------------------------*/
@@ -222,6 +319,19 @@ a.sourceLine:hover {
visibility: visible;
}
+/* headroom.js ------------------------ */
+
+.headroom {
+ will-change: transform;
+ transition: transform 200ms linear;
+}
+.headroom--pinned {
+ transform: translateY(0%);
+}
+.headroom--unpinned {
+ transform: translateY(-100%);
+}
+
/* mark.js ----------------------------*/
mark {
@@ -234,3 +344,41 @@ mark {
.html-widget {
margin-bottom: 10px;
}
+
+/* fontawesome ------------------------ */
+
+.fab {
+ font-family: "Font Awesome 5 Brands" !important;
+}
+
+/* don't display links in code chunks when printing */
+/* source: https://stackoverflow.com/a/10781533 */
+@media print {
+ code a:link:after, code a:visited:after {
+ content: "";
+ }
+}
+
+/* Section anchors ---------------------------------
+ Added in pandoc 2.11: https://github.com/jgm/pandoc-templates/commit/9904bf71
+*/
+
+div.csl-bib-body { }
+div.csl-entry {
+ clear: both;
+}
+.hanging-indent div.csl-entry {
+ margin-left:2em;
+ text-indent:-2em;
+}
+div.csl-left-margin {
+ min-width:2em;
+ float:left;
+}
+div.csl-right-inline {
+ margin-left:2em;
+ padding-left:1em;
+}
+div.csl-indent {
+ margin-left: 2em;
+}
diff --git a/docs/pkgdown.js b/docs/pkgdown.js
index eb7e83d..6f0eee4 100644
--- a/docs/pkgdown.js
+++ b/docs/pkgdown.js
@@ -2,18 +2,11 @@
(function($) {
$(function() {
- $("#sidebar")
- .stick_in_parent({offset_top: 40})
- .on('sticky_kit:bottom', function(e) {
- $(this).parent().css('position', 'static');
- })
- .on('sticky_kit:unbottom', function(e) {
- $(this).parent().css('position', 'relative');
- });
+ $('.navbar-fixed-top').headroom();
- $('body').scrollspy({
- target: '#sidebar',
- offset: 60
+ $('body').css('padding-top', $('.navbar').height() + 10);
+ $(window).resize(function(){
+ $('body').css('padding-top', $('.navbar').height() + 10);
});
$('[data-toggle="tooltip"]').tooltip();
@@ -87,7 +80,7 @@
$(document).ready(function() {
var copyButton = "";
- $(".examples, div.sourceCode").addClass("hasCopyButton");
+ $("div.sourceCode").addClass("hasCopyButton");
// Insert copy buttons:
$(copyButton).prependTo(".hasCopyButton");
@@ -98,7 +91,7 @@
// Initialize clipboard:
var clipboardBtnCopies = new ClipboardJS('[data-clipboard-copy]', {
text: function(trigger) {
- return trigger.parentNode.textContent;
+ return trigger.parentNode.textContent.replace(/\n#>[^\n]*/g, "");
}
});
diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml
index 6a18080..619f050 100644
--- a/docs/pkgdown.yml
+++ b/docs/pkgdown.yml
@@ -1,6 +1,7 @@
-pandoc: 2.3.1
-pkgdown: 1.3.0
+pandoc: 3.1.1
+pkgdown: 2.0.7
pkgdown_sha: ~
articles:
jsonify: jsonify.html
+last_built: 2024-01-17T21:33Z
diff --git a/docs/reference/Rplot001.png b/docs/reference/Rplot001.png
new file mode 100644
index 0000000000000000000000000000000000000000..17a358060aed2a86950757bbd25c6f92c08c458f
GIT binary patch
literal 1011
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zVg?3oArNM~bhqvg0|WD9PZ!6KiaBo&GBN^{G%5UFpXcEKVvd5*5Eu=C0SJK)8A6*F
U7`aXvEC5;V>FVdQ&MBb@00SN#Z2$lO
literal 0
HcmV?d00001
diff --git a/docs/reference/as.json.html b/docs/reference/as.json.html
new file mode 100644
index 0000000..596a781
--- /dev/null
+++ b/docs/reference/as.json.html
@@ -0,0 +1,101 @@
+
+Coerce string to JSON — as.json • jsonify
+
+
+
+
+
+
+
+
+
+
+
+
+ Coerce string to JSON
+
+
+
+ as.json(x)
+
+
+
+ Arguments
+ - x
+string to coerce to JSON
+
+
+ Examples
+
+js <- '{"x":1,"y":2}'
+as.json(js)
+#> {"x":1,"y":2}
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/docs/reference/from_json.html b/docs/reference/from_json.html
new file mode 100644
index 0000000..5d183b6
--- /dev/null
+++ b/docs/reference/from_json.html
@@ -0,0 +1,239 @@
+
+From JSON — from_json • jsonify
+
+
+
+
+
+
+
+
+
+
+
+
+ Converts JSON to an R object.
+
+
+
+ from_json(json, simplify = TRUE, fill_na = FALSE, buffer_size = 1024)
+
+
+
+ Arguments
+ - json
+JSON to convert to R object. Can be a string, url or link to a file.
- simplify
+logical, if TRUE, coerces JSON to the simplest R object possible. See Details
- fill_na
+logical, if TRUE and simplify is TRUE,
+data.frames will be na-filled if there are missing JSON keys.
+Ignored if simplify is FALSE. See details and examples.
- buffer_size
+size of buffer used when reading a file from disk. Defaults to 1024
+
+ Details
+ When simplify = TRUE
single arrays are coerced to vectors
array of arrays (all the same length) are coerced to matrices
objects with the same keys are coerced to data.frames
When simplify = TRUE and fill_na = TRUE
objects are coerced to data.frames, and any missing values are filled with NAs
+
+
+ Examples
+
+from_json('{"a":[1, 2, 3]}')
+#> $a
+#> [1] 1 2 3
+#>
+from_json('{"a":8, "b":99.5, "c":true, "d":"cats", "e":[1, "cats", 3]}')
+#> $a
+#> [1] 8
+#>
+#> $b
+#> [1] 99.5
+#>
+#> $c
+#> [1] TRUE
+#>
+#> $d
+#> [1] "cats"
+#>
+#> $e
+#> [1] "1" "cats" "3"
+#>
+from_json('{"a":8, "b":{"c":123, "d":{"e":456}}}')
+#> $a
+#> [1] 8
+#>
+#> $b
+#> $b$c
+#> [1] 123
+#>
+#> $b$d
+#> $b$d$e
+#> [1] 456
+#>
+#>
+#>
+
+lst <- list("a" = 5L, "b" = 1.43, "c" = "cats", "d" = FALSE)
+js <- jsonify::to_json(lst, unbox = TRUE)
+from_json( js )
+#> $a
+#> [1] 5
+#>
+#> $b
+#> [1] 1.43
+#>
+#> $c
+#> [1] "cats"
+#>
+#> $d
+#> [1] FALSE
+#>
+
+## Return a data frame
+from_json('[{"id":1,"val":"a"},{"id":2,"val":"b"}]')
+#> id val
+#> 1 1 a
+#> 2 2 b
+
+## Return a data frame with a list column
+from_json('[{"id":1,"val":"a"},{"id":2,"val":["b","c"]}]')
+#> id val
+#> 1 1 a
+#> 2 2 b, c
+
+## Without simplifying to a data.frame
+from_json('[{"id":1,"val":"a"},{"id":2,"val":["b","c"]}]', simplify = FALSE )
+#> [[1]]
+#> [[1]]$id
+#> [1] 1
+#>
+#> [[1]]$val
+#> [1] "a"
+#>
+#>
+#> [[2]]
+#> [[2]]$id
+#> [1] 2
+#>
+#> [[2]]$val
+#> [[2]]$val[[1]]
+#> [1] "b"
+#>
+#> [[2]]$val[[2]]
+#> [1] "c"
+#>
+#>
+#>
+
+## Missing JSON keys
+from_json('[{"x":1},{"x":2,"y":"hello"}]')
+#> [[1]]
+#> [[1]]$x
+#> [1] 1
+#>
+#>
+#> [[2]]
+#> [[2]]$x
+#> [1] 2
+#>
+#> [[2]]$y
+#> [1] "hello"
+#>
+#>
+
+## Missing JSON keys - filling with NAs
+from_json('[{"x":1},{"x":2,"y":"hello"}]', fill_na = TRUE )
+#> x y
+#> 1 1 <NA>
+#> 2 2 hello
+
+## Duplicate object keys
+from_json('[{"x":1,"x":"a"},{"x":2,"x":"b"}]')
+#> x
+#> 1 1
+#> 2 2
+
+from_json('[{"id":1,"val":"a","val":1},{"id":2,"val":"b"}]', fill_na = TRUE )
+#> id val
+#> 1 1 a
+#> 2 2 b
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/docs/reference/from_ndjson.html b/docs/reference/from_ndjson.html
new file mode 100644
index 0000000..e8151c5
--- /dev/null
+++ b/docs/reference/from_ndjson.html
@@ -0,0 +1,117 @@
+
+from ndjson — from_ndjson • jsonify
+
+
+
+
+
+
+
+
+
+
+
+
+ Converts ndjson into R objects
+
+
+
+ from_ndjson(ndjson, simplify = TRUE, fill_na = FALSE)
+
+
+
+ Arguments
+ - ndjson
+new-line delimited JSON to convert to R object. Can be a string, url or link to a file.
