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https://github.com/jeroen/js
Tools for Working with JavaScript in R
https://github.com/jeroen/js
Last synced: 10 days ago
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Tools for Working with JavaScript in R
- Host: GitHub
- URL: https://github.com/jeroen/js
- Owner: jeroen
- License: other
- Created: 2015-01-10T20:30:41.000Z (almost 10 years ago)
- Default Branch: master
- Last Pushed: 2024-10-03T12:53:05.000Z (about 1 month ago)
- Last Synced: 2024-10-11T18:19:49.375Z (25 days ago)
- Language: R
- Homepage:
- Size: 748 KB
- Stars: 68
- Watchers: 5
- Forks: 5
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- jimsghstars - jeroen/js - Tools for Working with JavaScript in R (R)
README
# js
##### *Tools for Working with JavaScript in R*
[](https://app.travis-ci.com/jeroen/js)
[](https://ci.appveyor.com/project/jeroen/js)
[](https://app.codecov.io/github/jeroen/js?branch=master)
[](http://cran.r-project.org/package=js)
[](http://cran.r-project.org/web/packages/js/index.html)
[](https://github.com/jeroen/js)
> A set of utility functions for working with JavaScript in R.
Currently includes functions to compile, validate, reformat, optimize
and analyze JavaScript code.
## Documentation
- Vignette: [Working with JavaScript in R](https://cran.r-project.org/web/packages/js/vignettes/intro.html)
The js package implements bindings to several popular JavaScript libraries for validating, reformatting, optimizing and analyzing JavaScript code. It builds on the [V8 package](https://cran.r-project.org/package=V8/vignettes/v8_intro.html) (a fully standalone JavaScript engine in R) to call out to these libraries.
## Syntax Validation
Several R packages allow the user to supply JavaScript code to be used as callback function or configuration object within a visualization or web application. By validating in R that the JavaScript code is syntactically correct and of the right type before actually inserting it in the HTML, we can avoid many annoying bugs.
The `js_typeof` function simply calls the `typeof` operator on the given code. If the code is invalid, a SyntaxError will be raised.
```r
callback <- 'function test(x, y){
var z = x*y ;
return z;
}'
js_typeof(callback)
```
```
[1] "function"
```
Same for objects:
```r
conf <- '{
foo : function (){},
bar : 123
}'
js_typeof(conf)
```
```
[1] "object"
```
Catch JavaScript typos:
```r
js_typeof('function(x,y){return x + y}}')
```
```
Error in context_eval(join(src), private$context): SyntaxError: Unexpected token }
```
## Script Validation
A JavaScript program typically consists of script with a collection of JavaScript statements. The `js_validate_script` function can be used to validate an entire script.
```r
jscode <- readLines(system.file("js/uglify.min.js", package="js"), warn = FALSE)
js_validate_script(jscode)
```
```
[1] TRUE
```
Note that JavaScript does not allow for defining anonymous functions in the global scope:
```r
js_validate_script('function(x, y){return x + y}', error = FALSE)
```
```
[1] FALSE
```
To validate individual functions or objects, use the `js_typeof` function.
## ESprima: Parsing
Esprima is a high performance, standard-compliant ECMAScript parser. It has full support for ECMAScript 2017 and returns a sensible syntax tree format as standardized by ESTree project.
```r
esprima_tokenize(callback)
```
```
type value
1 Keyword function
2 Identifier test
3 Punctuator (
4 Identifier x
5 Punctuator ,
6 Identifier y
7 Punctuator )
8 Punctuator {
9 Keyword var
10 Identifier z
11 Punctuator =
12 Identifier x
13 Punctuator *
14 Identifier y
15 Punctuator ;
16 Keyword return
17 Identifier z
18 Punctuator ;
19 Punctuator }
```
```r
esprima_parse(callback)
```
```js
{
"type": "Program",
"body": [
{
"type": "FunctionDeclaration",
"id": {
"type": "Identifier",
"name": "test"
},
"params": [
{
"type": "Identifier",
"name": "x"
},
{
"type": "Identifier",
"name": "y"
}
],
"body": {
"type": "BlockStatement",
"body": [
{
"type": "VariableDeclaration",
"declarations": [
{
"type": "VariableDeclarator",
"id": {
"type": "Identifier",
"name": "z"
},
"init": {
"type": "BinaryExpression",
"operator": "*",
"left": {
"type": "Identifier",
"name": "x"
},
"right": {
"type": "Identifier",
"name": "y"
}
}
}
],
"kind": "var"
},
{
"type": "ReturnStatement",
"argument": {
"type": "Identifier",
"name": "z"
}
}
]
},
"generator": false,
"expression": false,
"async": false
}
],
"sourceType": "script"
}
```
## Compiling CoffeeScript
[CoffeeScript](http://coffeescript.org/) is a little language that compiles into JavaScript. It is an attempt to expose the good parts of JavaScript in a simple way. The `coffee_compile` function binds to the coffee script compiler.
