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How to use _build_columns_index method in pandera

Best Python code snippet using pandera_python

model.py

Source:model.py

...150        df_registered_checks = _convert_extras_to_checks(151            {} if cls.__extras__ is None else cls.__extras__152        )153        cls.__dataframe_checks__ = df_custom_checks + df_registered_checks154        columns, index = cls._build_columns_index(155            cls.__fields__, cls.__checks__, **mi_kwargs156        )157        kwargs = {}158        if cls.__config__ is not None:159            kwargs = {160                "coerce": cls.__config__.coerce,161                "strict": cls.__config__.strict,162                "name": cls.__config__.name,163                "ordered": cls.__config__.ordered,164                "unique": cls.__config__.unique,165                "title": cls.__config__.title,166                "description": cls.__config__.description or cls.__doc__,167            }168        cls.__schema__ = DataFrameSchema(169            columns,170            index=index,171            checks=cls.__dataframe_checks__,  # type: ignore172            **kwargs,173        )174        if cls not in MODEL_CACHE:175            MODEL_CACHE[cls] = cls.__schema__  # type: ignore176        return cls.__schema__  # type: ignore177    @classmethod178    def to_yaml(cls, stream: Optional[os.PathLike] = None):179        """180        Convert `Schema` to yaml using `io.to_yaml`.181        """182        return cls.to_schema().to_yaml(stream)183    @classmethod184    @docstring_substitution(validate_doc=DataFrameSchema.validate.__doc__)185    def validate(186        cls: Type[TSchemaModel],187        check_obj: pd.DataFrame,188        head: Optional[int] = None,189        tail: Optional[int] = None,190        sample: Optional[int] = None,191        random_state: Optional[int] = None,192        lazy: bool = False,193        inplace: bool = False,194    ) -> DataFrameBase[TSchemaModel]:195        """%(validate_doc)s"""196        return cast(197            DataFrameBase[TSchemaModel],198            cls.to_schema().validate(199                check_obj, head, tail, sample, random_state, lazy, inplace200            ),201        )202    @classmethod203    @docstring_substitution(strategy_doc=DataFrameSchema.strategy.__doc__)204    @st.strategy_import_error205    def strategy(cls: Type[TSchemaModel], *, size: Optional[int] = None):206        """%(strategy_doc)s"""207        return cls.to_schema().strategy(size=size)208    @classmethod209    @docstring_substitution(example_doc=DataFrameSchema.strategy.__doc__)210    @st.strategy_import_error211    def example(212        cls: Type[TSchemaModel], *, size: Optional[int] = None213    ) -> DataFrameBase[TSchemaModel]:214        """%(example_doc)s"""215        return cast(216            DataFrameBase[TSchemaModel], cls.to_schema().example(size=size)217        )218    @classmethod219    def _build_columns_index(  # pylint:disable=too-many-locals220        cls,221        fields: Dict[str, Tuple[AnnotationInfo, FieldInfo]],222        checks: Dict[str, List[Check]],223        **multiindex_kwargs: Any,224    ) -> Tuple[225        Dict[str, schema_components.Column],226        Optional[Union[schema_components.Index, schema_components.MultiIndex]],227    ]:228        index_count = sum(229            annotation.origin in INDEX_TYPES230            for annotation, _ in fields.values()231        )232        columns: Dict[str, schema_components.Column] = {}233        indices: List[schema_components.Index] = []...

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