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