pytimetk 2.2.0

What's New

Polars .tk Accessor for LazyFrames: Added a .tk accessor for pl.LazyFrame objects, enabling direct access to pytimetk helpers (e.g., df.lazy().tk.augment_rolling(...)) with performance parity to pandas and Polars DataFrame paths. This enhances support for lazy evaluation pipelines, improving efficiency for large datasets.
GPU Installation Improvements: Updated GPU support with cudf-cu12 dependency for Python 3.10+ on Linux (x86_64 or aarch64), replacing the generic cudf dependency. This ensures better compatibility and performance for GPU-accelerated workflows.
Polars LazyFrame Compatibility: Extended Polars support to include LazyFrame checks in utility functions (e.g., check_date_column, check_value_column), ensuring seamless integration with lazy evaluation pipelines.

Refactored GroupBy Handling: Replaced direct .obj access on pandas GroupBy objects with resolve_pandas_groupby_frame across the codebase. This improves compatibility with accelerated backends like cudf.pandas, ensuring robust DataFrame extraction even when proxies are used.
Memory Optimization: Enhanced reduce_memory_usage to handle GroupBy objects more reliably by using resolve_pandas_groupby_frame and attempting categorical conversion only when safe, improving memory efficiency for large datasets.
Documentation Updates: Improved GPU acceleration guide (production/02_gpu_acceleration.html) with streamlined examples and updated changelog (changelog-news.html) to reflect new features and fixes.

Sorting Issue in GPU Workflows: Fixed a sorting issue in GPU-compatible operations to ensure consistent ordering in Polars and pandas pipelines.
Documentation Corrections: Addressed inconsistencies in the GPU guide documentation for clarity and accuracy.

The cudf dependency has been replaced with cudf-cu12 for GPU support, requiring users to update their installation commands to pip install pytimetk[gpu_cu12] --extra-index-url=https://pypi.nvidia.com for Python 3.10+ on supported Linux platforms.

To install pytimetk 2.2.0 with GPU support:

pip install pytimetk[gpu_cu12] --extra-index-url=https://pypi.nvidia.com
pip install "polars[gpu]" --extra-index-url=https://pypi.nvidia.com

Full Changelog: https://github.com/business-science/pytimetk/compare/v2.1.0...v2.2.0