Coverage for pydantic/type_adapter.py: 99.17%
162 statements
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1"""Type adapter specification."""
3from __future__ import annotations as _annotations 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
5import sys 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
6from contextlib import contextmanager 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
7from dataclasses import is_dataclass 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
8from functools import cached_property, wraps 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
9from typing import ( 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
10 TYPE_CHECKING,
11 Any,
12 Callable,
13 Dict,
14 Generic,
15 Iterable,
16 Iterator,
17 Literal,
18 Set,
19 TypeVar,
20 Union,
21 cast,
22 final,
23 overload,
24)
26from pydantic_core import CoreSchema, SchemaSerializer, SchemaValidator, Some 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
27from typing_extensions import Concatenate, ParamSpec, is_typeddict 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
29from pydantic.errors import PydanticUserError 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
30from pydantic.main import BaseModel 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
32from ._internal import _config, _generate_schema, _mock_val_ser, _typing_extra, _utils 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
33from .config import ConfigDict 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
34from .json_schema import ( 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
35 DEFAULT_REF_TEMPLATE,
36 GenerateJsonSchema,
37 JsonSchemaKeyT,
38 JsonSchemaMode,
39 JsonSchemaValue,
40)
41from .plugin._schema_validator import create_schema_validator 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
43T = TypeVar('T') 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
44R = TypeVar('R') 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
45P = ParamSpec('P') 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
46TypeAdapterT = TypeVar('TypeAdapterT', bound='TypeAdapter') 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
49if TYPE_CHECKING: 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
50 # should be `set[int] | set[str] | dict[int, IncEx] | dict[str, IncEx] | None`, but mypy can't cope
51 IncEx = Union[Set[int], Set[str], Dict[int, Any], Dict[str, Any]]
54def _get_schema(type_: Any, config_wrapper: _config.ConfigWrapper, parent_depth: int) -> CoreSchema: 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
55 """`BaseModel` uses its own `__module__` to find out where it was defined
56 and then looks for symbols to resolve forward references in those globals.
57 On the other hand this function can be called with arbitrary objects,
58 including type aliases, where `__module__` (always `typing.py`) is not useful.
59 So instead we look at the globals in our parent stack frame.
61 This works for the case where this function is called in a module that
62 has the target of forward references in its scope, but
63 does not always work for more complex cases.
65 For example, take the following:
67 a.py
68 ```python
69 from typing import Dict, List
71 IntList = List[int]
72 OuterDict = Dict[str, 'IntList']
73 ```
75 b.py
76 ```python test="skip"
77 from a import OuterDict
79 from pydantic import TypeAdapter
81 IntList = int # replaces the symbol the forward reference is looking for
82 v = TypeAdapter(OuterDict)
83 v({'x': 1}) # should fail but doesn't
84 ```
86 If `OuterDict` were a `BaseModel`, this would work because it would resolve
87 the forward reference within the `a.py` namespace.
88 But `TypeAdapter(OuterDict)` can't determine what module `OuterDict` came from.
90 In other words, the assumption that _all_ forward references exist in the
91 module we are being called from is not technically always true.
92 Although most of the time it is and it works fine for recursive models and such,
93 `BaseModel`'s behavior isn't perfect either and _can_ break in similar ways,
94 so there is no right or wrong between the two.
96 But at the very least this behavior is _subtly_ different from `BaseModel`'s.
97 """
98 local_ns = _typing_extra.parent_frame_namespace(parent_depth=parent_depth) 1ijklmnopabcdqrstuvwxefyzABCDEFgh
99 global_ns = sys._getframe(max(parent_depth - 1, 1)).f_globals.copy() 1ijklmnopabcdqrstuvwxefyzABCDEFgh
100 global_ns.update(local_ns or {}) 1ijklmnopabcdqrstuvwxefyzABCDEFgh
101 gen = _generate_schema.GenerateSchema(config_wrapper, types_namespace=global_ns, typevars_map={}) 1ijklmnopabcdqrstuvwxefyzABCDEFgh
102 schema = gen.generate_schema(type_) 1ijklmnopabcdqrstuvwxefyzABCDEFgh
103 schema = gen.clean_schema(schema) 1ijklmnopabcdqrstuvwxefyzABCDEFgh
104 return schema 1ijklmnopabcdqrstuvwxefyzABCDEFgh
107def _getattr_no_parents(obj: Any, attribute: str) -> Any: 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
108 """Returns the attribute value without attempting to look up attributes from parent types."""
