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https://github.com/zhenxun-org/zhenxun_bot.git
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* ✨ feat(hook): 增强认证钩子和运行时缓存管理 ``` ♻ refactor(hook): 移除未使用的配置项并优化缓存设置 移除 AUTH_HOOKS_CONCURRENCY_LIMIT 配置项,该配置项不再使用 ✨feat(auth_ban): 简化缓存配置并添加实体参数支持 将 BAN_CACHE_TTL 相关配置从动态配置改为常量定义, 移除复杂的 TTL 值转换逻辑,并为 auth_ban 函数添加可选的 entity 参数以支持外部传入实体信息 ♻ refactor(auth_limit): 移除未使用的配置依赖 移除 AUTH_LIMIT_NOTICE_CD 配置项,直接使用常量值 2 作为限制通知冷却时间 📦 依赖更新: update playwright dependency to version 1.57.0 in pyproject.toml and requirements.txt ``` * ✨ feat(auth_checker): 增强插件模块处理和预过滤逻辑,支持用户插件兼容性 * ✨ feat(http_utils): 添加内容缓存机制以优化HTTP响应处理 * ✨ feat(cache): 添加群组插件设置视图缓存类型并更新相关逻辑 * ✨ feat(renderer): 优化渲染引擎,增加内存缓存管理和HTML文档处理逻辑 * ✨ feat(sign_in): 添加好感度排行和好感度总排行命令 * ✨ feat(renderer): 增强浏览器实例管理和模板预处理,支持历史 include 语法兼容 * ✨ feat(renderer): 优化 Playwright 环境检查逻辑,增加结果缓存以提高性能 * ✨ feat(renderer): 增强模板文件渲染策略,优化资产加载路径处理 * 🚨 auto fix by pre-commit hooks * ✨ feat(log): 增加日志内容安全序列化,避免超长 base64 等污染日志 ✨ feat(log_sanitizer): 添加对嵌入超长 base64/data URI 的清理功能 ✨ feat(auth_checker): 添加 Alconna 快捷方式缓存检查,优化路由匹配逻辑 * feat(renderer): 添加渲染结果内存缓存功能以优化性能 feat(help): 实现帮助菜单图像缓存机制 feat(sign_in): 更新HTML卡片生成以支持动画禁用和剪裁 feat(superuser): 在启动时预热超级用户帮助缓存 feat(theme): 优化主题管理器的资源解析缓存 * 🚨 auto fix by pre-commit hooks * feat(renderer): 增加全页面视口最大宽度限制并优化内容尺寸计算 --------- Co-authored-by: ATTomatoo <1126160939@qq.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: HibiKier <45528451+HibiKier@users.noreply.github.com>
172 lines
5.6 KiB
Python
172 lines
5.6 KiB
Python
"""
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头像缓存服务
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提供一个统一的、带缓存的头像获取服务,支持多平台和可配置的过期策略。
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"""
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from collections import OrderedDict
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import os
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from pathlib import Path
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import time
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from nonebot_plugin_apscheduler import scheduler
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from zhenxun.configs.config import Config
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from zhenxun.configs.path_config import DATA_PATH
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from zhenxun.services.log import logger
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from zhenxun.utils.http_utils import AsyncHttpx
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from zhenxun.utils.platform import PlatformUtils
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Config.add_plugin_config(
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"avatar_cache",
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"ENABLED",
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True,
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help="是否启用头像缓存功能",
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default_value=True,
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type=bool,
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)
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Config.add_plugin_config(
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"avatar_cache",
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"TTL_DAYS",
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7,
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help="头像缓存的有效期(天)",
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default_value=7,
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type=int,
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)
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Config.add_plugin_config(
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"avatar_cache",
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"CLEANUP_INTERVAL_HOURS",
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24,
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help="后台清理过期缓存的间隔时间(小时)",
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default_value=24,
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type=int,
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)
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class AvatarService:
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"""
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一个集中式的头像缓存服务,提供L1(内存)和L2(文件)两级缓存。
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"""
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_MEMORY_CACHE_MAX_ITEMS = 2000
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def __init__(self):
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self.cache_path = (DATA_PATH / "cache" / "avatars").resolve()
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self.cache_path.mkdir(parents=True, exist_ok=True)
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self._memory_cache: OrderedDict[str, Path] = OrderedDict()
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def _get_cache_path(self, platform: str, identifier: str) -> Path:
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"""
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根据平台和ID生成存储的文件路径。
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例如: data/cache/avatars/qq/123456789.png
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"""
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identifier = str(identifier)
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return self.cache_path / platform / f"{identifier}.png"
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async def get_avatar_path(
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self, platform: str, identifier: str, force_refresh: bool = False
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) -> Path | None:
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"""
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获取用户或群组的头像本地路径。
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参数:
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platform: 平台名称 (e.g., 'qq')
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identifier: 用户ID或群组ID
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force_refresh: 是否强制刷新缓存
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返回:
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Path | None: 头像的本地文件路径,如果获取失败则返回None。
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"""
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if not Config.get_config("avatar_cache", "ENABLED"):
