基于Pydantic 2.7的自定义区间值验证类实现报错排查

你的错误根源是__get_pydantic_core_schema__方法的签名不符合Pydantic v2的要求，该方法需要接收三个参数：self、source_type（当前被处理的类型）和handler（用于生成基础类型Schema的回调函数）。之前的定义缺少了source_type参数，导致Pydantic调用时参数不匹配，触发了类型错误。

以下是两种正确的类实现方案：

方案一：基础类实现 #

直接修正方法签名并完善Schema生成逻辑：

from typing import Any, Callable
from pydantic_core import CoreSchema
from pydantic import validate_call


class ValueInInterval:
    def __init__(
        self,
        type_definition: Any,
        start: Any,
        end: Any,
        include_start: bool = True,
        include_end: bool = True,
    ):
        self.type_definition = type_definition
        self.start = start
        self.end = end
        self.include_start = include_start
        self.include_end = include_end

    def __get_pydantic_core_schema__(
        self,
        source_type: Any,
        handler: Callable[[Any], CoreSchema],
    ) -> CoreSchema:
        # 先获取基础类型的核心Schema
        base_schema = handler(self.type_definition)
        
        # 根据配置添加区间验证规则
        if self.include_start:
            base_schema["ge"] = self.start
        else:
            base_schema["gt"] = self.start
        
        if self.include_end:
            base_schema["le"] = self.end
        else:
            base_schema["lt"] = self.end
        
        return base_schema


@validate_call()
def test_interval(
    value: ValueInInterval(type_definition=int, start=1, end=10),
):
    print(value)


test_interval(value=1)  # 执行成功，输出1
# test_interval(value=0)  # 触发ValidationError，值小于区间下限

方案二：泛型类实现（推荐，类型提示更友好） #

通过泛型让类型注解具备更好的IDE提示能力：

from typing import Any, Callable, Generic, TypeVar
from pydantic_core import CoreSchema
from pydantic import validate_call

T = TypeVar('T')


class ValueInInterval(Generic[T]):
    def __init__(
        self,
        start: T,
        end: T,
        include_start: bool = True,
        include_end: bool = True,
    ):
        self.start = start
        self.end = end
        self.include_start = include_start
        self.include_end = include_end
        self.type_definition = T

    def __get_pydantic_core_schema__(
        self,
        source_type: Any,
        handler: Callable[[Any], CoreSchema],
    ) -> CoreSchema:
        base_schema = handler(self.type_definition)
        
        if self.include_start:
            base_schema["ge"] = self.start
        else:
            base_schema["gt"] = self.start
        
        if self.include_end:
            base_schema["le"] = self.end
        else:
            base_schema["lt"] = self.end
        
        return base_schema


@validate_call()
def test_interval(
    value: ValueInInterval[int](start=1, end=10),
):
    print(value)


test_interval(value=1)  # 执行成功，输出1
# test_interval(value=11) # 触发ValidationError，值大于区间上限

关键修正点说明 #

1. 修正方法签名：添加source_type参数，符合Pydantic v2对自定义类型Schema生成方法的要求
2. 正确生成基础Schema：通过handler回调获取传入类型的核心验证规则，再叠加区间验证逻辑
3. 泛型优化：方案二通过泛型让IDE能识别参数的实际类型（如int），提升开发体验

内容的提问来源于stack exchange，提问作者Jacob Ayers