a ~gr @sUdZddlmZddlZddlZddlmZddlm Z ddl m Z m Z m Z mZmZmZmZddlmZmZddlmZdd lmZmZmZmZd d lmZmZmZd d lm Z d d l!m"Z"ej#dkrddlm$Z$n ddl m$Z$ej%Z&ej'fddiej(GdddZ)ej'fddiej(GdddZ*ej'fddiej(GdddZ+ej'fddiej(GdddZ,e r:Gddde$Z-Gddde$Z.Gddde$Z/Gd d!d!e$Z0ee.ej1e-ej2fZ3ee0ej4e/ej5fZ6ee7e e e fe8e e fee fZ9d"e:d#<ed$ee3e9fd%Z;ed&ee6e9fd%Zed)d)d*d+d+d3d-d.d4d0d5d2Z>ed)d)d6d+d+d7d-d4d8d9d2Z>d:ded;d+d+d(d-d.ded>Z?ed?dd@Z@GdAdBdBejAe$e@ZBGdCdDdDe$e?ZCGdEdFdFe$e?ZDGdGdHdHe$ZEGdIdJdJe$ZFGdKdLdLe$ZGGdMdNdNe$ZHe e?ge?fZIe e?ejJge?fZKeeDe?eCe?fZLeeGeHeEeFfZMeeKe?eIe?fZNed,dOdPdQdRZOedSdTdPdUdRZOed7dVdPdWdRZOdXd.dPdYdRZOedZZPe r*eePd)fZQn ej'fiej(Gd[d\d\ZQe r^eePd)fZRn ej'fiej(Gd]d^d^ZRdS)_zBThis module contains related classes and functions for validation.) annotationsN) partialmethod) FunctionType) TYPE_CHECKINGAnyCallableTypeVarUnioncastoverload)PydanticUndefined core_schema)r ) AnnotatedLiteralSelf TypeAlias) _decorators _generics_internal_dataclass)GetCoreSchemaHandler)PydanticUserError) )ProtocolfrozenTc@s@eZdZUdZded<dddddd Zed d d d dZdS)AfterValidatora9Usage docs: https://docs.pydantic.dev/2.10/concepts/validators/#field-validators A metadata class that indicates that a validation should be applied **after** the inner validation logic. Attributes: func: The validator function. Example: ```python from typing_extensions import Annotated from pydantic import AfterValidator, BaseModel, ValidationError MyInt = Annotated[int, AfterValidator(lambda v: v + 1)] class Model(BaseModel): a: MyInt print(Model(a=1).a) #> 2 try: Model(a='a') except ValidationError as e: print(e.json(indent=2)) ''' [ { "type": "int_parsing", "loc": [ "a" ], "msg": "Input should be a valid integer, unable to parse string as an integer", "input": "a", "url": "https://errors.pydantic.dev/2/v/int_parsing" } ] ''' ``` Kcore_schema.NoInfoValidatorFunction | core_schema.WithInfoValidatorFunctionfuncrrcore_schema.CoreSchema source_typehandlerreturncCsX||}t|jd}|r8ttj|j}tj|||jdSttj|j}tj||dSdS)Nafter)schema field_name)r%) _inspect_validatorrr r WithInfoValidatorFunction"with_info_after_validator_functionr&NoInfoValidatorFunction no_info_after_validator_function)selfr!r"r%info_argrr.c/var/www/html/emsaiapi.evdpl.com/venv/lib/python3.9/site-packages/pydantic/functional_validators.py__get_pydantic_core_schema__Hs z+AfterValidator.__get_pydantic_core_schema__>_decorators.Decorator[_decorators.FieldValidatorDecoratorInfo]r decoratorr#cCs ||jdS)Nrr4clsr3r.r.r/_from_decoratorRszAfterValidator._from_decoratorN)__name__ __module__ __qualname____doc____annotations__r0 classmethodr7r.r.r.r/rs ) rc@sLeZdZUdZded<eZded<ddddd d Zed d d ddZ dS)BeforeValidatoraeUsage docs: https://docs.pydantic.dev/2.10/concepts/validators/#field-validators A metadata class that indicates that a validation should be applied **before** the inner validation logic. Attributes: func: The validator function. json_schema_input_type: The input type of the function. This is only used to generate the appropriate JSON Schema (in validation mode). Example: ```python from typing_extensions import Annotated from pydantic import BaseModel, BeforeValidator MyInt = Annotated[int, BeforeValidator(lambda v: v + 1)] class Model(BaseModel): a: MyInt print(Model(a=1).a) #> 2 try: Model(a='a') except TypeError as e: print(e) #> can only concatenate str (not "int") to str ``` rrrjson_schema_input_typerrr cCsv||}|jturdn ||j}t|jd}|rTttj|j}tj|||j |dSttj |j}tj |||dSdS)Nbeforer%r&json_schema_input_schemar%rB) r?r generate_schemar'rr r r(#with_info_before_validator_functionr&r*!no_info_before_validator_functionr,r!r"r% input_schemar-rr.r.r/r0{s$  z,BeforeValidator.