Shortcuts on this page
r m x toggle line displays
j k next/prev highlighted chunk
0 (zero) top of page
1 (one) first highlighted chunk
1"""Private logic for creating models."""
3from __future__ import annotations as _annotations
5import operator
6import sys
7import typing
8import warnings
9import weakref
10from abc import ABCMeta
11from functools import cache, partial, wraps
12from types import FunctionType
13from typing import TYPE_CHECKING, Any, Callable, Generic, Literal, NoReturn, TypeVar, cast
15from pydantic_core import PydanticUndefined, SchemaSerializer
16from typing_extensions import TypeAliasType, dataclass_transform, deprecated, get_args, get_origin
17from typing_inspection import typing_objects
19from ..errors import PydanticUndefinedAnnotation, PydanticUserError
20from ..plugin._schema_validator import create_schema_validator
21from ..warnings import GenericBeforeBaseModelWarning, PydanticDeprecatedSince20
22from ._config import ConfigWrapper
23from ._decorators import DecoratorInfos, PydanticDescriptorProxy, get_attribute_from_bases, unwrap_wrapped_function
24from ._fields import collect_model_fields, is_valid_field_name, is_valid_privateattr_name, rebuild_model_fields
25from ._generate_schema import GenerateSchema, InvalidSchemaError
26from ._generics import PydanticGenericMetadata, get_model_typevars_map
27from ._import_utils import import_cached_base_model, import_cached_field_info
28from ._mock_val_ser import set_model_mocks
29from ._namespace_utils import NsResolver
30from ._signature import generate_pydantic_signature
31from ._typing_extra import (
32 _make_forward_ref,
33 eval_type_backport,
34 is_classvar_annotation,
35 parent_frame_namespace,
36)
37from ._utils import LazyClassAttribute, SafeGetItemProxy
39if TYPE_CHECKING:
40 from ..fields import Field as PydanticModelField
41 from ..fields import FieldInfo, ModelPrivateAttr
42 from ..fields import PrivateAttr as PydanticModelPrivateAttr
43 from ..main import BaseModel
44else:
45 PydanticModelField = object()
46 PydanticModelPrivateAttr = object()
48object_setattr = object.__setattr__
51class _ModelNamespaceDict(dict):
52 """A dictionary subclass that intercepts attribute setting on model classes and
53 warns about overriding of decorators.
54 """
56 def __setitem__(self, k: str, v: object) -> None:
57 existing: Any = self.get(k, None)
58 if existing and v is not existing and isinstance(existing, PydanticDescriptorProxy):
59 warnings.warn(
60 f'`{k}` overrides an existing Pydantic `{existing.decorator_info.decorator_repr}` decorator',
61 stacklevel=2,
62 )
64 return super().__setitem__(k, v)
67def NoInitField(
68 *,
69 init: Literal[False] = False,
70) -> Any:
71 """Only for typing purposes. Used as default value of `__pydantic_fields_set__`,
72 `__pydantic_extra__`, `__pydantic_private__`, so they could be ignored when
73 synthesizing the `__init__` signature.
74 """
77# For ModelMetaclass.register():
78_T = TypeVar('_T')
81@dataclass_transform(kw_only_default=True, field_specifiers=(PydanticModelField, PydanticModelPrivateAttr, NoInitField))
82class ModelMetaclass(ABCMeta):
83 def __new__(
84 mcs,
85 cls_name: str,
86 bases: tuple[type[Any], ...],
87 namespace: dict[str, Any],
88 __pydantic_generic_metadata__: PydanticGenericMetadata | None = None,
89 __pydantic_reset_parent_namespace__: bool = True,
90 _create_model_module: str | None = None,
91 **kwargs: Any,
92 ) -> type:
93 """Metaclass for creating Pydantic models.
95 Args:
96 cls_name: The name of the class to be created.
97 bases: The base classes of the class to be created.
98 namespace: The attribute dictionary of the class to be created.
99 __pydantic_generic_metadata__: Metadata for generic models.
100 __pydantic_reset_parent_namespace__: Reset parent namespace.
101 _create_model_module: The module of the class to be created, if created by `create_model`.
102 **kwargs: Catch-all for any other keyword arguments.
104 Returns:
105 The new class created by the metaclass.
106 """
107 # Note `ModelMetaclass` refers to `BaseModel`, but is also used to *create* `BaseModel`, so we rely on the fact
108 # that `BaseModel` itself won't have any bases, but any subclass of it will, to determine whether the `__new__`
109 # call we're in the middle of is for the `BaseModel` class.