109 if hasattr(obj, '__dict__'): 1ijklmnopabcdqrstuvwxefyzABCDEFgh
110 try: 1ijklmnopabcdqrstuvwxefyzABCDEFgh
111 return obj.__dict__[attribute] 1ijklmnopabcdqrstuvwxefyzABCDEFgh
112 except KeyError: 1ijklmnopabcdqrstuvwxefyzABCDEFgh
113 pass 1ijklmnopabcdqrstuvwxefyzABCDEFgh
115 slots = getattr(obj, '__slots__', None) 1ijklmnopabcdqrstuvwxefyzABCDEFgh
116 if slots is not None and attribute in slots: 116 ↛ 117line 116 didn't jump to line 117, because the condition on line 116 was never true1ijklmnopabcdqrstuvwxefyzABCDEFgh
117 return getattr(obj, attribute)
118 else:
119 raise AttributeError(attribute) 1ijklmnopabcdqrstuvwxefyzABCDEFgh
122def _type_has_config(type_: Any) -> bool: 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
123 """Returns whether the type has config."""
124 type_ = _typing_extra.annotated_type(type_) or type_ 1ijklmnopabcdqrstuvwxefyzABCDEFgh
125 try: 1ijklmnopabcdqrstuvwxefyzABCDEFgh
126 return issubclass(type_, BaseModel) or is_dataclass(type_) or is_typeddict(type_) 1ijklmnopabcdqrstuvwxefyzABCDEFgh
127 except TypeError: 1ijklmnopabcdqrstuvwxefyzABCDEFgh
128 # type is not a class
129 return False 1ijklmnopabcdqrstuvwxefyzABCDEFgh
132# This is keeping track of the frame depth for the TypeAdapter functions. This is required for _parent_depth used for
133# ForwardRef resolution. We may enter the TypeAdapter schema building via different TypeAdapter functions. Hence, we
134# need to keep track of the frame depth relative to the originally provided _parent_depth.
135def _frame_depth( 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
136 depth: int,
137) -> Callable[[Callable[Concatenate[TypeAdapterT, P], R]], Callable[Concatenate[TypeAdapterT, P], R]]:
138 def wrapper(func: Callable[Concatenate[TypeAdapterT, P], R]) -> Callable[Concatenate[TypeAdapterT, P], R]: 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
139 @wraps(func) 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
140 def wrapped(self: TypeAdapterT, *args: P.args, **kwargs: P.kwargs) -> R: 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
141 with self._with_frame_depth(depth + 1): # depth + 1 for the wrapper function 1ijklmnopabcdqrstuvwxefyzABCDEFgh
142 return func(self, *args, **kwargs) 1ijklmnopabcdqrstuvwxefyzABCDEFgh
144 return wrapped 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
146 return wrapper 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
149@final 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
150class TypeAdapter(Generic[T]): 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
151 """Usage docs: https://docs.pydantic.dev/2.8/concepts/type_adapter/
153 Type adapters provide a flexible way to perform validation and serialization based on a Python type.
155 A `TypeAdapter` instance exposes some of the functionality from `BaseModel` instance methods
156 for types that do not have such methods (such as dataclasses, primitive types, and more).
158 **Note:** `TypeAdapter` instances are not types, and cannot be used as type annotations for fields.
160 **Note:** By default, `TypeAdapter` does not respect the
161 [`defer_build=True`][pydantic.config.ConfigDict.defer_build] setting in the
162 [`model_config`][pydantic.BaseModel.model_config] or in the `TypeAdapter` constructor `config`. You need to also
163 explicitly set [`experimental_defer_build_mode=('model', 'type_adapter')`][pydantic.config.ConfigDict.experimental_defer_build_mode] of the
164 config to defer the model validator and serializer construction. Thus, this feature is opt-in to ensure backwards
165 compatibility.
167 Attributes:
168 core_schema: The core schema for the type.
169 validator (SchemaValidator): The schema validator for the type.
170 serializer: The schema serializer for the type.
171 """
173 @overload 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
174 def __init__( 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
175 self,
176 type: type[T], 1abcdefGgh
177 *,
178 config: ConfigDict | None = ..., 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
179 _parent_depth: int = ..., 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
180 module: str | None = ..., 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
181 ) -> None: ... 1abcdefGgh
183 # This second overload is for unsupported special forms (such as Annotated, Union, etc.)