```r
# Hello world
cat(coffee_compile("square = (x) -> x * x"))
```
```js
(function() {
var square;
square = function(x) {
return x * x;
};
}).call(this);
```
```r
cat(coffee_compile("square = (x) -> x * x", bare = TRUE))
```
```
var square;
square = function(x) {
return x * x;
};
```
The golden rule of CoffeeScript is: *"It's just JavaScript"*. The code compiles one-to-one into the equivalent JS, and there is no interpretation at runtime. You can use any existing JavaScript library seamlessly from CoffeeScript (and vice-versa). The compiled output is readable and pretty-printed, will work in every JavaScript runtime, and tends to run as fast or faster than the equivalent handwritten JavaScript.
```r
# Simple script
demo <- readLines(system.file("example/demo.coffee", package = "js"))
cat(demo, sep = "\n")
```
```
# Assignment:
number = 42
opposite = true
# Conditions:
number = -42 if opposite
# Functions:
square = (x) -> x * x
# Arrays:
list = [1, 2, 3, 4, 5]
# Objects:
math =
root: Math.sqrt
square: square
cube: (x) -> x * square x
# Splats:
race = (winner, runners...) ->
print winner, runners
# Existence:
alert "I knew it!" if elvis?
# Array comprehensions:
cubes = (math.cube num for num in list)
```
```r
js <- coffee_compile(demo)
cat(js)
```
```js
(function() {
var cubes, list, math, num, number, opposite, race, square,
slice = [].slice;
number = 42;
opposite = true;
if (opposite) {
number = -42;
}
square = function(x) {
return x * x;
};
list = [1, 2, 3, 4, 5];
math = {
root: Math.sqrt,
square: square,
cube: function(x) {
return x * square(x);
}
};
race = function() {
var runners, winner;
winner = arguments[0], runners = 2 <= arguments.length ? slice.call(arguments, 1) : [];
return print(winner, runners);
};
if (typeof elvis !== "undefined" && elvis !== null) {
alert("I knew it!");
}
cubes = (function() {
var i, len, results;
results = [];
for (i = 0, len = list.length; i < len; i++) {
num = list[i];
results.push(math.cube(num));
}
return results;
})();
}).call(this);
```
```r
cat(uglify_optimize(js))
```
```
(function(){var cubes,list,math,num,number,opposite,race,square,slice=[].slice;number=42,opposite=!0,opposite&&(number=-42),square=function(x){return x*x},list=[1,2,3,4,5],math={root:Math.sqrt,square:square,cube:function(x){return x*square(x)}},race=function(){var runners,winner;return winner=arguments[0],runners=2<=arguments.length?slice.call(arguments,1):[],print(winner,runners)},"undefined"!=typeof elvis&&null!==elvis&&alert("I knew it!"),cubes=function(){var i,len,results;for(results=[],i=0,len=list.length;len>i;i++)num=list[i],results.push(math.cube(num));return results}()}).call(this);
```
## Uglify: reformatting
One of the most popular and powerful libraries for working with JavaScript code is [uglify-js](https://www.npmjs.com/package/uglify-js). Uglify provides an extensive toolkit for manipulating the syntax tree of a piece of JavaScript code.
The `uglify_reformat` binding parses a string with code and then feeds it to the [uglify code generator](https://lisperator.net/uglifyjs/codegen) which converts it back to JavaScript text, with custom formatting options. This is nice for fixing whitespace, semicolons, etc.
```r
code <- "function test(x, y){ x = x || 1; y = y || 1; return x*y;}"
cat(uglify_reformat(code, beautify = TRUE, indent_level = 2))
```
```js
function test(x, y) {
x = x || 1;
y = y || 1;
return x * y;
}
```
## Uglify: optimization
The more impressive part of uglify-js is the [compressor](https://lisperator.net/uglifyjs/compress) which refactors the entire syntax tree, effectively rewriting your code into a more compact but equivalent program. The `uglify_optimize` function in R is a simple wrapper which parses code and then feeds it to the compressor.
```r
cat(code)
```
```
function test(x, y){ x = x || 1; y = y || 1; return x*y;}
```
```r
cat(uglify_optimize(code))
```
```js
function test(x,y){return x=x||1,y=y||1,x*y}
```
You can pass [compressor options](https://lisperator.net/uglifyjs/compress) to `uglify_optimize` to control the various uglify optimization techniques.
## JSHint: code analysis
JSHint will automatically detect errors and potential problems in JavaScript code. The `jshint` function is R will return a data frame where each row is a problem detected by the library (type, line and reason of error):
```r
code <- "var foo = 123"
jshint(code)
```
```
id raw code evidence line character scope reason
1 (error) Missing semicolon. W033 var foo = 123 1 14 (main) Missing semicolon.
```
JSHint has many [configuration options](https://jshint.com/docs/options/) to control which types of code propblems it will report on.