__get_pydantic_core_schema__r1rr2cCs||j|jjdSN)rr?rinfor?r5r.r.r/r7szBeforeValidator._from_decoratorN r8r9r:r;r<r r?r0r=r7r.r.r.r/r>Ws  r>c@sLeZdZUdZded<eZded<ddddd d Zed d d ddZ dS)PlainValidatoraUsage docs: https://docs.pydantic.dev/2.10/concepts/validators/#field-validators A metadata class that indicates that a validation should be applied **instead** of the inner validation logic. !!! note Before v2.9, `PlainValidator` wasn't always compatible with JSON Schema generation for `mode='validation'`. You can now use the `json_schema_input_type` argument to specify the input type of the function to be used in the JSON schema when `mode='validation'` (the default). See the example below for more details. Attributes: func: The validator function. json_schema_input_type: The input type of the function. This is only used to generate the appropriate JSON Schema (in validation mode). If not provided, will default to `Any`. Example: ```python from typing import Union from typing_extensions import Annotated from pydantic import BaseModel, PlainValidator MyInt = Annotated[ int, PlainValidator( lambda v: int(v) + 1, json_schema_input_type=Union[str, int] # (1)! ), ] class Model(BaseModel): a: MyInt print(Model(a='1').a) #> 2 print(Model(a=1).a) #> 2 ``` 1. In this example, we've specified the `json_schema_input_type` as `Union[str, int]` which indicates to the JSON schema generator that in validation mode, the input type for the `a` field can be either a `str` or an `int`. rrrr?rrr c Csddlm}z.||}|dtjdd|||d}Wn|yPd}Yn0||j}t|jd}|rt tj |j}tj ||j ||dSt tj |j}tj|||d SdS) NrPydanticSchemaGenerationError serializationcSs||SNr.vhr.r.r/z=PlainValidator.__get_pydantic_core_schema__..)functionr% return_schemaplain)r&rPrB)rPrB)pydanticrOgetr #wrap_serializer_function_ser_schemarDr?r'rr r("with_info_plain_validator_functionr&r* no_info_plain_validator_function) r,r!r"rOr%rPrHr-rr.r.r/r0s:     z+PlainValidator.__get_pydantic_core_schema__r1rr2cCs||j|jjdSrIrJr5r.r.r/r7szPlainValidator._from_decoratorN) r8r9r:r;r<rr?r0r=r7r.r.r.r/rMs + *rMc@sLeZdZUdZded<eZded<ddddd d Zed d d ddZ dS) WrapValidatoraUsage docs: https://docs.pydantic.dev/2.10/concepts/validators/#field-validators A metadata class that indicates that a validation should be applied **around** the inner validation logic. Attributes: func: The validator function. json_schema_input_type: The input type of the function. This is only used to generate the appropriate JSON Schema (in validation mode). ```python from datetime import datetime from typing_extensions import Annotated from pydantic import BaseModel, ValidationError, WrapValidator def validate_timestamp(v, handler): if v == 'now': # we don't want to bother with further validation, just return the new value return datetime.now() try: return handler(v) except ValidationError: # validation failed, in this case we want to return a default value return datetime(2000, 1, 1) MyTimestamp = Annotated[datetime, WrapValidator(validate_timestamp)] class Model(BaseModel): a: MyTimestamp print(Model(a='now').a) #> 2032-01-02 03:04:05.000006 print(Model(a='invalid').a) #> 2000-01-01 00:00:00 ``` zScore_schema.NoInfoWrapValidatorFunction | core_schema.WithInfoWrapValidatorFunctionrrr?rrr cCsv||}|jturdn ||j}t|jd}|rTttj|j}tj|||j |dSttj |j}tj |||dSdS)NwraprArC) r?r rDr'rr r WithInfoWrapValidatorFunction!with_info_wrap_validator_functionr&NoInfoWrapValidatorFunctionno_info_wrap_validator_functionrGr.r.r/r0's(  z*WrapValidator.