184 # Currently there is no way to type this correctly
185 # See https://github.com/python/typing/pull/1618
186 @overload 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
187 def __init__( 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
188 self,
189 type: Any, 1abcdefGgh
190 *,
191 config: ConfigDict | None = ..., 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
192 _parent_depth: int = ..., 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
193 module: str | None = ..., 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
194 ) -> None: ... 1abcdefGgh
196 def __init__( 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
197 self,
198 type: Any,
199 *,
200 config: ConfigDict | None = None,
201 _parent_depth: int = 2,
202 module: str | None = None,
203 ) -> None:
204 """Initializes the TypeAdapter object.
206 Args:
207 type: The type associated with the `TypeAdapter`.
208 config: Configuration for the `TypeAdapter`, should be a dictionary conforming to [`ConfigDict`][pydantic.config.ConfigDict].
209 _parent_depth: depth at which to search the parent namespace to construct the local namespace.
210 module: The module that passes to plugin if provided.
212 !!! note
213 You cannot use the `config` argument when instantiating a `TypeAdapter` if the type you're using has its own
214 config that cannot be overridden (ex: `BaseModel`, `TypedDict`, and `dataclass`). A
215 [`type-adapter-config-unused`](../errors/usage_errors.md#type-adapter-config-unused) error will be raised in this case.
217 !!! note
218 The `_parent_depth` argument is named with an underscore to suggest its private nature and discourage use.
219 It may be deprecated in a minor version, so we only recommend using it if you're
220 comfortable with potential change in behavior / support.
222 ??? tip "Compatibility with `mypy`"
223 Depending on the type used, `mypy` might raise an error when instantiating a `TypeAdapter`. As a workaround, you can explicitly
224 annotate your variable:
226 ```py
227 from typing import Union
229 from pydantic import TypeAdapter
231 ta: TypeAdapter[Union[str, int]] = TypeAdapter(Union[str, int]) # type: ignore[arg-type]
232 ```
234 Returns:
235 A type adapter configured for the specified `type`.
236 """
237 if _type_has_config(type) and config is not None: 1ijklmnopabcdqrstuvwxefyzABCDEFgh
238 raise PydanticUserError( 1ijklmnopabcdqrstuvwxefyzABCDEFgh
239 'Cannot use `config` when the type is a BaseModel, dataclass or TypedDict.'
240 ' These types can have their own config and setting the config via the `config`'
241 ' parameter to TypeAdapter will not override it, thus the `config` you passed to'
242 ' TypeAdapter becomes meaningless, which is probably not what you want.',
243 code='type-adapter-config-unused',
244 )
246 self._type = type 1ijklmnopabcdqrstuvwxefyzABCDEFgh
247 self._config = config 1ijklmnopabcdqrstuvwxefyzABCDEFgh
248 self._parent_depth = _parent_depth 1ijklmnopabcdqrstuvwxefyzABCDEFgh
249 if module is None: 1ijklmnopabcdqrstuvwxefyzABCDEFgh
250 f = sys._getframe(1) 1ijklmnopabcdqrstuvwxefyzABCDEFgh
251 self._module_name = cast(str, f.f_globals.get('__name__', '')) 1ijklmnopabcdqrstuvwxefyzABCDEFgh
252 else:
253 self._module_name = module 1ijklmnopabcdqrstuvwxefyzABCDEFgh
255 self._core_schema: CoreSchema | None = None 1ijklmnopabcdqrstuvwxefyzABCDEFgh
256 self._validator: SchemaValidator | None = None 1ijklmnopabcdqrstuvwxefyzABCDEFgh
257 self._serializer: SchemaSerializer | None = None 1ijklmnopabcdqrstuvwxefyzABCDEFgh
259 if not self._defer_build(): 1ijklmnopabcdqrstuvwxefyzABCDEFgh
260 # Immediately initialize the core schema, validator and serializer
261 with self._with_frame_depth(1): # +1 frame depth for this __init__ 1ijklmnopabcdqrstuvwxefyzABCDEFgh
262 # Model itself may be using deferred building. For backward compatibility we don't rebuild model mocks
263 # here as part of __init__ even though TypeAdapter itself is not using deferred building.