110 if bases:
111 raw_annotations: dict[str, Any]
112 if sys.version_info >= (3, 14):
113 if (
114 '__annotations__' in namespace
115 ): # `from __future__ import annotations` was used in the model's module
116 raw_annotations = namespace['__annotations__']
117 else:
118 # See https://docs.python.org/3.14/library/annotationlib.html#using-annotations-in-a-metaclass:
119 from annotationlib import Format, call_annotate_function, get_annotate_from_class_namespace
121 if annotate := get_annotate_from_class_namespace(namespace):
122 raw_annotations = call_annotate_function(annotate, format=Format.FORWARDREF)
123 else:
124 raw_annotations = {}
125 else:
126 raw_annotations = namespace.get('__annotations__', {})
128 base_field_names, class_vars, base_private_attributes = mcs._collect_bases_data(bases)
130 config_wrapper = ConfigWrapper.for_model(bases, namespace, raw_annotations, kwargs)
131 namespace['model_config'] = config_wrapper.config_dict
132 private_attributes = inspect_namespace(
133 namespace, raw_annotations, config_wrapper.ignored_types, class_vars, base_field_names
134 )
135 if private_attributes or base_private_attributes:
136 original_model_post_init = get_model_post_init(namespace, bases)
137 if original_model_post_init is not None:
138 # if there are private_attributes and a model_post_init function, we handle both
140 @wraps(original_model_post_init)
141 def wrapped_model_post_init(self: BaseModel, context: Any, /) -> None:
142 """We need to both initialize private attributes and call the user-defined model_post_init
143 method.
144 """
145 init_private_attributes(self, context)
146 original_model_post_init(self, context)
148 namespace['model_post_init'] = wrapped_model_post_init
149 else:
150 namespace['model_post_init'] = init_private_attributes
152 namespace['__class_vars__'] = class_vars
153 namespace['__private_attributes__'] = {**base_private_attributes, **private_attributes}
155 cls = cast('type[BaseModel]', super().__new__(mcs, cls_name, bases, namespace, **kwargs))
156 BaseModel_ = import_cached_base_model()
158 mro = cls.__mro__
159 if Generic in mro and mro.index(Generic) < mro.index(BaseModel_):
160 warnings.warn(
161 GenericBeforeBaseModelWarning(
162 'Classes should inherit from `BaseModel` before generic classes (e.g. `typing.Generic[T]`) '
163 'for pydantic generics to work properly.'
164 ),
165 stacklevel=2,
166 )
168 cls.__pydantic_custom_init__ = not getattr(cls.__init__, '__pydantic_base_init__', False)
169 cls.__pydantic_post_init__ = (
170 None if cls.model_post_init is BaseModel_.model_post_init else 'model_post_init'
171 )
173 cls.__pydantic_setattr_handlers__ = {}
175 cls.__pydantic_decorators__ = DecoratorInfos.build(cls)
176 cls.__pydantic_decorators__.update_from_config(config_wrapper)
178 # Use the getattr below to grab the __parameters__ from the `typing.Generic` parent class
179 if __pydantic_generic_metadata__:
180 cls.__pydantic_generic_metadata__ = __pydantic_generic_metadata__
181 else:
182 parent_parameters = getattr(cls, '__pydantic_generic_metadata__', {}).get('parameters', ())
183 parameters = getattr(cls, '__parameters__', None) or parent_parameters
184 if parameters and parent_parameters and not all(x in parameters for x in parent_parameters):
185 from ..root_model import RootModelRootType
187 missing_parameters = tuple(x for x in parameters if x not in parent_parameters)
188 if RootModelRootType in parent_parameters and RootModelRootType not in parameters:
189 # This is a special case where the user has subclassed `RootModel`, but has not parametrized
190 # RootModel with the generic type identifiers being used. Ex:
191 # class MyModel(RootModel, Generic[T]):
192 # root: T
193 # Should instead just be:
194 # class MyModel(RootModel[T]):
195 # root: T
196 parameters_str = ', '.join([x.__name__ for x in missing_parameters])
197 error_message = (
198 f'{cls.__name__} is a subclass of `RootModel`, but does not include the generic type identifier(s) '
199 f'{parameters_str} in its parameters. '
200 f'You should parametrize RootModel directly, e.g., `class {cls.__name__}(RootModel[{parameters_str}]): ...`.'
