Coverage for pydantic/type_adapter.py: 89.16%

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1"""Type adapter specification.""" 

2 

3from __future__ import annotations as _annotations 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

4 

5import sys 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

6from collections.abc import Callable, Iterable 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

7from dataclasses import is_dataclass 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

8from types import FrameType 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

9from typing import ( 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

10 Any, 

11 Generic, 

12 Literal, 

13 TypeVar, 

14 cast, 

15 final, 

16 overload, 

17) 

18 

19from pydantic_core import CoreSchema, SchemaSerializer, SchemaValidator, Some 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

20from typing_extensions import ParamSpec, is_typeddict 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

21 

22from pydantic.errors import PydanticUserError 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

23from pydantic.main import BaseModel, IncEx 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

24 

25from ._internal import _config, _generate_schema, _mock_val_ser, _namespace_utils, _repr, _typing_extra, _utils 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

26from .config import ConfigDict 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

27from .errors import PydanticUndefinedAnnotation 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

28from .json_schema import ( 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

29 DEFAULT_REF_TEMPLATE, 

30 GenerateJsonSchema, 

31 JsonSchemaKeyT, 

32 JsonSchemaMode, 

33 JsonSchemaValue, 

34) 

35from .plugin._schema_validator import PluggableSchemaValidator, create_schema_validator 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

36 

37T = TypeVar('T') 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

38R = TypeVar('R') 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

39P = ParamSpec('P') 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

40TypeAdapterT = TypeVar('TypeAdapterT', bound='TypeAdapter') 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

41 

42 

43def _getattr_no_parents(obj: Any, attribute: str) -> Any: 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

44 """Returns the attribute value without attempting to look up attributes from parent types.""" 

45 if hasattr(obj, '__dict__'): 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

46 try: 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

47 return obj.__dict__[attribute] 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

48 except KeyError: 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

49 pass 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

50 

51 slots = getattr(obj, '__slots__', None) 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

52 if slots is not None and attribute in slots: 52 ↛ 53line 52 didn't jump to line 53 because the condition on line 52 was never true1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

53 return getattr(obj, attribute) 

54 else: 

55 raise AttributeError(attribute) 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

56 

57 

58def _type_has_config(type_: Any) -> bool: 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

59 """Returns whether the type has config.""" 

60 type_ = _typing_extra.annotated_type(type_) or type_ 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

61 try: 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

62 return issubclass(type_, BaseModel) or is_dataclass(type_) or is_typeddict(type_) 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

63 except TypeError: 

64 # type is not a class 

65 return False 

66 

67 

68@final 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

69class TypeAdapter(Generic[T]): 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

70 """!!! abstract "Usage Documentation" 

71 [`TypeAdapter`](../concepts/type_adapter.md) 

72 

73 Type adapters provide a flexible way to perform validation and serialization based on a Python type. 

74 

75 A `TypeAdapter` instance exposes some of the functionality from `BaseModel` instance methods 

76 for types that do not have such methods (such as dataclasses, primitive types, and more). 

77 

78 **Note:** `TypeAdapter` instances are not types, and cannot be used as type annotations for fields. 

79 

80 Args: 

81 type: The type associated with the `TypeAdapter`. 

82 config: Configuration for the `TypeAdapter`, should be a dictionary conforming to 

83 [`ConfigDict`][pydantic.config.ConfigDict]. 

84 

85 !!! note 

86 You cannot provide a configuration when instantiating a `TypeAdapter` if the type you're using 

87 has its own config that cannot be overridden (ex: `BaseModel`, `TypedDict`, and `dataclass`). A 

88 [`type-adapter-config-unused`](../errors/usage_errors.md#type-adapter-config-unused) error will 

89 be raised in this case. 

90 _parent_depth: Depth at which to search for the [parent frame][frame-objects]. This frame is used when 

91 resolving forward annotations during schema building, by looking for the globals and locals of this 

92 frame. Defaults to 2, which will result in the frame where the `TypeAdapter` was instantiated. 