- simplify
+logical, if TRUE, coerces JSON to the simplest R object possible. See Details
- fill_na
+logical, if TRUE and simplify is TRUE,
+data.frames will be na-filled if there are missing JSON keys.
+Ignored if simplify is FALSE. See details and examples.
+
+
+ Examples
+
+js <- to_ndjson( data.frame( x = 1:5, y = 6:10 ) )
+from_ndjson( js )
+#> x y
+#> 1 1 6
+#> 2 2 7
+#> 3 3 8
+#> 4 4 9
+#> 5 5 10
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/docs/reference/index.html b/docs/reference/index.html
index 24c1c74..9406733 100644
--- a/docs/reference/index.html
+++ b/docs/reference/index.html
@@ -1,55 +1,12 @@
-
-
-
-
-
-
-
-Function reference • jsonify
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-Function reference • jsonify
-
+
+
-
-
-
-
-
-
-
+
-
+
+
+
-
-
+
diff --git a/docs/reference/jsondf-package.html b/docs/reference/jsondf-package.html
deleted file mode 100644
index c2c01f0..0000000
--- a/docs/reference/jsondf-package.html
+++ /dev/null
@@ -1,174 +0,0 @@
-
-
-
-
-
-
-
-
-A short title line describing what the package does — jsondf-package • jsonify
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
- A short title line describing what the package does
-
- jsondf-package.Rd
-
-
-
-
- A more detailed description of what the package does. A length
- of about one to five lines is recommended.
-
-
-
-
- Details
-
- This section should provide a more detailed overview of how to use the
- package, including the most important functions.
-
- References
-
- This optional section can contain literature or other references for
- background information.
-
- See also
-
- Optional links to other man pages
-
-
- Examples
- # NOT RUN {
- ## Optional simple examples of the most important functions
- ## These can be in \dontrun{} and \donttest{} blocks.
-
-# }
-
-
-
-
-
-
-
-
-
-
-
-
-
diff --git a/docs/reference/minify_json.html b/docs/reference/minify_json.html
index 43c8418..9056933 100644
--- a/docs/reference/minify_json.html
+++ b/docs/reference/minify_json.html
@@ -1,58 +1,12 @@
-
-
-
-
-
-
-
-Minify Json — minify_json • jsonify
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-Minify Json — minify_json • jsonify
-
-
-
+
+
-
-
-
-
-
+
-
Removes indentiation from a JSON string
-
- minify_json(json, ...)
-
- Arguments
-
-
- json
- string of JSON
-
- ...
- other argments passed to to_json
-
-
+
+ minify_json(json, ...)
+
- Examples
-
-df <- data.frame(id = 1:10, val = rnorm(10))
-js <- to_json( df )
-jsp <- pretty_json(js)
-minify_json( jsp )#> [{"id":1,"val":-1.4000435167217549},{"id":2,"val":0.2553170548452597},{"id":3,"val":-2.437263611219531},{"id":4,"val":-0.005571286746160735},{"id":5,"val":0.6215527214152141},{"id":6,"val":1.1484116060260608},{"id":7,"val":-1.821817660976626},{"id":8,"val":-0.24732530207352436},{"id":9,"val":-0.24419960677838332},{"id":10,"val":-0.2827054488144648}]
-
-
-
+
-
+
+
+
-
-
+
diff --git a/docs/reference/pretty_json.html b/docs/reference/pretty_json.html
index 2b50153..54a767d 100644
--- a/docs/reference/pretty_json.html
+++ b/docs/reference/pretty_json.html
@@ -1,58 +1,12 @@
-
-
-
-
-
-
-
-Pretty Json — pretty_json • jsonify
-
-
-
-
-
-
-
-
-
-
-
-
-
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-
-
-Pretty Json — pretty_json • jsonify
-
-
-
+
+
-
-
-
-
-
+
-
Adds indentiation to a JSON string
-
- pretty_json(json, ...)
-
- Arguments
-
-
- json
- string of JSON
-
- ...
- other argments passed to to_json
-
-
-
- Examples
- #> [
-#> {
-#> "id": 1,
-#> "val": -0.5536993836887205
-#> },
-#> {
-#> "id": 2,
-#> "val": 0.628982042036008
-#> },
-#> {
-#> "id": 3,
-#> "val": 2.065024895359223
-#> },
-#> {
-#> "id": 4,
-#> "val": -1.6309894020822316
-#> },
-#> {
-#> "id": 5,
-#> "val": 0.5124269498518048
-#> },
-#> {
-#> "id": 6,
-#> "val": -1.863011492068328
-#> },
-#> {
-#> "id": 7,
-#> "val": -0.5220125147454544
-#> },
-#> {
-#> "id": 8,
-#> "val": -0.05260190995387954
-#> },
-#> {
-#> "id": 9,
-#> "val": 0.5429963426611403
-#> },
-#> {
-#> "id": 10,
-#> "val": -0.9140748272599284
-#> }
-#> ]
-## can also use directly on an R object
-pretty_json( df )#> [
-#> {
-#> "id": 1,
-#> "val": -0.5536993836887205
-#> },
-#> {
-#> "id": 2,
-#> "val": 0.628982042036008
-#> },
-#> {
-#> "id": 3,
-#> "val": 2.065024895359223
-#> },
-#> {
-#> "id": 4,
-#> "val": -1.6309894020822316
-#> },
-#> {
-#> "id": 5,
-#> "val": 0.5124269498518048
-#> },
-#> {
-#> "id": 6,
-#> "val": -1.863011492068328
-#> },
-#> {
-#> "id": 7,
-#> "val": -0.5220125147454544
-#> },
-#> {
-#> "id": 8,
-#> "val": -0.05260190995387954
-#> },
-#> {
-#> "id": 9,
-#> "val": 0.5429963426611403
-#> },
-#> {
-#> "id": 10,
-#> "val": -0.9140748272599284
-#> }
-#> ]
-
-
-
+
-
+
+
+
-
-
+
diff --git a/docs/reference/to_json.html b/docs/reference/to_json.html
index 76eacee..fea2f01 100644
--- a/docs/reference/to_json.html
+++ b/docs/reference/to_json.html
@@ -1,58 +1,12 @@
-
-
-
-
-
-
-
-To JSON — to_json • jsonify
-
-
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-
-
-To JSON — to_json • jsonify
-
-
-
+
+
-
-
-
-
-
+
-
Converts R objects to JSON
-
- to_json(x, unbox = FALSE, digits = NULL, numeric_dates = TRUE,
- factors_as_string = TRUE, by = "row")
-
- Arguments
-
-
- x
- object to convert to JSON
-
- unbox
- logical indicating if single-value arrays should be 'unboxed',
-that is, not contained inside an array.
-
- digits
- integer specifying the number of decimal places to round numerics.
-Default is NULL - no rounding
-
- numeric_dates
- logical indicating if dates should be treated as numerics.
-Defaults to TRUE for speed. If FALSE, the dates will be coerced to character in UTC time zone
-
- factors_as_string
- logical indicating if factors should be treated as strings. Defaults to TRUE.
-
- by
- either "row" or "column" indicating if data.frames and matrices should be processed
-row-wise or column-wise. Defaults to "row"
-
-
-
- Examples
-
-to_json(1:3)#> [1,2,3]to_json(letters[1:3])#> ["a","b","c"]#> [{"x":1,"y":"a"},{"x":2,"y":"b"},{"x":3,"y":"c"}]#> {"x":[1,2,3],"y":{"z":["a","b","c"]}}#> [17532,17533,17534,17535,17536]#> ["2018-01-01","2018-01-02","2018-01-03","2018-01-04","2018-01-05"]
-psx <- seq(
- as.POSIXct("2018-01-01", tz = "Australia/Melbourne"),
- as.POSIXct("2018-02-01", tz = "Australia/Melbourne"),
- length.out = 5
- )
-to_json(psx)#> [1514725200,1515394800,1516064400,1516734000,1517403600]to_json(psx, numeric_dates = FALSE)#> ["2017-12-31T13:00:00","2018-01-08T07:00:00","2018-01-16T01:00:00","2018-01-23T19:00:00","2018-01-31T13:00:00"]#> {"x":1.0}#> {"x":1.0,"y":"a","z":{"x":2.0,"y":"b"}}
-## rounding numbers using the digits argument
-to_json(1.23456789, digits = 2)#> [1.23]#> [{"x":1,"y":0.0,"z":"a"},{"x":2,"y":0.0,"z":"b"},{"x":3,"y":-1.0,"z":"c"}]
-## keeping factors
-to_json(df, digits = 2, factors_as_string = FALSE )#> [{"x":1,"y":0.47,"z":1},{"x":2,"y":0.36,"z":2},{"x":3,"y":-1.3,"z":3}]
-
-
-
-
+
-
+
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+
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-
+
diff --git a/docs/reference/to_ndjson.html b/docs/reference/to_ndjson.html
new file mode 100644
index 0000000..78be0f5
--- /dev/null
+++ b/docs/reference/to_ndjson.html
@@ -0,0 +1,199 @@
+
+To ndjson — to_ndjson • jsonify
+
+
+
+
+
+
+
+
+
+
+
+
+ Converts R objects to ndjson
+
+
+
+ to_ndjson(
+ x,
+ unbox = FALSE,
+ digits = NULL,
+ numeric_dates = TRUE,
+ factors_as_string = TRUE,
+ by = "row"
+)
+
+
+
+ Arguments
+ - x
+object to convert to JSON
- unbox
+logical indicating if single-value arrays should be 'unboxed',
+that is, not contained inside an array.
