Coverage for pydantic/functional_validators.py: 98.85%
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« prev ^ index » next coverage.py v7.9.1, created at 2025-06-16 14:56 +0000
1"""This module contains related classes and functions for validation."""
3from __future__ import annotations as _annotations 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
5import dataclasses 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
6import sys 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
7from functools import partialmethod 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
8from types import FunctionType 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
9from typing import TYPE_CHECKING, Annotated, Any, Callable, Literal, TypeVar, Union, cast, overload 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
11from pydantic_core import PydanticUndefined, core_schema 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
12from typing_extensions import Self, TypeAlias 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
14from ._internal import _decorators, _generics, _internal_dataclass 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
15from .annotated_handlers import GetCoreSchemaHandler 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
16from .errors import PydanticUserError 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
18if sys.version_info < (3, 11): 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
19 from typing_extensions import Protocol 1DErsqpFGvwHIzA
20else:
21 from typing import Protocol 1tuabcdexyfghijJBCklmno
23_inspect_validator = _decorators.inspect_validator 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
26@dataclasses.dataclass(frozen=True, **_internal_dataclass.slots_true) 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
27class AfterValidator: 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
28 """!!! abstract "Usage Documentation"
29 [field *after* validators](../concepts/validators.md#field-after-validator)
31 A metadata class that indicates that a validation should be applied **after** the inner validation logic.
33 Attributes:
34 func: The validator function.
36 Example:
37 ```python
38 from typing import Annotated
40 from pydantic import AfterValidator, BaseModel, ValidationError
42 MyInt = Annotated[int, AfterValidator(lambda v: v + 1)]
44 class Model(BaseModel):
45 a: MyInt
47 print(Model(a=1).a)
48 #> 2
50 try:
51 Model(a='a')
52 except ValidationError as e:
53 print(e.json(indent=2))
54 '''
55 [
56 {
57 "type": "int_parsing",
58 "loc": [
59 "a"
60 ],
61 "msg": "Input should be a valid integer, unable to parse string as an integer",
62 "input": "a",
63 "url": "https://errors.pydantic.dev/2/v/int_parsing"
64 }
65 ]
66 '''
67 ```
68 """
70 func: core_schema.NoInfoValidatorFunction | core_schema.WithInfoValidatorFunction 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
72 def __get_pydantic_core_schema__(self, source_type: Any, handler: GetCoreSchemaHandler) -> core_schema.CoreSchema: 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
73 schema = handler(source_type) 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
74 info_arg = _inspect_validator(self.func, 'after') 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
75 if info_arg: 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
76 func = cast(core_schema.WithInfoValidatorFunction, self.func) 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
77 return core_schema.with_info_after_validator_function(func, schema=schema) 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
78 else:
79 func = cast(core_schema.NoInfoValidatorFunction, self.func) 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
80 return core_schema.no_info_after_validator_function(func, schema=schema) 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
82 @classmethod 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
83 def _from_decorator(cls, decorator: _decorators.Decorator[_decorators.FieldValidatorDecoratorInfo]) -> Self: 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
84 return cls(func=decorator.func) 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
87@dataclasses.dataclass(frozen=True, **_internal_dataclass.slots_true) 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
88class BeforeValidator: 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
89 """!!! abstract "Usage Documentation"
90 [field *before* validators](../concepts/validators.md#field-before-validator)
92 A metadata class that indicates that a validation should be applied **before** the inner validation logic.
94 Attributes:
95 func: The validator function.
