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如何创建pydantic泛型类型来检查validate上的min_length和max_length?

pydantic types generics python-3.x

Alan Latte · 技术社区 · 3 年前

我有个主意。在我的个人项目中,我有很多方法来检查所描述的模型(检查密码长度、用户名字符等),但如果我描述一个Generic类,它将按照在其中指定某些参数的原则工作呢?

如:


class User(BaseModel):
     username: String[15,32]
     password: SecretBytes[6,100]

另一个用例: 我经常使用不同的int基,而不是处理值,我希望能够指定类型 Int[16] 或 Int[10] ,如果可能的话,由于pydantic本身将把值转换为我需要的值

你有什么想法可以做到这一点吗?

我在官方文档中找到了一个例子,但我不明白如何将其升级到我的愿望。

from typing import Any, Callable, Sequence, TypeVar

from pydantic_core import ValidationError, core_schema
from typing_extensions import get_args

from pydantic import BaseModel

T = TypeVar('T')


class MySequence(Sequence[T]):
    def __init__(self, v: Sequence[T]):
        self.v = v

    def __getitem__(self, i):
        return self.v[i]

    def __len__(self):
        return len(self.v)

    @classmethod
    def __get_pydantic_core_schema__(
        cls, source: Any, handler: Callable[[Any], core_schema.CoreSchema]
    ) -> core_schema.CoreSchema:
        instance_schema = core_schema.is_instance_schema(cls)

        args = get_args(source)
        if args:
            # replace the type and rely on Pydantic to generate the right schema
            # for `Sequence`
            sequence_t_schema = handler.generate_schema(Sequence[args[0]])
        else:
            sequence_t_schema = handler.generate_schema(Sequence)

        non_instance_schema = core_schema.general_after_validator_function(
            lambda v, i: MySequence(v), sequence_t_schema
        )
        return core_schema.union_schema([instance_schema, non_instance_schema])


class M(BaseModel):
    model_config = dict(validate_default=True)

    s1: MySequence = [3]


m = M()
print(m)
#> s1=<__main__.MySequence object at 0x0123456789ab>
print(m.s1.v)
#> [3]


class M(BaseModel):
    s1: MySequence[int]


M(s1=[1])
try:
    M(s1=['a'])
except ValidationError as exc:
    print(exc)
    """
    2 validation errors for M
    s1.is-instance[MySequence]
      Input should be an instance of MySequence [type=is_instance_of, input_value=['a'], input_type=list]
    s1.function-after[<lambda>(), json-or-python[json=list[int],python=chain[is-instance[Sequence],function-wrap[sequence_validator()]]]].0
      Input should be a valid integer, unable to parse string as an integer [type=int_parsing, input_value='a', input_type=str]
    """

代码来源: https://docs.pydantic.dev/latest/usage/types/custom/#generic-containers

0 回复 | 直到 3 年前

Svidrig_cth01 2 年前

您可以在python中使用带有雷电方法的Metaclass __getitem__

我使用python3.9和pydantic1.10,但它需要在pydantic2上工作

from typing import Annotated, TypeVar

from pydantic import BaseModel, Field

T = TypeVar("T", bound=int)


class MetaMaxStr(type):
    def __getitem__(cls, tuple_length: tuple = (0, 1)):
        min_length, max_length = tuple_length
        if min_length > max_length:
            raise ValueError("min_length must be less than max_length")
        return Annotated[str, Field(min_length=min_length, max_length=max_length)]


class MaxStr(metaclass=MetaMaxStr):
    pass


class Item(BaseModel):
    id: int
    name: MaxStr[5, 5]


def main() -> None:
    item = Item(id=1, name="test1")
    print(item.dict())


if __name__ == "__main__":
    main()