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pydantic_mixin

PydanticMixin

Bases: RelationMixin

Source code in ormar/models/mixins/pydantic_mixin.py
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class PydanticMixin(RelationMixin):

    __cache__: Dict[str, Type[pydantic.BaseModel]] = {}

    if TYPE_CHECKING:  # pragma: no cover
        __fields__: Dict[str, ModelField]
        _skip_ellipsis: Callable
        _get_not_excluded_fields: Callable

    @classmethod
    def get_pydantic(
        cls, *, include: Union[Set, Dict] = None, exclude: Union[Set, Dict] = None
    ) -> Type[pydantic.BaseModel]:
        """
        Returns a pydantic model out of ormar model.

        Converts also nested ormar models into pydantic models.

        Can be used to fully exclude certain fields in fastapi response and requests.

        :param include: fields of own and nested models to include
        :type include: Union[Set, Dict, None]
        :param exclude: fields of own and nested models to exclude
        :type exclude: Union[Set, Dict, None]
        """
        relation_map = translate_list_to_dict(cls._iterate_related_models())

        return cls._convert_ormar_to_pydantic(
            include=include, exclude=exclude, relation_map=relation_map
        )

    @classmethod
    def _convert_ormar_to_pydantic(
        cls,
        relation_map: Dict[str, Any],
        include: Union[Set, Dict] = None,
        exclude: Union[Set, Dict] = None,
    ) -> Type[pydantic.BaseModel]:
        if include and isinstance(include, Set):
            include = translate_list_to_dict(include)
        if exclude and isinstance(exclude, Set):
            exclude = translate_list_to_dict(exclude)
        fields_dict: Dict[str, Any] = dict()
        defaults: Dict[str, Any] = dict()
        fields_to_process = cls._get_not_excluded_fields(
            fields={*cls.Meta.model_fields.keys()}, include=include, exclude=exclude
        )
        fields_to_process.sort(
            key=lambda x: list(cls.Meta.model_fields.keys()).index(x)
        )

        cache_key = f"{cls.__name__}_{str(include)}_{str(exclude)}"
        if cache_key in cls.__cache__:
            return cls.__cache__[cache_key]

        for name in fields_to_process:
            field = cls._determine_pydantic_field_type(
                name=name,
                defaults=defaults,
                include=include,
                exclude=exclude,
                relation_map=relation_map,
            )
            if field is not None:
                fields_dict[name] = field
        model = type(
            f"{cls.__name__}_{''.join(choices(string.ascii_uppercase, k=3))}",
            (pydantic.BaseModel,),
            {"__annotations__": fields_dict, **defaults},
        )
        model = cast(Type[pydantic.BaseModel], model)
        cls._copy_field_validators(model=model)
        cls.__cache__[cache_key] = model
        return model

    @classmethod
    def _determine_pydantic_field_type(
        cls,
        name: str,
        defaults: Dict,
        include: Union[Set, Dict, None],
        exclude: Union[Set, Dict, None],
        relation_map: Dict[str, Any],
    ) -> Any:
        field = cls.Meta.model_fields[name]
        target: Any = None
        if field.is_relation and name in relation_map:  # type: ignore
            target = field.to._convert_ormar_to_pydantic(
                include=cls._skip_ellipsis(include, name),
                exclude=cls._skip_ellipsis(exclude, name),
                relation_map=cls._skip_ellipsis(
                    relation_map, name, default_return=dict()
                ),
            )
            if field.is_multi or field.virtual:
                target = List[target]  # type: ignore
        elif not field.is_relation:
            defaults[name] = cls.__fields__[name].field_info
            target = field.__type__
        if target is not None and field.nullable:
            target = Optional[target]
        return target

    @classmethod
    def _copy_field_validators(cls, model: Type[pydantic.BaseModel]) -> None:
        """
        Copy field validators from ormar model to generated pydantic model.
        """
        for field_name, field in model.__fields__.items():
            if (
                field_name not in cls.__fields__
                or cls.Meta.model_fields[field_name].is_relation
            ):
                continue
            validators = cls.__fields__[field_name].validators
            already_attached = [
                validator.__wrapped__ for validator in field.validators  # type: ignore
            ]
            validators_to_copy = [
                validator
                for validator in validators
                if validator.__wrapped__ not in already_attached  # type: ignore
            ]
            field.validators.extend(copy.deepcopy(validators_to_copy))
            class_validators = cls.__fields__[field_name].class_validators
            field.class_validators.update(copy.deepcopy(class_validators))
            field.pre_validators = copy.deepcopy(
                cls.__fields__[field_name].pre_validators
            )
            field.post_validators = copy.deepcopy(
                cls.__fields__[field_name].post_validators
            )

get_pydantic(*, include=None, exclude=None) classmethod

Returns a pydantic model out of ormar model.

Converts also nested ormar models into pydantic models.

Can be used to fully exclude certain fields in fastapi response and requests.

Parameters:

Name Type Description Default
include Union[Set, Dict]

fields of own and nested models to include

None
exclude Union[Set, Dict]

fields of own and nested models to exclude

None
Source code in ormar/models/mixins/pydantic_mixin.py
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@classmethod
def get_pydantic(
    cls, *, include: Union[Set, Dict] = None, exclude: Union[Set, Dict] = None
) -> Type[pydantic.BaseModel]:
    """
    Returns a pydantic model out of ormar model.

    Converts also nested ormar models into pydantic models.

    Can be used to fully exclude certain fields in fastapi response and requests.

    :param include: fields of own and nested models to include
    :type include: Union[Set, Dict, None]
    :param exclude: fields of own and nested models to exclude
    :type exclude: Union[Set, Dict, None]
    """
    relation_map = translate_list_to_dict(cls._iterate_related_models())

    return cls._convert_ormar_to_pydantic(
        include=include, exclude=exclude, relation_map=relation_map
    )