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return None
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cache_key = f"{platform}-{identifier}"
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if not force_refresh and cache_key in self._memory_cache:
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cached_path = self._memory_cache[cache_key]
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if cached_path.exists():
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self._memory_cache.move_to_end(cache_key)
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return cached_path
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self._memory_cache.pop(cache_key, None)
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local_path = self._get_cache_path(platform, identifier)
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ttl_seconds = Config.get_config("avatar_cache", "TTL_DAYS", 7) * 86400
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if not force_refresh and local_path.exists():
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try:
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file_mtime = os.path.getmtime(local_path)
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if time.time() - file_mtime < ttl_seconds:
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self._memory_cache[cache_key] = local_path
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self._memory_cache.move_to_end(cache_key)
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while len(self._memory_cache) > self._MEMORY_CACHE_MAX_ITEMS:
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self._memory_cache.popitem(last=False)
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return local_path
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except FileNotFoundError:
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pass
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avatar_url = PlatformUtils.get_user_avatar_url(identifier, platform)
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if not avatar_url:
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return None
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local_path.parent.mkdir(parents=True, exist_ok=True)
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if await AsyncHttpx.download_file(avatar_url, local_path):
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self._memory_cache[cache_key] = local_path
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self._memory_cache.move_to_end(cache_key)
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while len(self._memory_cache) > self._MEMORY_CACHE_MAX_ITEMS:
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self._memory_cache.popitem(last=False)
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return local_path
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else:
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logger.warning(f"下载头像失败: {avatar_url}", "AvatarService")
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return None
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async def _cleanup_cache(self):
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"""后台定时清理过期的缓存文件"""
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if not Config.get_config("avatar_cache", "ENABLED"):
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return
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logger.info("开始执行头像缓存清理任务...", "AvatarService")
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ttl_seconds = Config.get_config("avatar_cache", "TTL_DAYS", 7) * 86400
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now = time.time()
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deleted_count = 0
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for root, _, files in os.walk(self.cache_path):
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for name in files:
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file_path = Path(root) / name
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try:
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if now - os.path.getmtime(file_path) > ttl_seconds:
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file_path.unlink()
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deleted_count += 1
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except FileNotFoundError:
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continue
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if self._memory_cache:
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stale_keys = []
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for key, cached_path in self._memory_cache.items():
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if not cached_path.exists():
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stale_keys.append(key)
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continue
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try:
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if now - os.path.getmtime(cached_path) > ttl_seconds:
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stale_keys.append(key)
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except OSError:
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stale_keys.append(key)
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for key in stale_keys:
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self._memory_cache.pop(key, None)
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while len(self._memory_cache) > self._MEMORY_CACHE_MAX_ITEMS:
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self._memory_cache.popitem(last=False)
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logger.info(
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f"头像缓存清理完成,共删除 {deleted_count} 个过期文件。", "AvatarService"
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)
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avatar_service = AvatarService()
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@scheduler.scheduled_job(
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"cron",
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hour=4,
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minute=30,
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)
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async def _run_avatar_cache_cleanup():
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await avatar_service._cleanup_cache()
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