93 

94 !!! note 

95 This parameter is named with an underscore to suggest its private nature and discourage use. 

96 It may be deprecated in a minor version, so we only recommend using it if you're comfortable 

97 with potential change in behavior/support. It's default value is 2 because internally, 

98 the `TypeAdapter` class makes another call to fetch the frame. 

99 module: The module that passes to plugin if provided. 

100 

101 Attributes: 

102 core_schema: The core schema for the type. 

103 validator: The schema validator for the type. 

104 serializer: The schema serializer for the type. 

105 pydantic_complete: Whether the core schema for the type is successfully built. 

106 

107 ??? tip "Compatibility with `mypy`" 

108 Depending on the type used, `mypy` might raise an error when instantiating a `TypeAdapter`. As a workaround, you can explicitly 

109 annotate your variable: 

110 

111 ```py 

112 from typing import Union 

113 

114 from pydantic import TypeAdapter 

115 

116 ta: TypeAdapter[Union[str, int]] = TypeAdapter(Union[str, int]) # type: ignore[arg-type] 

117 ``` 

118 

119 ??? info "Namespace management nuances and implementation details" 

120 

121 Here, we collect some notes on namespace management, and subtle differences from `BaseModel`: 

122 

123 `BaseModel` uses its own `__module__` to find out where it was defined 

124 and then looks for symbols to resolve forward references in those globals. 

125 On the other hand, `TypeAdapter` can be initialized with arbitrary objects, 

126 which may not be types and thus do not have a `__module__` available. 

127 So instead we look at the globals in our parent stack frame. 

128 

129 It is expected that the `ns_resolver` passed to this function will have the correct 

130 namespace for the type we're adapting. See the source code for `TypeAdapter.__init__` 

131 and `TypeAdapter.rebuild` for various ways to construct this namespace. 

132 

133 This works for the case where this function is called in a module that 

134 has the target of forward references in its scope, but 

135 does not always work for more complex cases. 

136 

137 For example, take the following: 

138 

139 ```python {title="a.py"} 

140 IntList = list[int] 

141 OuterDict = dict[str, 'IntList'] 

142 ``` 

143 

144 ```python {test="skip" title="b.py"} 

145 from a import OuterDict 

146 

147 from pydantic import TypeAdapter 

148 

149 IntList = int # replaces the symbol the forward reference is looking for 

150 v = TypeAdapter(OuterDict) 

151 v({'x': 1}) # should fail but doesn't 

152 ``` 

153 

154 If `OuterDict` were a `BaseModel`, this would work because it would resolve 

155 the forward reference within the `a.py` namespace. 

156 But `TypeAdapter(OuterDict)` can't determine what module `OuterDict` came from. 

157 

158 In other words, the assumption that _all_ forward references exist in the 

159 module we are being called from is not technically always true. 

160 Although most of the time it is and it works fine for recursive models and such, 

161 `BaseModel`'s behavior isn't perfect either and _can_ break in similar ways, 

162 so there is no right or wrong between the two. 

163 

164 But at the very least this behavior is _subtly_ different from `BaseModel`'s. 

165 """ 

166 

167 core_schema: CoreSchema 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

168 validator: SchemaValidator | PluggableSchemaValidator 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

169 serializer: SchemaSerializer 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

170 pydantic_complete: bool 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

171 

172 @overload 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

173 def __init__( 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

174 self, 

175 type: type[T], 1abcdefghijklmn

176 *, 

177 config: ConfigDict | None = ..., 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

178 _parent_depth: int = ..., 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

179 module: str | None = ..., 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

180 ) -> None: ... 1abcdefghijklmn

181 

182 # This second overload is for unsupported special forms (such as Annotated, Union, etc.) 