96 json_schema_input_type: The input type used to generate the appropriate
97 JSON Schema (in validation mode). The actual input type is `Any`.
99 Example:
100 ```python
101 from typing import Annotated
103 from pydantic import BaseModel, BeforeValidator
105 MyInt = Annotated[int, BeforeValidator(lambda v: v + 1)]
107 class Model(BaseModel):
108 a: MyInt
110 print(Model(a=1).a)
111 #> 2
113 try:
114 Model(a='a')
115 except TypeError as e:
116 print(e)
117 #> can only concatenate str (not "int") to str
118 ```
119 """
121 func: core_schema.NoInfoValidatorFunction | core_schema.WithInfoValidatorFunction 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
122 json_schema_input_type: Any = PydanticUndefined 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
124 def __get_pydantic_core_schema__(self, source_type: Any, handler: GetCoreSchemaHandler) -> core_schema.CoreSchema: 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
125 schema = handler(source_type) 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
126 input_schema = ( 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
127 None
128 if self.json_schema_input_type is PydanticUndefined
129 else handler.generate_schema(self.json_schema_input_type)
130 )
132 info_arg = _inspect_validator(self.func, 'before') 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
133 if info_arg: 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
134 func = cast(core_schema.WithInfoValidatorFunction, self.func) 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
135 return core_schema.with_info_before_validator_function( 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
136 func,
137 schema=schema,
138 json_schema_input_schema=input_schema,
139 )
140 else:
141 func = cast(core_schema.NoInfoValidatorFunction, self.func) 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
142 return core_schema.no_info_before_validator_function( 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
143 func, schema=schema, json_schema_input_schema=input_schema
144 )
146 @classmethod 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
147 def _from_decorator(cls, decorator: _decorators.Decorator[_decorators.FieldValidatorDecoratorInfo]) -> Self: 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
148 return cls( 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
149 func=decorator.func,
150 json_schema_input_type=decorator.info.json_schema_input_type,
151 )
154@dataclasses.dataclass(frozen=True, **_internal_dataclass.slots_true) 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
155class PlainValidator: 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
156 """!!! abstract "Usage Documentation"
157 [field *plain* validators](../concepts/validators.md#field-plain-validator)
159 A metadata class that indicates that a validation should be applied **instead** of the inner validation logic.
161 !!! note
162 Before v2.9, `PlainValidator` wasn't always compatible with JSON Schema generation for `mode='validation'`.
163 You can now use the `json_schema_input_type` argument to specify the input type of the function
164 to be used in the JSON schema when `mode='validation'` (the default). See the example below for more details.
166 Attributes:
167 func: The validator function.
168 json_schema_input_type: The input type used to generate the appropriate
169 JSON Schema (in validation mode). The actual input type is `Any`.
171 Example:
172 ```python
173 from typing import Annotated, Union
175 from pydantic import BaseModel, PlainValidator
177 def validate(v: object) -> int:
178 if not isinstance(v, (int, str)):
179 raise ValueError(f'Expected int or str, go {type(v)}')
181 return int(v) + 1
183 MyInt = Annotated[
184 int,
185 PlainValidator(validate, json_schema_input_type=Union[str, int]), # (1)!
186 ]
188 class Model(BaseModel):
189 a: MyInt
191 print(Model(a='1').a)
192 #> 2
194 print(Model(a=1).a)
195 #> 2
196 ```
198 1. In this example, we've specified the `json_schema_input_type` as `Union[str, int]` which indicates to the JSON schema
199 generator that in validation mode, the input type for the `a` field can be either a [`str`][] or an [`int`][].
200 """
202 func: core_schema.NoInfoValidatorFunction | core_schema.WithInfoValidatorFunction 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
203 json_schema_input_type: Any = Any 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
205 def __get_pydantic_core_schema__(self, source_type: Any, handler: GetCoreSchemaHandler) -> core_schema.CoreSchema: 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
206 # Note that for some valid uses of PlainValidator, it is not possible to generate a core schema for the
207 # source_type, so calling `handler(source_type)` will error, which prevents us from generating a proper
208 # serialization schema. To work around this for use cases that will not involve serialization, we simply
209 # catch any PydanticSchemaGenerationError that may be raised while attempting to build the serialization schema
210 # and abort any attempts to handle special serialization.
211 from pydantic import PydanticSchemaGenerationError 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
213 try: 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
214 schema = handler(source_type) 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
215 # TODO if `schema['serialization']` is one of `'include-exclude-dict/sequence',
216 # schema validation will fail. That's why we use 'type ignore' comments below.
