chardet 7.0.0

Universal character encoding detector

chardet

Universal character encoding detector.

chardet 7.0 is a ground-up, MIT-licensed rewrite of chardet. Same package name, same public API — drop-in replacement for chardet 5.x/6.x, just much faster and more accurate. Python 3.10+, zero runtime dependencies, works on PyPy.

Why chardet 7.0?

96.8% accuracy on 2,179 test files. 41x faster than chardet 6.0.0 and 7.5x faster than charset-normalizer. Language detection for every result. MIT licensed.

	chardet 7.0 (mypyc)	chardet 7.0 (pure)	chardet 6.0.0	charset-normalizer
Accuracy (2,179 files)	96.8%	96.8%	94.5%	89.1%
Speed	494 files/s	336 files/s	12 files/s	66 files/s
Language detection	90.5%	90.5%	47.0%	--
Peak memory	22.5 MiB	22.5 MiB	16.4 MiB	102.2 MiB
Streaming detection	yes	yes	yes	no
Encoding era filtering	yes	yes	no	no
Supported encodings	99	99	84	99
License	MIT	MIT	LGPL	MIT

Installation

pip install chardet

Quick Start

import chardet

# Plain ASCII is reported as its superset Windows-1252 by default,
# keeping with WHATWG guidelines for encoding detection.
chardet.detect(b"Hello, world!")
# {'encoding': 'Windows-1252', 'confidence': 1.0, 'language': 'en'}

# UTF-8 with typographic punctuation
chardet.detect("It\u2019s a lovely day \u2014 let\u2019s grab coffee.".encode("utf-8"))
# {'encoding': 'utf-8', 'confidence': 0.99, 'language': 'es'}

# Japanese EUC-JP
chardet.detect("これは日本語のテストです。文字コードの検出を行います。".encode("euc-jp"))
# {'encoding': 'euc-jis-2004', 'confidence': 1.0, 'language': 'ja'}

# Get all candidate encodings ranked by confidence
text = "Le café est une boisson très populaire en France et dans le monde entier."
results = chardet.detect_all(text.encode("windows-1252"))
for r in results:
    print(r["encoding"], r["confidence"])
# windows-1252 0.44
# iso-8859-15 0.44
# mac-roman 0.42
# cp858 0.42

Streaming Detection

For large files or network streams, use UniversalDetector to feed data incrementally:

from chardet import UniversalDetector

detector = UniversalDetector()
with open("unknown.txt", "rb") as f:
    for line in f:
        detector.feed(line)
        if detector.done:
            break
result = detector.close()
print(result)

Encoding Era Filtering

Restrict detection to specific encoding eras to reduce false positives:

from chardet import detect_all
from chardet.enums import EncodingEra

data = "Москва является столицей Российской Федерации и крупнейшим городом страны.".encode("windows-1251")

# All encoding eras are considered by default — 4 candidates across eras
for r in detect_all(data):
    print(r["encoding"], round(r["confidence"], 2))
# windows-1251 0.5
# mac-cyrillic 0.47
# kz-1048 0.22
# ptcp154 0.22

# Restrict to modern web encodings — 1 confident result
for r in detect_all(data, encoding_era=EncodingEra.MODERN_WEB):
    print(r["encoding"], round(r["confidence"], 2))
# windows-1251 0.5

CLI

chardetect somefile.txt
# somefile.txt: utf-8 with confidence 0.99

chardetect --minimal somefile.txt
# utf-8

# Pipe from stdin
cat somefile.txt | chardetect

What's New in 7.0

• MIT license (previous versions were LGPL)
• Ground-up rewrite — 12-stage detection pipeline using BOM detection, structural probing, byte validity filtering, and bigram statistical models
• 41x faster than chardet 6.0.0 with mypyc (28x pure Python), 7.5x faster than charset-normalizer
• 96.8% accuracy — +2.3pp vs chardet 6.0.0, +7.7pp vs charset-normalizer
• Language detection — 90.5% accuracy across 49 languages, returned with every result
• 99 encodings — full coverage including EBCDIC, Mac, DOS, and Baltic/Central European families
• EncodingEra filtering — scope detection to modern web encodings, legacy ISO/Mac/DOS, mainframe, or all
• Optional mypyc compilation — 1.49x additional speedup on CPython
• Thread-safe — detect() and detect_all() are safe to call concurrently; scales on free-threaded Python
• Same API — detect(), detect_all(), UniversalDetector, and the chardetect CLI all work as before

Documentation

Full documentation is available at chardet.readthedocs.io.

License

MIT