Best Python code snippet using pandera_python
test_schema_inference.py
Source:test_schema_inference.py
...57@pytest.mark.parametrize(58 "multi_index",59 [False, True],60)61def test_infer_dataframe_schema(multi_index: bool) -> None:62 """Test dataframe schema is correctly inferred."""63 dataframe = _create_dataframe(multi_index=multi_index)64 schema = schema_inference.infer_dataframe_schema(dataframe)65 assert isinstance(schema, pa.DataFrameSchema)66 if multi_index:67 assert isinstance(schema.index, pa.MultiIndex)68 else:69 assert isinstance(schema.index, pa.Index)70 with pytest.warns(71 UserWarning,72 match="^This .+ is an inferred schema that hasn't been modified",73 ):74 schema.validate(dataframe)75 # modifying an inferred schema should set _is_inferred to False76 schema_with_added_cols = schema.add_columns({"foo": pa.Column(pa.String)})77 assert schema._is_inferred78 assert not schema_with_added_cols._is_inferred...
schema_inference.py
Source:schema_inference.py
...16 :returns: DataFrameSchema or SeriesSchema17 :raises: TypeError if pandas_obj is not expected type.18 """19 if isinstance(pandas_obj, pd.DataFrame):20 return infer_dataframe_schema(pandas_obj)21 elif isinstance(pandas_obj, pd.Series):22 return infer_series_schema(pandas_obj)23 else:24 raise TypeError(25 "pandas_obj type not recognized. Expected a pandas DataFrame or "26 f"Series, found {type(pandas_obj)}"27 )28def _create_index(index_statistics):29 index = [30 Index(31 properties["dtype"],32 checks=parse_check_statistics(properties["checks"]),33 nullable=properties["nullable"],34 name=properties["name"],35 )36 for properties in index_statistics37 ]38 if len(index) == 1:39 index = index[0] # type: ignore40 else:41 index = MultiIndex(index) # type: ignore42 return index43def infer_dataframe_schema(df: pd.DataFrame) -> DataFrameSchema:44 """Infer a DataFrameSchema from a pandas DataFrame.45 :param df: DataFrame object to infer.46 :returns: DataFrameSchema47 """48 df_statistics = infer_dataframe_statistics(df)49 schema = DataFrameSchema(50 columns={51 colname: Column(52 properties["dtype"],53 checks=parse_check_statistics(properties["checks"]),54 nullable=properties["nullable"],55 )56 for colname, properties in df_statistics["columns"].items()57 },...
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