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[python-package] add type hints on feature_name and categorical_feature in sklearn interface #5747

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merged 2 commits into from
Feb 27, 2023
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[python-package] add type hints on feature_name and categorical_feature in sklearn interface #5747

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[python-package] add type hints on feature_name and categorical_featu…
jameslamb Feb 27, 2023
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jameslamb Feb 27, 2023
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19 changes: 10 additions & 9 deletions python-package/lightgbm/sklearn.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,8 @@
import numpy as np

from .basic import (Booster, Dataset, LightGBMError, _choose_param_value, _ConfigAliases, _LGBM_BoosterBestScoreType,
_LGBM_EvalFunctionResultType, _log_warning)
_LGBM_CategoricalFeatureConfiguration, _LGBM_EvalFunctionResultType, _LGBM_FeatureNameConfiguration,
_log_warning)
from .callback import _EvalResultDict, record_evaluation
from .compat import (SKLEARN_INSTALLED, LGBMNotFittedError, _LGBMAssertAllFinite, _LGBMCheckArray,
_LGBMCheckClassificationTargets, _LGBMCheckSampleWeight, _LGBMCheckXY, _LGBMClassifierBase,
Expand Down Expand Up @@ -708,8 +709,8 @@ def fit(
eval_init_score=None,
eval_group=None,
eval_metric: Optional[_LGBM_ScikitEvalMetricType] = None,
feature_name='auto',
categorical_feature='auto',
feature_name: _LGBM_FeatureNameConfiguration = 'auto',
categorical_feature: _LGBM_CategoricalFeatureConfiguration = 'auto',
callbacks=None,
init_model: Optional[Union[str, Path, Booster, "LGBMModel"]] = None
):
Expand Down Expand Up @@ -999,8 +1000,8 @@ def fit( # type: ignore[override]
eval_sample_weight=None,
eval_init_score=None,
eval_metric: Optional[_LGBM_ScikitEvalMetricType] = None,
feature_name='auto',
categorical_feature='auto',
feature_name: _LGBM_FeatureNameConfiguration = 'auto',
categorical_feature: _LGBM_CategoricalFeatureConfiguration = 'auto',
callbacks=None,
init_model: Optional[Union[str, Path, Booster, LGBMModel]] = None
):
Expand Down Expand Up @@ -1046,8 +1047,8 @@ def fit( # type: ignore[override]
eval_class_weight=None,
eval_init_score=None,
eval_metric: Optional[_LGBM_ScikitEvalMetricType] = None,
feature_name='auto',
categorical_feature='auto',
feature_name: _LGBM_FeatureNameConfiguration = 'auto',
categorical_feature: _LGBM_CategoricalFeatureConfiguration = 'auto',
callbacks=None,
init_model: Optional[Union[str, Path, Booster, LGBMModel]] = None
):
Expand Down Expand Up @@ -1216,8 +1217,8 @@ def fit( # type: ignore[override]
eval_group=None,
eval_metric: Optional[_LGBM_ScikitEvalMetricType] = None,
eval_at: Union[List[int], Tuple[int, ...]] = (1, 2, 3, 4, 5),
feature_name='auto',
categorical_feature='auto',
feature_name: _LGBM_FeatureNameConfiguration = 'auto',
categorical_feature: _LGBM_CategoricalFeatureConfiguration = 'auto',
callbacks=None,
init_model: Optional[Union[str, Path, Booster, LGBMModel]] = None
):
Expand Down