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🌏 Truly Universal Encoding Detection in Python 🌎

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Truly Universal Encoding Detection in Python

Charamel is a pure Python universal character encoding library that supports all of Python character encodings. The library is based on machine learning and trained to handle more than 60 languages. All that with no external dependencies. Ain't it sweet? 🍭

Installation

$ pip install charamel

Features

  • 🌈 Powered by machine learning
  • 📦 No dependencies
  • ⚡ Faster than other pure Python libraries
  • 🐍 Supports all 98 Python encodings
  • 🌍 Works on 60+ languages
  • 🔎 97% accuracy

Usage

API is centered around Detector class, with detect method being responsible for basic encoding detection:

>>> from charamel import Detector
>>> detector = Detector()
>>> content = b'El espa\xf1ol o castellano del lat\xedn hablado'
>>> detector.detect(content)
<Encoding.ISO_8859_14: 'iso8859_14'>

This returns the most likely encoding that can decode the byte string. Let's try it out:

>>> from charamel import Encoding
>>> content.decode(Encoding.ISO_8859_14)
'El español o castellano del latín hablado'

To get multiple likely encodings along with confidences in range [0, 1], use probe method:

>>> detector.probe(content, top=3)
[(<Encoding.ISO_8859_14: 'iso8859_14'>, 0.9964286725192874),
 (<Encoding.CP_1258: 'cp1258'>, 0.9919203166700203),
 (<Encoding.ISO_8859_3: 'iso8859_3'>, 0.9915028923264849)]

Detector can be configured to use a subset of encodings. Less possible encodings lead to faster detection:

>>> detector = Detector(encodings=[Encoding.UTF_8, Encoding.BIG_5])

Another useful Detector parameter is min_confidence. Basically, this parameter regulates how conservative the Detector will be. Confidence for encodings that are returned by detect and probe methods must be greater that min_confidence:

>>> detector = Detector(min_confidence=0.5)

If no encoding confidences exceed min_confidence, detect will return None and probe will return an empty list.

Benchmark

Below is the comparison between Charamel and other available Python encoding detection libraries:

Detector Supported Encodings Sec / File (Mean) Sec / File (99%) Sec / File (Max) KB / Sec Accuracy Accuracy on Supported
Chardet v3.0.4 26 0.029259 0.416156 3.115 220 61% 97%
Cchardet v2.1.6 40 0.000383 0.003913 0.062855 16811 67% 79%
Charset-Normalizer v1.3.4 89 0.126674 0.502882 1.41848 51 77% 78%
Charamel v1.0.0 98 0.009053 0.04277 0.120667 712 97% 97%

How to run this benchmark (requires Python 3.6+):

$ git clone git@github.com:chomechome/charamel.git
$ cd charamel
$ pip install poetry>=1.0.5
$ make benchmark

It also produces a detailed breakdown for all represented encodings:

