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How to use invalid_input_dataframe method in pandera

Best Python code snippet using pandera_python

test_from_to_format_conversions.py

Source:test_from_to_format_conversions.py

...51        to_format = "pickle"52def mock_dataframe() -> pd.DataFrame:53    """Create a valid mock dataframe."""54    return pd.DataFrame({"str_col": ["a"], "int_col": [1]})55def invalid_input_dataframe() -> pd.DataFrame:56    """Invalid data under the InSchema* models defined above."""57    return pd.DataFrame({"str_col": ["a"]})58@pytest.mark.parametrize(59    "schema,to_fn,buf_cls",60    [61        [InSchemaCsv, lambda df, x: df.to_csv(x, index=None), io.StringIO],62        [InSchemaDict, lambda df: df.to_dict(orient="records"), None],63        [64            InSchemaJson,65            lambda df, x: df.to_json(x, orient="records"),66            io.StringIO,67        ],68        [InSchemaJson, lambda df: df.to_json(orient="records"), None],69        [InSchemaFeather, lambda df, x: df.to_feather(x), io.BytesIO],70        [InSchemaParquet, lambda df, x: df.to_parquet(x), io.BytesIO],71        [InSchemaPickle, lambda df, x: df.to_pickle(x), io.BytesIO],72    ],73)74def test_from_format(schema, to_fn, buf_cls):75    """76    Test that check_types-guarded function reads data from source serialization77    format.78    """79    @pa.check_types80    def fn(df: pa.typing.DataFrame[schema]):81        return df82    for df, invalid in [83        (mock_dataframe(), False),84        (invalid_input_dataframe(), True),85    ]:86        buf = None if buf_cls is None else buf_cls()87        arg = to_fn(df, *([buf] if buf else []))88        if buf:89            if buf.closed:90                pytest.skip(91                    "skip test for older pandas versions where to_pickle "92                    "closes user-provided buffers: "93                    "https://github.com/pandas-dev/pandas/issues/35679"94                )95            buf.seek(0)96            arg = buf97        if invalid:98            with pytest.raises(pa.errors.SchemaError):...

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