chore(deps): bump polars from 0.20.16 to 0.20.24

[dependabot]

Bumps polars from 0.20.16 to 0.20.24.

Release notes

Sourced from polars's releases.

Python Polars 0.20.24

🏆 Highlights

• Support pytorch Tensor and Dataset export with new to_torch DataFrame/Series method (#15931)

🚀 Performance improvements

• Don't traverse deep datasets that we repr as union in CSE (#16096)
• Ensure better chunk sizes (#16071)

✨ Enhancements

• split out rolling_*(..., by='foo') into rolling_*_by('foo', ...) (#16059)
• add date pattern dd.mm.YYYY (#16045)
• split Expr.top_k and Expr.top_k_by into separate functions (#16041)
• Support non-coalescing joins in default engine (#16036)
• Support pytorch Tensor and Dataset export with new to_torch DataFrame/Series method (#15931)
• Minor DB type inference updates (#16030)
• Move diagonal & horizontal concat schema resolving to IR phase (#16034)
• raise more informative error messages in rolling_* aggregations instead of panicking (#15979)
• Convert concat during IR conversion (#16016)
• Improve dynamic supertypes (#16009)
• Additional uint datatype support for the SQL interface (#15993)
• Add post-optimization callback (#15972)
• Support Decimal read from IPC (#15965)
• Expose plan and expression nodes through NodeTraverser to Python (#15776)
• Add typed collection from par iterators (#15961)
• Add by argument for Expr.top_k and Expr.bottom_k (#15468)

🐞 Bug fixes

• Respect user passed 'reader_schema' in 'scan_csv' (#16080)
• Lazy csv + projection; respect null values arg (#16077)
• Materialize dtypes when converting to arrow (#16074)
• Fix casting decimal to decimal for high precision (#16049)
• Fix Series constructor failure for Array types for large integers (#16050)
• Fix printing max scale decimals (#16048)
• Decimal supertype for dyn int (#16046)
• Correctly handle large timedelta objects in Series constructor (#16043)
• Do not close connection just because we're not returning Arrow data in batches (#16031)
• properly handle nulls in DictionaryArray::iter_typed (#16013)
• Fix CSE case where upper plan has no projection (#16011)
• Crash/incorrect group_by/n_unique on categoricals created by (q)cut (#16006)
• converting from numpy datetime64 and overriding dtype with a different resolution was returning incorrect results (#15994)
• Ternary supertype dynamics (#15995)
• Fix PartialEq for DataType::Unknown (#15992)
• Finish adding typed_lit to help schema determination in SQL "extract" func (#15955)
• Fix dtype parameter in pandas_to_pyseries function (#15948)
• do not panic when comparing against categorical with incompatible dtype (#15857)
• Join validation for multiple keys (#15947)

... (truncated)

Commits

• 2970c57 python Polars 0.20.24 (#16089)
• c5489ac perf: Don't traverse deep datasets that we repr as union in CSE (#16096)
• 6ded6f0 ci: Bump sccache action (#16088)
• d1f3ef4 ci: Fix failures in test coverage workflow (#16083)
• dd6e2ee fix: Respect user passed 'reader_schema' in 'scan_csv' (#16080)
• 575e917 fix: Lazy csv + projection; respect null values arg (#16077)
• 3600b16 fix: Materialize dtypes when converting to arrow (#16074)
• 421db23 docs(python): Ensure consistent docstring warning in fill_nan methods (poin...
• 49265a6 ci(python): Update benchmarks/coverage jobs with "requirements-ci" (#16072)
• 4b63818 perf: Ensure better chunk sizes (#16071)
• Additional commits viewable in compare view

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[dependabot]

Superseded by #113.