201 )
202 else:
203 combined_parameters = parent_parameters + missing_parameters
204 parameters_str = ', '.join([str(x) for x in combined_parameters])
205 generic_type_label = f'typing.Generic[{parameters_str}]'
206 error_message = (
207 f'All parameters must be present on typing.Generic;'
208 f' you should inherit from {generic_type_label}.'
209 )
210 if Generic not in bases: # pragma: no cover
211 # We raise an error here not because it is desirable, but because some cases are mishandled.
212 # It would be nice to remove this error and still have things behave as expected, it's just
213 # challenging because we are using a custom `__class_getitem__` to parametrize generic models,
214 # and not returning a typing._GenericAlias from it.
215 bases_str = ', '.join([x.__name__ for x in bases] + [generic_type_label])
216 error_message += (
217 f' Note: `typing.Generic` must go last: `class {cls.__name__}({bases_str}): ...`)'
218 )
219 raise TypeError(error_message)
221 cls.__pydantic_generic_metadata__ = {
222 'origin': None,
223 'args': (),
224 'parameters': parameters,
225 }
227 cls.__pydantic_complete__ = False # Ensure this specific class gets completed
229 # preserve `__set_name__` protocol defined in https://peps.python.org/pep-0487
230 # for attributes not in `new_namespace` (e.g. private attributes)
231 for name, obj in private_attributes.items():
232 obj.__set_name__(cls, name)
234 if __pydantic_reset_parent_namespace__:
235 cls.__pydantic_parent_namespace__ = build_lenient_weakvaluedict(parent_frame_namespace())
236 parent_namespace: dict[str, Any] | None = getattr(cls, '__pydantic_parent_namespace__', None)
237 if isinstance(parent_namespace, dict):
238 parent_namespace = unpack_lenient_weakvaluedict(parent_namespace)
240 ns_resolver = NsResolver(parent_namespace=parent_namespace)
242 set_model_fields(cls, config_wrapper=config_wrapper, ns_resolver=ns_resolver)
244 # This is also set in `complete_model_class()`, after schema gen because they are recreated.
245 # We set them here as well for backwards compatibility:
246 cls.__pydantic_computed_fields__ = {
247 k: v.info for k, v in cls.__pydantic_decorators__.computed_fields.items()
248 }
250 if config_wrapper.defer_build:
251 set_model_mocks(cls)
252 else:
253 # Any operation that requires accessing the field infos instances should be put inside
254 # `complete_model_class()`:
255 complete_model_class(
256 cls,
257 config_wrapper,
258 ns_resolver,
259 raise_errors=False,
260 create_model_module=_create_model_module,
261 )
263 if config_wrapper.frozen and '__hash__' not in namespace:
264 set_default_hash_func(cls, bases)
266 # using super(cls, cls) on the next line ensures we only call the parent class's __pydantic_init_subclass__
267 # I believe the `type: ignore` is only necessary because mypy doesn't realize that this code branch is
268 # only hit for _proper_ subclasses of BaseModel
269 super(cls, cls).__pydantic_init_subclass__(**kwargs) # type: ignore[misc]
270 return cls
271 else:
272 # These are instance variables, but have been assigned to `NoInitField` to trick the type checker.
273 for instance_slot in '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__':
274 namespace.pop(
275 instance_slot,
276 None, # In case the metaclass is used with a class other than `BaseModel`.
277 )
278 namespace.get('__annotations__', {}).clear()
279 return super().__new__(mcs, cls_name, bases, namespace, **kwargs)
281 if not TYPE_CHECKING: # pragma: no branch
282 # We put `__getattr__` in a non-TYPE_CHECKING block because otherwise, mypy allows arbitrary attribute access
284 def __getattr__(self, item: str) -> Any:
285 """This is necessary to keep attribute access working for class attribute access."""
286 private_attributes = self.__dict__.get('__private_attributes__')
287 if private_attributes and item in private_attributes:
288 return private_attributes[item]
289 raise AttributeError(item)
291 @classmethod
292 def __prepare__(cls, *args: Any, **kwargs: Any) -> dict[str, object]:
293 return _ModelNamespaceDict()
295 # Due to performance and memory issues, in the ABCMeta.__subclasscheck__ implementation, we don't support
296 # registered virtual subclasses. See https://github.com/python/cpython/issues/92810#issuecomment-2762454345.