264 self._init_core_attrs(rebuild_mocks=False) 1ijklmnopabcdqrstuvwxefyzABCDEFgh
266 @contextmanager 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
267 def _with_frame_depth(self, depth: int) -> Iterator[None]: 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
268 self._parent_depth += depth 1ijklmnopabcdqrstuvwxefyzABCDEFgh
269 try: 1ijklmnopabcdqrstuvwxefyzABCDEFgh
270 yield 1ijklmnopabcdqrstuvwxefyzABCDEFgh
271 finally:
272 self._parent_depth -= depth 1ijklmnopabcdqrstuvwxefyzABCDEFgh
274 @_frame_depth(1) 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
275 def _init_core_attrs(self, rebuild_mocks: bool) -> None: 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
276 try: 1ijklmnopabcdqrstuvwxefyzABCDEFgh
277 self._core_schema = _getattr_no_parents(self._type, '__pydantic_core_schema__') 1ijklmnopabcdqrstuvwxefyzABCDEFgh
278 self._validator = _getattr_no_parents(self._type, '__pydantic_validator__') 1ijklmnopabcdqrstuvwxefyzABCDEFgh
279 self._serializer = _getattr_no_parents(self._type, '__pydantic_serializer__') 1ijklmnopabcdqrstuvwxefyzABCDEFgh
280 except AttributeError: 1ijklmnopabcdqrstuvwxefyzABCDEFgh
281 config_wrapper = _config.ConfigWrapper(self._config) 1ijklmnopabcdqrstuvwxefyzABCDEFgh
282 core_config = config_wrapper.core_config(None) 1ijklmnopabcdqrstuvwxefyzABCDEFgh
284 self._core_schema = _get_schema(self._type, config_wrapper, parent_depth=self._parent_depth) 1ijklmnopabcdqrstuvwxefyzABCDEFgh
285 self._validator = create_schema_validator( 1ijklmnopabcdqrstuvwxefyzABCDEFgh
286 schema=self._core_schema,
287 schema_type=self._type,
288 schema_type_module=self._module_name,
289 schema_type_name=str(self._type),
290 schema_kind='TypeAdapter',
291 config=core_config,
292 plugin_settings=config_wrapper.plugin_settings,
293 )
294 self._serializer = SchemaSerializer(self._core_schema, core_config) 1ijklmnopabcdqrstuvwxefyzABCDEFgh
296 if rebuild_mocks and isinstance(self._core_schema, _mock_val_ser.MockCoreSchema): 1ijklmnopabcdqrstuvwxefyzABCDEFgh
297 self._core_schema.rebuild() 1ijklmnopabcdqrstuvwxefyzABCDEFgh
298 self._init_core_attrs(rebuild_mocks=False) 1ijklmnopabcdqrstuvwxefyzABCDEFgh
299 assert not isinstance(self._core_schema, _mock_val_ser.MockCoreSchema) 1ijklmnopabcdqrstuvwxefyzABCDEFgh
300 assert not isinstance(self._validator, _mock_val_ser.MockValSer) 1ijklmnopabcdqrstuvwxefyzABCDEFgh
301 assert not isinstance(self._serializer, _mock_val_ser.MockValSer) 1ijklmnopabcdqrstuvwxefyzABCDEFgh
303 @cached_property 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
304 @_frame_depth(2) # +2 for @cached_property and core_schema(self) 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
305 def core_schema(self) -> CoreSchema: 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
306 """The pydantic-core schema used to build the SchemaValidator and SchemaSerializer."""
307 if self._core_schema is None or isinstance(self._core_schema, _mock_val_ser.MockCoreSchema): 1ijklmnopabcdqrstuvwxefyzABCDEFgh
308 self._init_core_attrs(rebuild_mocks=True) # Do not expose MockCoreSchema from public function 1ijklmnopabcdqrstuvwxefyzABCDEFgh
309 assert self._core_schema is not None and not isinstance(self._core_schema, _mock_val_ser.MockCoreSchema) 1ijklmnopabcdqrstuvwxefyzABCDEFgh
310 return self._core_schema 1ijklmnopabcdqrstuvwxefyzABCDEFgh
312 @cached_property 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
313 @_frame_depth(2) # +2 for @cached_property + validator(self) 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
314 def validator(self) -> SchemaValidator: 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
315 """The pydantic-core SchemaValidator used to validate instances of the model."""