- digits
+integer specifying the number of decimal places to round numerics.
+Default is NULL - no rounding
- numeric_dates
+logical indicating if dates should be treated as numerics.
+Defaults to TRUE for speed. If FALSE, the dates will be coerced to character in UTC time zone
- factors_as_string
+logical indicating if factors should be treated as strings. Defaults to TRUE.
- by
+either "row" or "column" indicating if data.frames and matrices should be processed
+row-wise or column-wise. Defaults to "row"
+
+ Details
+ Lists are converted to ndjson non-recursively. That is, each of the objects
+in the list at the top level are converted to a new-line JSON object. Any nested
+sub-elements are then contained within that JSON object. See examples
+
+
+
+ Examples
+
+to_ndjson( 1:5 )
+#> [1,2,3,4,5]
+to_ndjson( letters )
+#> ["a","b","c","d","e","f","g","h","i","j","k","l","m","n","o","p","q","r","s","t","u","v","w","x","y","z"]
+
+mat <- matrix(1:6, ncol = 2)
+
+to_ndjson( x = mat )
+#> [1,4]
+#> [2,5]
+#> [3,6]
+to_ndjson( x = mat, by = "col" )
+#> [1,2,3]
+#> [4,5,6]
+
+df <- data.frame(
+ x = 1:5
+ , y = letters[1:5]
+ , z = as.Date(seq(18262, 18262 + 4, by = 1 ), origin = "1970-01-01" )
+ )
+
+to_ndjson( x = df )
+#> {"x":1,"y":"a","z":18262.0}
+#> {"x":2,"y":"b","z":18263.0}
+#> {"x":3,"y":"c","z":18264.0}
+#> {"x":4,"y":"d","z":18265.0}
+#> {"x":5,"y":"e","z":18266.0}
+to_ndjson( x = df, numeric_dates = FALSE )
+#> {"x":1,"y":"a","z":"2020-01-01"}
+#> {"x":2,"y":"b","z":"2020-01-02"}
+#> {"x":3,"y":"c","z":"2020-01-03"}
+#> {"x":4,"y":"d","z":"2020-01-04"}
+#> {"x":5,"y":"e","z":"2020-01-05"}
+to_ndjson( x = df, factors_as_string = FALSE )
+#> {"x":1,"y":"a","z":18262.0}
+#> {"x":2,"y":"b","z":18263.0}
+#> {"x":3,"y":"c","z":18264.0}
+#> {"x":4,"y":"d","z":18265.0}
+#> {"x":5,"y":"e","z":18266.0}
+to_ndjson( x = df, by = "column" )
+#> {"x":[1,2,3,4,5]}
+#> {"y":["a","b","c","d","e"]}
+#> {"z":[18262.0,18263.0,18264.0,18265.0,18266.0]}
+to_ndjson( x = df, by = "column", numeric_dates = FALSE )
+#> {"x":[1,2,3,4,5]}
+#> {"y":["a","b","c","d","e"]}
+#> {"z":["2020-01-01","2020-01-02","2020-01-03","2020-01-04","2020-01-05"]}
+
+## Lists are non-recurisve; only elements `x` and `y` are converted to ndjson
+lst <- list(
+ x = 1:5
+ , y = list(
+ a = letters[1:5]
+ , b = data.frame(i = 10:15, j = 20:25)
+ )
+)
+
+to_ndjson( x = lst )
+#> {"x":[1,2,3,4,5]}
+#> {"y":{"a":["a","b","c","d","e"],"b":[{"i":10,"j":20},{"i":11,"j":21},{"i":12,"j":22},{"i":13,"j":23},{"i":14,"j":24},{"i":15,"j":25}]}}
+to_ndjson( x = lst, by = "column")
+#> {"x":[1,2,3,4,5]}
+#> {"y":{"a":["a","b","c","d","e"],"b":{"i":[10,11,12,13,14,15],"j":[20,21,22,23,24,25]}}}
+
+
+
+
+
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+
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+
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+
diff --git a/docs/reference/validate_json.html b/docs/reference/validate_json.html
index 8d3e6d5..7a31dfa 100644
--- a/docs/reference/validate_json.html
+++ b/docs/reference/validate_json.html
@@ -1,58 +1,12 @@
-
-
-
-
-
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-validate JSON — validate_json • jsonify
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-validate JSON — validate_json • jsonify
-
-
-
+
+
-
-
-
-
-
+
-
Validates JSON
-
- validate_json(json)
-
- Arguments
-
-
- json
- character or json object
-
-
- Value
+
+ validate_json(json)
+
- logical vector
+
+ Arguments
+ - json
+character or json object
+
+ Value
- Examples
-
-validate_json('[]')#> [1] TRUE#> [1] TRUE
-validate_json('{"x":1,"y":2,"z":"a"}')#> [1] TRUE#> [1] TRUE TRUE#> [1] FALSE TRUE
-
-
-
+
+ Examples
+
+validate_json('[]')
+#> [1] TRUE
+df <- data.frame(id = 1:5, val = letters[1:5])
+validate_json( to_json(df) )
+#> [1] TRUE
+
+validate_json('{"x":1,"y":2,"z":"a"}')
+#> [1] TRUE
+
+validate_json( c('{"x":1,"y":2,"z":"a"}', to_json(df) ) )
+#> [1] TRUE TRUE
+validate_json( c('{"x":1,"y":2,"z":a}', to_json(df) ) )
+#> [1] FALSE TRUE
+
+
+
+
-
+
+
+
-
-
+
diff --git a/docs/sitemap.xml b/docs/sitemap.xml
new file mode 100644
index 0000000..af36988
--- /dev/null
+++ b/docs/sitemap.xml
@@ -0,0 +1,54 @@
+
+
+
+ /404.html
+
+
+ /LICENSE-text.html
+
+
+ /LICENSE.html
+
+
+ /articles/index.html
+
+
+ /articles/jsonify.html
+
+
+ /authors.html
+
+
+ /index.html
+
+
+ /news/index.html
+
+
+ /reference/as.json.html
+
+
+ /reference/from_json.html
+
+
+ /reference/from_ndjson.html
+
+
+ /reference/index.html
+
+
+ /reference/minify_json.html
+
+
+ /reference/pretty_json.html
+
+
+ /reference/to_json.html
+
+
+ /reference/to_ndjson.html
+
+
+ /reference/validate_json.html
+
+
-
-
+
-
-
-
-
-
jsonify converts R objects to JSON.
-
-
-There are already JSON converters, why did you build this one?
+ +
+
+
+
Converts between R objects and JSON.
+
+js <- '[{"x":1,"y":"a"},{"x":2,"y":"b"}]'
+( df <- from_json( js ) )
+# x y
+# 1 1 a
+# 2 2 b
+( to_json( df ) )
+# [{"x":1,"y":"a"},{"x":2,"y":"b"}]
+
-There are already JSON converters, why did you build this one? +
Because I wanted it available at the source ( C++ ) level for integrating into other packages.
-
+
-Is it fast?
-yeah it’s pretty good.
-
-library(microbenchmark)
-library(jsonlite)
-
-n <- 1e6
-df <- data.frame(
- id = 1:n
- , value = sample(letters, size = n, replace = T)
- , val2 = rnorm(n = n)
- , log = sample(c(T,F), size = n, replace = T)
- , stringsAsFactors = FALSE
-)
-
-microbenchmark(
- jsonlite = {
- js <- jsonlite::toJSON( df )
- },
- jsonify = {
- js <- jsonify::to_json( df )
- },
- times = 3
-)
-
-# Unit: seconds
-# expr min lq mean median uq max neval
-# jsonlite 2.017081 2.063732 2.540350 2.110383 2.801984 3.493585 3
-# jsonify 1.186239 1.202719 1.514067 1.219198 1.677981 2.136763 3
-
-n <- 1e4
-x <- list(
- x = rnorm(n = n)
- , y = list(x = rnorm(n = n))
- , z = list( list( x = rnorm(n = n)))
- , xx = rnorm(n = n)
- , yy = data.frame(
- id = 1:n
- , value = sample(letters, size = n, replace = T)
- , val2 = rnorm(n = n)
- , log = sample(c(T,F), size = n, replace = T)
- )
-)
-
-microbenchmark(
- jsonlite = {
- js <- jsonlite::toJSON( x )
- },
- jsonify = {
- js <- jsonify::to_json( x )
- },
- times = 5
-)
-
-# Unit: milliseconds
-# expr min lq mean median uq max neval
-# jsonlite 18.52028 18.82241 19.32112 18.99683 19.18103 21.08508 5
-# jsonify 17.72060 18.19092 19.58308 19.52457 21.14687 21.33241 5
-
+
+
-What do you mean by “available at the source” ? +
+I want to be able to call the C++ code from another package, without going to & from R. Therefore, the C++ code is implemented in headers, so you can “link to” it in your own package.