297 # This may change once the CPython gets fixed (possibly in 3.15), in which case we should conditionally
298 # define `register()`.
299 def register(self, subclass: type[_T]) -> type[_T]:
300 warnings.warn(
301 f"For performance reasons, virtual subclasses registered using '{self.__qualname__}.register()' "
302 "are not supported in 'isinstance()' and 'issubclass()' checks.",
303 stacklevel=2,
304 )
305 return super().register(subclass)
307 __instancecheck__ = type.__instancecheck__ # pyright: ignore[reportAssignmentType]
308 __subclasscheck__ = type.__subclasscheck__ # pyright: ignore[reportAssignmentType]
310 @staticmethod
311 def _collect_bases_data(bases: tuple[type[Any], ...]) -> tuple[set[str], set[str], dict[str, ModelPrivateAttr]]:
312 BaseModel = import_cached_base_model()
314 field_names: set[str] = set()
315 class_vars: set[str] = set()
316 private_attributes: dict[str, ModelPrivateAttr] = {}
317 for base in bases:
318 if issubclass(base, BaseModel) and base is not BaseModel:
319 # model_fields might not be defined yet in the case of generics, so we use getattr here:
320 field_names.update(getattr(base, '__pydantic_fields__', {}).keys())
321 class_vars.update(base.__class_vars__)
322 private_attributes.update(base.__private_attributes__)
323 return field_names, class_vars, private_attributes
325 @property
326 @deprecated(
327 'The `__fields__` attribute is deprecated, use the `model_fields` class property instead.', category=None
328 )
329 def __fields__(self) -> dict[str, FieldInfo]:
330 warnings.warn(
331 'The `__fields__` attribute is deprecated, use the `model_fields` class property instead.',
332 PydanticDeprecatedSince20,
333 stacklevel=2,
334 )
335 return getattr(self, '__pydantic_fields__', {})
337 @property
338 def __pydantic_fields_complete__(self) -> bool:
339 """Whether the fields where successfully collected (i.e. type hints were successfully resolves).
341 This is a private attribute, not meant to be used outside Pydantic.
342 """
343 if not hasattr(self, '__pydantic_fields__'):
344 return False
346 field_infos = cast('dict[str, FieldInfo]', self.__pydantic_fields__) # pyright: ignore[reportAttributeAccessIssue]
348 return all(field_info._complete for field_info in field_infos.values())
350 def __dir__(self) -> list[str]:
351 attributes = list(super().__dir__())
352 if '__fields__' in attributes:
353 attributes.remove('__fields__')
354 return attributes
357def init_private_attributes(self: BaseModel, context: Any, /) -> None:
358 """This function is meant to behave like a BaseModel method to initialise private attributes.
360 It takes context as an argument since that's what pydantic-core passes when calling it.
362 Args:
363 self: The BaseModel instance.
364 context: The context.
365 """
366 if getattr(self, '__pydantic_private__', None) is None:
367 pydantic_private = {}
368 for name, private_attr in self.__private_attributes__.items():
369 default = private_attr.get_default()
370 if default is not PydanticUndefined:
371 pydantic_private[name] = default
372 object_setattr(self, '__pydantic_private__', pydantic_private)
375def get_model_post_init(namespace: dict[str, Any], bases: tuple[type[Any], ...]) -> Callable[..., Any] | None:
376 """Get the `model_post_init` method from the namespace or the class bases, or `None` if not defined."""
377 if 'model_post_init' in namespace:
378 return namespace['model_post_init']
380 BaseModel = import_cached_base_model()
382 model_post_init = get_attribute_from_bases(bases, 'model_post_init')
383 if model_post_init is not BaseModel.model_post_init:
384 return model_post_init
387def inspect_namespace( # noqa C901
388 namespace: dict[str, Any],
389 raw_annotations: dict[str, Any],
390 ignored_types: tuple[type[Any], ...],
391 base_class_vars: set[str],
392 base_class_fields: set[str],
393) -> dict[str, ModelPrivateAttr]:
394 """Iterate over the namespace and:
395 * gather private attributes
396 * check for items which look like fields but are not (e.g. have no annotation) and warn.
398 Args:
399 namespace: The attribute dictionary of the class to be created.
