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JsChardet

Port of python's chardet (https://github.com/chardet/chardet).

License

LGPL

How To Use It

Node

npm install jschardet

var jschardet = require("jschardet")

// "àíàçã" in UTF-8
jschardet.detect("\xc3\xa0\xc3\xad\xc3\xa0\xc3\xa7\xc3\xa3")
// { encoding: "UTF-8", confidence: 0.9690625 }

// "次常用國字標準字體表" in Big5
jschardet.detect("\xa6\xb8\xb1\x60\xa5\xce\xb0\xea\xa6\x72\xbc\xd0\xb7\xc7\xa6\x72\xc5\xe9\xaa\xed")
// { encoding: "Big5", confidence: 0.99 }

// Martin Kühl
// jschardet.detectAll("\x3c\x73\x74\x72\x69\x6e\x67\x3e\x4d\x61\x72\x74\x69\x6e\x20\x4b\xfc\x68\x6c\x3c\x2f\x73\x74\x72\x69\x6e\x67\x3e")
// [
//   {encoding: "windows-1252", confidence: 0.95},
//   {encoding: "ISO-8859-2", confidence: 0.8796300205763055},
//   {encoding: "SHIFT_JIS", confidence: 0.01}
// ]

Browser

Copy and include jschardet.min.js in your web page.

This library is also available in cdnjs at https://cdnjs.cloudflare.com/ajax/libs/jschardet/1.4.1/jschardet.min.js

Options

// See all information related to the confidence levels of each encoding.
// This is useful to see why you're not getting the expected encoding.
jschardet.enableDebug();

// Default minimum accepted confidence level is 0.20 but sometimes this is not
// enough, specially when dealing with files mostly with numbers.
// To change this to 0 to always get something or any other value that can
// work for you.
jschardet.detect(str, { minimumThreshold: 0 });

// Lock down which encodings to detect, can be useful in situations jschardet
// is giving a higher probability to encodings that you never use.
jschardet.detect(str, { detectEncodings: ["UTF-8", "windows-1252"] });

Supported Charsets

Technical Information

I haven't been able to create tests to correctly detect:

Development

Use npm run dist to update the distribution files. They're available at https://github.com/aadsm/jschardet/tree/master/dist.

Authors

Ported from python to JavaScript by António Afonso (https://github.com/aadsm/jschardet)

Transformed into an npm package by Markus Ast (https://github.com/brainafk)