+For example, the LinkingTo section in DESCRIPTION will look something like
And in a c++ source file you can #include the header and use the available functions
#include "jsonify/jsonify.hpp"
+
+Rcpp::StringVector my_json( Rcpp::DataFrame df ) {
+ return jsonify::api::to_json( df );
+}You can see an example of this in my geojsonsf package
+-
+
- Description +
- #include +
-
-I thought you had an example of it being MUCH quicker than
-
-I thought you had an example of it being MUCH quicker than jsonlite ?
-Yeah, but I realised it was comparing two different methods. When jsonify was parsing nested lists, it was parsing data.frames column-wise, whereas jsonlite was row-wise. Which is a slower operation
+
-Can I call it from R if I want to? +
+Yes. Just like the examples in this readme use to_json()
+df <- data.frame(
+ id = 1:3
+ , val = letters[1:3]
+ )
+jsonify::to_json( df )
+# [{"id":1,"val":"a"},{"id":2,"val":"b"},{"id":3,"val":"c"}]
-
+
-Oh right. So it wasn’t a fair test then.
-Correct.
-Here’s a more suitable comparison
-n <- 1e4
-x <- list(
- x = rnorm(n = n)
- , y = list(x = rnorm(n = n))
- , z = list( list( x = rnorm(n = n)))
- , xx = rnorm(n = n)
- , yy = data.frame(
- id = 1:n
- , value = sample(letters, size = n, replace = T)
- , val2 = rnorm(n = n)
- , log = sample(c(T,F), size = n, replace = T)
- )
-)
-
-microbenchmark(
- jsonlite_row = {
- js <- jsonlite::toJSON( x )
- },
- jsonlite_col = {
- js <- jsonlite::toJSON( x, dataframe = "columns" )
- },
- jsonify_row = {
- js <- jsonify::to_json( x )
- },
- jsonify_col = {
- js <- jsonify::to_json( x, by = "column" )
- },
- times = 5
-)
-
-# Unit: milliseconds
-# expr min lq mean median uq max neval
-# jsonlite_row 20.533642 20.717894 27.294220 21.122860 21.426250 52.670456 5
-# jsonlite_col 13.691643 13.812459 15.683795 14.293177 15.655705 20.965993 5
-# jsonify_row 17.506507 17.951948 20.929641 19.827791 21.161389 28.200572 5
-# jsonify_col 7.262305 7.382238 7.409085 7.434759 7.435476 7.530645 5
+
-Is it fast? +
+yeah it’s pretty good.
+
+
+library(microbenchmark)
+library(jsonlite)
+
+n <- 1e6
+df <- data.frame(
+ id = 1:n
+ , value = sample(letters, size = n, replace = T)
+ , val2 = rnorm(n = n)
+ , log = sample(c(T,F), size = n, replace = T)
+ , stringsAsFactors = FALSE
+)
+
+microbenchmark(
+ jsonlite = {
+ jlt <- jsonlite::toJSON( df )
+ },
+ jsonify = {
+ jfy <- jsonify::to_json( df )
+ },
+ times = 3
+)
+
+# Unit: seconds
+# expr min lq mean median uq max neval
+# jsonlite 2.017081 2.063732 2.540350 2.110383 2.801984 3.493585 3
+# jsonify 1.186239 1.202719 1.514067 1.219198 1.677981 2.136763 3
+
+
+microbenchmark(
+ jsonlite = {
+ df_jlt <- jsonlite::fromJSON( jlt )
+ },
+ jsonify = {
+ df_jfy <- jsonify::from_json( jfy )
+ },
+ times = 3
+)
+
+# Unit: seconds
+# expr min lq mean median uq max neval
+# jsonlite 5.034888 5.149688 5.229363 5.264489 5.326601 5.388713 3
+# jsonify 4.551434 4.629683 4.678198 4.707932 4.741579 4.775227 3
+
+n <- 1e4
+x <- list(
+ x = rnorm(n = n)
+ , y = list(x = rnorm(n = n))
+ , z = list( list( x = rnorm(n = n)))
+ , xx = rnorm(n = n)
+ , yy = data.frame(
+ id = 1:n
+ , value = sample(letters, size = n, replace = T)
+ , val2 = rnorm(n = n)
+ , log = sample(c(T,F), size = n, replace = T)
+ )
+)
+
+microbenchmark(
+ jsonlite = {
+ jlt <- jsonlite::toJSON( x )
+ },
+ jsonify = {
+ jfy <- jsonify::to_json( x )
+ },
+ times = 5
+)
+
+# Unit: milliseconds
+# expr min lq mean median uq max neval
+# jsonlite 18.52028 18.82241 19.32112 18.99683 19.18103 21.08508 5
+# jsonify 17.72060 18.19092 19.58308 19.52457 21.14687 21.33241 5
+
+
+microbenchmark(
+ jsonlite = {
+ df_jlt <- jsonlite::fromJSON( jlt )
+ },
+ jsonify = {
+ df_jfy <- jsonify::from_json( jfy )
+ },
+ times = 3
+)
+
+# Unit: milliseconds
+# expr min lq mean median uq max neval
+# jsonlite 62.53554 62.96435 63.12574 63.39316 63.42084 63.44853 3
+# jsonify 42.47449 42.53826 43.38475 42.60204 43.83988 45.07773 3
-
-There’s no
+Changelog • jsonify
-
-
-
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-
-
-Changelog • jsonify
-
+
+
-
-
-
-There’s no Date type in JSON, how have you handled this?
+
+There’s no
+
-There’s no Date type in JSON, how have you handled this?
+
At its core Dates in R are numeric, so they are treated as numbers when converted to JSON. However, the user can coerce to character through the numeric_dates argument.
df <- data.frame(dte = as.Date("2018-01-01"))
-jsonify::to_json( df )
-# [{"dte":17532.0}]
-
-df <- data.frame(dte = as.Date("2018-01-01"))
-jsonify::to_json( df, numeric_dates = FALSE )
-# [{"dte":"2018-01-01"}]
+df <- data.frame(dte = as.Date("2018-01-01"))
+jsonify::to_json( df )
+# [{"dte":17532.0}]
+
+df <- data.frame(dte = as.Date("2018-01-01"))
+jsonify::to_json( df, numeric_dates = FALSE )
+# [{"dte":"2018-01-01"}]
-
-And
+
+
+
+
diff --git a/docs/news/index.html b/docs/news/index.html
index 2738134..55662fb 100644
--- a/docs/news/index.html
+++ b/docs/news/index.html
@@ -1,55 +1,12 @@
-
-
-
-
-
-
-
-
-And POSIXct and POSIXlt?
+
+And
+
-
-And POSIXct and POSIXlt?
+
The same
-
-jsonify::to_json( as.POSIXct("2018-01-01 10:00:00") )
-# [1514761200.0]
-jsonify::to_json( as.POSIXct("2018-01-01 10:00:00"), numeric_dates = FALSE)
-# ["2017-12-31T23:00:00"]
+
+jsonify::to_json( as.POSIXct("2018-01-01 10:00:00") )
+# [1514761200.0]
+jsonify::to_json( as.POSIXct("2018-01-01 10:00:00"), numeric_dates = FALSE)
+# ["2017-12-31T23:00:00"]However, here the POSIXct values are returned in UTC timezone. This is by design.
POSIXlt will return each component of the date-time
-x <- as.POSIXlt("2018-01-01 01:00:00", tz = "GMT")
-jsonify::to_json( x )
-# {"sec":[0.0],"min":[0],"hour":[1],"mday":[1],"mon":[0],"year":[118],"wday":[1],"yday":[0],"isdst":[0]}
-
-jsonify::to_json( x, numeric_dates = FALSE)
-# {"sec":[0.0],"min":[0],"hour":[1],"mday":[1],"mon":[0],"year":[118],"wday":[1],"yday":[0],"isdst":[0]}
-
-
-
+
--What about lists?
-The purpose of this library is speed. A lot of overhead is incurred iterating over a list to find and convert objects from one type to another.
For v0.2.0 I’ve managed to get the date handling at the c++ level, so there’s no penalty for recursing through the list to coerce to character.
