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How to use function_check_input_output method in pandera

Best Python code snippet using pandera_python

test_schemas_on_koalas.py

Source:test_schemas_on_koalas.py

...444    class OutSchema(InSchema):445        b: pa.typing.koalas.Series[int]446    @pa.check_input(in_schema)447    @pa.check_output(out_schema)448    def function_check_input_output(df: ks.DataFrame) -> ks.DataFrame:449        df["b"] = df["a"] + 1450        return df451    @pa.check_input(in_schema)452    @pa.check_output(out_schema)453    def function_check_input_output_invalid(df: ks.DataFrame) -> ks.DataFrame:454        return df455    @pa.check_io(df=in_schema, out=out_schema)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]})475    function_check_input_output(valid_df)476    function_check_io(valid_df)477    function_check_types(valid_df)478    for fn in (479        function_check_input_output,480        function_check_input_output_invalid,481        function_check_io,482        function_check_io_invalid,483        function_check_types,484        function_check_types_invalid,485    ):486        with pytest.raises(pa.errors.SchemaError):487            fn(invalid_df)488    for fn in (489        function_check_input_output_invalid,...

test_schemas_on_modin.py

Source:test_schemas_on_modin.py

...358    class OutSchema(InSchema):359        b: pa.typing.modin.Series[int]360    @pa.check_input(in_schema)361    @pa.check_output(out_schema)362    def function_check_input_output(df: mpd.DataFrame) -> mpd.DataFrame:363        df["b"] = df["a"] + 1364        return df365    @pa.check_input(in_schema)366    @pa.check_output(out_schema)367    def function_check_input_output_invalid(368        df: mpd.DataFrame,369    ) -> mpd.DataFrame:370        return df371    @pa.check_io(df=in_schema, out=out_schema)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]})391    function_check_input_output(valid_df)392    function_check_io(valid_df)393    function_check_types(valid_df)394    for fn in (395        function_check_input_output,396        function_check_input_output_invalid,397        function_check_io,398        function_check_io_invalid,399        function_check_types,400        function_check_types_invalid,401    ):402        with pytest.raises(pa.errors.SchemaError):403            fn(invalid_df)404    for fn in (405        function_check_input_output_invalid,...

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