包含多个会话的累积代码变更: - backend: AI 聊天服务、触发器调度、认证增强、WebSocket、调度器最小间隔 - admin-web: ETL 状态页、任务管理、调度配置、登录优化 - miniprogram: 看板页面、聊天集成、UI 组件、导航更新 - etl: DWS 新任务(finance_area_daily/board_cache)、连接器增强 - tenant-admin: 项目初始化 - db: 19 个迁移脚本(etl_feiqiu 11 + zqyy_app 8) - packages/shared: 枚举和工具函数更新 - tools: 数据库工具、报表生成、健康检查 - docs: PRD/架构/部署/合约文档更新 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
74 lines
2.1 KiB
Python
74 lines
2.1 KiB
Python
"""限流器 — 滑动窗口内存计数器。
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App1 按 user_id 限流(每用户每分钟 10 次),
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App2~8 按 site_id 限流(每门店每小时 100 次)。
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内存实现,单实例部署,不依赖外部存储。
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"""
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from __future__ import annotations
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import time
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from collections import deque
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class RateLimiter:
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"""滑动窗口内存限流器。
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- check_user_rate():App1 每用户每分钟限流
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- check_store_rate():App2~8 每门店每小时限流
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每个 key 维护一个时间戳 deque,检查时先清除过期条目,
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再判断窗口内请求数是否低于阈值。
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"""
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def __init__(self) -> None:
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self._user_windows: dict[str, deque[float]] = {} # App1: user_id → 时间戳队列
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self._store_windows: dict[str, deque[float]] = {} # App2~8: site_id → 时间戳队列
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def _check(
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self,
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windows: dict[str, deque[float]],
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key: str,
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limit: int,
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window_seconds: int,
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) -> bool:
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"""通用滑动窗口检查。返回 True 表示允许。"""
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now = time.monotonic()
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if key not in windows:
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windows[key] = deque()
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window = windows[key]
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# 清除窗口外的过期时间戳
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cutoff = now - window_seconds
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while window and window[0] <= cutoff:
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window.popleft()
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# 判断是否超限
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if len(window) >= limit:
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return False
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# 未超限,记录本次请求时间戳
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window.append(now)
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return True
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def check_user_rate(
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self,
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user_id: str,
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limit: int = 10,
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window_seconds: int = 60,
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) -> bool:
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"""App1 每用户每分钟限流。返回 True 表示允许。"""
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return self._check(self._user_windows, user_id, limit, window_seconds)
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def check_store_rate(
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self,
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site_id: int,
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limit: int = 100,
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window_seconds: int = 3600,
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) -> bool:
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"""App2~8 每门店每小时限流。返回 True 表示允许。"""
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# site_id 为 int,转为 str 作为 dict key
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return self._check(self._store_windows, str(site_id), limit, window_seconds)
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