183 # Currently there is no way to type this correctly 

184 # See https://github.com/python/typing/pull/1618 

185 @overload 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

186 def __init__( 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

187 self, 

188 type: Any, 1abcdefghijklmn

189 *, 

190 config: ConfigDict | None = ..., 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

191 _parent_depth: int = ..., 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

192 module: str | None = ..., 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

193 ) -> None: ... 1abcdefghijklmn

194 

195 def __init__( 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

196 self, 

197 type: Any, 

198 *, 

199 config: ConfigDict | None = None, 

200 _parent_depth: int = 2, 

201 module: str | None = None, 

202 ) -> None: 

203 if _type_has_config(type) and config is not None: 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

204 raise PydanticUserError( 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

205 'Cannot use `config` when the type is a BaseModel, dataclass or TypedDict.' 

206 ' These types can have their own config and setting the config via the `config`' 

207 ' parameter to TypeAdapter will not override it, thus the `config` you passed to' 

208 ' TypeAdapter becomes meaningless, which is probably not what you want.', 

209 code='type-adapter-config-unused', 

210 ) 

211 

212 self._type = type 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

213 self._config = config 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

214 self._parent_depth = _parent_depth 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

215 self.pydantic_complete = False 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

216 

217 parent_frame = self._fetch_parent_frame() 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

218 if parent_frame is not None: 218 ↛ 223line 218 didn't jump to line 223 because the condition on line 218 was always true1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

219 globalns = parent_frame.f_globals 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

220 # Do not provide a local ns if the type adapter happens to be instantiated at the module level: 

221 localns = parent_frame.f_locals if parent_frame.f_locals is not globalns else {} 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

222 else: 

223 globalns = {} 

224 localns = {} 

225 

226 self._module_name = module or cast(str, globalns.get('__name__', '')) 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

227 self._init_core_attrs( 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

228 ns_resolver=_namespace_utils.NsResolver( 

229 namespaces_tuple=_namespace_utils.NamespacesTuple(locals=localns, globals=globalns), 

230 parent_namespace=localns, 

231 ), 

232 force=False, 

233 ) 

234 

235 def _fetch_parent_frame(self) -> FrameType | None: 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

236 frame = sys._getframe(self._parent_depth) 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

237 if frame.f_globals.get('__name__') == 'typing': 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

238 # Because `TypeAdapter` is generic, explicitly parametrizing the class results 

239 # in a `typing._GenericAlias` instance, which proxies instantiation calls to the 

240 # "real" `TypeAdapter` class and thus adding an extra frame to the call. To avoid 

241 # pulling anything from the `typing` module, use the correct frame (the one before): 

242 return frame.f_back 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

243 

244 return frame 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

245 

246 def _init_core_attrs( 1opqrstabcdGHIuvwxyzghijJKLABCDEFklmnMNO

247 self, ns_resolver: _namespace_utils.NsResolver, force: bool, raise_errors: bool = False 

248 ) -> bool: 

249 """Initialize the core schema, validator, and serializer for the type. 

250 

251 Args: 

252 ns_resolver: The namespace resolver to use when building the core schema for the adapted type. 

253 force: Whether to force the construction of the core schema, validator, and serializer. 

254 If `force` is set to `False` and `_defer_build` is `True`, the core schema, validator, and serializer will be set to mocks. 

255 raise_errors: Whether to raise errors if initializing any of the core attrs fails. 

256 

257 Returns: 

258 `True` if the core schema, validator, and serializer were successfully initialized, otherwise `False`. 

259 

260 Raises: 

261 PydanticUndefinedAnnotation: If `PydanticUndefinedAnnotation` occurs in`__get_pydantic_core_schema__` 

262 and `raise_errors=True`. 

