Fix Python 3.12 compatibility by upgrading setuptools requirement#7
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nicklecoder wants to merge 3 commits intofastdatascience:mainfrom
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Fix Python 3.12 compatibility by upgrading setuptools requirement#7nicklecoder wants to merge 3 commits intofastdatascience:mainfrom
nicklecoder wants to merge 3 commits intofastdatascience:mainfrom
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Fixes fastdatascience#5 This resolves the 'AttributeError: module pkgutil has no attribute ImpImporter' error that occurs when installing faststylometry on Python 3.12+. Root cause: Python 3.12 removed the deprecated pkgutil.ImpImporter class, but setuptools versions < 68.0.0 still reference it during the build process. Changes: - Updated setuptools requirement from >=46.4.0 to >=68.0.0 - Removed twine from build-system requires (only needed for publishing) This eliminates the need for the numpy downgrade workaround previously documented in the README. Tested successfully on Python 3.12.3 with pip install. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
setuptools 66.1.0 specifically fixed the pkgutil.ImpImporter issue in #3685. Using the earliest compatible version provides better backwards compatibility.
While twine is not strictly necessary for building, removing it is unrelated to the Python 3.12 compatibility fix. Keeping the PR focused on only the setuptools version change.
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Summary
Fixes #5
This PR resolves the
AttributeError: module 'pkgutil' has no attribute 'ImpImporter'error that occurs when installing faststylometry on Python 3.12+.Root Cause
Python 3.12 removed the deprecated
pkgutil.ImpImporterclass. The previous setuptools requirement (>=46.4.0) allowed versions that still reference this removed class during the build process, causing installation failures.Changes
>=46.4.0to>=66.1.0inpyproject.tomlWhy 66.1.0?
This is the earliest setuptools version that fixes the
pkgutil.ImpImporterissue (setuptools#3685). Using the minimum compatible version provides better backwards compatibility.Impact
This eliminates the need for the numpy downgrade workaround currently documented in the README (lines 44-64).
Testing
🤖 Generated with Claude Code