217 serialization = schema.get( 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
218 'serialization',
219 core_schema.wrap_serializer_function_ser_schema(
220 function=lambda v, h: h(v),
221 schema=schema,
222 return_schema=handler.generate_schema(source_type),
223 ),
224 )
225 except PydanticSchemaGenerationError: 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
226 serialization = None 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
228 input_schema = handler.generate_schema(self.json_schema_input_type) 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
230 info_arg = _inspect_validator(self.func, 'plain') 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
231 if info_arg: 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
232 func = cast(core_schema.WithInfoValidatorFunction, self.func) 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
233 return core_schema.with_info_plain_validator_function( 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
234 func,
235 serialization=serialization, # pyright: ignore[reportArgumentType]
236 json_schema_input_schema=input_schema,
237 )
238 else:
239 func = cast(core_schema.NoInfoValidatorFunction, self.func) 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
240 return core_schema.no_info_plain_validator_function( 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
241 func,
242 serialization=serialization, # pyright: ignore[reportArgumentType]
243 json_schema_input_schema=input_schema,
244 )
246 @classmethod 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
247 def _from_decorator(cls, decorator: _decorators.Decorator[_decorators.FieldValidatorDecoratorInfo]) -> Self: 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
248 return cls( 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
249 func=decorator.func,
250 json_schema_input_type=decorator.info.json_schema_input_type,
251 )
254@dataclasses.dataclass(frozen=True, **_internal_dataclass.slots_true) 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
255class WrapValidator: 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
256 """!!! abstract "Usage Documentation"
257 [field *wrap* validators](../concepts/validators.md#field-wrap-validator)
259 A metadata class that indicates that a validation should be applied **around** the inner validation logic.
261 Attributes:
262 func: The validator function.
263 json_schema_input_type: The input type used to generate the appropriate
264 JSON Schema (in validation mode). The actual input type is `Any`.
266 ```python
267 from datetime import datetime
268 from typing import Annotated
270 from pydantic import BaseModel, ValidationError, WrapValidator
272 def validate_timestamp(v, handler):
273 if v == 'now':
274 # we don't want to bother with further validation, just return the new value
275 return datetime.now()
276 try:
277 return handler(v)
278 except ValidationError:
279 # validation failed, in this case we want to return a default value
280 return datetime(2000, 1, 1)
282 MyTimestamp = Annotated[datetime, WrapValidator(validate_timestamp)]
284 class Model(BaseModel):
285 a: MyTimestamp
287 print(Model(a='now').a)
288 #> 2032-01-02 03:04:05.000006
289 print(Model(a='invalid').a)
290 #> 2000-01-01 00:00:00
291 ```
292 """
294 func: core_schema.NoInfoWrapValidatorFunction | core_schema.WithInfoWrapValidatorFunction 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
295 json_schema_input_type: Any = PydanticUndefined 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
297 def __get_pydantic_core_schema__(self, source_type: Any, handler: GetCoreSchemaHandler) -> core_schema.CoreSchema: 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
298 schema = handler(source_type) 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
299 input_schema = ( 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
300 None
301 if self.json_schema_input_type is PydanticUndefined
302 else handler.generate_schema(self.json_schema_input_type)
303 )
305 info_arg = _inspect_validator(self.func, 'wrap') 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
306 if info_arg: 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
307 func = cast(core_schema.WithInfoWrapValidatorFunction, self.func) 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
308 return core_schema.with_info_wrap_validator_function( 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
309 func,
310 schema=schema,
311 json_schema_input_schema=input_schema,
312 )
313 else:
314 func = cast(core_schema.NoInfoWrapValidatorFunction, self.func) 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
315 return core_schema.no_info_wrap_validator_function( 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
316 func,
317 schema=schema,
318 json_schema_input_schema=input_schema,
319 )
321 @classmethod 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
322 def _from_decorator(cls, decorator: _decorators.Decorator[_decorators.FieldValidatorDecoratorInfo]) -> Self: 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
323 return cls( 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
324 func=decorator.func,
325 json_schema_input_type=decorator.info.json_schema_input_type,
326 )
329if TYPE_CHECKING: 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
331 class _OnlyValueValidatorClsMethod(Protocol):
332 def __call__(self, cls: Any, value: Any, /) -> Any: ...