400 raw_annotations: The (non-evaluated) annotations of the model.
401 ignored_types: A tuple of ignore types.
402 base_class_vars: A set of base class class variables.
403 base_class_fields: A set of base class fields.
405 Returns:
406 A dict contains private attributes info.
408 Raises:
409 TypeError: If there is a `__root__` field in model.
410 NameError: If private attribute name is invalid.
411 PydanticUserError:
412 - If a field does not have a type annotation.
413 - If a field on base class was overridden by a non-annotated attribute.
414 """
415 from ..fields import ModelPrivateAttr, PrivateAttr
417 FieldInfo = import_cached_field_info()
419 all_ignored_types = ignored_types + default_ignored_types()
421 private_attributes: dict[str, ModelPrivateAttr] = {}
423 if '__root__' in raw_annotations or '__root__' in namespace:
424 raise TypeError("To define root models, use `pydantic.RootModel` rather than a field called '__root__'")
426 ignored_names: set[str] = set()
427 for var_name, value in list(namespace.items()):
428 if var_name == 'model_config' or var_name == '__pydantic_extra__':
429 continue
430 elif (
431 isinstance(value, type)
432 and value.__module__ == namespace['__module__']
433 and '__qualname__' in namespace
434 and value.__qualname__.startswith(f'{namespace["__qualname__"]}.')
435 ):
436 # `value` is a nested type defined in this namespace; don't error
437 continue
438 elif isinstance(value, all_ignored_types) or value.__class__.__module__ == 'functools':
439 ignored_names.add(var_name)
440 continue
441 elif isinstance(value, ModelPrivateAttr):
442 if var_name.startswith('__'):
443 raise NameError(
444 'Private attributes must not use dunder names;'
445 f' use a single underscore prefix instead of {var_name!r}.'
446 )
447 elif is_valid_field_name(var_name):
448 raise NameError(
449 'Private attributes must not use valid field names;'
450 f' use sunder names, e.g. {"_" + var_name!r} instead of {var_name!r}.'
451 )
452 private_attributes[var_name] = value
453 del namespace[var_name]
454 elif isinstance(value, FieldInfo) and not is_valid_field_name(var_name):
455 suggested_name = var_name.lstrip('_') or 'my_field' # don't suggest '' for all-underscore name
456 raise NameError(
457 f'Fields must not use names with leading underscores;'
458 f' e.g., use {suggested_name!r} instead of {var_name!r}.'
459 )
461 elif var_name.startswith('__'):
462 continue
463 elif is_valid_privateattr_name(var_name):
464 if var_name not in raw_annotations or not is_classvar_annotation(raw_annotations[var_name]):
465 private_attributes[var_name] = cast(ModelPrivateAttr, PrivateAttr(default=value))
466 del namespace[var_name]
467 elif var_name in base_class_vars:
468 continue
469 elif var_name not in raw_annotations:
470 if var_name in base_class_fields:
471 raise PydanticUserError(
472 f'Field {var_name!r} defined on a base class was overridden by a non-annotated attribute. '
473 f'All field definitions, including overrides, require a type annotation.',
474 code='model-field-overridden',
475 )
476 elif isinstance(value, FieldInfo):
477 raise PydanticUserError(
478 f'Field {var_name!r} requires a type annotation', code='model-field-missing-annotation'
479 )
480 else:
481 raise PydanticUserError(
482 f'A non-annotated attribute was detected: `{var_name} = {value!r}`. All model fields require a '
483 f'type annotation; if `{var_name}` is not meant to be a field, you may be able to resolve this '
484 f"error by annotating it as a `ClassVar` or updating `model_config['ignored_types']`.",
485 code='model-field-missing-annotation',
486 )
488 for ann_name, ann_type in raw_annotations.items():
489 if (
490 is_valid_privateattr_name(ann_name)
491 and ann_name not in private_attributes
492 and ann_name not in ignored_names
493 # This condition can be a false negative when `ann_type` is stringified,
494 # but it is handled in most cases in `set_model_fields`:
495 and not is_classvar_annotation(ann_type)
496 and ann_type not in all_ignored_types
497 and getattr(ann_type, '__module__', None) != 'functools'
498 ):
499 if isinstance(ann_type, str):
500 # Walking up the frames to get the module namespace where the model is defined
501 # (as the model class wasn't created yet, we unfortunately can't use `cls.__module__`):
502 frame = sys._getframe(2)
503 if frame is not None:
504 try:
505 ann_type = eval_type_backport(
506 _make_forward_ref(ann_type, is_argument=False, is_class=True),
507 globalns=frame.f_globals,
508 localns=frame.f_locals,
509 )
510 except (NameError, TypeError):
511 pass
513 if typing_objects.is_annotated(get_origin(ann_type)):
514 _, *metadata = get_args(ann_type)
515 private_attr = next((v for v in metadata if isinstance(v, ModelPrivateAttr)), None)
516 if private_attr is not None:
517 private_attributes[ann_name] = private_attr
518 continue
519 private_attributes[ann_name] = PrivateAttr()
521 return private_attributes
524def set_default_hash_func(cls: type[BaseModel], bases: tuple[type[Any], ...]) -> None:
525 base_hash_func = get_attribute_from_bases(bases, '__hash__')
526 new_hash_func = make_hash_func(cls)
527 if base_hash_func in {None, object.__hash__} or getattr(base_hash_func, '__code__', None) == new_hash_func.__code__:
528 # If `__hash__` is some default, we generate a hash function.
