import json
from pydantic import BaseModel, model_validator
from typing import Optional, Any
from datetime import datetime


class ConfigurationBase(BaseModel):
    config_key: Optional[str] = None
    config_value: Optional[str] = None
    description: Optional[str] = None
    type: Optional[str] = None


class ConfigurationCreate(ConfigurationBase):
    config_key: str
    config_value: str


class ConfigurationUpdate(ConfigurationBase):
    config_value: Optional[str] = None
    description: Optional[str] = None
    type: Optional[str] = None


class ConfigurationOut(ConfigurationBase):
    id: int
    # 关键点 1: 必须覆盖 config_value 的类型注解为 Any，
    # 否则 Pydantic 会在输出时强行把它转换回字符串，或者报错
    config_value: Any 
    
    model_config = {
        "from_attributes": True
    }

    @model_validator(mode='after')
    def parse_config_value_by_type(self) -> 'ConfigurationOut':
        """
        根据 type 字段自动转换 config_value 的类型
        """
        if self.config_value is None or self.type is None:
            return self

        # 获取原始字符串值
        raw_value = str(self.config_value)
        target_type = self.type.lower()

        try:
            if target_type == 'int' or target_type == 'integer':
                self.config_value = int(raw_value)
            
            elif target_type == 'float':
                self.config_value = float(raw_value)
            
            elif target_type == 'bool' or target_type == 'boolean':
                # 处理 "true", "1", "yes" 等情况
                self.config_value = raw_value.lower() in ('true', '1', 'yes', 'on')
            
            elif target_type in ('json', 'list', 'dict', 'array', 'object'):
                # 尝试解析 JSON
                self.config_value = json.loads(raw_value)
                
            # 如果是 string 或其他未定义类型，保持原样
        except (ValueError, json.JSONDecodeError):
            # 如果转换失败（比如类型是 int 但值是 "abc"），
            # 这里选择保持原始字符串不报错，或者你可以选择抛出错误
            pass

        return self