[python-package] Replace bare Any with specific types in sklearn helpers#12111
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PavelGuzenfeld wants to merge 2 commits intodmlc:masterfrom
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[python-package] Replace bare Any with specific types in sklearn helpers#12111PavelGuzenfeld wants to merge 2 commits intodmlc:masterfrom
PavelGuzenfeld wants to merge 2 commits intodmlc:masterfrom
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Replace generic Any annotations with ArrayLike for data parameters and DMatrix for return types in internal helper functions: - _wrap_evaluation_matrices: 13 params Any -> ArrayLike, return Tuple[Any, ...] -> Tuple[DMatrix, List[Tuple[DMatrix, str]]] - pick_ref_categories: X param Any -> ArrayLike - invalid_type: m param Any -> object Remaining Any usages (**kwargs, Dict[str, Any] for params) are intentional as they represent genuinely heterogeneous data. Follow-up to dmlc#6496.
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trivialfis
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| return wrapped | ||
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| def invalid_type(m: Any) -> None: | ||
| def invalid_type(m: object) -> None: |
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object is the proper top type in Python — it means "accepts anything" while keeping type safety. Any disables type checking entirely (both co- and contra-variant), so mypy silently skips any misuse. Since invalid_type only calls type(m), which works on every object, object is the accurate annotation.
That said, this is a minor stylistic point — happy to revert if you prefer keeping Any here.
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Summary
Replace generic
Anyannotations with more descriptive types in sklearn.py internal helper functions. Follow-up to #6496.Changes:
_wrap_evaluation_matricesX,yAnyArrayLike_wrap_evaluation_matricesgroup,qid,sample_weight,base_marginOptional[Any]Optional[ArrayLike]_wrap_evaluation_matriceseval_setOptional[Sequence[Tuple[Any, Any]]]Optional[Sequence[Tuple[ArrayLike, ArrayLike]]]_wrap_evaluation_matrices*_eval_set,eval_group,eval_qidOptional[Sequence[Any]]Optional[Sequence[ArrayLike]]pick_ref_categoriesXAnyArrayLikeinvalid_typemAnyobjectThe return type of
_wrap_evaluation_matricesstaysTuple[Any, ...]since it is called with bothDMatrixandDaskDMatrix(which does not extendDMatrix).Remaining
Anyusages (**kwargs: Any,Dict[str, Any]for params) are intentional — they represent genuinely heterogeneous data or standard sklearn patterns.Test plan