* - not officially support for detector

Encoding Total Chardet v3.0.4 Cchardet v2.1.6 Charset-Normalizer v1.3.4 Charamel v1.0.0
ascii 8 7 (88%) 8 (100%) 7 (88%) 8 (100%)
big5 33 33 (100%) 33 (100%) 32 (97%) 31 (94%)
big5hkscs 9 6 (67%) * 6 (67%) * 8 (89%) 9 (100%)
cp037 14 0 (0%) * 0 (0%) * 12 (86%) 14 (100%)
cp1006 4 4 (100%) * 4 (100%) * 4 (100%) * 4 (100%)
cp1026 14 0 (0%) * 0 (0%) * 10 (71%) 14 (100%)
cp1125 5 4 (80%) * 4 (80%) * 5 (100%) 5 (100%)
cp1140 14 0 (0%) * 0 (0%) * 12 (86%) 14 (100%)
cp1250 23 7 (30%) * 22 (96%) 11 (48%) 23 (100%)
cp1251 45 44 (98%) 45 (100%) 45 (100%) 45 (100%)
cp1252 36 36 (100%) 30 (83%) 18 (50%) 36 (100%)
cp1253 6 4 (67%) 6 (100%) 6 (100%) 6 (100%)
cp1254 16 15 (94%) * 13 (81%) * 12 (75%) 16 (100%)
cp1255 29 29 (100%) 29 (100%) 29 (100%) 29 (100%)
cp1256 8 6 (75%) * 7 (88%) 8 (100%) 8 (100%)
cp1257 13 7 (54%) * 10 (77%) 6 (46%) 13 (100%)
cp1258 15 14 (93%) * 12 (80%) * 12 (80%) 15 (100%)
cp273 14 0 (0%) * 0 (0%) * 7 (50%) 14 (100%)
cp424 4 0 (0%) * 0 (0%) * 4 (100%) 4 (100%)
cp437 11 4 (36%) * 4 (36%) * 9 (82%) 11 (100%)
cp500 14 0 (0%) * 0 (0%) * 7 (50%) 14 (100%)
cp720 6 4 (67%) * 4 (67%) * 6 (100%) * 6 (100%)
cp737 4 4 (100%) * 4 (100%) * 4 (100%) * 4 (100%)
cp775 11 4 (36%) * 4 (36%) * 8 (73%) 11 (100%)
cp850 14 4 (29%) * 4 (29%) * 11 (79%) 14 (100%)
cp852 14 4 (29%) * 12 (86%) 6 (43%) 14 (100%)
cp855 26 26 (100%) 26 (100%) 26 (100%) 26 (100%)
cp856 4 4 (100%) * 4 (100%) * 4 (100%) * 4 (100%)
cp857 14 4 (29%) * 4 (29%) * 11 (79%) 14 (100%)
cp858 14 4 (29%) * 4 (29%) * 11 (79%) 14 (100%)
cp860 7 4 (57%) * 4 (57%) * 6 (86%) 7 (100%)
cp861 9 4 (44%) * 4 (44%) * 8 (89%) 9 (100%)
cp862 4 4 (100%) * 4 (100%) * 4 (100%) 4 (100%)
cp863 7 4 (57%) * 4 (57%) * 6 (86%) 7 (100%)
cp864 4 4 (100%) * 4 (100%) * 4 (100%) 4 (100%)
cp865 12 4 (33%) * 4 (33%) * 10 (83%) 12 (100%)
cp866 23 23 (100%) 23 (100%) 23 (100%) 23 (100%)
cp869 4 4 (100%) * 4 (100%) * 4 (100%) 4 (100%)
cp874 8 6 (75%) * 7 (88%) * 8 (100%) * 8 (100%)
cp875 4 0 (0%) * 0 (0%) * 3 (75%) * 4 (100%)
cp932 11 11 (100%) 8 (73%) * 11 (100%) 9 (82%)
cp949 6 6 (100%) * 6 (100%) 6 (100%) 6 (100%)
cp950 6 6 (100%) * 6 (100%) * 6 (100%) 6 (100%)
euc_jis_2004 29 8 (28%) * 8 (28%) * 20 (69%) 29 (100%)
euc_jisx0213 29 8 (28%) * 8 (28%) * 20 (69%) 29 (100%)
euc_jp 56 39 (70%) 38 (68%) 53 (95%) 56 (100%)
euc_kr 38 38 (100%) 38 (100%) 37 (97%) 38 (100%)
gb18030 48 6 (12%) * 47 (98%) 33 (69%) 48 (100%)
gb2312 26 25 (96%) 24 (92%) * 23 (88%) 26 (100%)
gbk 10 5 (50%) * 9 (90%) * 9 (90%) 10 (100%)