__get_pydantic_core_schema__r1rr2cCs||j|jjdSrIrJr5r.r.r/r7@szWrapValidator._from_decoratorNrLr.r.r.r/r_s & r_c@seZdZddddddZdS)_OnlyValueValidatorClsMethodrr6valuer#cCsdSrQr.r,r6rgr.r.r/__call__KrVz%_OnlyValueValidatorClsMethod.__call__Nr8r9r:rir.r.r.r/reJsrec@s eZdZdddddddZdS)_V2ValidatorClsMethodr_core_schema.ValidationInfor6rgrKr#cCsdSrQr.r,r6rgrKr.r.r/riNrVz_V2ValidatorClsMethod.__call__Nrjr.r.r.r/rkMsrkc@s eZdZdddddddZdS) _OnlyValueWrapValidatorClsMethodr)_core_schema.ValidatorFunctionWrapHandlerr6rgr"r#cCsdSrQr.r,r6rgr"r.r.r/riQrVz)_OnlyValueWrapValidatorClsMethod.__call__Nrjr.r.r.r/roPsroc@s"eZdZddddddddZdS)_V2WrapValidatorClsMethodrrprlr6rgr"rKr#cCsdSrQr.r,r6rgr"rKr.r.r/riTsz"_V2WrapValidatorClsMethod.__call__Nrjr.r.r.r/rsSsrsr_PartialClsOrStaticMethod"_V2BeforeAfterOrPlainValidatorType)bound_V2WrapValidatorType)r@r$r`rYFieldValidatorModes.) check_fieldsr?strzLiteral['wrap']z bool | Nonerz6Callable[[_V2WrapValidatorType], _V2WrapValidatorType])fieldfieldsmoder{r?r#cGsdSrQr.r}rr{r?r~r.r.r/field_validatorvsrzLiteral['before', 'plain']zRCallable[[_V2BeforeAfterOrPlainValidatorType], _V2BeforeAfterOrPlainValidatorType]cGsdSrQr.rr.r.r/rs)rr{zLiteral['after'])r}r~rr{r#cGsdSrQr.)r}rr{r~r.r.r/rsr$)rr{r?zCallable[[Any], Any]cst|trtddddvr8tur8tdddturLdkrLt|gRtdd Dsvtd d dd d dfdd }|S)a6Usage docs: https://docs.pydantic.dev/2.10/concepts/validators/#field-validators Decorate methods on the class indicating that they should be used to validate fields. Example usage: ```python from typing import Any from pydantic import ( BaseModel, ValidationError, field_validator, ) class Model(BaseModel): a: str @field_validator('a') @classmethod def ensure_foobar(cls, v: Any): if 'foobar' not in v: raise ValueError('"foobar" not found in a') return v print(repr(Model(a='this is foobar good'))) #> Model(a='this is foobar good') try: Model(a='snap') except ValidationError as exc_info: print(exc_info) ''' 1 validation error for Model a Value error, "foobar" not found in a [type=value_error, input_value='snap', input_type=str] ''' ``` For more in depth examples, see [Field Validators](../concepts/validators.md#field-validators). Args: field: The first field the `field_validator` should be called on; this is separate from `fields` to ensure an error is raised if you don't pass at least one. *fields: Additional field(s) the `field_validator` should be called on. mode: Specifies whether to validate the fields before or after validation. check_fields: Whether to check that the fields actually exist on the model. json_schema_input_type: The input type of the function. This is only used to generate the appropriate JSON Schema (in validation mode) and can only specified when `mode` is either `'before'`, `'plain'` or `'wrap'`. Returns: A decorator that can be used to decorate a function to be used as a field_validator. Raises: PydanticUserError: - If `@field_validator` is used bare (with no fields). - If the args passed to `@field_validator` as fields are not strings. - If `@field_validator` applied to instance methods. z`@field_validator` should be used with fields and keyword arguments, not bare. E.g. usage should be `@validator('', ...)