263 """ 

264 if not force and self._defer_build: 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

265 _mock_val_ser.set_type_adapter_mocks(self) 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

266 self.pydantic_complete = False 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

267 return False 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

268 

269 try: 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

270 self.core_schema = _getattr_no_parents(self._type, '__pydantic_core_schema__') 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

271 self.validator = _getattr_no_parents(self._type, '__pydantic_validator__') 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

272 self.serializer = _getattr_no_parents(self._type, '__pydantic_serializer__') 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

273 

274 # TODO: we don't go through the rebuild logic here directly because we don't want 

275 # to repeat all of the namespace fetching logic that we've already done 

276 # so we simply skip to the block below that does the actual schema generation 

277 if ( 1opqrstefuvwxyzABCDEF

278 isinstance(self.core_schema, _mock_val_ser.MockCoreSchema) 

279 or isinstance(self.validator, _mock_val_ser.MockValSer) 

280 or isinstance(self.serializer, _mock_val_ser.MockValSer) 

281 ): 

282 raise AttributeError() 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

283 except AttributeError: 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

284 config_wrapper = _config.ConfigWrapper(self._config) 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

285 

286 schema_generator = _generate_schema.GenerateSchema(config_wrapper, ns_resolver=ns_resolver) 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

287 

288 try: 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

289 core_schema = schema_generator.generate_schema(self._type) 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

290 except PydanticUndefinedAnnotation: 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

291 if raise_errors: 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

292 raise 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

293 _mock_val_ser.set_type_adapter_mocks(self) 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

294 return False 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

295 

296 try: 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

297 self.core_schema = schema_generator.clean_schema(core_schema) 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

298 except _generate_schema.InvalidSchemaError: 

299 _mock_val_ser.set_type_adapter_mocks(self) 

300 return False 

301 

302 core_config = config_wrapper.core_config(None) 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

303 

304 self.validator = create_schema_validator( 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

305 schema=self.core_schema, 

306 schema_type=self._type, 

307 schema_type_module=self._module_name, 

308 schema_type_name=str(self._type), 

309 schema_kind='TypeAdapter', 

310 config=core_config, 

311 plugin_settings=config_wrapper.plugin_settings, 

312 ) 

313 self.serializer = SchemaSerializer(self.core_schema, core_config) 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

314 

315 self.pydantic_complete = True 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

316 return True 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

317 

318 @property 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

319 def _defer_build(self) -> bool: 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

320 config = self._config if self._config is not None else self._model_config 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

321 if config: 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

322 return config.get('defer_build') is True 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

323 return False 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

324 

325 @property 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

326 def _model_config(self) -> ConfigDict | None: 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

327 type_: Any = _typing_extra.annotated_type(self._type) or self._type # Eg FastAPI heavily uses Annotated 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

328 if _utils.lenient_issubclass(type_, BaseModel): 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

329 return type_.model_config 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

330 return getattr(type_, '__pydantic_config__', None) 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

331 

332 def __repr__(self) -> str: 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

333 return f'TypeAdapter({_repr.display_as_type(self._type)})' 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

334 

335 def rebuild( 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

336 self, 

337 *, 

338 force: bool = False, 

339 raise_errors: bool = True, 

340 _parent_namespace_depth: int = 2, 

341 _types_namespace: _namespace_utils.MappingNamespace | None = None, 

342 ) -> bool | None: 

343 """Try to rebuild the pydantic-core schema for the adapter's type. 

344 

345 This may be necessary when one of the annotations is a ForwardRef which could not be resolved during 

346 the initial attempt to build the schema, and automatic rebuilding fails. 

347 

348 Args: 

349 force: Whether to force the rebuilding of the type adapter's schema, defaults to `False`. 

350 raise_errors: Whether to raise errors, defaults to `True`. 

351 _parent_namespace_depth: Depth at which to search for the [parent frame][frame-objects]. This 

352 frame is used when resolving forward annotations during schema rebuilding, by looking for 

353 the locals of this frame. Defaults to 2, which will result in the frame where the method 

354 was called. 

355 _types_namespace: An explicit types namespace to use, instead of using the local namespace 

356 from the parent frame. Defaults to `None`. 

