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How to use test_lazy_dataframe_scalar_false_check method in pandera

Best Python code snippet using pandera_python

test_schemas.py

Source:test_schemas.py

...1079            pd.DataFrame(index=pd.Index([1, 2, 3], name="index")),1080        ],1081    ],1082)1083def test_lazy_dataframe_scalar_false_check(1084    schema_cls: Type[Union[DataFrameSchema, SeriesSchema, Column, Index]],1085    data: Union[pd.DataFrame, pd.Series, pd.Index],1086) -> None:1087    """Lazy validation handles checks returning scalar False values."""1088    # define a check that always returns a scalare False value1089    check = Check(1090        check_fn=lambda _: False, element_wise=False, error="failing check"1091    )1092    schema = schema_cls(checks=check)1093    with pytest.raises(errors.SchemaErrors):1094        schema(data, lazy=True)1095def test_lazy_dataframe_unique() -> None:1096    """Tests the lazy evaluation of the unique keyword"""1097    data = pd.DataFrame.from_dict(...

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