-Therefore, lists will work too
-l <- list(
- dte = as.Date("2018-01-01")
- , psx = seq(as.POSIXct("2018-01-01 13:00:00"), as.POSIXct("2018-01-05 13:00:00"), length.out = 5)
- , df = data.frame(psx = seq(as.POSIXct("2018-01-01 13:00:00"), as.POSIXct("2018-01-05 13:00:00"), length.out = 5))
-)
-jsonify::to_json( l )
-# {"dte":[17532.0],"psx":[1514772000,1514858400,1514944800,1515031200,1515117600],"df":[{"psx":1514772000},{"psx":1514858400},{"psx":1514944800},{"psx":1515031200},{"psx":1515117600}]}js <- jsonify::to_json( l, numeric_dates = FALSE )
-jsonify::pretty_json( js )
-# {
-# "dte": [
-# "2018-01-01"
-# ],
-# "psx": [
-# "2018-01-01T02:00:00",
-# "2018-01-02T02:00:00",
-# "2018-01-03T02:00:00",
-# "2018-01-04T02:00:00",
-# "2018-01-05T02:00:00"
-# ],
-# "df": [
-# {
-# "psx": "2018-01-01T02:00:00"
-# },
-# {
-# "psx": "2018-01-02T02:00:00"
-# },
-# {
-# "psx": "2018-01-03T02:00:00"
-# },
-# {
-# "psx": "2018-01-04T02:00:00"
-# },
-# {
-# "psx": "2018-01-05T02:00:00"
-# }
-# ]
-# }And it’s still fast because of the design choice to coerce dates to UTC. All the date handling is done at the C++ leve, not R. So it’s faster.
-dtes <- seq(as.Date("2018-01-01"), as.Date("2019-01-01"), length.out = 365)
-psx <- seq(as.POSIXct("2018-01-01"), as.POSIXct("2019-01-01"), length.out = 365)
-n <- 1e5
-
-lst <- list(
- x = sample(dtes, size = n, replace = T)
- , y = list(
- ya = sample(dtes, size = n, replace = TRUE)
- , yb = rnorm(n = n)
- , yx = list( sample(dtes, size = n, replace = T ) )
- )
- , p = psx
-)
-
-library( microbenchmark )
-
-microbenchmark(
- jsonify1 = {
- jsonify::to_json( lst, numeric_dates = TRUE )
- },
- jsonify2 = {
- jsonify::to_json( lst, numeric_dates = FALSE )
- },
- jsonlite = {
- jsonlite::toJSON( lst )
- },
- times = 3
-)
-# Unit: milliseconds
-# expr min lq mean median uq max neval
-# jsonify1 60.26762 62.9191 70.36983 65.57057 75.42093 85.2713 3
-# jsonify2 314.75788 315.3369 331.71612 315.91598 340.19524 364.4745 3
-# jsonlite 674.26576 709.8997 737.83201 745.53362 769.61514 793.6967 3
+x <- as.POSIXlt("2018-01-01 01:00:00", tz = "GMT")
+jsonify::to_json( x )
+# {"sec":[0.0],"min":[0],"hour":[1],"mday":[1],"mon":[0],"year":[118],"wday":[1],"yday":[0],"isdst":[0]}
+
+jsonify::to_json( x, numeric_dates = FALSE)
+# {"sec":[0.0],"min":[0],"hour":[1],"mday":[1],"mon":[0],"year":[118],"wday":[1],"yday":[0],"isdst":[0]}
-
-That output looks nice, is that
-
-That output looks nice, is that pretty_json() function new?
-Yep, it’s a new feature in v0.2.0
+
+
-I see factors are converted to strings +
+Yep. Even though I constructed a data.frame() without setting stringsAsFactros = FALSE, jsonify automatically treats factors as strings.
-
-
--What do you mean by “available at the source” ?
-I want to be able to call the C++ code from another package, without going to & from R. Therefore, the C++ code is implemented in headers, so you can “link to” it in your own package.
-For example, the LinkingTo section in DESCRIPTION will look something like
LinkingTo:
- Rcpp,
- jsonifyAnd in a c++ source file you can #include the header and use the available functions
-
--Can I call it from R if I want to?
-Yes. Just like the examples in this readme use to_json()
-
--I see factors are converted to strings
-Yep. Even though I constructed a data.frame() without setting stringsAsFactros = FALSE, jsonify automatically treats factors as strings.
-
-
-Has this changed from v0.1?
+
+
+
-Has this changed from v0.1? +
Yes. And it’s to keep the data more inline with modern concepts and design patterns.
If you want factors, use factors_as_string = FALSE in the to_json() call
jsonify::to_json( df, factors_as_string = FALSE )
-# [{"id":1,"val":1},{"id":2,"val":2},{"id":3,"val":3}]
+jsonify::to_json( df, factors_as_string = FALSE )
+# [{"dte":17532.0}]
-
+
-How do I install it?
+
+
+
How do I install it? +
Get the latest release version from CRAN
- -Or the development version from GitHub with:
- +
+install.packages("jsonify")Or the development version from GitHub with:
+
+# install.packages("devtools")
+devtools::install_github("SymbolixAU/jsonify")
-
-
-
-Coerce string to JSON — as.json • jsonify
+
+
+ From JSON — from_json • jsonify
+
+
+ from ndjson — from_ndjson • jsonify
+
+
+ Function reference • jsonify
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-Function reference • jsonify
-
+
+
-
-
-
+
-
+
-
+
+
+
-
-
+
diff --git a/docs/pkgdown.css b/docs/pkgdown.css
index c03fb08..80ea5b8 100644
--- a/docs/pkgdown.css
+++ b/docs/pkgdown.css
@@ -17,12 +17,14 @@ html, body {
height: 100%;
}
+body {
+ position: relative;
+}
+
body > .container {
display: flex;
height: 100%;
flex-direction: column;
-
- padding-top: 60px;
}
body > .container .row {
@@ -54,8 +56,10 @@ img.icon {
float: right;
}
-img {
+/* Ensure in-page images don't run outside their container */
+.contents img {
max-width: 100%;
+ height: auto;
}
/* Fix bug in bootstrap (only seen in firefox) */
@@ -69,14 +73,17 @@ summary {
margin-top: calc(-60px + 1em);
}
+dd {
+ margin-left: 3em;
+}
+
/* Section anchors ---------------------------------*/
a.anchor {
- margin-left: -30px;
- display:inline-block;
- width: 30px;
- height: 30px;
- visibility: hidden;
+ display: none;
+ margin-left: 5px;
+ width: 20px;
+ height: 20px;
background-image: url(./link.svg);
background-repeat: no-repeat;
@@ -84,17 +91,15 @@ a.anchor {
background-position: center center;
}
-.hasAnchor:hover a.anchor {
- visibility: visible;
-}
-
-@media (max-width: 767px) {
- .hasAnchor:hover a.anchor {
- visibility: hidden;
- }
+h1:hover .anchor,
+h2:hover .anchor,
+h3:hover .anchor,
+h4:hover .anchor,
+h5:hover .anchor,
+h6:hover .anchor {
+ display: inline-block;
}
-
/* Fixes for fixed navbar --------------------------*/
.contents h1, .contents h2, .contents h3, .contents h4 {
@@ -102,37 +107,135 @@ a.anchor {
margin-top: -40px;
}
-/* Static header placement on mobile devices */
-@media (max-width: 767px) {
- .navbar-fixed-top {
- position: absolute;
- }
- .navbar {
- padding: 0;
- }
+/* Navbar submenu --------------------------*/
+
+.dropdown-submenu {
+ position: relative;
+}
+
+.dropdown-submenu>.dropdown-menu {
+ top: 0;
+ left: 100%;
+ margin-top: -6px;
+ margin-left: -1px;
+ border-radius: 0 6px 6px 6px;
+}
+
+.dropdown-submenu:hover>.dropdown-menu {
+ display: block;
+}
+
+.dropdown-submenu>a:after {
+ display: block;
+ content: " ";
+ float: right;
+ width: 0;
+ height: 0;
+ border-color: transparent;
+ border-style: solid;
+ border-width: 5px 0 5px 5px;
+ border-left-color: #cccccc;
+ margin-top: 5px;
+ margin-right: -10px;
+}
+
+.dropdown-submenu:hover>a:after {
+ border-left-color: #ffffff;
}
+.dropdown-submenu.pull-left {
+ float: none;
+}
+
+.dropdown-submenu.pull-left>.dropdown-menu {
+ left: -100%;
+ margin-left: 10px;
+ border-radius: 6px 0 6px 6px;
+}
/* Sidebar --------------------------*/
-#sidebar {
+#pkgdown-sidebar {
margin-top: 30px;
+ position: -webkit-sticky;
+ position: sticky;
+ top: 70px;
}
-#sidebar h2 {
+
+#pkgdown-sidebar h2 {
font-size: 1.5em;
margin-top: 1em;
}
-#sidebar h2:first-child {
+#pkgdown-sidebar h2:first-child {
margin-top: 0;
}
-#sidebar .list-unstyled li {
+#pkgdown-sidebar .list-unstyled li {
margin-bottom: 0.5em;
}
+/* bootstrap-toc tweaks ------------------------------------------------------*/
+
+/* All levels of nav */
+
+nav[data-toggle='toc'] .nav > li > a {
+ padding: 4px 20px 4px 6px;