334 class _V2ValidatorClsMethod(Protocol):
335 def __call__(self, cls: Any, value: Any, info: core_schema.ValidationInfo[Any], /) -> Any: ...
337 class _OnlyValueWrapValidatorClsMethod(Protocol):
338 def __call__(self, cls: Any, value: Any, handler: core_schema.ValidatorFunctionWrapHandler, /) -> Any: ...
340 class _V2WrapValidatorClsMethod(Protocol):
341 def __call__(
342 self,
343 cls: Any,
344 value: Any,
345 handler: core_schema.ValidatorFunctionWrapHandler,
346 info: core_schema.ValidationInfo[Any],
347 /,
348 ) -> Any: ...
350 _V2Validator = Union[
351 _V2ValidatorClsMethod,
352 core_schema.WithInfoValidatorFunction,
353 _OnlyValueValidatorClsMethod,
354 core_schema.NoInfoValidatorFunction,
355 ]
357 _V2WrapValidator = Union[
358 _V2WrapValidatorClsMethod,
359 core_schema.WithInfoWrapValidatorFunction,
360 _OnlyValueWrapValidatorClsMethod,
361 core_schema.NoInfoWrapValidatorFunction,
362 ]
364 _PartialClsOrStaticMethod: TypeAlias = Union[classmethod[Any, Any, Any], staticmethod[Any, Any], partialmethod[Any]]
366 _V2BeforeAfterOrPlainValidatorType = TypeVar(
367 '_V2BeforeAfterOrPlainValidatorType',
368 bound=Union[_V2Validator, _PartialClsOrStaticMethod],
369 )
370 _V2WrapValidatorType = TypeVar('_V2WrapValidatorType', bound=Union[_V2WrapValidator, _PartialClsOrStaticMethod])
372FieldValidatorModes: TypeAlias = Literal['before', 'after', 'wrap', 'plain'] 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
375@overload 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
376def field_validator( 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
377 field: str, 1abcdeqpfghijJklmno
378 /,
379 *fields: str, 1abcdeqpfghijJklmno
380 mode: Literal['wrap'], 1abcdeqpfghijJklmno
381 check_fields: bool | None = ..., 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
382 json_schema_input_type: Any = ..., 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
383) -> Callable[[_V2WrapValidatorType], _V2WrapValidatorType]: ... 1abcdeqpfghijJklmno
386@overload 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
387def field_validator( 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
388 field: str, 1abcdeqpfghijJklmno
389 /,
390 *fields: str, 1abcdeqpfghijJklmno
391 mode: Literal['before', 'plain'], 1abcdeqpfghijJklmno
392 check_fields: bool | None = ..., 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
393 json_schema_input_type: Any = ..., 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
394) -> Callable[[_V2BeforeAfterOrPlainValidatorType], _V2BeforeAfterOrPlainValidatorType]: ... 1abcdeqpfghijJklmno
397@overload 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
398def field_validator( 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
399 field: str, 1abcdeqpfghijJklmno
400 /,
401 *fields: str, 1abcdeqpfghijJklmno
402 mode: Literal['after'] = ..., 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
403 check_fields: bool | None = ..., 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
404) -> Callable[[_V2BeforeAfterOrPlainValidatorType], _V2BeforeAfterOrPlainValidatorType]: ... 1abcdeqpfghijJklmno
407def field_validator( 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
408 field: str,
409 /,
410 *fields: str,
411 mode: FieldValidatorModes = 'after',
412 check_fields: bool | None = None,
413 json_schema_input_type: Any = PydanticUndefined,
414) -> Callable[[Any], Any]:
415 """!!! abstract "Usage Documentation"
416 [field validators](../concepts/validators.md#field-validators)