529 # It will be `None` if not overridden from BaseModel.
530 # It may be `object.__hash__` if there is another
531 # parent class earlier in the bases which doesn't override `__hash__` (e.g. `typing.Generic`).
532 # It may be a value set by `set_default_hash_func` if `cls` is a subclass of another frozen model.
533 # In the last case we still need a new hash function to account for new `model_fields`.
534 cls.__hash__ = new_hash_func
537def make_hash_func(cls: type[BaseModel]) -> Any:
538 getter = operator.itemgetter(*cls.__pydantic_fields__.keys()) if cls.__pydantic_fields__ else lambda _: 0
540 def hash_func(self: Any) -> int:
541 try:
542 return hash(getter(self.__dict__))
543 except KeyError:
544 # In rare cases (such as when using the deprecated copy method), the __dict__ may not contain
545 # all model fields, which is how we can get here.
546 # getter(self.__dict__) is much faster than any 'safe' method that accounts for missing keys,
547 # and wrapping it in a `try` doesn't slow things down much in the common case.
548 return hash(getter(SafeGetItemProxy(self.__dict__)))
550 return hash_func
553def set_model_fields(
554 cls: type[BaseModel],
555 config_wrapper: ConfigWrapper,
556 ns_resolver: NsResolver | None,
557) -> None:
558 """Collect and set `cls.__pydantic_fields__` and `cls.__class_vars__`.
560 Args:
561 cls: BaseModel or dataclass.
562 config_wrapper: The config wrapper instance.
563 ns_resolver: Namespace resolver to use when getting model annotations.
564 """
565 typevars_map = get_model_typevars_map(cls)
566 fields, class_vars = collect_model_fields(cls, config_wrapper, ns_resolver, typevars_map=typevars_map)
568 cls.__pydantic_fields__ = fields
569 cls.__class_vars__.update(class_vars)
571 for k in class_vars:
572 # Class vars should not be private attributes
573 # We remove them _here_ and not earlier because we rely on inspecting the class to determine its classvars,
574 # but private attributes are determined by inspecting the namespace _prior_ to class creation.
575 # In the case that a classvar with a leading-'_' is defined via a ForwardRef (e.g., when using
576 # `__future__.annotations`), we want to remove the private attribute which was detected _before_ we knew it
577 # evaluated to a classvar
579 value = cls.__private_attributes__.pop(k, None)
580 if value is not None and value.default is not PydanticUndefined:
581 setattr(cls, k, value.default)
584def complete_model_class(
585 cls: type[BaseModel],
586 config_wrapper: ConfigWrapper,
587 ns_resolver: NsResolver,
588 *,
589 raise_errors: bool = True,
590 call_on_complete_hook: bool = True,
591 create_model_module: str | None = None,
592) -> bool:
593 """Finish building a model class.
595 This logic must be called after class has been created since validation functions must be bound
596 and `get_type_hints` requires a class object.
598 Args:
599 cls: BaseModel or dataclass.
600 config_wrapper: The config wrapper instance.
601 ns_resolver: The namespace resolver instance to use during schema building.
602 raise_errors: Whether to raise errors.
603 call_on_complete_hook: Whether to call the `__pydantic_on_complete__` hook.
604 create_model_module: The module of the class to be created, if created by `create_model`.