316 if not isinstance(self._validator, SchemaValidator): 1ijklmnopabcdqrstuvwxefyzABCDEFgh
317 self._init_core_attrs(rebuild_mocks=True) # Do not expose MockValSer from public function 1ijklmnopabcdqrstuvwxefyzABCDEFgh
318 assert isinstance(self._validator, SchemaValidator) 1ijklmnopabcdqrstuvwxefyzABCDEFgh
319 return self._validator 1ijklmnopabcdqrstuvwxefyzABCDEFgh
321 @cached_property 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
322 @_frame_depth(2) # +2 for @cached_property + serializer(self) 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
323 def serializer(self) -> SchemaSerializer: 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
324 """The pydantic-core SchemaSerializer used to dump instances of the model."""
325 if not isinstance(self._serializer, SchemaSerializer): 1ijklmnopabcdqrstuvwxefyzABCDEFgh
326 self._init_core_attrs(rebuild_mocks=True) # Do not expose MockValSer from public function 1ijklmnopabcdqrstuvwxefyzABCDEFgh
327 assert isinstance(self._serializer, SchemaSerializer) 1ijklmnopabcdqrstuvwxefyzABCDEFgh
328 return self._serializer 1ijklmnopabcdqrstuvwxefyzABCDEFgh
330 def _defer_build(self) -> bool: 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
331 config = self._config if self._config is not None else self._model_config() 1ijklmnopabcdqrstuvwxefyzABCDEFgh
332 return self._is_defer_build_config(config) if config is not None else False 1ijklmnopabcdqrstuvwxefyzABCDEFgh
334 def _model_config(self) -> ConfigDict | None: 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
335 type_: Any = _typing_extra.annotated_type(self._type) or self._type # Eg FastAPI heavily uses Annotated 1ijklmnopabcdqrstuvwxefyzABCDEFgh
336 if _utils.lenient_issubclass(type_, BaseModel): 1ijklmnopabcdqrstuvwxefyzABCDEFgh
337 return type_.model_config 1ijklmnopabcdqrstuvwxefyzABCDEFgh
338 return getattr(type_, '__pydantic_config__', None) 1ijklmnopabcdqrstuvwxefyzABCDEFgh
340 @staticmethod 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
341 def _is_defer_build_config(config: ConfigDict) -> bool: 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
342 # TODO reevaluate this logic when we have a better understanding of how defer_build should work with TypeAdapter
343 # Should we drop the special experimental_defer_build_mode check?
344 return config.get('defer_build', False) is True and 'type_adapter' in config.get( 1ijklmnopabcdqrstuvwxefyzABCDEFgh
345 'experimental_defer_build_mode', tuple()
346 )
348 @_frame_depth(1) 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
349 def validate_python( 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
350 self,
351 object: Any,
352 /,
353 *,
354 strict: bool | None = None,
355 from_attributes: bool | None = None,
356 context: dict[str, Any] | None = None,
357 ) -> T:
358 """Validate a Python object against the model.
360 Args:
361 object: The Python object to validate against the model.
362 strict: Whether to strictly check types.
363 from_attributes: Whether to extract data from object attributes.
364 context: Additional context to pass to the validator.
366 !!! note
367 When using `TypeAdapter` with a Pydantic `dataclass`, the use of the `from_attributes`
368 argument is not supported.
370 Returns:
371 The validated object.
372 """
373 return self.validator.validate_python(object, strict=strict, from_attributes=from_attributes, context=context) 1ijklmnopabcdqrstuvwxefyzABCDEFgh
375 @_frame_depth(1) 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
376 def validate_json( 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
377 self, data: str | bytes, /, *, strict: bool | None = None, context: dict[str, Any] | None = None
378 ) -> T:
379 """Usage docs: https://docs.pydantic.dev/2.8/concepts/json/#json-parsing
381 Validate a JSON string or bytes against the model.
383 Args:
384 data: The JSON data to validate against the model.
385 strict: Whether to strictly check types.
386 context: Additional context to use during validation.
388 Returns:
389 The validated object.
390 """
391 return self.validator.validate_json(data, strict=strict, context=context) 1ijklmnopabcdqrstuvwxefyzABCDEFgh
393 @_frame_depth(1) 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
394 def validate_strings(self, obj: Any, /, *, strict: bool | None = None, context: dict[str, Any] | None = None) -> T: 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
395 """Validate object contains string data against the model.
397 Args:
398 obj: The object contains string data to validate.
399 strict: Whether to strictly check types.
400 context: Additional context to use during validation.