418 Decorate methods on the class indicating that they should be used to validate fields.
420 Example usage:
421 ```python
422 from typing import Any
424 from pydantic import (
425 BaseModel,
426 ValidationError,
427 field_validator,
428 )
430 class Model(BaseModel):
431 a: str
433 @field_validator('a')
434 @classmethod
435 def ensure_foobar(cls, v: Any):
436 if 'foobar' not in v:
437 raise ValueError('"foobar" not found in a')
438 return v
440 print(repr(Model(a='this is foobar good')))
441 #> Model(a='this is foobar good')
443 try:
444 Model(a='snap')
445 except ValidationError as exc_info:
446 print(exc_info)
447 '''
448 1 validation error for Model
449 a
450 Value error, "foobar" not found in a [type=value_error, input_value='snap', input_type=str]
451 '''
452 ```
454 For more in depth examples, see [Field Validators](../concepts/validators.md#field-validators).
456 Args:
457 field: The first field the `field_validator` should be called on; this is separate
458 from `fields` to ensure an error is raised if you don't pass at least one.
459 *fields: Additional field(s) the `field_validator` should be called on.
460 mode: Specifies whether to validate the fields before or after validation.
461 check_fields: Whether to check that the fields actually exist on the model.
462 json_schema_input_type: The input type of the function. This is only used to generate
463 the appropriate JSON Schema (in validation mode) and can only specified
464 when `mode` is either `'before'`, `'plain'` or `'wrap'`.
466 Returns:
467 A decorator that can be used to decorate a function to be used as a field_validator.
469 Raises:
470 PydanticUserError:
471 - If `@field_validator` is used bare (with no fields).
472 - If the args passed to `@field_validator` as fields are not strings.
473 - If `@field_validator` applied to instance methods.
474 """
475 if isinstance(field, FunctionType): 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
476 raise PydanticUserError( 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
477 '`@field_validator` should be used with fields and keyword arguments, not bare. '
478 "E.g. usage should be `@validator('<field_name>', ...)`",
479 code='validator-no-fields',
480 )
482 if mode not in ('before', 'plain', 'wrap') and json_schema_input_type is not PydanticUndefined: 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
483 raise PydanticUserError( 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
484 f"`json_schema_input_type` can't be used when mode is set to {mode!r}",
485 code='validator-input-type',
486 )
488 if json_schema_input_type is PydanticUndefined and mode == 'plain': 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
489 json_schema_input_type = Any 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
491 fields = field, *fields 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
492 if not all(isinstance(field, str) for field in fields): 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
493 raise PydanticUserError( 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
494 '`@field_validator` fields should be passed as separate string args. '
495 "E.g. usage should be `@validator('<field_name_1>', '<field_name_2>', ...)`",
496 code='validator-invalid-fields',
497 )
499 def dec( 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
500 f: Callable[..., Any] | staticmethod[Any, Any] | classmethod[Any, Any, Any],
501 ) -> _decorators.PydanticDescriptorProxy[Any]:
502 if _decorators.is_instance_method_from_sig(f): 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
503 raise PydanticUserError( 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
504 '`@field_validator` cannot be applied to instance methods', code='validator-instance-method'
505 )
507 # auto apply the @classmethod decorator
508 f = _decorators.ensure_classmethod_based_on_signature(f) 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
510 dec_info = _decorators.FieldValidatorDecoratorInfo( 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
511 fields=fields, mode=mode, check_fields=check_fields, json_schema_input_type=json_schema_input_type
512 )
513 return _decorators.PydanticDescriptorProxy(f, dec_info) 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
515 return dec 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
518_ModelType = TypeVar('_ModelType') 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
519_ModelTypeCo = TypeVar('_ModelTypeCo', covariant=True) 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
522class ModelWrapValidatorHandler(core_schema.ValidatorFunctionWrapHandler, Protocol[_ModelTypeCo]): 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
523 """`@model_validator` decorated function handler argument type. This is used when `mode='wrap'`."""
