How to use function_check_io_invalid method in pandera

Best Python code snippet using pandera_python

test_schemas_on_koalas.py

Source:test_schemas_on_koalas.py

...456    def function_check_io(df: ks.DataFrame) -> ks.DataFrame:457        df["b"] = df["a"] + 1458        return df459    @pa.check_io(df=in_schema, out=out_schema)460    def function_check_io_invalid(df: ks.DataFrame) -> ks.DataFrame:461        return df462    @pa.check_types463    def function_check_types(464        df: pa.typing.koalas.DataFrame[InSchema],465    ) -> pa.typing.koalas.DataFrame[OutSchema]:466        df["b"] = df["a"] + 1467        return df468    @pa.check_types469    def function_check_types_invalid(470        df: pa.typing.koalas.DataFrame[InSchema],471    ) -> pa.typing.koalas.DataFrame[OutSchema]:472        return df473    valid_df = ks.DataFrame({"a": [1, 2, 3]})474    invalid_df = ks.DataFrame({"b": [1, 2, 3]})...

test_schemas_on_modin.py

Source:test_schemas_on_modin.py

...372    def function_check_io(df: mpd.DataFrame) -> mpd.DataFrame:373        df["b"] = df["a"] + 1374        return df375    @pa.check_io(df=in_schema, out=out_schema)376    def function_check_io_invalid(df: mpd.DataFrame) -> mpd.DataFrame:377        return df378    @pa.check_types379    def function_check_types(380        df: pa.typing.modin.DataFrame[InSchema],381    ) -> pa.typing.modin.DataFrame[OutSchema]:382        df["b"] = df["a"] + 1383        return df384    @pa.check_types385    def function_check_types_invalid(386        df: pa.typing.modin.DataFrame[InSchema],387    ) -> pa.typing.modin.DataFrame[OutSchema]:388        return df389    valid_df = mpd.DataFrame({"a": [1, 2, 3]})390    invalid_df = mpd.DataFrame({"b": [1, 2, 3]})...

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