606 Returns:
607 `True` if the model is successfully completed, else `False`.
609 Raises:
610 PydanticUndefinedAnnotation: If `PydanticUndefinedAnnotation` occurs in`__get_pydantic_core_schema__`
611 and `raise_errors=True`.
612 """
613 typevars_map = get_model_typevars_map(cls)
615 if not cls.__pydantic_fields_complete__:
616 # Note: when coming from `ModelMetaclass.__new__()`, this results in fields being built twice.
617 # We do so a second time here so that we can get the `NameError` for the specific undefined annotation.
618 # Alternatively, we could let `GenerateSchema()` raise the error, but there are cases where incomplete
619 # fields are inherited in `collect_model_fields()` and can actually have their annotation resolved in the
620 # generate schema process. As we want to avoid having `__pydantic_fields_complete__` set to `False`
621 # when `__pydantic_complete__` is `True`, we rebuild here:
622 try:
623 cls.__pydantic_fields__ = rebuild_model_fields(
624 cls,
625 config_wrapper=config_wrapper,
626 ns_resolver=ns_resolver,
627 typevars_map=typevars_map,
628 )
629 except NameError as e:
630 exc = PydanticUndefinedAnnotation.from_name_error(e)
631 set_model_mocks(cls, f'`{exc.name}`')
632 if raise_errors:
633 raise exc from e
635 if not raise_errors and not cls.__pydantic_fields_complete__:
636 # No need to continue with schema gen, it is guaranteed to fail
637 return False
639 assert cls.__pydantic_fields_complete__
641 gen_schema = GenerateSchema(
642 config_wrapper,
643 ns_resolver,
644 typevars_map,
645 )
647 try:
648 schema = gen_schema.generate_schema(cls)
649 except PydanticUndefinedAnnotation as e:
650 if raise_errors:
651 raise
652 set_model_mocks(cls, f'`{e.name}`')
653 return False
655 core_config = config_wrapper.core_config(title=cls.__name__)
657 try:
658 schema = gen_schema.clean_schema(schema)
659 except InvalidSchemaError:
660 set_model_mocks(cls)
661 return False
663 # This needs to happen *after* model schema generation, as the return type
664 # of the properties are evaluated and the `ComputedFieldInfo` are recreated:
665 cls.__pydantic_computed_fields__ = {k: v.info for k, v in cls.__pydantic_decorators__.computed_fields.items()}
667 set_deprecated_descriptors(cls)
669 cls.__pydantic_core_schema__ = schema
671 cls.__pydantic_validator__ = create_schema_validator(
672 schema,
673 cls,
674 create_model_module or cls.__module__,
675 cls.__qualname__,
676 'create_model' if create_model_module else 'BaseModel',
677 core_config,
678 config_wrapper.plugin_settings,
679 )
680 cls.__pydantic_serializer__ = SchemaSerializer(schema, core_config)
682 # set __signature__ attr only for model class, but not for its instances
683 # (because instances can define `__call__`, and `inspect.signature` shouldn't
684 # use the `__signature__` attribute and instead generate from `__call__`).
685 cls.__signature__ = LazyClassAttribute(
686 '__signature__',
687 partial(
688 generate_pydantic_signature,
689 init=cls.__init__,
690 fields=cls.__pydantic_fields__,
691 validate_by_name=config_wrapper.validate_by_name,
692 extra=config_wrapper.extra,
693 ),
694 )
696 cls.__pydantic_complete__ = True
698 if call_on_complete_hook:
699 cls.__pydantic_on_complete__()
701 return True
704def set_deprecated_descriptors(cls: type[BaseModel]) -> None:
705 """Set data descriptors on the class for deprecated fields."""
706 for field, field_info in cls.__pydantic_fields__.items():
707 if (msg := field_info.deprecation_message) is not None:
708 desc = _DeprecatedFieldDescriptor(msg)
709 desc.__set_name__(cls, field)
710 setattr(cls, field, desc)
712 for field, computed_field_info in cls.__pydantic_computed_fields__.items():
713 if (
714 (msg := computed_field_info.deprecation_message) is not None
715 # Avoid having two warnings emitted:
716 and not hasattr(unwrap_wrapped_function(computed_field_info.wrapped_property), '__deprecated__')
717 ):
718 desc = _DeprecatedFieldDescriptor(msg, computed_field_info.wrapped_property)
719 desc.__set_name__(cls, field)
720 setattr(cls, field, desc)
723class _DeprecatedFieldDescriptor:
724 """Read-only data descriptor used to emit a runtime deprecation warning before accessing a deprecated field.