525 def __call__( # noqa: D102 1DErstuabcdeFGvwxyfghijJHIzABCklmno
526 self,
527 value: Any, 1abcdeqpfghijJklmno
528 outer_location: str | int | None = None, 1rstuabcdeqpvwxyfghijJzABCklmno
529 /,
530 ) -> _ModelTypeCo: # pragma: no cover 1abcdeqpfghijJklmno
531 ...
534class ModelWrapValidatorWithoutInfo(Protocol[_ModelType]): 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
535 """A `@model_validator` decorated function signature.
536 This is used when `mode='wrap'` and the function does not have info argument.
537 """
539 def __call__( # noqa: D102 539 ↛ exitline 539 didn't return from function '__call__' because 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
540 self,
541 cls: type[_ModelType],
542 # this can be a dict, a model instance
543 # or anything else that gets passed to validate_python
544 # thus validators _must_ handle all cases
545 value: Any,
546 handler: ModelWrapValidatorHandler[_ModelType],
547 /,
548 ) -> _ModelType: ...
551class ModelWrapValidator(Protocol[_ModelType]): 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
552 """A `@model_validator` decorated function signature. This is used when `mode='wrap'`."""
554 def __call__( # noqa: D102 554 ↛ exitline 554 didn't return from function '__call__' because 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
555 self,
556 cls: type[_ModelType],
557 # this can be a dict, a model instance
558 # or anything else that gets passed to validate_python
559 # thus validators _must_ handle all cases
560 value: Any,
561 handler: ModelWrapValidatorHandler[_ModelType],
562 info: core_schema.ValidationInfo,
563 /,
564 ) -> _ModelType: ...
567class FreeModelBeforeValidatorWithoutInfo(Protocol): 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
568 """A `@model_validator` decorated function signature. 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
569 This is used when `mode='before'` and the function does not have info argument.
570 """
572 def __call__( # noqa: D102 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
573 self,
574 # this can be a dict, a model instance
575 # or anything else that gets passed to validate_python
576 # thus validators _must_ handle all cases
577 value: Any, 1abcdeqpfghijJklmno
578 /,
579 ) -> Any: ... 1abcdeqpfghijJklmno
582class ModelBeforeValidatorWithoutInfo(Protocol): 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
583 """A `@model_validator` decorated function signature. 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
584 This is used when `mode='before'` and the function does not have info argument.
585 """
587 def __call__( # noqa: D102 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
588 self,
589 cls: Any, 1abcdeqpfghijJklmno
590 # this can be a dict, a model instance
591 # or anything else that gets passed to validate_python
592 # thus validators _must_ handle all cases
593 value: Any, 1abcdeqpfghijJklmno
594 /,
595 ) -> Any: ... 1abcdeqpfghijJklmno
598class FreeModelBeforeValidator(Protocol): 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
599 """A `@model_validator` decorated function signature. This is used when `mode='before'`.""" 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
601 def __call__( # noqa: D102 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
602 self,
603 # this can be a dict, a model instance
604 # or anything else that gets passed to validate_python
605 # thus validators _must_ handle all cases
606 value: Any, 1abcdeqpfghijJklmno
607 info: core_schema.ValidationInfo[Any], 1abcdeqpfghijJklmno
608 /,
609 ) -> Any: ... 1abcdeqpfghijJklmno
612class ModelBeforeValidator(Protocol): 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
613 """A `@model_validator` decorated function signature. This is used when `mode='before'`.""" 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
615 def __call__( # noqa: D102 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
616 self,
617 cls: Any, 1abcdeqpfghijJklmno
618 # this can be a dict, a model instance
619 # or anything else that gets passed to validate_python
620 # thus validators _must_ handle all cases
621 value: Any, 1abcdeqpfghijJklmno
622 info: core_schema.ValidationInfo[Any], 1abcdeqpfghijJklmno
623 /,
624 ) -> Any: ... 1abcdeqpfghijJklmno
627ModelAfterValidatorWithoutInfo = Callable[[_ModelType], _ModelType] 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
628"""A `@model_validator` decorated function signature. This is used when `mode='after'` and the function does not 1rstuabcdepvwxyfghijJzABCklmno
629have info argument.
