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from __future__ import annotations
import typing
from abc import abstractmethod
from inspect import getmodule
from typing import TYPE_CHECKING, Collection, Generic, TypeVar
from typing_extensions import NotRequired, TypedDict, get_type_hints
from litestar.dto._backend import DTOBackend
from litestar.dto._codegen_backend import DTOCodegenBackend
from litestar.dto.config import DTOConfig
from litestar.dto.data_structures import DTOData
from litestar.dto.types import RenameStrategy
from litestar.enums import RequestEncodingType
from litestar.exceptions.dto_exceptions import InvalidAnnotationException
from litestar.types.builtin_types import NoneType
from litestar.types.composite_types import TypeEncodersMap
from litestar.typing import FieldDefinition
if TYPE_CHECKING:
from typing import Any, ClassVar, Generator
from typing_extensions import Self
from litestar._openapi.schema_generation import SchemaCreator
from litestar.connection import ASGIConnection
from litestar.dto.data_structures import DTOFieldDefinition
from litestar.openapi.spec import Reference, Schema
from litestar.types.serialization import LitestarEncodableType
__all__ = ("AbstractDTO",)
T = TypeVar("T")
class _BackendDict(TypedDict):
data_backend: NotRequired[DTOBackend]
return_backend: NotRequired[DTOBackend]
class AbstractDTO(Generic[T]):
"""Base class for DTO types."""
__slots__ = ("asgi_connection",)
config: ClassVar[DTOConfig]
"""Config objects to define properties of the DTO."""
model_type: type[T]
"""If ``annotation`` is an iterable, this is the inner type, otherwise will be the same as ``annotation``."""
_dto_backends: ClassVar[dict[str, _BackendDict]] = {}
def __init__(self, asgi_connection: ASGIConnection) -> None:
"""Create an AbstractDTOFactory type.
Args:
asgi_connection: A :class:`ASGIConnection <litestar.connection.base.ASGIConnection>` instance.
"""
self.asgi_connection = asgi_connection
def __class_getitem__(cls, annotation: Any) -> type[Self]:
field_definition = FieldDefinition.from_annotation(annotation)
if (field_definition.is_optional and len(field_definition.args) > 2) or (
field_definition.is_union and not field_definition.is_optional
):
raise InvalidAnnotationException("Unions are currently not supported as type argument to DTOs.")
if field_definition.is_forward_ref:
raise InvalidAnnotationException("Forward references are not supported as type argument to DTO")
# if a configuration is not provided, and the type narrowing is a type var, we don't want to create a subclass
config = cls.get_dto_config_from_annotated_type(field_definition)
if not config:
if field_definition.is_type_var:
return cls
config = cls.config if hasattr(cls, "config") else DTOConfig()
cls_dict: dict[str, Any] = {"config": config, "_type_backend_map": {}, "_handler_backend_map": {}}
if not field_definition.is_type_var:
cls_dict.update(model_type=field_definition.annotation)
return type(f"{cls.__name__}[{annotation}]", (cls,), cls_dict) # pyright: ignore
def decode_builtins(self, value: dict[str, Any]) -> Any:
"""Decode a dictionary of Python values into an the DTO's datatype."""
backend = self._dto_backends[self.asgi_connection.route_handler.handler_id]["data_backend"] # pyright: ignore
return backend.populate_data_from_builtins(value, self.asgi_connection)
def decode_bytes(self, value: bytes) -> Any:
"""Decode a byte string into an the DTO's datatype."""
backend = self._dto_backends[self.asgi_connection.route_handler.handler_id]["data_backend"] # pyright: ignore
return backend.populate_data_from_raw(value, self.asgi_connection)
def data_to_encodable_type(self, data: T | Collection[T]) -> LitestarEncodableType:
backend = self._dto_backends[self.asgi_connection.route_handler.handler_id]["return_backend"] # pyright: ignore
return backend.encode_data(data)
@classmethod
@abstractmethod
def generate_field_definitions(cls, model_type: type[Any]) -> Generator[DTOFieldDefinition, None, None]:
"""Generate ``FieldDefinition`` instances from ``model_type``.
Yields:
``FieldDefinition`` instances.
"""
@classmethod
@abstractmethod
def detect_nested_field(cls, field_definition: FieldDefinition) -> bool:
"""Return ``True`` if ``field_definition`` represents a nested model field.
Args:
field_definition: inspect type to determine if field represents a nested model.
Returns:
``True`` if ``field_definition`` represents a nested model field.
"""
@classmethod
def is_supported_model_type_field(cls, field_definition: FieldDefinition) -> bool:
"""Check support for the given type.
Args:
field_definition: A :class:`FieldDefinition <litestar.typing.FieldDefinition>` instance.
Returns:
Whether the type of the field definition is supported by the DTO.
"""
return field_definition.is_subclass_of(cls.model_type) or (
field_definition.origin
and any(
cls.resolve_model_type(inner_field).is_subclass_of(cls.model_type)
for inner_field in field_definition.inner_types
)
)
@classmethod
def create_for_field_definition(
cls,
field_definition: FieldDefinition,
handler_id: str,
backend_cls: type[DTOBackend] | None = None,
) -> None:
"""Creates a DTO subclass for a field definition.