726 Attributes:
727 msg: The deprecation message to be emitted.
728 wrapped_property: The property instance if the deprecated field is a computed field, or `None`.
729 field_name: The name of the field being deprecated.
730 """
732 field_name: str
734 def __init__(self, msg: str, wrapped_property: property | None = None) -> None:
735 self.msg = msg
736 self.wrapped_property = wrapped_property
738 def __set_name__(self, cls: type[BaseModel], name: str) -> None:
739 self.field_name = name
741 def __get__(self, obj: BaseModel | None, obj_type: type[BaseModel] | None = None) -> Any:
742 if obj is None:
743 if self.wrapped_property is not None:
744 return self.wrapped_property.__get__(None, obj_type)
745 raise AttributeError(self.field_name)
747 warnings.warn(self.msg, DeprecationWarning, stacklevel=2)
749 if self.wrapped_property is not None:
750 return self.wrapped_property.__get__(obj, obj_type)
751 return obj.__dict__[self.field_name]
753 # Defined to make it a data descriptor and take precedence over the instance's dictionary.
754 # Note that it will not be called when setting a value on a model instance
755 # as `BaseModel.__setattr__` is defined and takes priority.
756 def __set__(self, obj: Any, value: Any) -> NoReturn:
757 raise AttributeError(self.field_name)
760class _PydanticWeakRef:
761 """Wrapper for `weakref.ref` that enables `pickle` serialization.
763 Cloudpickle fails to serialize `weakref.ref` objects due to an arcane error related
764 to abstract base classes (`abc.ABC`). This class works around the issue by wrapping
765 `weakref.ref` instead of subclassing it.
767 See https://github.com/pydantic/pydantic/issues/6763 for context.
769 Semantics:
770 - If not pickled, behaves the same as a `weakref.ref`.
771 - If pickled along with the referenced object, the same `weakref.ref` behavior
772 will be maintained between them after unpickling.
773 - If pickled without the referenced object, after unpickling the underlying
774 reference will be cleared (`__call__` will always return `None`).
775 """
777 def __init__(self, obj: Any):
778 if obj is None:
779 # The object will be `None` upon deserialization if the serialized weakref
780 # had lost its underlying object.
781 self._wr = None
782 else:
783 self._wr = weakref.ref(obj)
785 def __call__(self) -> Any:
786 if self._wr is None:
787 return None
788 else:
789 return self._wr()
791 def __reduce__(self) -> tuple[Callable, tuple[weakref.ReferenceType | None]]:
792 return _PydanticWeakRef, (self(),)
795def build_lenient_weakvaluedict(d: dict[str, Any] | None) -> dict[str, Any] | None:
796 """Takes an input dictionary, and produces a new value that (invertibly) replaces the values with weakrefs.
798 We can't just use a WeakValueDictionary because many types (including int, str, etc.) can't be stored as values
799 in a WeakValueDictionary.
801 The `unpack_lenient_weakvaluedict` function can be used to reverse this operation.
802 """
803 if d is None:
804 return None
805 result = {}
806 for k, v in d.items():
807 try:
808 proxy = _PydanticWeakRef(v)
809 except TypeError:
810 proxy = v
811 result[k] = proxy
812 return result
815def unpack_lenient_weakvaluedict(d: dict[str, Any] | None) -> dict[str, Any] | None:
816 """Inverts the transform performed by `build_lenient_weakvaluedict`."""
817 if d is None:
818 return None
820 result = {}
821 for k, v in d.items():
822 if isinstance(v, _PydanticWeakRef):
823 v = v()
824 if v is not None:
825 result[k] = v
826 else:
827 result[k] = v
828 return result
831@cache
832def default_ignored_types() -> tuple[type[Any], ...]:
833 from ..fields import ComputedFieldInfo
835 ignored_types = [
836 FunctionType,
837 property,
838 classmethod,
839 staticmethod,
840 PydanticDescriptorProxy,
841 ComputedFieldInfo,
842 TypeAliasType, # from `typing_extensions`
843 ]
845 if sys.version_info >= (3, 12):
846 ignored_types.append(typing.TypeAliasType)
848 return tuple(ignored_types)