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# mypy: strict-equality=False
from __future__ import annotations
from typing import TYPE_CHECKING, Any
from typing_extensions import Annotated, get_type_hints
from litestar.params import KwargDefinition
from litestar.types import Empty
from litestar.typing import FieldDefinition
from litestar.utils import deprecated, is_class_and_subclass
from litestar.utils.predicates import is_generic
from litestar.utils.typing import (
_substitute_typevars,
get_origin_or_inner_type,
get_type_hints_with_generics_resolved,
normalize_type_annotation,
)
# isort: off
try:
from pydantic import v1 as pydantic_v1
import pydantic as pydantic_v2
from pydantic.fields import PydanticUndefined as Pydantic2Undefined # type: ignore[attr-defined]
from pydantic.v1.fields import Undefined as Pydantic1Undefined
PYDANTIC_UNDEFINED_SENTINELS = {Pydantic1Undefined, Pydantic2Undefined}
except ImportError:
try:
import pydantic as pydantic_v1 # type: ignore[no-redef]
from pydantic.fields import Undefined as Pydantic1Undefined # type: ignore[attr-defined, no-redef]
pydantic_v2 = Empty # type: ignore[assignment]
PYDANTIC_UNDEFINED_SENTINELS = {Pydantic1Undefined}
except ImportError: # pyright: ignore
pydantic_v1 = Empty # type: ignore[assignment]
pydantic_v2 = Empty # type: ignore[assignment]
PYDANTIC_UNDEFINED_SENTINELS = set()
# isort: on
if TYPE_CHECKING:
from typing_extensions import TypeGuard
def is_pydantic_model_class(
annotation: Any,
) -> TypeGuard[type[pydantic_v1.BaseModel | pydantic_v2.BaseModel]]: # pyright: ignore
"""Given a type annotation determine if the annotation is a subclass of pydantic's BaseModel.
Args:
annotation: A type.
Returns:
A typeguard determining whether the type is :data:`BaseModel pydantic.BaseModel>`.
"""
tests: list[bool] = []
if pydantic_v1 is not Empty: # pragma: no cover
tests.append(is_class_and_subclass(annotation, pydantic_v1.BaseModel))
if pydantic_v2 is not Empty: # pragma: no cover
tests.append(is_class_and_subclass(annotation, pydantic_v2.BaseModel))
return any(tests)
def is_pydantic_model_instance(
annotation: Any,
) -> TypeGuard[pydantic_v1.BaseModel | pydantic_v2.BaseModel]: # pyright: ignore
"""Given a type annotation determine if the annotation is an instance of pydantic's BaseModel.
Args:
annotation: A type.
Returns:
A typeguard determining whether the type is :data:`BaseModel pydantic.BaseModel>`.
"""
tests: list[bool] = []
if pydantic_v1 is not Empty: # pragma: no cover
tests.append(isinstance(annotation, pydantic_v1.BaseModel))
if pydantic_v2 is not Empty: # pragma: no cover
tests.append(isinstance(annotation, pydantic_v2.BaseModel))
return any(tests)
def is_pydantic_constrained_field(annotation: Any) -> bool:
"""Check if the given annotation is a constrained pydantic type.
Args:
annotation: A type annotation
Returns:
True if pydantic is installed and the type is a constrained type, otherwise False.
"""
if pydantic_v1 is Empty: # pragma: no cover
return False # type: ignore[unreachable]
return any(
is_class_and_subclass(annotation, constrained_type) # pyright: ignore
for constrained_type in (
pydantic_v1.ConstrainedBytes,
pydantic_v1.ConstrainedDate,
pydantic_v1.ConstrainedDecimal,
pydantic_v1.ConstrainedFloat,
pydantic_v1.ConstrainedFrozenSet,
pydantic_v1.ConstrainedInt,
pydantic_v1.ConstrainedList,
pydantic_v1.ConstrainedSet,
pydantic_v1.ConstrainedStr,
)
)
def pydantic_unwrap_and_get_origin(annotation: Any) -> Any | None:
if pydantic_v2 is Empty or (pydantic_v1 is not Empty and is_class_and_subclass(annotation, pydantic_v1.BaseModel)):
return get_origin_or_inner_type(annotation)
origin = annotation.__pydantic_generic_metadata__["origin"]
return normalize_type_annotation(origin)
def pydantic_get_type_hints_with_generics_resolved(
annotation: Any,
globalns: dict[str, Any] | None = None,
localns: dict[str, Any] | None = None,
include_extras: bool = False,
model_annotations: dict[str, Any] | None = None,
) -> dict[str, Any]:
if pydantic_v2 is Empty or (pydantic_v1 is not Empty and is_class_and_subclass(annotation, pydantic_v1.BaseModel)):
return get_type_hints_with_generics_resolved(annotation, type_hints=model_annotations)
origin = pydantic_unwrap_and_get_origin(annotation)
if origin is None:
if model_annotations is None: # pragma: no cover
model_annotations = get_type_hints(
annotation, globalns=globalns, localns=localns, include_extras=include_extras
)
typevar_map = {p: p for p in annotation.__pydantic_generic_metadata__["parameters"]}
else:
if model_annotations is None:
model_annotations = get_type_hints(
origin, globalns=globalns, localns=localns, include_extras=include_extras
)
args = annotation.__pydantic_generic_metadata__["args"]
parameters = origin.__pydantic_generic_metadata__["parameters"]
typevar_map = dict(zip(parameters, args))
return {n: _substitute_typevars(type_, typevar_map) for n, type_ in model_annotations.items()}
@deprecated(version="2.6.2")
def pydantic_get_unwrapped_annotation_and_type_hints(annotation: Any) -> tuple[Any, dict[str, Any]]: # pragma: pver
"""Get the unwrapped annotation and the type hints after resolving generics.
Args:
annotation: A type annotation.
Returns:
A tuple containing the unwrapped annotation and the type hints.
"""
if is_generic(annotation):
origin = pydantic_unwrap_and_get_origin(annotation)
return origin or annotation, pydantic_get_type_hints_with_generics_resolved(annotation, include_extras=True)
return annotation, get_type_hints(annotation, include_extras=True)
def is_pydantic_2_model(
obj: type[pydantic_v1.BaseModel | pydantic_v2.BaseModel], # pyright: ignore
) -> TypeGuard[pydantic_v2.BaseModel]: # pyright: ignore
return pydantic_v2 is not Empty and issubclass(obj, pydantic_v2.BaseModel)
def is_pydantic_undefined(value: Any) -> bool:
return any(v is value for v in PYDANTIC_UNDEFINED_SENTINELS)
def create_field_definitions_for_computed_fields(
model: type[pydantic_v1.BaseModel | pydantic_v2.BaseModel], # pyright: ignore
prefer_alias: bool,
) -> dict[str, FieldDefinition]:
"""Create field definitions for computed fields.
Args:
model: A pydantic model.
prefer_alias: Whether to prefer the alias or the name of the field.
Returns:
A dictionary containing the field definitions for the computed fields.
"""
pydantic_decorators = getattr(model, "__pydantic_decorators__", None)
if pydantic_decorators is None:
return {}
def get_name(k: str, dec: Any) -> str:
if not dec.info.alias:
return k
return dec.info.alias if prefer_alias else k # type: ignore[no-any-return]
return {
(name := get_name(k, dec)): FieldDefinition.from_annotation(
Annotated[
dec.info.return_type,
KwargDefinition(title=dec.info.title, description=dec.info.description, read_only=True),
],
name=name,
)
for k, dec in pydantic_decorators.computed_fields.items()
}
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