`zvalidator-no-fieldscode)r@rYr`z;`json_schema_input_type` can't be used when mode is set to zvalidator-input-typerYcss|]}t|tVqdSrQ) isinstancer|).0r}r.r.r/ rVz"field_validator..z`@field_validator` fields should be passed as separate string args. E.g. usage should be `@validator('', '', ...)`zvalidator-invalid-fieldszHCallable[..., Any] | staticmethod[Any, Any] | classmethod[Any, Any, Any](_decorators.PydanticDescriptorProxy[Any]fr#cs>t|rtdddt|}tjd}t||S)Nz8`@field_validator` cannot be applied to instance methodszvalidator-instance-methodr)r~rr{r?)ris_instance_method_from_sigr%ensure_classmethod_based_on_signatureFieldValidatorDecoratorInfoPydanticDescriptorProxyrdec_infor{r~r?rr.r/decs  zfield_validator..dec)rrrr rall)r}rr{r?r~rr.rr/rs(C   _ModelType _ModelTypeCo) covariantc@s$eZdZdZd ddddddZdS) ModelWrapValidatorHandlerz]`@model_validator` decorated function handler argument type. This is used when `mode='wrap'`.Nrzstr | int | Noner)rgouter_locationr#cCsdSrQr.)r,rgrr.r.r/ri sz"ModelWrapValidatorHandler.__call__)Nr8r9r:r;rir.r.r.r/rsrc@s$eZdZdZdddddddZd S) ModelWrapValidatorWithoutInfozA `@model_validator` decorated function signature. This is used when `mode='wrap'` and the function does not have info argument. type[_ModelType]r%ModelWrapValidatorHandler[_ModelType]rrqcCsdSrQr.rrr.r.r/ris z&ModelWrapValidatorWithoutInfo.__call__Nrr.r.r.r/rsrc@s&eZdZdZdddddddd Zd S) ModelWrapValidatorzSA `@model_validator` decorated function signature. This is used when `mode='wrap'`.rrrrlrrtcCsdSrQr.rur.r.r/ri(s zModelWrapValidator.__call__Nrr.r.r.r/r%src@s eZdZdZdddddZdS)#FreeModelBeforeValidatorWithoutInfoA `@model_validator` decorated function signature. This is used when `mode='before'` and the function does not have info argument. r)rgr#cCsdSrQr.)r,rgr.r.r/ri:sz,FreeModelBeforeValidatorWithoutInfo.__call__Nrr.r.r.r/r5src@s"eZdZdZddddddZdS)ModelBeforeValidatorWithoutInforrrfcCsdSrQr.rhr.r.r/riIsz(ModelBeforeValidatorWithoutInfo.__call__Nrr.r.r.r/rDsrc@s"eZdZdZddddddZdS)FreeModelBeforeValidatorUA `@model_validator` decorated function signature. This is used when `mode='before'`.rrl)rgrKr#cCsdSrQr.)r,rgrKr.r.r/riWsz!FreeModelBeforeValidator.__call__Nrr.r.r.r/rTsrc@s$eZdZdZdddddddZdS)ModelBeforeValidatorrrrlrmcCsdSrQr.rnr.r.r/ries zModelBeforeValidator.__call__Nrr.r.r.r/rbsrz|Callable[[_AnyModelWrapValidator[_ModelType]], _decorators.PydanticDescriptorProxy[_decorators.ModelValidatorDecoratorInfo]])rr#cCsdSrQr.rr.r.r/model_validatorsrzLiteral['before']zrCallable[[_AnyModelBeforeValidator], _decorators.PydanticDescriptorProxy[_decorators.ModelValidatorDecoratorInfo]]cCsdSrQr.rr.r.r/rsz}Callable[[_AnyModelAfterValidator[_ModelType]], _decorators.PydanticDescriptorProxy[_decorators.ModelValidatorDecoratorInfo]]cCsdSrQr.rr.r.r/rsz"Literal['wrap', 'before', 'after']csdddfdd }|S)a'Usage docs: https://docs.pydantic.dev/2.10/concepts/validators/#model-validators Decorate model methods for validation purposes. Example usage: ```python from typing_extensions import Self from pydantic import BaseModel, ValidationError, model_validator class Square(BaseModel): width: float height: float @model_validator(mode='after') def