357 

358 Returns: 

359 Returns `None` if the schema is already "complete" and rebuilding was not required. 

360 If rebuilding _was_ required, returns `True` if rebuilding was successful, otherwise `False`. 

361 """ 

362 if not force and self.pydantic_complete: 362 ↛ 363line 362 didn't jump to line 363 because the condition on line 362 was never true1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

363 return None 

364 

365 if _types_namespace is not None: 365 ↛ 366line 365 didn't jump to line 366 because the condition on line 365 was never true1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

366 rebuild_ns = _types_namespace 

367 elif _parent_namespace_depth > 0: 367 ↛ 370line 367 didn't jump to line 370 because the condition on line 367 was always true1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

368 rebuild_ns = _typing_extra.parent_frame_namespace(parent_depth=_parent_namespace_depth, force=True) or {} 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

369 else: 

370 rebuild_ns = {} 

371 

372 # we have to manually fetch globals here because there's no type on the stack of the NsResolver 

373 # and so we skip the globalns = get_module_ns_of(typ) call that would normally happen 

374 globalns = sys._getframe(max(_parent_namespace_depth - 1, 1)).f_globals 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

375 ns_resolver = _namespace_utils.NsResolver( 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

376 namespaces_tuple=_namespace_utils.NamespacesTuple(locals=rebuild_ns, globals=globalns), 

377 parent_namespace=rebuild_ns, 

378 ) 

379 return self._init_core_attrs(ns_resolver=ns_resolver, force=True, raise_errors=raise_errors) 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

380 

381 def validate_python( 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

382 self, 

383 object: Any, 

384 /, 

385 *, 

386 strict: bool | None = None, 

387 from_attributes: bool | None = None, 

388 context: dict[str, Any] | None = None, 

389 experimental_allow_partial: bool | Literal['off', 'on', 'trailing-strings'] = False, 

390 by_alias: bool | None = None, 

391 by_name: bool | None = None, 

392 ) -> T: 

393 """Validate a Python object against the model. 

394 

395 Args: 

396 object: The Python object to validate against the model. 

397 strict: Whether to strictly check types. 

398 from_attributes: Whether to extract data from object attributes. 

399 context: Additional context to pass to the validator. 

400 experimental_allow_partial: **Experimental** whether to enable 

401 [partial validation](../concepts/experimental.md#partial-validation), e.g. to process streams. 

402 * False / 'off': Default behavior, no partial validation. 

403 * True / 'on': Enable partial validation. 

404 * 'trailing-strings': Enable partial validation and allow trailing strings in the input. 

405 by_alias: Whether to use the field's alias when validating against the provided input data. 

406 by_name: Whether to use the field's name when validating against the provided input data. 

407 

408 !!! note 

409 When using `TypeAdapter` with a Pydantic `dataclass`, the use of the `from_attributes` 

410 argument is not supported. 

411 

412 Returns: 

413 The validated object. 

414 """ 

415 if by_alias is False and by_name is not True: 415 ↛ 416line 415 didn't jump to line 416 because the condition on line 415 was never true1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

416 raise PydanticUserError( 

417 'At least one of `by_alias` or `by_name` must be set to True.', 

418 code='validate-by-alias-and-name-false', 

419 ) 

420 

421 return self.validator.validate_python( 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

422 object, 

423 strict=strict, 

424 from_attributes=from_attributes, 

425 context=context, 

426 allow_partial=experimental_allow_partial, 

427 by_alias=by_alias, 

428 by_name=by_name, 

429 ) 

430 

431 def validate_json( 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

432 self, 

433 data: str | bytes | bytearray, 

434 /, 

435 *, 

436 strict: bool | None = None, 

437 context: dict[str, Any] | None = None, 

438 experimental_allow_partial: bool | Literal['off', 'on', 'trailing-strings'] = False, 

439 by_alias: bool | None = None, 

440 by_name: bool | None = None, 

441 ) -> T: 

442 """!!! abstract "Usage Documentation" 

443 [JSON Parsing](../concepts/json.md#json-parsing) 

444 

445 Validate a JSON string or bytes against the model. 

446 

447 Args: 

448 data: The JSON data to validate against the model. 

449 strict: Whether to strictly check types. 

450 context: Additional context to use during validation. 

451 experimental_allow_partial: **Experimental** whether to enable 

452 [partial validation](../concepts/experimental.md#partial-validation), e.g. to process streams. 

