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How to use test_dataframe_checks method in pandera

Best Python code snippet using pandera_python

test_strategies.py

Source:test_strategies.py

...490@hypothesis.settings(491    suppress_health_check=[hypothesis.HealthCheck.too_slow],492)493@hypothesis.given(st.data())494def test_dataframe_checks(data_type, data):495    """Test dataframe strategy with checks defined at the dataframe level."""496    min_value, max_value = data.draw(value_ranges(data_type))497    dataframe_schema = pa.DataFrameSchema(498        {f"{data_type}_col": pa.Column(data_type) for _ in range(5)},499        checks=pa.Check.in_range(min_value, max_value),500    )501    strat = dataframe_schema.strategy(size=5)502    example = data.draw(strat)503    dataframe_schema(example)504@pytest.mark.parametrize(505    "data_type", [pa.Int(), pa.Float, pa.String, pa.DateTime]506)507@hypothesis.given(st.data())508@hypothesis.settings(...

test_checks.py

Source:test_checks.py

...244        with pytest.raises(245            errors.SchemaInitError, match="^Cannot use groupby checks with"246        ):247            schema_class(Int, Check(lambda s: s["bar"] == 1, groupby="foo"))248def test_dataframe_checks() -> None:249    """Tests that dataframe checks validate, error when a DataFrame doesn't250    comply with the schema, simple tests of the groupby checks which are251    covered in more detail above."""252    schema = DataFrameSchema(253        columns={254            "col1": Column(Int),255            "col2": Column(Float),256            "col3": Column(String),257            "col4": Column(String),258        },259        checks=[260            Check(lambda df: df["col1"] < df["col2"]),261            Check(lambda df: df["col3"] == df["col4"]),262        ],...

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