refactor creation base for narwhals compatibility - #990
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…andas imports BaseCreation, BaseNumericalTransformer, and mixins.py (TransformXyMixin, FitFromDictMixin, GetFeatureNamesOutMixin) are used by every transformer in the creation module, so their remaining pandas-only code blocked a polars-only install regardless of which transformer was migrated. Adds pandas fast paths (benchmarked ~2-11x) alongside narwhals-generic branches, replaces y.loc[X.index] row alignment in TransformXyMixin with a narwhals with_row_index()-based mechanism for non-pandas backends, and adds test_base_creation.py plus polars coverage for transform_x_y.
solegalli
commented
Aug 24, 2026
solegalli
commented
Aug 24, 2026
…process rules to AGENTS.md The 48 failures here were pre-existing (unrelated to the to_list() fix, confirmed identical before/after): check_X no longer accepts raw numpy arrays, and most of this file's tests fit() on df_vartypes.to_numpy() or feed a raw-array-outputting sklearn transformer upstream. Fixes: - array-input tests converted to set feature_names_in_/n_features_in_ directly, since that's the only way left to reach the mixin's x0/x1/... naming branch (fit() rejects arrays outright now). - SimpleImputer/PolynomialFeatures steps get .set_output(transform="pandas") so they hand a dataframe to the next pipeline step instead of an array - this is also the fix any real user chaining sklearn + feature-engine transformers in a Pipeline now needs. - pure Mock-only tests (no sklearn transformer involved) parametrized over pandas and polars. Also adds two AGENTS.md rules: run a changed function/class's tests and resolve any failures, and keep user-guide docs in sync with new transformer functionality.
This branch handled feature_names_in_ == ["x0", "x1", ...], the naming sklearn gives an estimator fit on a raw array. check_X no longer accepts arrays (dataframe-only input, per AGENTS.md), so fit() can never produce that pattern anymore - the branch, its indices=True path in _remove_feature_names, and get_support(indices=True) were all unreachable. It was also a latent correctness gap: a dataframe with columns genuinely named x0..xn would have hit this branch and skipped the usual input_features-must-match-feature_names_in_ validation. Verified via git history (#519, 2022) this was built for the old array-accepting check_X; confirmed no other code in the library still generates x0/x1/... names. Removed the branch, its now-single-path _remove_feature_names, and the tests that existed only to reach it - replaced by tests/test_base_transformers/test_get_feature_names_out_mixin.py's remaining pandas+polars dataframe coverage, which already exercises the same validation/renaming logic through the one reachable path.
solegalli
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Aug 30, 2026
* Migrate creation/mixins shared base classes to narwhals, remove all pandas imports BaseCreation, BaseNumericalTransformer, and mixins.py (TransformXyMixin, FitFromDictMixin, GetFeatureNamesOutMixin) are used by every transformer in the creation module, so their remaining pandas-only code blocked a polars-only install regardless of which transformer was migrated. Adds pandas fast paths (benchmarked ~2-11x) alongside narwhals-generic branches, replaces y.loc[X.index] row alignment in TransformXyMixin with a narwhals with_row_index()-based mechanism for non-pandas backends, and adds test_base_creation.py plus polars coverage for transform_x_y. * Apply suggestion from @FBruzzesi * Fix test_get_feature_names_out_mixin.py after to_list() removal, add process rules to AGENTS.md The 48 failures here were pre-existing (unrelated to the to_list() fix, confirmed identical before/after): check_X no longer accepts raw numpy arrays, and most of this file's tests fit() on df_vartypes.to_numpy() or feed a raw-array-outputting sklearn transformer upstream. Fixes: - array-input tests converted to set feature_names_in_/n_features_in_ directly, since that's the only way left to reach the mixin's x0/x1/... naming branch (fit() rejects arrays outright now). - SimpleImputer/PolynomialFeatures steps get .set_output(transform="pandas") so they hand a dataframe to the next pipeline step instead of an array - this is also the fix any real user chaining sklearn + feature-engine transformers in a Pipeline now needs. - pure Mock-only tests (no sklearn transformer involved) parametrized over pandas and polars. Also adds two AGENTS.md rules: run a changed function/class's tests and resolve any failures, and keep user-guide docs in sync with new transformer functionality. * Remove dead array-input branch from GetFeatureNamesOutMixin This branch handled feature_names_in_ == ["x0", "x1", ...], the naming sklearn gives an estimator fit on a raw array. check_X no longer accepts arrays (dataframe-only input, per AGENTS.md), so fit() can never produce that pattern anymore - the branch, its indices=True path in _remove_feature_names, and get_support(indices=True) were all unreachable. It was also a latent correctness gap: a dataframe with columns genuinely named x0..xn would have hit this branch and skipped the usual input_features-must-match-feature_names_in_ validation. Verified via git history (#519, 2022) this was built for the old array-accepting check_X; confirmed no other code in the library still generates x0/x1/... names. Removed the branch, its now-single-path _remove_feature_names, and the tests that existed only to reach it - replaced by tests/test_base_transformers/test_get_feature_names_out_mixin.py's remaining pandas+polars dataframe coverage, which already exercises the same validation/renaming logic through the one reachable path.
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