#  Copyright 2026 zhaoxi826
#
#  Licensed under the Apache License, Version 2.0 (the "License");
#  you may not use this file except in compliance with the License.
#  You may obtain a copy of the License at
#
#       http://www.apache.org/licenses/LICENSE-2.0
#
#  Unless required by applicable law or agreed to in writing, software
#  distributed under the License is distributed on an "AS IS" BASIS,
#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
#  See the License for the specific language governing permissions and
#  limitations under the License.

from typing import Type, TypeVar
from pydantic import BaseModel

T = TypeVar("T", bound=Type[BaseModel])

def pickle(cls: T) -> T:
    """
    类装饰器pickle
    通过装饰继承了BaseModel的类，用pydantic的高效序列化替代python原生__reduce__魔术方法,实现ray在通讯时的高效序列化
    Args:
        cls: 继承了BaseModel类的类，需要被装饰的对象

    Returns:
        返回被重写了__reduce__魔术方法的cls类
    """
    def __reduce__(self):
        # 1. 序列化：触发 Pydantic-core (Rust) 的极速序列化
        data = self.model_dump_json()
        # 2. 反序列化：告诉 Pickle 重建时调用 cls.model_validate_json
        return cls.model_validate_json, (data,)
    cls.__reduce__ = __reduce__
    return cls