453 * False / 'off': Default behavior, no partial validation. 

454 * True / 'on': Enable partial validation. 

455 * 'trailing-strings': Enable partial validation and allow trailing strings in the input. 

456 by_alias: Whether to use the field's alias when validating against the provided input data. 

457 by_name: Whether to use the field's name when validating against the provided input data. 

458 

459 Returns: 

460 The validated object. 

461 """ 

462 if by_alias is False and by_name is not True: 462 ↛ 463line 462 didn't jump to line 463 because the condition on line 462 was never true1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

463 raise PydanticUserError( 

464 'At least one of `by_alias` or `by_name` must be set to True.', 

465 code='validate-by-alias-and-name-false', 

466 ) 

467 

468 return self.validator.validate_json( 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

469 data, 

470 strict=strict, 

471 context=context, 

472 allow_partial=experimental_allow_partial, 

473 by_alias=by_alias, 

474 by_name=by_name, 

475 ) 

476 

477 def validate_strings( 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

478 self, 

479 obj: Any, 

480 /, 

481 *, 

482 strict: bool | None = None, 

483 context: dict[str, Any] | None = None, 

484 experimental_allow_partial: bool | Literal['off', 'on', 'trailing-strings'] = False, 

485 by_alias: bool | None = None, 

486 by_name: bool | None = None, 

487 ) -> T: 

488 """Validate object contains string data against the model. 

489 

490 Args: 

491 obj: The object contains string data to validate. 

492 strict: Whether to strictly check types. 

493 context: Additional context to use during validation. 

494 experimental_allow_partial: **Experimental** whether to enable 

495 [partial validation](../concepts/experimental.md#partial-validation), e.g. to process streams. 

496 * False / 'off': Default behavior, no partial validation. 

497 * True / 'on': Enable partial validation. 

498 * 'trailing-strings': Enable partial validation and allow trailing strings in the input. 

499 by_alias: Whether to use the field's alias when validating against the provided input data. 

500 by_name: Whether to use the field's name when validating against the provided input data. 

501 

502 Returns: 

503 The validated object. 

504 """ 

505 if by_alias is False and by_name is not True: 505 ↛ 506line 505 didn't jump to line 506 because the condition on line 505 was never true1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

506 raise PydanticUserError( 

507 'At least one of `by_alias` or `by_name` must be set to True.', 

508 code='validate-by-alias-and-name-false', 

509 ) 

510 

511 return self.validator.validate_strings( 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

512 obj, 

513 strict=strict, 

514 context=context, 

515 allow_partial=experimental_allow_partial, 

516 by_alias=by_alias, 

517 by_name=by_name, 

518 ) 

519 

520 def get_default_value(self, *, strict: bool | None = None, context: dict[str, Any] | None = None) -> Some[T] | None: 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

521 """Get the default value for the wrapped type. 

522 

523 Args: 

524 strict: Whether to strictly check types. 

525 context: Additional context to pass to the validator. 

526 

527 Returns: 

528 The default value wrapped in a `Some` if there is one or None if not. 

529 """ 

530 return self.validator.get_default_value(strict=strict, context=context) 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

531 

532 def dump_python( 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

533 self, 

534 instance: T, 

535 /, 

536 *, 

537 mode: Literal['json', 'python'] = 'python', 

538 include: IncEx | None = None, 

539 exclude: IncEx | None = None, 

540 by_alias: bool | None = None, 

541 exclude_unset: bool = False, 

542 exclude_defaults: bool = False, 

543 exclude_none: bool = False, 

544 round_trip: bool = False, 

545 warnings: bool | Literal['none', 'warn', 'error'] = True, 

546 fallback: Callable[[Any], Any] | None = None, 

547 serialize_as_any: bool = False, 

548 context: dict[str, Any] | None = None, 

549 ) -> Any: 

550 """Dump an instance of the adapted type to a Python object. 

551 

552 Args: 

553 instance: The Python object to serialize. 

