Bump chardet from 5.2.0 to 7.4.0.post1

[dependabot]

Bumps chardet from 5.2.0 to 7.4.0.post1.

Release notes

Sourced from chardet's releases.

chardet 7.4.0 brings accuracy up to 99.3% (from 98.6% in 7.3.0) and significantly faster cold start thanks to a new dense model format.

What's New

Performance:

• New dense zlib-compressed model format (v2) drops cold start (import + first detect) from ~75ms to ~13ms with mypyc

Accuracy (98.6% → 99.3%):

• Eliminated train/test data overlap via content fingerprinting
• Added MADLAD-400 and Wikipedia as supplemental training sources
• Improved non-ASCII bigram scoring: high-byte bigrams are now preserved during training and weighted by per-bigram IDF
• Encoding-aware substitution filtering (substitutions only apply for characters the target encoding can't represent)
• Increased training samples from 15K to 25K per language/encoding pair

Bug fixes:

• Added dedicated structural analyzers for CP932, CP949, and Big5-HKSCS (these were previously sharing their base encoding's byte-range analyzer, missing extended ranges)

Metrics

	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%

Full changelog: https://chardet.readthedocs.io/en/latest/changelog.html

7.3.0

License

• 0BSD license — the project license has been changed from MIT to 0BSD, a maximally permissive license with no attribution requirement. All prior 7.x releases should also be considered 0BSD licensed as of this release.

Features

• Added mime_type field to detection results — identifies file types for both binary (via magic number matching) and text content. Returned in all detect(), detect_all(), and UniversalDetector results. (#350)
• New pipeline/magic.py module detects 40+ binary file formats including images, audio/video, archives, documents, executables, and fonts. ZIP-based formats (XLSX, DOCX, JAR, APK, EPUB, wheel, OpenDocument) are distinguished by entry filenames. (#350)

Bug Fixes

• Fixed incorrect equivalence between UTF-16-LE and UTF-16-BE in accuracy testing — these are distinct encodings with different byte order, not interchangeable

Performance

• Added 4 new modules to mypyc compilation (orchestrator, confusion, magic, ascii), bringing the total to 11 compiled modules
• Capped statistical scoring at 16 KB — bigram models converge quickly, so large files no longer score the full 200 KB. Worst-case detection time dropped from 62ms to 26ms with no accuracy loss.
• Replaced dataclasses.replace() with direct DetectionResult construction on hot paths, eliminating ~354k function calls per full test suite run

Build

... (truncated)

Changelog

Sourced from chardet's changelog.

Changelog

.. note::

Entries marked "via Claude" were developed with Claude Code <https://claude.ai/code>_. Dan directed the design, reviewed all output, and takes responsibility for the result. Unmarked entries by Dan were written without AI assistance.

7.4.0 (2026-03-26)

Performance:

• Switched to dense zlib-compressed model format (v2): models are now stored as contiguous memoryview slices of a single decompressed blob, eliminating per-model struct.unpack overhead. Cold start (import + first detect) dropped from ~75ms to ~13ms with mypyc. (Dan Blanchard <https://github.com/dan-blanchard>_ via Claude, [#354](https://github.com/chardet/chardet/issues/354) <https://github.com/chardet/chardet/pull/354>_)

Accuracy:

• Accuracy improved from 98.6% to 99.3% (2499/2517 files) through a combination of training and scoring improvements:

  • Eliminated train/test data overlap by content-fingerprinting test suite articles and excluding them from training data ([#351](https://github.com/chardet/chardet/issues/351) <https://github.com/chardet/chardet/pull/351>_)
  • Added MADLAD-400 and Wikipedia as supplemental training sources to fill gaps left by exclusion filtering ([#351](https://github.com/chardet/chardet/issues/351) <https://github.com/chardet/chardet/pull/351>_)
  • Improved non-ASCII bigram scoring: high-byte bigrams are now preserved during training (instead of being crushed by global normalization), and weighted by per-bigram IDF so encoding-specific byte patterns contribute proportionally to how discriminative they are ([#352](https://github.com/chardet/chardet/issues/352) <https://github.com/chardet/chardet/pull/352>_)
  • Added encoding-aware substitution filtering: character substitutions during training now only apply for characters the target encoding cannot represent
  • Increased training samples from 15K to 25K per language/encoding pair (Dan Blanchard <https://github.com/dan-blanchard>_ via Claude)

Bug Fixes:

• Added dedicated structural analyzers for CP932, CP949, and Big5-HKSCS: these superset encodings previously shared their base encoding's byte-range analyzer, missing extended ranges unique to each superset

... (truncated)

Commits

• 15b2d8a fix: use separate=true on Windows only via pre-cibuildwheel patching
• 26a1b25 fix: also drop orchestrator.py from mypyc (still over MSVC limit)
• 26d425c fix: drop magic.py and ascii.py from mypyc to fix Windows C2026
• 2e9542a fix: use multi_file=true for mypyc to fix Windows C2026
• 0e33686 fix: use separate=true (not multi_file) for mypyc compilation
• 22f29d2 fix: enable mypyc multi_file unconditionally to fix Windows C2026
• 326adde fix: enable mypyc multi_file on Windows to avoid MSVC C2026
• 582c664 docs: set 7.4.0 release date to 2026-03-26
• a515745 docs: update version references from 7.3.1 to 7.4.0
• 870988d docs: add 7.4.0 changelog and "via Claude" attribution markers
• Additional commits viewable in compare view

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[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 54.72%. Comparing base (b98e44b) to head (59e0512).
⚠️ Report is 1 commits behind head on main.
✅ All tests successful. No failed tests found.

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #1659      +/-   ##
==========================================
- Coverage   54.74%   54.72%   -0.02%     
==========================================
  Files         335      335              
  Lines       27400    27400              
==========================================
- Hits        15000    14996       -4     
- Misses      12400    12404       +4     

Flag	Coverage Δ
functionaltests	0.00% <ø> (ø)
unittests	54.72% <ø> (-0.02%)	⬇️

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[dependabot]

Superseded by #1662.