zhenxun_bot/zhenxun/utils/pydantic_compat.py
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feat(group-settings): 实现群插件配置管理系统 (#2072)
*  feat(group-settings): 实现群插件配置管理系统

- 引入 GroupSettingsService 服务,提供统一的群插件配置管理接口
- 新增 GroupPluginSetting 模型,用于持久化存储插件在不同群组的配置
- 插件扩展数据 PluginExtraData 增加 group_config_model 字段,用于注册分群配置模型
- 新增 GetGroupConfig 依赖注入,允许插件轻松获取和解析当前群组的配置

【核心服务 GroupSettingsService】
- 支持按群组、插件名和键设置、获取和删除配置项
- 实现配置聚合缓存机制,提升配置读取效率,减少数据库查询
- 支持配置继承与覆盖逻辑(群配置覆盖全局默认值)
- 提供批量设置功能 set_bulk,方便为多个群组同时更新配置

【管理与缓存】
- 新增超级用户命令 pconf (plugin_config_manager),用于命令行管理插件的分群和全局配置
- 新增 CacheType.GROUP_PLUGIN_SETTINGS 缓存类型并注册
- 增加 Pydantic model_construct 兼容函数

* 🐛 fix(codeql): 移除对 JavaScript 和 TypeScript 的分析支持

---------

Co-authored-by: webjoin111 <455457521@qq.com>
2025-12-01 14:52:36 +08:00

146 lines
4.0 KiB
Python

"""
Pydantic V1 & V2 兼容层模块
为 Pydantic V1 与 V2 版本提供统一的便捷函数与类,
包括 model_dump, model_copy, model_json_schema, parse_as 等。
"""
from datetime import datetime
from enum import Enum
from pathlib import Path
from typing import Any, TypeVar, get_args, get_origin
from nonebot.compat import PYDANTIC_V2, model_dump
from pydantic import VERSION, BaseModel
import ujson as json
T = TypeVar("T", bound=BaseModel)
V = TypeVar("V")
__all__ = [
"PYDANTIC_V2",
"_dump_pydantic_obj",
"_is_pydantic_type",
"compat_computed_field",
"dump_json_safely",
"model_construct",
"model_copy",
"model_dump",
"model_json_schema",
"model_validate",
"parse_as",
]
def model_copy(
model: T, *, update: dict[str, Any] | None = None, deep: bool = False
) -> T:
"""
Pydantic `model.copy()` (v1) 和 `model.model_copy()` (v2) 的兼容函数。
"""
if PYDANTIC_V2:
return model.model_copy(update=update, deep=deep)
else:
update_dict = update or {}
return model.copy(update=update_dict, deep=deep)
def model_construct(model_class: type[T], **kwargs: Any) -> T:
"""
Pydantic `model_construct` (v2) 与 `construct` (v1) 的兼容函数。
"""
if PYDANTIC_V2:
return model_class.model_construct(**kwargs)
else:
return model_class.construct(**kwargs)
def model_validate(model_class: type[T], obj: Any) -> T:
"""
Pydantic `model_validate` (v2) 与 `parse_obj` (v1) 的兼容函数。
"""
if PYDANTIC_V2:
return model_class.model_validate(obj)
else:
return model_class.parse_obj(obj)
if PYDANTIC_V2:
from pydantic import computed_field as compat_computed_field
else:
compat_computed_field = property
def model_json_schema(model_class: type[BaseModel], **kwargs: Any) -> dict[str, Any]:
"""
Pydantic `Model.schema()` (v1) 和 `Model.model_json_schema()` (v2) 的兼容函数。
"""
if PYDANTIC_V2:
return model_class.model_json_schema(**kwargs)
else:
return model_class.schema(by_alias=kwargs.get("by_alias", True))
def _is_pydantic_type(t: Any) -> bool:
"""
递归检查一个类型注解是否与 Pydantic BaseModel 相关。
"""
if t is None:
return False
origin = get_origin(t)
if origin:
return any(_is_pydantic_type(arg) for arg in get_args(t))
return isinstance(t, type) and issubclass(t, BaseModel)
def _dump_pydantic_obj(obj: Any) -> Any:
"""
递归地将一个对象内部的 Pydantic BaseModel 实例转换为字典。
支持单个实例、实例列表、实例字典等情况。
"""
if isinstance(obj, BaseModel):
return model_dump(obj)
if isinstance(obj, list):
return [_dump_pydantic_obj(item) for item in obj]
if isinstance(obj, dict):
return {key: _dump_pydantic_obj(value) for key, value in obj.items()}
return obj
def parse_as(type_: type[V], obj: Any) -> V:
"""
一个兼容 Pydantic V1 的 parse_obj_as 和V2的TypeAdapter.validate_python 的辅助函数。
"""
if VERSION.startswith("1"):
from pydantic import parse_obj_as
return parse_obj_as(type_, obj)
else:
from pydantic import TypeAdapter # type: ignore
return TypeAdapter(type_).validate_python(obj)
def dump_json_safely(obj: Any, **kwargs) -> str:
"""
安全地将可能包含 Pydantic 特定类型 (如 Enum) 的对象序列化为 JSON 字符串。
"""
def default_serializer(o):
if isinstance(o, Enum):
return o.value
if isinstance(o, datetime):
return o.isoformat()
if isinstance(o, Path):
return str(o.as_posix())
if isinstance(o, set):
return list(o)
if isinstance(o, BaseModel):
return model_dump(o)
raise TypeError(
f"Object of type {o.__class__.__name__} is not JSON serializable"
)
return json.dumps(obj, default=default_serializer, **kwargs)