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release-0.35.3 - #1204
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release-0.35.3#1204
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Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
fixes #1202) Such an array carries no information beyond its shape, so broadcast_with now matches its axes positionally instead of failing to match the target axes. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Values like Excel ranges produced a misleading "Range dtype" unsafe cast warning. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Upper bounds only: older versions which work stay allowed. Update them on each release (see hardcoded_version). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
numpy 2.4.5 undid the deprecation for the np.dtype() signature used by old pickles (numpy PR #31177), so it no longer warns when loading old H5 files. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
The pydantic 2 only imports made `import larray` fail. Older pydantic versions are now treated like a missing pydantic. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
…er type The default integer type is int32 with numpy < 2 on Windows. Declaring the CheckedSession test array as int64 also avoids warnings when loading it from CSV or Excel files, which always produce int64. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
larray fails to import with numpy < 1.25 (numpy.exceptions) and the test suite fails with pandas 1.5. numpy 1.25.0 and pandas 2.0.3 (the oldest versions available for Python 3.11 in conda defaults after those) pass the test suite. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
The dtype and memory lines depend on the platform default integer type. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
….35.3 changelog Most users only care about the other sections. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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0.35.3