How to use test_regex_columns method in pandera

Best Python code snippet using pandera_python

test_schemas_on_pyspark.py

Source:test_schemas_on_pyspark.py

...334    series_schema.unique = False335    assert isinstance(schema(data_non_unique), ps.DataFrame)336    assert isinstance(column_schema(data_non_unique), ps.DataFrame)337    assert isinstance(series_schema(data_non_unique["field"]), ps.Series)338def test_regex_columns():339    """Test regex column selection works on on pyspark.pandas dataframes."""340    schema = pa.DataFrameSchema({r"field_\d+": pa.Column(int, regex=True)})341    n_fields = 3342    data = ps.DataFrame({f"field_{i}": [1, 2, 3] for i in range(n_fields)})343    schema(data)344    for i in range(n_fields):345        invalid_data = data.copy()346        invalid_data[f"field_{i}"] = ["a", "b", "c"]347        with pytest.raises(pa.errors.SchemaError):348            schema(invalid_data)349def test_required_column():350    """Test the required column raises error."""351    required_schema = pa.DataFrameSchema(352        {"field": pa.Column(int, required=True)}...

test_schemas_on_koalas.py

Source:test_schemas_on_koalas.py

...303    series_schema.unique = False304    assert isinstance(schema(data_non_unique), ks.DataFrame)305    assert isinstance(column_schema(data_non_unique), ks.DataFrame)306    assert isinstance(series_schema(data_non_unique["field"]), ks.Series)307def test_regex_columns():308    """Test regex column selection works on on koalas dataframes."""309    schema = pa.DataFrameSchema({r"field_\d+": pa.Column(int, regex=True)})310    n_fields = 3311    data = ks.DataFrame({f"field_{i}": [1, 2, 3] for i in range(n_fields)})312    schema(data)313    for i in range(n_fields):314        invalid_data = data.copy()315        invalid_data[f"field_{i}"] = ["a", "b", "c"]316        with pytest.raises(pa.errors.SchemaError):317            schema(invalid_data)318def test_required_column():319    """Test the required column raises error."""320    required_schema = pa.DataFrameSchema(321        {"field": pa.Column(int, required=True)}...

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