+ font-size: 1.5rem;
+ font-weight: 400;
+ color: inherit;
+}
+
+nav[data-toggle='toc'] .nav > li > a:hover,
+nav[data-toggle='toc'] .nav > li > a:focus {
+ padding-left: 5px;
+ color: inherit;
+ border-left: 1px solid #878787;
+}
+
+nav[data-toggle='toc'] .nav > .active > a,
+nav[data-toggle='toc'] .nav > .active:hover > a,
+nav[data-toggle='toc'] .nav > .active:focus > a {
+ padding-left: 5px;
+ font-size: 1.5rem;
+ font-weight: 400;
+ color: inherit;
+ border-left: 2px solid #878787;
+}
+
+/* Nav: second level (shown on .active) */
+
+nav[data-toggle='toc'] .nav .nav {
+ display: none; /* Hide by default, but at >768px, show it */
+ padding-bottom: 10px;
+}
+
+nav[data-toggle='toc'] .nav .nav > li > a {
+ padding-left: 16px;
+ font-size: 1.35rem;
+}
+
+nav[data-toggle='toc'] .nav .nav > li > a:hover,
+nav[data-toggle='toc'] .nav .nav > li > a:focus {
+ padding-left: 15px;
+}
+
+nav[data-toggle='toc'] .nav .nav > .active > a,
+nav[data-toggle='toc'] .nav .nav > .active:hover > a,
+nav[data-toggle='toc'] .nav .nav > .active:focus > a {
+ padding-left: 15px;
+ font-weight: 500;
+ font-size: 1.35rem;
+}
+
+/* orcid ------------------------------------------------------------------- */
+
.orcid {
- height: 16px;
+ font-size: 16px;
+ color: #A6CE39;
+ /* margins are required by official ORCID trademark and display guidelines */
+ margin-left:4px;
+ margin-right:4px;
vertical-align: middle;
}
@@ -140,14 +243,14 @@ a.anchor {
.ref-index th {font-weight: normal;}
-.ref-index td {vertical-align: top;}
+.ref-index td {vertical-align: top; min-width: 100px}
.ref-index .icon {width: 40px;}
.ref-index .alias {width: 40%;}
.ref-index-icons .alias {width: calc(40% - 40px);}
.ref-index .title {width: 60%;}
.ref-arguments th {text-align: right; padding-right: 10px;}
-.ref-arguments th, .ref-arguments td {vertical-align: top;}
+.ref-arguments th, .ref-arguments td {vertical-align: top; min-width: 100px}
.ref-arguments .name {width: 20%;}
.ref-arguments .desc {width: 80%;}
@@ -160,31 +263,26 @@ table {
/* Syntax highlighting ---------------------------------------------------- */
-pre {
- word-wrap: normal;
- word-break: normal;
- border: 1px solid #eee;
-}
-
-pre, code {
+pre, code, pre code {
background-color: #f8f8f8;
color: #333;
}
+pre, pre code {
+ white-space: pre-wrap;
+ word-break: break-all;
+ overflow-wrap: break-word;
+}
-pre code {
- overflow: auto;
- word-wrap: normal;
- white-space: pre;
+pre {
+ border: 1px solid #eee;
}
-pre .img {
+pre .img, pre .r-plt {
margin: 5px 0;
}
-pre .img img {
+pre .img img, pre .r-plt img {
background-color: #fff;
- display: block;
- height: auto;
}
code a, pre a {
@@ -201,9 +299,8 @@ a.sourceLine:hover {
.kw {color: #264D66;} /* keyword */
.co {color: #888888;} /* comment */
-.message { color: black; font-weight: bolder;}
-.error { color: orange; font-weight: bolder;}
-.warning { color: #6A0366; font-weight: bolder;}
+.error {font-weight: bolder;}
+.warning {font-weight: bolder;}
/* Clipboard --------------------------*/
@@ -222,6 +319,19 @@ a.sourceLine:hover {
visibility: visible;
}
+/* headroom.js ------------------------ */
+
+.headroom {
+ will-change: transform;
+ transition: transform 200ms linear;
+}
+.headroom--pinned {
+ transform: translateY(0%);
+}
+.headroom--unpinned {
+ transform: translateY(-100%);
+}
+
/* mark.js ----------------------------*/
mark {
@@ -234,3 +344,41 @@ mark {
.html-widget {
margin-bottom: 10px;
}
+
+/* fontawesome ------------------------ */
+
+.fab {
+ font-family: "Font Awesome 5 Brands" !important;
+}
+
+/* don't display links in code chunks when printing */
+/* source: https://stackoverflow.com/a/10781533 */
+@media print {
+ code a:link:after, code a:visited:after {
+ content: "";
+ }
+}
+
+/* Section anchors ---------------------------------
+ Added in pandoc 2.11: https://github.com/jgm/pandoc-templates/commit/9904bf71
+*/
+
+div.csl-bib-body { }
+div.csl-entry {
+ clear: both;
+}
+.hanging-indent div.csl-entry {
+ margin-left:2em;
+ text-indent:-2em;
+}
+div.csl-left-margin {
+ min-width:2em;
+ float:left;
+}
+div.csl-right-inline {
+ margin-left:2em;
+ padding-left:1em;
+}
+div.csl-indent {
+ margin-left: 2em;
+}
diff --git a/docs/pkgdown.js b/docs/pkgdown.js
index eb7e83d..6f0eee4 100644
--- a/docs/pkgdown.js
+++ b/docs/pkgdown.js
@@ -2,18 +2,11 @@
(function($) {
$(function() {
- $("#sidebar")
- .stick_in_parent({offset_top: 40})
- .on('sticky_kit:bottom', function(e) {
- $(this).parent().css('position', 'static');
- })
- .on('sticky_kit:unbottom', function(e) {
- $(this).parent().css('position', 'relative');
- });
+ $('.navbar-fixed-top').headroom();
- $('body').scrollspy({
- target: '#sidebar',
- offset: 60
+ $('body').css('padding-top', $('.navbar').height() + 10);
+ $(window).resize(function(){
+ $('body').css('padding-top', $('.navbar').height() + 10);
});
$('[data-toggle="tooltip"]').tooltip();
@@ -87,7 +80,7 @@
$(document).ready(function() {
var copyButton = "";
- $(".examples, div.sourceCode").addClass("hasCopyButton");
+ $("div.sourceCode").addClass("hasCopyButton");
// Insert copy buttons:
$(copyButton).prependTo(".hasCopyButton");
@@ -98,7 +91,7 @@
// Initialize clipboard:
var clipboardBtnCopies = new ClipboardJS('[data-clipboard-copy]', {
text: function(trigger) {
- return trigger.parentNode.textContent;
+ return trigger.parentNode.textContent.replace(/\n#>[^\n]*/g, "");
}
});
diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml
index 6a18080..619f050 100644
--- a/docs/pkgdown.yml
+++ b/docs/pkgdown.yml
@@ -1,6 +1,7 @@
-pandoc: 2.3.1
-pkgdown: 1.3.0
+pandoc: 3.1.1
+pkgdown: 2.0.7
pkgdown_sha: ~
articles:
jsonify: jsonify.html
+last_built: 2024-01-17T21:33Z
diff --git a/docs/reference/Rplot001.png b/docs/reference/Rplot001.png
new file mode 100644
index 0000000000000000000000000000000000000000..17a358060aed2a86950757bbd25c6f92c08c458f
GIT binary patch
literal 1011
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literal 0
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diff --git a/docs/reference/as.json.html b/docs/reference/as.json.html
new file mode 100644
index 0000000..596a781
--- /dev/null
+++ b/docs/reference/as.json.html
@@ -0,0 +1,101 @@
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/docs/reference/from_json.html b/docs/reference/from_json.html
new file mode 100644
index 0000000..5d183b6
--- /dev/null
+++ b/docs/reference/from_json.html
@@ -0,0 +1,239 @@
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Coerce string to JSON
+
+
+
+
+ as.json(x)
+
+
+ Arguments
+- x +
string to coerce to JSON
+
+
+
+
+ Examples
+
+js <- '{"x":1,"y":2}'
+as.json(js)
+#> {"x":1,"y":2}
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/docs/reference/from_ndjson.html b/docs/reference/from_ndjson.html
new file mode 100644
index 0000000..e8151c5
--- /dev/null
+++ b/docs/reference/from_ndjson.html
@@ -0,0 +1,117 @@
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Converts JSON to an R object.
+
+
+
+
+ from_json(json, simplify = TRUE, fill_na = FALSE, buffer_size = 1024)
+
+ Arguments
+- json +
JSON to convert to R object. Can be a string, url or link to a file.
+
+
+- simplify +
logical, if
TRUE, coerces JSON to the simplest R object possible. See Details
+
+
+- fill_na +
logical, if
TRUEandsimplifyisTRUE, +data.frames will be na-filled if there are missing JSON keys. +Ignored ifsimplifyisFALSE. See details and examples.
