156 lines
6.0 KiB
Python
156 lines
6.0 KiB
Python
"""RootModel class and type definitions."""
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from __future__ import annotations as _annotations
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import typing
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from copy import copy, deepcopy
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from pydantic_core import PydanticUndefined
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from . import PydanticUserError
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from ._internal import _model_construction, _repr
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from .main import BaseModel, _object_setattr
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if typing.TYPE_CHECKING:
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from typing import Any
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from typing_extensions import Literal, dataclass_transform
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from .fields import Field as PydanticModelField
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# dataclass_transform could be applied to RootModel directly, but `ModelMetaclass`'s dataclass_transform
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# takes priority (at least with pyright). We trick type checkers into thinking we apply dataclass_transform
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# on a new metaclass.
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@dataclass_transform(kw_only_default=False, field_specifiers=(PydanticModelField,))
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class _RootModelMetaclass(_model_construction.ModelMetaclass):
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...
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else:
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_RootModelMetaclass = _model_construction.ModelMetaclass
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__all__ = ('RootModel',)
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Model = typing.TypeVar('Model', bound='BaseModel')
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RootModelRootType = typing.TypeVar('RootModelRootType')
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class RootModel(BaseModel, typing.Generic[RootModelRootType], metaclass=_RootModelMetaclass):
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"""Usage docs: https://docs.pydantic.dev/2.7/concepts/models/#rootmodel-and-custom-root-types
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A Pydantic `BaseModel` for the root object of the model.
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Attributes:
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root: The root object of the model.
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__pydantic_root_model__: Whether the model is a RootModel.
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__pydantic_private__: Private fields in the model.
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__pydantic_extra__: Extra fields in the model.
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"""
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__pydantic_root_model__ = True
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__pydantic_private__ = None
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__pydantic_extra__ = None
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root: RootModelRootType
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def __init_subclass__(cls, **kwargs):
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extra = cls.model_config.get('extra')
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if extra is not None:
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raise PydanticUserError(
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"`RootModel` does not support setting `model_config['extra']`", code='root-model-extra'
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)
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super().__init_subclass__(**kwargs)
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def __init__(self, /, root: RootModelRootType = PydanticUndefined, **data) -> None: # type: ignore
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__tracebackhide__ = True
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if data:
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if root is not PydanticUndefined:
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raise ValueError(
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'"RootModel.__init__" accepts either a single positional argument or arbitrary keyword arguments'
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)
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root = data # type: ignore
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self.__pydantic_validator__.validate_python(root, self_instance=self)
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__init__.__pydantic_base_init__ = True # pyright: ignore[reportFunctionMemberAccess]
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@classmethod
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def model_construct(cls: type[Model], root: RootModelRootType, _fields_set: set[str] | None = None) -> Model: # type: ignore
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"""Create a new model using the provided root object and update fields set.
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Args:
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root: The root object of the model.
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_fields_set: The set of fields to be updated.
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Returns:
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The new model.
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Raises:
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NotImplemented: If the model is not a subclass of `RootModel`.
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"""
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return super().model_construct(root=root, _fields_set=_fields_set)
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def __getstate__(self) -> dict[Any, Any]:
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return {
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'__dict__': self.__dict__,
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'__pydantic_fields_set__': self.__pydantic_fields_set__,
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}
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def __setstate__(self, state: dict[Any, Any]) -> None:
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_object_setattr(self, '__pydantic_fields_set__', state['__pydantic_fields_set__'])
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_object_setattr(self, '__dict__', state['__dict__'])
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def __copy__(self: Model) -> Model:
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"""Returns a shallow copy of the model."""
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cls = type(self)
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m = cls.__new__(cls)
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_object_setattr(m, '__dict__', copy(self.__dict__))
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_object_setattr(m, '__pydantic_fields_set__', copy(self.__pydantic_fields_set__))
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return m
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def __deepcopy__(self: Model, memo: dict[int, Any] | None = None) -> Model:
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"""Returns a deep copy of the model."""
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cls = type(self)
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m = cls.__new__(cls)
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_object_setattr(m, '__dict__', deepcopy(self.__dict__, memo=memo))
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# This next line doesn't need a deepcopy because __pydantic_fields_set__ is a set[str],
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# and attempting a deepcopy would be marginally slower.
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_object_setattr(m, '__pydantic_fields_set__', copy(self.__pydantic_fields_set__))
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return m
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if typing.TYPE_CHECKING:
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def model_dump( # type: ignore
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self,
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*,
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mode: Literal['json', 'python'] | str = 'python',
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include: Any = None,
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exclude: Any = None,
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context: dict[str, Any] | None = None,
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by_alias: bool = False,
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exclude_unset: bool = False,
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exclude_defaults: bool = False,
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exclude_none: bool = False,
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round_trip: bool = False,
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warnings: bool | Literal['none', 'warn', 'error'] = True,
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serialize_as_any: bool = False,
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) -> Any:
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"""This method is included just to get a more accurate return type for type checkers.
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It is included in this `if TYPE_CHECKING:` block since no override is actually necessary.
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See the documentation of `BaseModel.model_dump` for more details about the arguments.
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Generally, this method will have a return type of `RootModelRootType`, assuming that `RootModelRootType` is
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not a `BaseModel` subclass. If `RootModelRootType` is a `BaseModel` subclass, then the return
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type will likely be `dict[str, Any]`, as `model_dump` calls are recursive. The return type could
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even be something different, in the case of a custom serializer.
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Thus, `Any` is used here to catch all of these cases.
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"""
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...
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def __eq__(self, other: Any) -> bool:
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if not isinstance(other, RootModel):
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return NotImplemented
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return self.model_fields['root'].annotation == other.model_fields['root'].annotation and super().__eq__(other)
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def __repr_args__(self) -> _repr.ReprArgs:
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yield 'root', self.root
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