402 Returns:
403 The validated object.
404 """
405 return self.validator.validate_strings(obj, strict=strict, context=context) 1ijklmnopabcdqrstuvwxefyzABCDEFgh
407 @_frame_depth(1) 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
408 def get_default_value(self, *, strict: bool | None = None, context: dict[str, Any] | None = None) -> Some[T] | None: 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
409 """Get the default value for the wrapped type.
411 Args:
412 strict: Whether to strictly check types.
413 context: Additional context to pass to the validator.
415 Returns:
416 The default value wrapped in a `Some` if there is one or None if not.
417 """
418 return self.validator.get_default_value(strict=strict, context=context) 1ijklmnopabcdqrstuvwxefyzABCDEFgh
420 @_frame_depth(1) 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
421 def dump_python( 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
422 self,
423 instance: T,
424 /,
425 *,
426 mode: Literal['json', 'python'] = 'python',
427 include: IncEx | None = None,
428 exclude: IncEx | None = None,
429 by_alias: bool = False,
430 exclude_unset: bool = False,
431 exclude_defaults: bool = False,
432 exclude_none: bool = False,
433 round_trip: bool = False,
434 warnings: bool | Literal['none', 'warn', 'error'] = True,
435 serialize_as_any: bool = False,
436 context: dict[str, Any] | None = None,
437 ) -> Any:
438 """Dump an instance of the adapted type to a Python object.
440 Args:
441 instance: The Python object to serialize.
442 mode: The output format.
443 include: Fields to include in the output.
444 exclude: Fields to exclude from the output.
445 by_alias: Whether to use alias names for field names.
446 exclude_unset: Whether to exclude unset fields.
447 exclude_defaults: Whether to exclude fields with default values.
448 exclude_none: Whether to exclude fields with None values.
449 round_trip: Whether to output the serialized data in a way that is compatible with deserialization.
450 warnings: How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors,
451 "error" raises a [`PydanticSerializationError`][pydantic_core.PydanticSerializationError].
452 serialize_as_any: Whether to serialize fields with duck-typing serialization behavior.
453 context: Additional context to pass to the serializer.
455 Returns:
456 The serialized object.
457 """
458 return self.serializer.to_python( 1ijklmnopabcdqrstuvwxefyzABCDEFgh
459 instance,
460 mode=mode,
461 by_alias=by_alias,
462 include=include,
463 exclude=exclude,
464 exclude_unset=exclude_unset,
465 exclude_defaults=exclude_defaults,
466 exclude_none=exclude_none,
467 round_trip=round_trip,
468 warnings=warnings,
469 serialize_as_any=serialize_as_any,
470 context=context,
471 )
473 @_frame_depth(1) 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
474 def dump_json( 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
475 self,
476 instance: T,
477 /,
478 *,
479 indent: int | None = None,
480 include: IncEx | None = None,
481 exclude: IncEx | None = None,
482 by_alias: bool = False,
483 exclude_unset: bool = False,
484 exclude_defaults: bool = False,
485 exclude_none: bool = False,
486 round_trip: bool = False,
487 warnings: bool | Literal['none', 'warn', 'error'] = True,
488 serialize_as_any: bool = False,
489 context: dict[str, Any] | None = None,
490 ) -> bytes:
491 """Usage docs: https://docs.pydantic.dev/2.8/concepts/json/#json-serialization
493 Serialize an instance of the adapted type to JSON.
495 Args:
496 instance: The instance to be serialized.
497 indent: Number of spaces for JSON indentation.
498 include: Fields to include.
499 exclude: Fields to exclude.
500 by_alias: Whether to use alias names for field names.
501 exclude_unset: Whether to exclude unset fields.
502 exclude_defaults: Whether to exclude fields with default values.
503 exclude_none: Whether to exclude fields with a value of `None`.
504 round_trip: Whether to serialize and deserialize the instance to ensure round-tripping.
505 warnings: How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors,
506 "error" raises a [`PydanticSerializationError`][pydantic_core.PydanticSerializationError].
507 serialize_as_any: Whether to serialize fields with duck-typing serialization behavior.
508 context: Additional context to pass to the serializer.