+
+
+- buffer_size +
size of buffer used when reading a file from disk. Defaults to 1024
+
+
+
+
+ Details
+When simplify = TRUE
single arrays are coerced to vectors
+array of arrays (all the same length) are coerced to matrices
+objects with the same keys are coerced to data.frames
+
When simplify = TRUE and fill_na = TRUE
objects are coerced to data.frames, and any missing values are filled with NAs
+
+
+
+ Examples
+
+from_json('{"a":[1, 2, 3]}')
+#> $a
+#> [1] 1 2 3
+#>
+from_json('{"a":8, "b":99.5, "c":true, "d":"cats", "e":[1, "cats", 3]}')
+#> $a
+#> [1] 8
+#>
+#> $b
+#> [1] 99.5
+#>
+#> $c
+#> [1] TRUE
+#>
+#> $d
+#> [1] "cats"
+#>
+#> $e
+#> [1] "1" "cats" "3"
+#>
+from_json('{"a":8, "b":{"c":123, "d":{"e":456}}}')
+#> $a
+#> [1] 8
+#>
+#> $b
+#> $b$c
+#> [1] 123
+#>
+#> $b$d
+#> $b$d$e
+#> [1] 456
+#>
+#>
+#>
+
+lst <- list("a" = 5L, "b" = 1.43, "c" = "cats", "d" = FALSE)
+js <- jsonify::to_json(lst, unbox = TRUE)
+from_json( js )
+#> $a
+#> [1] 5
+#>
+#> $b
+#> [1] 1.43
+#>
+#> $c
+#> [1] "cats"
+#>
+#> $d
+#> [1] FALSE
+#>
+
+## Return a data frame
+from_json('[{"id":1,"val":"a"},{"id":2,"val":"b"}]')
+#> id val
+#> 1 1 a
+#> 2 2 b
+
+## Return a data frame with a list column
+from_json('[{"id":1,"val":"a"},{"id":2,"val":["b","c"]}]')
+#> id val
+#> 1 1 a
+#> 2 2 b, c
+
+## Without simplifying to a data.frame
+from_json('[{"id":1,"val":"a"},{"id":2,"val":["b","c"]}]', simplify = FALSE )
+#> [[1]]
+#> [[1]]$id
+#> [1] 1
+#>
+#> [[1]]$val
+#> [1] "a"
+#>
+#>
+#> [[2]]
+#> [[2]]$id
+#> [1] 2
+#>
+#> [[2]]$val
+#> [[2]]$val[[1]]
+#> [1] "b"
+#>
+#> [[2]]$val[[2]]
+#> [1] "c"
+#>
+#>
+#>
+
+## Missing JSON keys
+from_json('[{"x":1},{"x":2,"y":"hello"}]')
+#> [[1]]
+#> [[1]]$x
+#> [1] 1
+#>
+#>
+#> [[2]]
+#> [[2]]$x
+#> [1] 2
+#>
+#> [[2]]$y
+#> [1] "hello"
+#>
+#>
+
+## Missing JSON keys - filling with NAs
+from_json('[{"x":1},{"x":2,"y":"hello"}]', fill_na = TRUE )
+#> x y
+#> 1 1 <NA>
+#> 2 2 hello
+
+## Duplicate object keys
+from_json('[{"x":1,"x":"a"},{"x":2,"x":"b"}]')
+#> x
+#> 1 1
+#> 2 2
+
+from_json('[{"id":1,"val":"a","val":1},{"id":2,"val":"b"}]', fill_na = TRUE )
+#> id val
+#> 1 1 a
+#> 2 2 b
+
+
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diff --git a/docs/reference/index.html b/docs/reference/index.html
index 24c1c74..9406733 100644
--- a/docs/reference/index.html
+++ b/docs/reference/index.html
@@ -1,55 +1,12 @@
-
-
-
-
-
-
-
-
+
+
+
+
+
+
+
+
+
+
+
+ Converts ndjson into R objects
+
+
+
+
+ from_ndjson(ndjson, simplify = TRUE, fill_na = FALSE)
+
+
+ Arguments
+- ndjson +
new-line delimited JSON to convert to R object. Can be a string, url or link to a file.
+
+
+- simplify +
logical, if
TRUE, coerces JSON to the simplest R object possible. See Details
+
+
+- fill_na +
logical, if
TRUEandsimplifyisTRUE, +data.frames will be na-filled if there are missing JSON keys. +Ignored ifsimplifyisFALSE. See details and examples.
+
+
+
+
+ Examples
+
+js <- to_ndjson( data.frame( x = 1:5, y = 6:10 ) )
+from_ndjson( js )
+#> x y
+#> 1 1 6
+#> 2 2 7
+#> 3 3 8
+#> 4 4 9
+#> 5 5 10
+
+
+
-
-
-
-A short title line describing what the package does — jsondf-package • jsonify
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- Minify Json — minify_json • jsonify
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-Minify Json — minify_json • jsonify
-
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diff --git a/docs/reference/jsondf-package.html b/docs/reference/jsondf-package.html
deleted file mode 100644
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--- a/docs/reference/jsondf-package.html
+++ /dev/null
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diff --git a/docs/reference/minify_json.html b/docs/reference/minify_json.html
index 43c8418..9056933 100644
--- a/docs/reference/minify_json.html
+++ b/docs/reference/minify_json.html
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-
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- A short title line describing what the package does
- -jsondf-package.Rd
-
-
-
-
- A more detailed description of what the package does. A length - of about one to five lines is recommended.
- -Details
- -This section should provide a more detailed overview of how to use the - package, including the most important functions.
- -References
- -This optional section can contain literature or other references for - background information.
- -See also
- -Optional links to other man pages
Examples
--# NOT RUN { - ## Optional simple examples of the most important functions - ## These can be in \dontrun{} and \donttest{} blocks. - -# } -
-
-
-
-Pretty Json — pretty_json • jsonify
-
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-Pretty Json — pretty_json • jsonify
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diff --git a/docs/reference/pretty_json.html b/docs/reference/pretty_json.html
index 2b50153..54a767d 100644
--- a/docs/reference/pretty_json.html
+++ b/docs/reference/pretty_json.html
@@ -1,58 +1,12 @@
-
-
-
-
-
-
-
-
-
- Removes indentiation from a JSON string
-minify_json(json, ...)- -
Arguments
-| json | -string of JSON |
-
|---|---|
| ... | -other argments passed to to_json |
-
+
+
- minify_json(json, ...)Examples
---df <- data.frame(id = 1:10, val = rnorm(10)) -js <- to_json( df ) -jsp <- pretty_json(js) -minify_json( jsp )#> [{"id":1,"val":-1.4000435167217549},{"id":2,"val":0.2553170548452597},{"id":3,"val":-2.437263611219531},{"id":4,"val":-0.005571286746160735},{"id":5,"val":0.6215527214152141},{"id":6,"val":1.1484116060260608},{"id":7,"val":-1.821817660976626},{"id":8,"val":-0.24732530207352436},{"id":9,"val":-0.24419960677838332},{"id":10,"val":-0.2827054488144648}]-
-
-
-
-To JSON — to_json • jsonify
-
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-To JSON — to_json • jsonify
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diff --git a/docs/reference/to_json.html b/docs/reference/to_json.html
index 76eacee..fea2f01 100644
--- a/docs/reference/to_json.html
+++ b/docs/reference/to_json.html
@@ -1,58 +1,12 @@
-
-
-
-
-
-
-
-
-
- Adds indentiation to a JSON string
-pretty_json(json, ...)- -
Arguments
-| json | -string of JSON |
-
|---|---|
| ... | -other argments passed to to_json |
-
Examples
--#> [ -#> { -#> "id": 1, -#> "val": -0.5536993836887205 -#> }, -#> { -#> "id": 2, -#> "val": 0.628982042036008 -#> }, -#> { -#> "id": 3, -#> "val": 2.065024895359223 -#> }, -#> { -#> "id": 4, -#> "val": -1.6309894020822316 -#> }, -#> { -#> "id": 5, -#> "val": 0.5124269498518048 -#> }, -#> { -#> "id": 6, -#> "val": -1.863011492068328 -#> }, -#> { -#> "id": 7, -#> "val": -0.5220125147454544 -#> }, -#> { -#> "id": 8, -#> "val": -0.05260190995387954 -#> }, -#> { -#> "id": 9, -#> "val": 0.5429963426611403 -#> }, -#> { -#> "id": 10, -#> "val": -0.9140748272599284 -#> } -#> ]-## can also use directly on an R object -pretty_json( df )#> [ -#> { -#> "id": 1, -#> "val": -0.5536993836887205 -#> }, -#> { -#> "id": 2, -#> "val": 0.628982042036008 -#> }, -#> { -#> "id": 3, -#> "val": 2.065024895359223 -#> }, -#> { -#> "id": 4, -#> "val": -1.6309894020822316 -#> }, -#> { -#> "id": 5, -#> "val": 0.5124269498518048 -#> }, -#> { -#> "id": 6, -#> "val": -1.863011492068328 -#> }, -#> { -#> "id": 7, -#> "val": -0.5220125147454544 -#> }, -#> { -#> "id": 8, -#> "val": -0.05260190995387954 -#> }, -#> { -#> "id": 9, -#> "val": 0.5429963426611403 -#> }, -#> { -#> "id": 10, -#> "val": -0.9140748272599284 -#> } -#> ]-
-
-
-
-To ndjson — to_ndjson • jsonify
+
+
+ validate JSON — validate_json • jsonify
-
-
-
-
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-validate JSON — validate_json • jsonify
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diff --git a/docs/reference/to_ndjson.html b/docs/reference/to_ndjson.html
new file mode 100644
index 0000000..78be0f5
--- /dev/null
+++ b/docs/reference/to_ndjson.html
@@ -0,0 +1,199 @@
+
+
-
- Converts R objects to JSON
-to_json(x, unbox = FALSE, digits = NULL, numeric_dates = TRUE, - factors_as_string = TRUE, by = "row")- -
Arguments
-| x | -object to convert to JSON |
-
|---|---|
| unbox | -logical indicating if single-value arrays should be 'unboxed', -that is, not contained inside an array. |
-
| digits | -integer specifying the number of decimal places to round numerics.