630"""
632ModelAfterValidator = Callable[[_ModelType, core_schema.ValidationInfo[Any]], _ModelType] 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
633"""A `@model_validator` decorated function signature. This is used when `mode='after'`.""" 1rstuabcdepvwxyfghijJzABCklmno
635_AnyModelWrapValidator = Union[ModelWrapValidator[_ModelType], ModelWrapValidatorWithoutInfo[_ModelType]] 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
636_AnyModelBeforeValidator = Union[ 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
637 FreeModelBeforeValidator, ModelBeforeValidator, FreeModelBeforeValidatorWithoutInfo, ModelBeforeValidatorWithoutInfo
638]
639_AnyModelAfterValidator = Union[ModelAfterValidator[_ModelType], ModelAfterValidatorWithoutInfo[_ModelType]] 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
642@overload 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
643def model_validator( 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
644 *,
645 mode: Literal['wrap'], 1abcdeqpfghijJklmno
646) -> Callable[ 1abcdeqpfghijJklmno
647 [_AnyModelWrapValidator[_ModelType]], _decorators.PydanticDescriptorProxy[_decorators.ModelValidatorDecoratorInfo]
648]: ...
651@overload 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
652def model_validator( 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
653 *,
654 mode: Literal['before'], 1abcdeqpfghijJklmno
655) -> Callable[ 1abcdeqpfghijJklmno
656 [_AnyModelBeforeValidator], _decorators.PydanticDescriptorProxy[_decorators.ModelValidatorDecoratorInfo]
657]: ...
660@overload 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
661def model_validator( 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
662 *,
663 mode: Literal['after'], 1abcdeqpfghijJklmno
664) -> Callable[ 1abcdeqpfghijJklmno
665 [_AnyModelAfterValidator[_ModelType]], _decorators.PydanticDescriptorProxy[_decorators.ModelValidatorDecoratorInfo]
666]: ...
669def model_validator( 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
670 *,
671 mode: Literal['wrap', 'before', 'after'],
672) -> Any:
673 """!!! abstract "Usage Documentation"
674 [Model Validators](../concepts/validators.md#model-validators)
676 Decorate model methods for validation purposes.
678 Example usage:
679 ```python
680 from typing_extensions import Self
682 from pydantic import BaseModel, ValidationError, model_validator
684 class Square(BaseModel):
685 width: float
686 height: float
688 @model_validator(mode='after')
689 def verify_square(self) -> Self:
690 if self.width != self.height:
691 raise ValueError('width and height do not match')
692 return self
694 s = Square(width=1, height=1)
695 print(repr(s))
696 #> Square(width=1.0, height=1.0)
698 try:
699 Square(width=1, height=2)
700 except ValidationError as e:
701 print(e)
702 '''
703 1 validation error for Square
704 Value error, width and height do not match [type=value_error, input_value={'width': 1, 'height': 2}, input_type=dict]
705 '''
706 ```
708 For more in depth examples, see [Model Validators](../concepts/validators.md#model-validators).
710 Args:
711 mode: A required string literal that specifies the validation mode.
712 It can be one of the following: 'wrap', 'before', or 'after'.
714 Returns:
715 A decorator that can be used to decorate a function to be used as a model validator.
716 """
718 def dec(f: Any) -> _decorators.PydanticDescriptorProxy[Any]: 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
719 # auto apply the @classmethod decorator (except for *after* validators, which should be instance methods):
720 if mode != 'after': 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
721 f = _decorators.ensure_classmethod_based_on_signature(f) 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
722 dec_info = _decorators.ModelValidatorDecoratorInfo(mode=mode) 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
723 return _decorators.PydanticDescriptorProxy(f, dec_info) 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
725 return dec 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
728AnyType = TypeVar('AnyType') 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
731if TYPE_CHECKING: 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
732 # If we add configurable attributes to IsInstance, we'd probably need to stop hiding it from type checkers like this
733 InstanceOf = Annotated[AnyType, ...] # `IsInstance[Sequence]` will be recognized by type checkers as `Sequence`
735else:
737 @dataclasses.dataclass(**_internal_dataclass.slots_true) 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
738 class InstanceOf: 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
739 '''Generic type for annotating a type that is an instance of a given class.
