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How to use _collect_config_and_extras method in pandera

Best Python code snippet using pandera_python

model.py

Source:model.py

...126                # Field omitted127                field = Field()128                field.__set_name__(cls, field_name)129                setattr(cls, field_name, field)130        cls.__config__, cls.__extras__ = cls._collect_config_and_extras()131    @classmethod132    def to_schema(cls) -> DataFrameSchema:133        """Create :class:`~pandera.DataFrameSchema` from the :class:`.SchemaModel`."""134        if cls in MODEL_CACHE:135            return MODEL_CACHE[cls]136        mi_kwargs = {137            name[len("multiindex_") :]: value138            for name, value in vars(cls.__config__).items()139            if name.startswith("multiindex_")140        }141        cls.__fields__ = cls._collect_fields()142        check_infos = typing.cast(143            List[FieldCheckInfo], cls._collect_check_infos(CHECK_KEY)144        )145        cls.__checks__ = cls._extract_checks(146            check_infos, field_names=list(cls.__fields__.keys())147        )148        df_check_infos = cls._collect_check_infos(DATAFRAME_CHECK_KEY)149        df_custom_checks = cls._extract_df_checks(df_check_infos)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] = []234        for field_name, (annotation, field) in fields.items():235            field_checks = checks.get(field_name, [])236            field_name = field.name237            check_name = getattr(field, "check_name", None)238            if annotation.metadata:239                if field.dtype_kwargs:240                    raise TypeError(241                        "Cannot specify redundant 'dtype_kwargs' "242                        + f"for {annotation.raw_annotation}."243                        + "\n Usage Tip: Drop 'typing.Annotated'."244                    )245                dtype_kwargs = _get_dtype_kwargs(annotation)246                dtype = annotation.arg(**dtype_kwargs)  # type: ignore247            elif annotation.default_dtype:248                dtype = annotation.default_dtype249            else:250                dtype = annotation.arg251            dtype = None if dtype is Any else dtype252            if (253                annotation.origin in SERIES_TYPES254                or annotation.raw_annotation in SERIES_TYPES255            ):256                col_constructor = (257                    field.to_column if field else schema_components.Column258                )259                if check_name is False:260                    raise SchemaInitError(261                        f"'check_name' is not supported for {field_name}."262                    )263                columns[field_name] = col_constructor(  # type: ignore264                    dtype,265                    required=not annotation.optional,266                    checks=field_checks,267                    name=field_name,268                )269            elif (270                annotation.origin in INDEX_TYPES271                or annotation.raw_annotation in INDEX_TYPES272            ):273                if annotation.optional:274                    raise SchemaInitError(275                        f"Index '{field_name}' cannot be Optional."276                    )277                if check_name is False or (278                    # default single index279                    check_name is None280                    and index_count == 1281                ):282                    field_name = None  # type:ignore283                index_constructor = (284                    field.to_index if field else schema_components.Index285                )286                index = index_constructor(  # type: ignore287                    dtype, checks=field_checks, name=field_name288                )289                indices.append(index)290            else:291                raise SchemaInitError(292                    f"Invalid annotation '{field_name}: "293                    f"{annotation.raw_annotation}'"294                )295        return columns, _build_schema_index(indices, **multiindex_kwargs)296    @classmethod297    def _get_model_attrs(cls) -> Dict[str, Any]:298        """Return all attributes.299        Similar to inspect.get_members but bypass descriptors __get__.300        """301        bases = inspect.getmro(cls)[:-1]  # bases -> SchemaModel -> object302        attrs = {}303        for base in reversed(bases):304            attrs.update(base.__dict__)305        return attrs306    @classmethod307    def _collect_fields(cls) -> Dict[str, Tuple[AnnotationInfo, FieldInfo]]:308        """Centralize publicly named fields and their corresponding annotations."""309        annotations = get_type_hints(  # pylint:disable=unexpected-keyword-arg310            cls, include_extras=True311        )312        attrs = cls._get_model_attrs()313        missing = []314        for name, attr in attrs.items():315            if inspect.isroutine(attr):316                continue317            if not _is_field(name):318                annotations.pop(name, None)319            elif name not in annotations:320                missing.append(name)321        if missing:322            raise SchemaInitError(f"Found missing annotations: {missing}")323        fields = {}324        for field_name, annotation in annotations.items():325            field = attrs[field_name]  # __init_subclass__ guarantees existence326            if not isinstance(field, FieldInfo):327                raise SchemaInitError(328                    f"'{field_name}' can only be assigned a 'Field', "329                    + f"not a '{type(field)}.'"330                )331            fields[field.name] = (AnnotationInfo(annotation), field)332        return fields333    @classmethod334    def _collect_config_and_extras(335        cls,336    ) -> Tuple[Type[BaseConfig], Dict[str, Any]]:337        """Collect config options from bases, splitting off unknown options."""338        bases = inspect.getmro(cls)[:-1]339        bases = typing.cast(Tuple[Type[SchemaModel]], bases)340        root_model, *models = reversed(bases)341        options, extras = _extract_config_options_and_extras(root_model.Config)342        for model in models:343            config = getattr(model, _CONFIG_KEY, {})344            base_options, base_extras = _extract_config_options_and_extras(345                config346            )347            options.update(base_options)348            extras.update(base_extras)...

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