verify_square(self) -> Self: if self.width != self.height: raise ValueError('width and height do not match') return self s = Square(width=1, height=1) print(repr(s)) #> Square(width=1.0, height=1.0) try: Square(width=1, height=2) except ValidationError as e: print(e) ''' 1 validation error for Square Value error, width and height do not match [type=value_error, input_value={'width': 1, 'height': 2}, input_type=dict] ''' ``` For more in depth examples, see [Model Validators](../concepts/validators.md#model-validators). Args: mode: A required string literal that specifies the validation mode. It can be one of the following: 'wrap', 'before', or 'after'. Returns: A decorator that can be used to decorate a function to be used as a model validator. rrrcs"t|}tjd}t||S)Nr)rrModelValidatorDecoratorInforrrr.r/rs  zmodel_validator..decr.)rrr.rr/rs0AnyTypec@s@eZdZdZedddddZedddd d d ZejZd S) InstanceOfuGeneric type for annotating a type that is an instance of a given class. Example: ```python from pydantic import BaseModel, InstanceOf class Foo: ... class Bar(BaseModel): foo: InstanceOf[Foo] Bar(foo=Foo()) try: Bar(foo=42) except ValidationError as e: print(e) """ [ │ { │ │ 'type': 'is_instance_of', │ │ 'loc': ('foo',), │ │ 'msg': 'Input should be an instance of Foo', │ │ 'input': 42, │ │ 'ctx': {'class': 'Foo'}, │ │ 'url': 'https://errors.pydantic.dev/0.38.0/v/is_instance_of' │ } ] """ ``` ritemr#cCst||fSrQ)rr6rr.r.r/__class_getitem__szInstanceOf.__class_getitem__rrrsourcer"r#cCslddlm}tt|p|}z ||}Wn|yB|YS0tjdd|d|d<tj||dSdS)NrrNcSs||SrQr.rRr.r.r/rUrVz9InstanceOf.__get_pydantic_core_schema__..rWr%rP) python_schema json_schema)rZrOr is_instance_schemar get_originr\json_or_python_schema)r6rr"rOZinstance_of_schemaoriginal_schemar.r.r/r0s     z'InstanceOf.__get_pydantic_core_schema__N) r8r9r:r;r=rr0object__hash__r.r.r.r/rs  rc@s<eZdZdZdddddZeddddd d ZejZd S) SkipValidationaIf this is applied as an annotation (e.g., via `x: Annotated[int, SkipValidation]`), validation will be skipped. You can also use `SkipValidation[int]` as a shorthand for `Annotated[int, SkipValidation]`. This can be useful if you want to use a type annotation for documentation/IDE/type-checking purposes, and know that it is safe to skip validation for one or more of the fields. Because this converts the validation schema to `any_schema`, subsequent annotation-applied transformations may not have the expected effects. Therefore, when used, this annotation should generally be the final annotation applied to a type. rrcCst|tfSrQ)rrrr.r.r/r+sz SkipValidation.__class_getitem__rrrcs6||dfddgi}tj|tjddddS)N pydantic_js_annotation_functionscs|SrQr.)Z_crTrr.r/rU1rVz=SkipValidation.__get_pydantic_core_schema__..cSs||SrQr.rRr.r.r/rU5rVr)metadatarP)r any_schemar\)r6rr"rr.rr/r0.sz+SkipValidation.__get_pydantic_core_schema__N) r8r9r:r;rr=r0rrr.r.r.r/rs   r)Sr; __future__r _annotations dataclassessys functoolsrtypesrtypingrrrrr r r pydantic_corer r _core_schematyping_extensionsrrrr _internalrrrannotated_handlersrerrorsr version_inforinspect_validatorr' dataclass slots_truerr>rMr_rerkrorsr(r*Z _V2ValidatorrarcZ_V2WrapValidatorr= staticmethodrvr<rwryrzrrrValidatorFunctionWrapHandlerrrrrrrrZModelAfterValidatorWithoutInfoValidationInfoZModelAfterValidatorZ_AnyModelWrapValidatorZ_AnyModelBeforeValidatorZ_AnyModelAfterValidatorrrrrr.r.r.r/s   $     ;BaK ,    n   9<