-Default is |
-
| numeric_dates | -logical indicating if dates should be treated as numerics. -Defaults to TRUE for speed. If FALSE, the dates will be coerced to character in UTC time zone |
-
| factors_as_string | -logical indicating if factors should be treated as strings. Defaults to TRUE. |
-
| by | -either "row" or "column" indicating if data.frames and matrices should be processed -row-wise or column-wise. Defaults to "row" |
-
Examples
---to_json(1:3)#> [1,2,3]to_json(letters[1:3])#> ["a","b","c"]#> [{"x":1,"y":"a"},{"x":2,"y":"b"},{"x":3,"y":"c"}]#> {"x":[1,2,3],"y":{"z":["a","b","c"]}}#> [17532,17533,17534,17535,17536]#> ["2018-01-01","2018-01-02","2018-01-03","2018-01-04","2018-01-05"]-psx <- seq( - as.POSIXct("2018-01-01", tz = "Australia/Melbourne"), - as.POSIXct("2018-02-01", tz = "Australia/Melbourne"), - length.out = 5 - ) -to_json(psx)#> [1514725200,1515394800,1516064400,1516734000,1517403600]to_json(psx, numeric_dates = FALSE)#> ["2017-12-31T13:00:00","2018-01-08T07:00:00","2018-01-16T01:00:00","2018-01-23T19:00:00","2018-01-31T13:00:00"]#> {"x":1.0}#> {"x":1.0,"y":"a","z":{"x":2.0,"y":"b"}}-## rounding numbers using the digits argument -to_json(1.23456789, digits = 2)#> [1.23]#> [{"x":1,"y":0.0,"z":"a"},{"x":2,"y":0.0,"z":"b"},{"x":3,"y":-1.0,"z":"c"}]-## keeping factors -to_json(df, digits = 2, factors_as_string = FALSE )#> [{"x":1,"y":0.47,"z":1},{"x":2,"y":0.36,"z":2},{"x":3,"y":-1.3,"z":3}]- -
+
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diff --git a/docs/reference/validate_json.html b/docs/reference/validate_json.html
index 8d3e6d5..7a31dfa 100644
--- a/docs/reference/validate_json.html
+++ b/docs/reference/validate_json.html
@@ -1,58 +1,12 @@
-
-
-
-
-
-
-
-
+
+
+
+
+
+
+
+
+
+
+
+ Converts R objects to ndjson
+
+
+
+
+ to_ndjson(
+ x,
+ unbox = FALSE,
+ digits = NULL,
+ numeric_dates = TRUE,
+ factors_as_string = TRUE,
+ by = "row"
+)
+
+ Arguments
+- x +
object to convert to JSON
+
+
+- unbox +
logical indicating if single-value arrays should be 'unboxed', +that is, not contained inside an array.
+
+
+- digits +
integer specifying the number of decimal places to round numerics. +Default is
NULL- no rounding
+
+
+- numeric_dates +
logical indicating if dates should be treated as numerics. +Defaults to TRUE for speed. If FALSE, the dates will be coerced to character in UTC time zone
+
+
+- factors_as_string +
logical indicating if factors should be treated as strings. Defaults to TRUE.
+
+
+- by +
either "row" or "column" indicating if data.frames and matrices should be processed +row-wise or column-wise. Defaults to "row"
+
+
+
+
+ Details
+Lists are converted to ndjson non-recursively. That is, each of the objects +in the list at the top level are converted to a new-line JSON object. Any nested +sub-elements are then contained within that JSON object. See examples
+
+
+
+ Examples
+
+to_ndjson( 1:5 )
+#> [1,2,3,4,5]
+to_ndjson( letters )
+#> ["a","b","c","d","e","f","g","h","i","j","k","l","m","n","o","p","q","r","s","t","u","v","w","x","y","z"]
+
+mat <- matrix(1:6, ncol = 2)
+
+to_ndjson( x = mat )
+#> [1,4]
+#> [2,5]
+#> [3,6]
+to_ndjson( x = mat, by = "col" )
+#> [1,2,3]
+#> [4,5,6]
+
+df <- data.frame(
+ x = 1:5
+ , y = letters[1:5]
+ , z = as.Date(seq(18262, 18262 + 4, by = 1 ), origin = "1970-01-01" )
+ )
+
+to_ndjson( x = df )
+#> {"x":1,"y":"a","z":18262.0}
+#> {"x":2,"y":"b","z":18263.0}
+#> {"x":3,"y":"c","z":18264.0}
+#> {"x":4,"y":"d","z":18265.0}
+#> {"x":5,"y":"e","z":18266.0}
+to_ndjson( x = df, numeric_dates = FALSE )
+#> {"x":1,"y":"a","z":"2020-01-01"}
+#> {"x":2,"y":"b","z":"2020-01-02"}
+#> {"x":3,"y":"c","z":"2020-01-03"}
+#> {"x":4,"y":"d","z":"2020-01-04"}
+#> {"x":5,"y":"e","z":"2020-01-05"}
+to_ndjson( x = df, factors_as_string = FALSE )
+#> {"x":1,"y":"a","z":18262.0}
+#> {"x":2,"y":"b","z":18263.0}
+#> {"x":3,"y":"c","z":18264.0}
+#> {"x":4,"y":"d","z":18265.0}
+#> {"x":5,"y":"e","z":18266.0}
+to_ndjson( x = df, by = "column" )
+#> {"x":[1,2,3,4,5]}
+#> {"y":["a","b","c","d","e"]}
+#> {"z":[18262.0,18263.0,18264.0,18265.0,18266.0]}
+to_ndjson( x = df, by = "column", numeric_dates = FALSE )
+#> {"x":[1,2,3,4,5]}
+#> {"y":["a","b","c","d","e"]}
+#> {"z":["2020-01-01","2020-01-02","2020-01-03","2020-01-04","2020-01-05"]}
+
+## Lists are non-recurisve; only elements `x` and `y` are converted to ndjson
+lst <- list(
+ x = 1:5
+ , y = list(
+ a = letters[1:5]
+ , b = data.frame(i = 10:15, j = 20:25)
+ )
+)
+
+to_ndjson( x = lst )
+#> {"x":[1,2,3,4,5]}
+#> {"y":{"a":["a","b","c","d","e"],"b":[{"i":10,"j":20},{"i":11,"j":21},{"i":12,"j":22},{"i":13,"j":23},{"i":14,"j":24},{"i":15,"j":25}]}}
+to_ndjson( x = lst, by = "column")
+#> {"x":[1,2,3,4,5]}
+#> {"y":{"a":["a","b","c","d","e"],"b":{"i":[10,11,12,13,14,15],"j":[20,21,22,23,24,25]}}}
+
+
+
-
-
-
-
+
+ /404.html
+
+
+ /LICENSE-text.html
+
+
+ /LICENSE.html
+
+
+ /articles/index.html
+
+
+ /articles/jsonify.html
+
+
+ /authors.html
+
+
+ /index.html
+
+
+ /news/index.html
+
+
+ /reference/as.json.html
+
+
+ /reference/from_json.html
+
+
+ /reference/from_ndjson.html
+
+
+ /reference/index.html
+
+
+ /reference/minify_json.html
+
+
+ /reference/pretty_json.html
+
+
+ /reference/to_json.html
+
+
+ /reference/to_ndjson.html
+
+
+ /reference/validate_json.html
+
+
+
-
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-
+
-
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+
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+
diff --git a/docs/sitemap.xml b/docs/sitemap.xml
new file mode 100644
index 0000000..af36988
--- /dev/null
+++ b/docs/sitemap.xml
@@ -0,0 +1,54 @@
+
+
-
- Validates JSON
-validate_json(json)- -
Arguments
-| json | -character or json object |
-
|---|
Value
+
+
+
- validate_json(json)logical vector
+
+
+ Arguments
+- json +
character or json object
+
+
+
-
+ Value
-Examples
---validate_json('[]')#> [1] TRUE#> [1] TRUE-validate_json('{"x":1,"y":2,"z":"a"}')#> [1] TRUE#> [1] TRUE TRUE#> [1] FALSE TRUE-
+
+
Examples
+
+validate_json('[]')
+#> [1] TRUE
+df <- data.frame(id = 1:5, val = letters[1:5])
+validate_json( to_json(df) )
+#> [1] TRUE
+
+validate_json('{"x":1,"y":2,"z":"a"}')
+#> [1] TRUE
+
+validate_json( c('{"x":1,"y":2,"z":"a"}', to_json(df) ) )
+#> [1] TRUE TRUE
+validate_json( c('{"x":1,"y":2,"z":a}', to_json(df) ) )
+#> [1] FALSE TRUE
+
+