Args:
field_definition: A :class:`FieldDefinition <litestar.typing.FieldDefinition>` instance.
handler_id: ID of the route handler for which to create a DTO instance.
backend_cls: Alternative DTO backend class to use
Returns:
None
"""
if handler_id not in cls._dto_backends:
cls._dto_backends[handler_id] = {}
backend_context = cls._dto_backends[handler_id]
key = "data_backend" if field_definition.name == "data" else "return_backend"
if key not in backend_context:
model_type_field_definition = cls.resolve_model_type(field_definition=field_definition)
wrapper_attribute_name: str | None = None
if not model_type_field_definition.is_subclass_of(cls.model_type):
if resolved_generic_result := cls.resolve_generic_wrapper_type(
field_definition=model_type_field_definition
):
model_type_field_definition, field_definition, wrapper_attribute_name = resolved_generic_result
else:
raise InvalidAnnotationException(
f"DTO narrowed with '{cls.model_type}', handler type is '{field_definition.annotation}'"
)
if backend_cls is None:
backend_cls = DTOCodegenBackend if cls.config.experimental_codegen_backend else DTOBackend
elif backend_cls is DTOCodegenBackend and cls.config.experimental_codegen_backend is False:
backend_cls = DTOBackend
backend_context[key] = backend_cls( # type: ignore[literal-required]
dto_factory=cls,
field_definition=field_definition,
model_type=model_type_field_definition.annotation,
wrapper_attribute_name=wrapper_attribute_name,
is_data_field=field_definition.name == "data",
handler_id=handler_id,
)
@classmethod
def create_openapi_schema(
cls, field_definition: FieldDefinition, handler_id: str, schema_creator: SchemaCreator
) -> Reference | Schema:
"""Create an OpenAPI request body.
Returns:
OpenAPI request body.
"""
key = "data_backend" if field_definition.name == "data" else "return_backend"
backend = cls._dto_backends[handler_id][key] # type: ignore[literal-required]
return schema_creator.for_field_definition(FieldDefinition.from_annotation(backend.annotation))
@classmethod
def resolve_generic_wrapper_type(
cls, field_definition: FieldDefinition
) -> tuple[FieldDefinition, FieldDefinition, str] | None:
"""Handle where DTO supported data is wrapped in a generic container type.
Args:
field_definition: A parsed type annotation that represents the annotation used to narrow the DTO type.
Returns:
The data model type.
"""
if field_definition.origin and (
inner_fields := [
inner_field
for inner_field in field_definition.inner_types
if cls.resolve_model_type(inner_field).is_subclass_of(cls.model_type)
]
):
inner_field = inner_fields[0]
model_field_definition = cls.resolve_model_type(inner_field)
for attr, attr_type in cls.get_model_type_hints(field_definition.origin).items():
if isinstance(attr_type.annotation, TypeVar) or any(
isinstance(t.annotation, TypeVar) for t in attr_type.inner_types
):
if attr_type.is_non_string_collection:
# the inner type of the collection type is the type var, so we need to specialize the
# collection type with the DTO supported type.
specialized_annotation = attr_type.safe_generic_origin[model_field_definition.annotation]
return model_field_definition, FieldDefinition.from_annotation(specialized_annotation), attr
return model_field_definition, inner_field, attr
return None
@staticmethod
def get_model_type_hints(
model_type: type[Any], namespace: dict[str, Any] | None = None
) -> dict[str, FieldDefinition]:
"""Retrieve type annotations for ``model_type``.
Args:
model_type: Any type-annotated class.
namespace: Optional namespace to use for resolving type hints.
Returns:
Parsed type hints for ``model_type`` resolved within the scope of its module.
"""
namespace = namespace or {}
namespace.update(vars(typing))
namespace.update(
{
"TypeEncodersMap": TypeEncodersMap,
"DTOConfig": DTOConfig,
"RenameStrategy": RenameStrategy,
"RequestEncodingType": RequestEncodingType,
}
)
if model_module := getmodule(model_type):
namespace.update(vars(model_module))
return {
k: FieldDefinition.from_kwarg(annotation=v, name=k)
for k, v in get_type_hints(model_type, localns=namespace, include_extras=True).items() # pyright: ignore
}
@staticmethod
def get_dto_config_from_annotated_type(field_definition: FieldDefinition) -> DTOConfig | None:
"""Extract data type and config instances from ``Annotated`` annotation.
Args:
field_definition: A parsed type annotation that represents the annotation used to narrow the DTO type.
Returns:
The type and config object extracted from the annotation.
"""
return next((item for item in field_definition.metadata if isinstance(item, DTOConfig)), None)
@classmethod
def resolve_model_type(cls, field_definition: FieldDefinition) -> FieldDefinition:
"""Resolve the data model type from a parsed type.
Args:
field_definition: A parsed type annotation that represents the annotation used to narrow the DTO type.
Returns:
A :class:`FieldDefinition <.typing.FieldDefinition>` that represents the data model type.
"""
if field_definition.is_optional:
return cls.resolve_model_type(
next(t for t in field_definition.inner_types if not t.is_subclass_of(NoneType))
)
if field_definition.is_subclass_of(DTOData):
return cls.resolve_model_type(field_definition.inner_types[0])
if field_definition.is_collection:
if field_definition.is_mapping:
return cls.resolve_model_type(field_definition.inner_types[1])
if field_definition.is_tuple:
if any(t is Ellipsis for t in field_definition.args):
return cls.resolve_model_type(field_definition.inner_types[0])
elif field_definition.is_non_string_collection:
return cls.resolve_model_type(field_definition.inner_types[0])
return field_definition
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