全面架构重构:建立分层架构与高度可扩展的插件系统
后端重构: - 新增分层架构:API Routes -> Services -> Repositories -> Infrastructure - 彻底移除全局单例,全面采用 FastAPI 依赖注入 - 新增 api/ 目录拆分路由(proxies, plugins, scheduler, settings, stats) - 新增 services/ 业务逻辑层:ProxyService, PluginService, SchedulerService, ValidatorService, SettingsService - 新增 repositories/ 数据访问层:ProxyRepository, SettingsRepository, PluginSettingsRepository - 新增 models/ 层:Pydantic Schemas + Domain Models - 重写 core/config.py:采用 Pydantic Settings 管理配置 - 新增 core/db.py:基于 asynccontextmanager 的连接管理,支持数据库迁移 - 新增 core/exceptions.py:统一业务异常体系 插件系统重构(核心): - 新增 core/plugin_system/:BaseCrawlerPlugin + PluginRegistry - 采用显式注册模式(装饰器 + plugins/__init__.py),类型安全、测试友好 - 新增 plugins/base.py:BaseHTTPPlugin 通用 HTTP 爬虫基类 - 迁移全部 7 个插件到新架构(fate0, proxylist_download, ip3366, ip89, kuaidaili, speedx, yundaili) - 插件状态持久化到 plugin_settings 表 任务调度重构: - 新增 core/tasks/queue.py:ValidationQueue + WorkerPool - 解耦爬取与验证:爬虫只负责爬取,代理提交队列后由 Worker 异步验证 - 调度器定时从数据库拉取存量代理并分批投入验证队列 前端调整: - 新增 frontend/src/services/ 层拆分 API 调用逻辑 - 调整 stores/ 和 views/ 使用 Service 层 - 保持 API 兼容性,页面无需大幅修改 其他: - 新增 main.py 作为新入口 - 新增 DESIGN.md 架构设计文档 - 更新 requirements.txt 增加 pydantic-settings
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30
api/routes/stats.py
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30
api/routes/stats.py
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"""统计信息路由"""
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from fastapi import APIRouter, Depends
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from services.proxy_service import ProxyService
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from services.scheduler_service import SchedulerService
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from api.deps import get_proxy_service, get_scheduler_service
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from core.log import logger
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router = APIRouter(prefix="/api/stats", tags=["stats"])
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def success_response(message: str, data=None):
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return {"code": 200, "message": message, "data": data}
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def error_response(message: str, code: int = 500):
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return {"code": code, "message": message, "data": None}
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@router.get("")
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async def get_stats(
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proxy_service: ProxyService = Depends(get_proxy_service),
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scheduler_service: SchedulerService = Depends(get_scheduler_service),
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):
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try:
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stats = await proxy_service.get_stats()
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stats["scheduler_running"] = scheduler_service.running
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return success_response("获取统计信息成功", stats)
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except Exception as e:
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logger.error(f"Get stats failed: {e}")
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return error_response("获取统计信息失败")
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