554 mode: The output format. 

555 include: Fields to include in the output. 

556 exclude: Fields to exclude from the output. 

557 by_alias: Whether to use alias names for field names. 

558 exclude_unset: Whether to exclude unset fields. 

559 exclude_defaults: Whether to exclude fields with default values. 

560 exclude_none: Whether to exclude fields with None values. 

561 round_trip: Whether to output the serialized data in a way that is compatible with deserialization. 

562 warnings: How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, 

563 "error" raises a [`PydanticSerializationError`][pydantic_core.PydanticSerializationError]. 

564 fallback: A function to call when an unknown value is encountered. If not provided, 

565 a [`PydanticSerializationError`][pydantic_core.PydanticSerializationError] error is raised. 

566 serialize_as_any: Whether to serialize fields with duck-typing serialization behavior. 

567 context: Additional context to pass to the serializer. 

568 

569 Returns: 

570 The serialized object. 

571 """ 

572 return self.serializer.to_python( 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

573 instance, 

574 mode=mode, 

575 by_alias=by_alias, 

576 include=include, 

577 exclude=exclude, 

578 exclude_unset=exclude_unset, 

579 exclude_defaults=exclude_defaults, 

580 exclude_none=exclude_none, 

581 round_trip=round_trip, 

582 warnings=warnings, 

583 fallback=fallback, 

584 serialize_as_any=serialize_as_any, 

585 context=context, 

586 ) 

587 

588 def dump_json( 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

589 self, 

590 instance: T, 

591 /, 

592 *, 

593 indent: int | None = None, 

594 ensure_ascii: bool = False, 

595 include: IncEx | None = None, 

596 exclude: IncEx | None = None, 

597 by_alias: bool | None = None, 

598 exclude_unset: bool = False, 

599 exclude_defaults: bool = False, 

600 exclude_none: bool = False, 

601 round_trip: bool = False, 

602 warnings: bool | Literal['none', 'warn', 'error'] = True, 

603 fallback: Callable[[Any], Any] | None = None, 

604 serialize_as_any: bool = False, 

605 context: dict[str, Any] | None = None, 

606 ) -> bytes: 

607 """!!! abstract "Usage Documentation" 

608 [JSON Serialization](../concepts/json.md#json-serialization) 

609 

610 Serialize an instance of the adapted type to JSON. 

611 

612 Args: 

613 instance: The instance to be serialized. 

614 indent: Number of spaces for JSON indentation. 

615 ensure_ascii: If `True`, the output is guaranteed to have all incoming non-ASCII characters escaped. 

616 If `False` (the default), these characters will be output as-is. 

617 include: Fields to include. 

618 exclude: Fields to exclude. 

619 by_alias: Whether to use alias names for field names. 

620 exclude_unset: Whether to exclude unset fields. 

621 exclude_defaults: Whether to exclude fields with default values. 

622 exclude_none: Whether to exclude fields with a value of `None`. 

623 round_trip: Whether to serialize and deserialize the instance to ensure round-tripping. 

624 warnings: How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, 

625 "error" raises a [`PydanticSerializationError`][pydantic_core.PydanticSerializationError]. 

626 fallback: A function to call when an unknown value is encountered. If not provided, 

627 a [`PydanticSerializationError`][pydantic_core.PydanticSerializationError] error is raised. 

628 serialize_as_any: Whether to serialize fields with duck-typing serialization behavior. 

629 context: Additional context to pass to the serializer. 

630 

631 Returns: 

632 The JSON representation of the given instance as bytes. 

633 """ 

634 return self.serializer.to_json( 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

635 instance, 

636 indent=indent, 

637 include=include, 

638 exclude=exclude, 

639 by_alias=by_alias, 

640 exclude_unset=exclude_unset, 

641 exclude_defaults=exclude_defaults, 

642 exclude_none=exclude_none, 

643 round_trip=round_trip, 

644 warnings=warnings, 

645 fallback=fallback, 

646 serialize_as_any=serialize_as_any, 

647 context=context, 

648 ) 

649 

650 def json_schema( 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

651 self, 

652 *, 

653 by_alias: bool = True, 

654 ref_template: str = DEFAULT_REF_TEMPLATE, 

655 schema_generator: type[GenerateJsonSchema] = GenerateJsonSchema, 

656 mode: JsonSchemaMode = 'validation', 

657 ) -> dict[str, Any]: 

658 """Generate a JSON schema for the adapted type. 

