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155 | 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
)
|