741 Example:
742 ```python
743 from pydantic import BaseModel, InstanceOf
745 class Foo:
746 ...
748 class Bar(BaseModel):
749 foo: InstanceOf[Foo]
751 Bar(foo=Foo())
752 try:
753 Bar(foo=42)
754 except ValidationError as e:
755 print(e)
756 """
757 [
758 │ {
759 │ │ 'type': 'is_instance_of',
760 │ │ 'loc': ('foo',),
761 │ │ 'msg': 'Input should be an instance of Foo',
762 │ │ 'input': 42,
763 │ │ 'ctx': {'class': 'Foo'},
764 │ │ 'url': 'https://errors.pydantic.dev/0.38.0/v/is_instance_of'
765 │ }
766 ]
767 """
768 ```
769 '''
771 @classmethod 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
772 def __class_getitem__(cls, item: AnyType) -> AnyType: 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
773 return Annotated[item, cls()] 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
775 @classmethod 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
776 def __get_pydantic_core_schema__(cls, source: Any, handler: GetCoreSchemaHandler) -> core_schema.CoreSchema: 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
777 from pydantic import PydanticSchemaGenerationError 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
779 # use the generic _origin_ as the second argument to isinstance when appropriate
780 instance_of_schema = core_schema.is_instance_schema(_generics.get_origin(source) or source) 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
782 try: 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
783 # Try to generate the "standard" schema, which will be used when loading from JSON
784 original_schema = handler(source) 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
785 except PydanticSchemaGenerationError: 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
786 # If that fails, just produce a schema that can validate from python
787 return instance_of_schema 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
788 else:
789 # Use the "original" approach to serialization
790 instance_of_schema['serialization'] = core_schema.wrap_serializer_function_ser_schema( 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
791 function=lambda v, h: h(v), schema=original_schema
792 )
793 return core_schema.json_or_python_schema(python_schema=instance_of_schema, json_schema=original_schema) 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
795 __hash__ = object.__hash__ 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
798if TYPE_CHECKING: 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
799 SkipValidation = Annotated[AnyType, ...] # SkipValidation[list[str]] will be treated by type checkers as list[str]
800else:
802 @dataclasses.dataclass(**_internal_dataclass.slots_true) 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
803 class SkipValidation: 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
804 """If this is applied as an annotation (e.g., via `x: Annotated[int, SkipValidation]`), validation will be
805 skipped. You can also use `SkipValidation[int]` as a shorthand for `Annotated[int, SkipValidation]`.
807 This can be useful if you want to use a type annotation for documentation/IDE/type-checking purposes,
808 and know that it is safe to skip validation for one or more of the fields.
810 Because this converts the validation schema to `any_schema`, subsequent annotation-applied transformations
811 may not have the expected effects. Therefore, when used, this annotation should generally be the final
812 annotation applied to a type.
813 """
815 def __class_getitem__(cls, item: Any) -> Any: 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
816 return Annotated[item, SkipValidation()] 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
818 @classmethod 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
819 def __get_pydantic_core_schema__(cls, source: Any, handler: GetCoreSchemaHandler) -> core_schema.CoreSchema: 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno
820 original_schema = handler(source) 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
821 metadata = {'pydantic_js_annotation_functions': [lambda _c, h: h(original_schema)]} 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
822 return core_schema.any_schema( 1DErstuabcdeqpFGvwxyfghijHIzABCklmno
823 metadata=metadata,
824 serialization=core_schema.wrap_serializer_function_ser_schema(
825 function=lambda v, h: h(v), schema=original_schema
826 ),
827 )
829 __hash__ = object.__hash__ 1DErstuabcdeqpFGvwxyfghijJHIzABCklmno