659 

660 Args: 

661 by_alias: Whether to use alias names for field names. 

662 ref_template: The format string used for generating $ref strings. 

663 schema_generator: The generator class used for creating the schema. 

664 mode: The mode to use for schema generation. 

665 

666 Returns: 

667 The JSON schema for the model as a dictionary. 

668 """ 

669 schema_generator_instance = schema_generator(by_alias=by_alias, ref_template=ref_template) 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

670 if isinstance(self.core_schema, _mock_val_ser.MockCoreSchema): 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

671 self.core_schema.rebuild() 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

672 assert not isinstance(self.core_schema, _mock_val_ser.MockCoreSchema), 'this is a bug! please report it' 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

673 return schema_generator_instance.generate(self.core_schema, mode=mode) 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

674 

675 @staticmethod 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

676 def json_schemas( 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

677 inputs: Iterable[tuple[JsonSchemaKeyT, JsonSchemaMode, TypeAdapter[Any]]], 

678 /, 

679 *, 

680 by_alias: bool = True, 

681 title: str | None = None, 

682 description: str | None = None, 

683 ref_template: str = DEFAULT_REF_TEMPLATE, 

684 schema_generator: type[GenerateJsonSchema] = GenerateJsonSchema, 

685 ) -> tuple[dict[tuple[JsonSchemaKeyT, JsonSchemaMode], JsonSchemaValue], JsonSchemaValue]: 

686 """Generate a JSON schema including definitions from multiple type adapters. 

687 

688 Args: 

689 inputs: Inputs to schema generation. The first two items will form the keys of the (first) 

690 output mapping; the type adapters will provide the core schemas that get converted into 

691 definitions in the output JSON schema. 

692 by_alias: Whether to use alias names. 

693 title: The title for the schema. 

694 description: The description for the schema. 

695 ref_template: The format string used for generating $ref strings. 

696 schema_generator: The generator class used for creating the schema. 

697 

698 Returns: 

699 A tuple where: 

700 

701 - The first element is a dictionary whose keys are tuples of JSON schema key type and JSON mode, and 

702 whose values are the JSON schema corresponding to that pair of inputs. (These schemas may have 

703 JsonRef references to definitions that are defined in the second returned element.) 

704 - The second element is a JSON schema containing all definitions referenced in the first returned 

705 element, along with the optional title and description keys. 

706 

707 """ 

708 schema_generator_instance = schema_generator(by_alias=by_alias, ref_template=ref_template) 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

709 

710 inputs_ = [] 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

711 for key, mode, adapter in inputs: 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

712 # This is the same pattern we follow for model json schemas - we attempt a core schema rebuild if we detect a mock 

713 if isinstance(adapter.core_schema, _mock_val_ser.MockCoreSchema): 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

714 adapter.core_schema.rebuild() 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

715 assert not isinstance(adapter.core_schema, _mock_val_ser.MockCoreSchema), ( 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

716 'this is a bug! please report it' 

717 ) 

718 inputs_.append((key, mode, adapter.core_schema)) 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

719 

720 json_schemas_map, definitions = schema_generator_instance.generate_definitions(inputs_) 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

721 

722 json_schema: dict[str, Any] = {} 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

723 if definitions: 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

724 json_schema['$defs'] = definitions 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

725 if title: 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

726 json_schema['title'] = title 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

727 if description: 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

728 json_schema['description'] = description 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO

729 

730 return json_schemas_map, json_schema 1opqrstabcdGHIefuvwxyzghijJKLABCDEFklmnMNO