510 Returns:
511 The JSON representation of the given instance as bytes.
512 """
513 return self.serializer.to_json( 1ijklmnopabcdqrstuvwxefyzABCDEFgh
514 instance,
515 indent=indent,
516 include=include,
517 exclude=exclude,
518 by_alias=by_alias,
519 exclude_unset=exclude_unset,
520 exclude_defaults=exclude_defaults,
521 exclude_none=exclude_none,
522 round_trip=round_trip,
523 warnings=warnings,
524 serialize_as_any=serialize_as_any,
525 context=context,
526 )
528 @_frame_depth(1) 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
529 def json_schema( 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
530 self,
531 *,
532 by_alias: bool = True,
533 ref_template: str = DEFAULT_REF_TEMPLATE,
534 schema_generator: type[GenerateJsonSchema] = GenerateJsonSchema,
535 mode: JsonSchemaMode = 'validation',
536 ) -> dict[str, Any]:
537 """Generate a JSON schema for the adapted type.
539 Args:
540 by_alias: Whether to use alias names for field names.
541 ref_template: The format string used for generating $ref strings.
542 schema_generator: The generator class used for creating the schema.
543 mode: The mode to use for schema generation.
545 Returns:
546 The JSON schema for the model as a dictionary.
547 """
548 schema_generator_instance = schema_generator(by_alias=by_alias, ref_template=ref_template) 1ijklmnopabcdqrstuvwxefyzABCDEFgh
549 return schema_generator_instance.generate(self.core_schema, mode=mode) 1ijklmnopabcdqrstuvwxefyzABCDEFgh
551 @staticmethod 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
552 def json_schemas( 1ijklmnopabcdqrstuvwxefHIJKLMNOGyzABCDEFgh
553 inputs: Iterable[tuple[JsonSchemaKeyT, JsonSchemaMode, TypeAdapter[Any]]],
554 /,
555 *,
556 by_alias: bool = True,
557 title: str | None = None,
558 description: str | None = None,
559 ref_template: str = DEFAULT_REF_TEMPLATE,
560 schema_generator: type[GenerateJsonSchema] = GenerateJsonSchema,
561 ) -> tuple[dict[tuple[JsonSchemaKeyT, JsonSchemaMode], JsonSchemaValue], JsonSchemaValue]:
562 """Generate a JSON schema including definitions from multiple type adapters.
564 Args:
565 inputs: Inputs to schema generation. The first two items will form the keys of the (first)
566 output mapping; the type adapters will provide the core schemas that get converted into
567 definitions in the output JSON schema.
568 by_alias: Whether to use alias names.
569 title: The title for the schema.
570 description: The description for the schema.
571 ref_template: The format string used for generating $ref strings.
572 schema_generator: The generator class used for creating the schema.
574 Returns:
575 A tuple where:
577 - The first element is a dictionary whose keys are tuples of JSON schema key type and JSON mode, and
578 whose values are the JSON schema corresponding to that pair of inputs. (These schemas may have
579 JsonRef references to definitions that are defined in the second returned element.)
580 - The second element is a JSON schema containing all definitions referenced in the first returned
581 element, along with the optional title and description keys.
583 """
584 schema_generator_instance = schema_generator(by_alias=by_alias, ref_template=ref_template) 1ijklmnopabcdqrstuvwxefyzABCDEFgh
586 inputs_ = [] 1ijklmnopabcdqrstuvwxefyzABCDEFgh
587 for key, mode, adapter in inputs: 1ijklmnopabcdqrstuvwxefyzABCDEFgh
588 with adapter._with_frame_depth(1): # +1 for json_schemas staticmethod 1ijklmnopabcdqrstuvwxefyzABCDEFgh
589 inputs_.append((key, mode, adapter.core_schema)) 1ijklmnopabcdqrstuvwxefyzABCDEFgh
591 json_schemas_map, definitions = schema_generator_instance.generate_definitions(inputs_) 1ijklmnopabcdqrstuvwxefyzABCDEFgh
593 json_schema: dict[str, Any] = {} 1ijklmnopabcdqrstuvwxefyzABCDEFgh
594 if definitions: 1ijklmnopabcdqrstuvwxefyzABCDEFgh
595 json_schema['$defs'] = definitions 1ijklmnopabcdqrstuvwxefyzABCDEFgh
596 if title: 1ijklmnopabcdqrstuvwxefyzABCDEFgh
597 json_schema['title'] = title 1ijklmnopabcdqrstuvwxefyzABCDEFgh
598 if description: 1ijklmnopabcdqrstuvwxefyzABCDEFgh
599 json_schema['description'] = description 1ijklmnopabcdqrstuvwxefyzABCDEFgh
601 return json_schemas_map, json_schema 1ijklmnopabcdqrstuvwxefyzABCDEFgh