hz 6 6 (100%) 6 (100%) 5 (83%) 6 (100%)
iso2022_jp 10 10 (100%) 10 (100%) 9 (90%) 10 (100%)
iso2022_jp_1 26 8 (31%) * 8 (31%) * 25 (96%) 26 (100%)
iso2022_jp_2 29 8 (28%) * 8 (28%) * 28 (97%) 29 (100%)
iso2022_jp_2004 21 8 (38%) * 8 (38%) * 20 (95%) 21 (100%)
iso2022_jp_3 21 8 (38%) * 8 (38%) * 20 (95%) 21 (100%)
iso2022_jp_ext 26 8 (31%) * 8 (31%) * 25 (96%) 26 (100%)
iso2022_kr 8 8 (100%) 8 (100%) 8 (100%) 8 (100%)
iso8859_10 14 9 (64%) * 13 (93%) 7 (50%) 14 (100%)
iso8859_11 9 6 (67%) * 8 (89%) * 9 (100%) 8 (89%)
iso8859_13 16 7 (44%) * 14 (88%) 6 (38%) 16 (100%)
iso8859_14 14 14 (100%) * 11 (79%) * 12 (86%) 14 (100%)
iso8859_15 18 14 (78%) * 14 (78%) 12 (67%) 18 (100%)
iso8859_16 13 8 (62%) * 11 (85%) 7 (54%) 13 (100%)
iso8859_2 28 7 (25%) * 27 (96%) 16 (57%) 28 (100%)
iso8859_3 13 10 (77%) * 10 (77%) 9 (69%) 13 (100%)
iso8859_4 15 9 (60%) * 14 (93%) 7 (47%) 15 (100%)
iso8859_5 39 39 (100%) 39 (100%) 39 (100%) 39 (100%)
iso8859_6 6 4 (67%) * 6 (100%) 6 (100%) 6 (100%)
iso8859_7 17 16 (94%) 17 (100%) 17 (100%) 17 (100%)
iso8859_8 5 5 (100%) 5 (100%) 4 (80%) 5 (100%)
iso8859_9 18 14 (78%) * 15 (83%) 13 (72%) 18 (100%)
johab 5 4 (80%) * 4 (80%) * 5 (100%) 5 (100%)
koi8_r 26 26 (100%) 26 (100%) 26 (100%) 26 (100%)
koi8_t 4 4 (100%) * 4 (100%) * 4 (100%) * 4 (100%)
koi8_u 5 4 (80%) * 4 (80%) * 4 (80%) * 5 (100%)
kz1048 5 4 (80%) * 4 (80%) * 5 (100%) 5 (100%)
latin_1 29 29 (100%) 26 (90%) 24 (83%) 29 (100%)
mac_cyrillic 25 25 (100%) 25 (100%) 23 (92%) 25 (100%)
mac_greek 7 4 (57%) * 4 (57%) * 6 (86%) 7 (100%)
mac_iceland 15 4 (27%) * 4 (27%) * 9 (60%) 15 (100%)
mac_latin2 16 4 (25%) * 11 (69%) * 6 (38%) 16 (100%)
mac_roman 15 4 (27%) * 4 (27%) * 9 (60%) 15 (100%)
mac_turkish 15 4 (27%) * 4 (27%) * 9 (60%) 15 (100%)
ptcp154 5 4 (80%) * 4 (80%) * 5 (100%) 5 (100%)
shift_jis 40 40 (100%) 40 (100%) 38 (95%) 40 (100%)
shift_jis_2004 21 8 (38%) * 8 (38%) * 15 (71%) 21 (100%)
shift_jisx0213 21 8 (38%) * 8 (38%) * 15 (71%) 21 (100%)
tis_620 13 12 (92%) 12 (92%) * 13 (100%) 13 (100%)
utf_16 40 40 (100%) 40 (100%) * 33 (82%) 40 (100%)
utf_16_be 42 0 (0%) * 0 (0%) 35 (83%) 30 (71%)
utf_16_le 43 0 (0%) * 0 (0%) 35 (81%) 37 (86%)
utf_32 42 42 (100%) 42 (100%) * 22 (52%) 41 (98%)
utf_32_be 41 0 (0%) * 0 (0%) 20 (49%) 27 (66%)
utf_32_le 40 0 (0%) * 0 (0%) 20 (50%) 28 (70%)
utf_7 40 4 (10%) * 4 (10%) * 20 (50%) 39 (98%)
utf_8 101 100 (99%) 100 (99%) 78 (77%) 101 (100%)
utf_8_sig 42 42 (100%) * 42 (100%) * 0 (0%) * 42 (100%)

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