如何在验证错误中从 loc 中删除鉴别器值？

Question

我使用 Pydantic v2。现在我想从

loc

或验证错误中删除鉴别器值。请看下面的代码：

from pprint import pprint
from typing import Literal, Union, Annotated, Any

from pydantic import BaseModel, Field, RootModel, ValidationError
from pydantic.main import Model


class Tiger(BaseModel):
    animal_type: Literal["tiger"] = "tiger"
    ferocity_scale: float = Field(..., ge=0, le=10)


class Shark(BaseModel):
    animal_type: Literal["shark"] = "shark"
    ferocity_scale: float = Field(..., ge=0, le=10)


class Lion(BaseModel):
    animal_type: Literal["lion"] = "lion"
    ferocity_scale: float


class WildAnimal(RootModel):
    root: Annotated[Union[Tiger, Shark, Lion], Field(..., discriminator='animal_type')]


try:
    my_shark = WildAnimal.model_validate({'animal_type': 'shark', 'ferocity_scale': 115})
except ValidationError as exc:
    pprint(exc.errors())

代码打印：

[{'ctx': {'le': 10.0},
  'input': 115,
  'loc': ('shark', 'ferocity_scale'),  <------ how to drop "shark"?
  'msg': 'Input should be less than or equal to 10',
  'type': 'less_than_equal',
  'url': 'https://errors.pydantic.dev/2.7/v/less_than_equal'}]

在

loc

键中，您可以注意到

('shark', 'ferocity_scale')

。值

shark

是鉴别器

animal_type

值。

如何通过Pydantic删除它？或者如何动态检测

loc

的第一个值是鉴别器值？

我唯一能弄清楚的是：

class WildAnimal(RootModel):
    root: Annotated[Union[Tiger, Shark, Lion], Field(..., discriminator='animal_type')]

    @classmethod
    def model_validate(cls: type[Model], obj: Any, *, strict: bool | None = None, from_attributes: bool | None = None,
                       context: dict[str, Any] | None = None) -> Model:
        try:
            return super().model_validate(obj, strict=strict, from_attributes=from_attributes, context=context)
        except ValidationError as exc:
            # modify loc
            # reraise ValidationError

Answer 1

必须实现装饰器：

def reconstruct_validation_error(func):
    @wraps(func)
    def wrapper(*args, **kwargs):
        try:
            return func(*args, **kwargs)
        except ValidationError as e:
            errors = e.errors()
            for error in errors:
                error["loc"] = tuple(list(error["loc"])[1:])
            title, _ = func.__qualname__.split(".", maxsplit=1)
            raise ValidationError.from_exception_data(title=title, line_errors=errors)
    return wrapper


class WildAnimal(RootModel):
    root: Annotated[
        Union[Tiger, Shark, Lion],
        Field(..., discriminator='animal_type'),
    ]

    @reconstruct_validation_error
    def __init__(self, /, root: RootModelRootType = PydanticUndefined, **data) -> None:
        super().__init__(root, **data)