chardet

Universal character encoding detector.

chardet 7 is a ground-up, 0BSD-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?

99.3% accuracy on 2,517 test files. 47x faster than chardet 6.0.0 and 1.5x faster than charset-normalizer 3.4.6. Language detection for every result. MIME type detection for binary files. 0BSD licensed.

	chardet 7.4.0 (mypyc)	chardet 6.0.0	charset-normalizer 3.4.6
Accuracy (2,517 files)	99.3%	88.2%	85.4%
Speed	551 files/s	12 files/s	376 files/s
Language detection	95.7%	40.0%	59.2%
Peak memory	52.9 MiB	29.5 MiB	78.8 MiB
Streaming detection	yes	yes	no
Encoding era filtering	yes	no	no
Encoding filters	yes	no	yes
MIME type detection	yes	no	no
Supported encodings	99	84	99
License	0BSD	LGPL	MIT

Installation

pip install chardet

Quick Start

import chardet

chardet.detect(b"Hello, world!")
# {'encoding': 'ascii', 'confidence': 1.0, 'language': 'en', 'mime_type': 'text/plain'}

# 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', 'mime_type': 'text/plain'}

# 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-JP', 'confidence': 1.0, 'language': 'ja', 'mime_type': 'text/plain'}

# 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[:4]:
    print(r["encoding"], round(r["confidence"], 2))
# Windows-1252 0.44
# iso8859-15 0.44
# ISO-8859-1 0.44
# MacRoman 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
# MacCyrillic 0.47
# KZ1048 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

Encoding Filters

Restrict detection to specific encodings, or exclude encodings you don't want:

# Only consider UTF-8 and Windows-1252
chardet.detect(data, include_encodings=["utf-8", "windows-1252"])

# Consider everything except EBCDIC
chardet.detect(data, exclude_encodings=["cp037", "cp500"])

CLI

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

chardetect --minimal somefile.txt
# utf-8

# Include detected language
chardetect -l somefile.txt
# somefile.txt: utf-8 en (English) with confidence 0.99

# Only consider specific encodings
chardetect -i utf-8,windows-1252 somefile.txt
# somefile.txt: utf-8 with confidence 0.99

# Pipe from stdin
cat somefile.txt | chardetect
# stdin: utf-8 with confidence 0.99

What's New in chardet 7?

• 0BSD license (previous versions were LGPL)
• Ground-up rewrite: 13-stage detection pipeline using BOM detection, magic number identification, structural probing, byte validity filtering, and bigram statistical models
• 47x faster than chardet 6.0.0 with mypyc, 1.5x faster than charset-normalizer 3.4.6
• 99.3% accuracy: +11.1pp vs chardet 6.0.0, +13.9pp vs charset-normalizer 3.4.6
• Language detection: 95.7% accuracy across 49 languages, returned with every result
• MIME type detection: identifies 40+ binary file formats (images, audio/video, archives, documents, executables, fonts) via magic number signatures, plus text/html, text/xml, and text/x-python for markup
• Encoding filters: include_encodings and exclude_encodings parameters to restrict or exclude specific encodings from the candidate set
• 99 encodings: full coverage including EBCDIC, Mac, DOS, and Baltic/Central European families
• Optional mypyc compilation: 1.67x 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

0BSD