generated from kgod/ai-review-template
hypandClaude
ae2d9b128d
自内部仓库剥离深度优化与 RAG 知识库后的交付版本： - Builder 对话式简历生成（FSM + 意图路由 LLM 兜底增强） - 条目级轻度优化：事实覆盖门禁 + STAR/bullet 修复链，功能/简介/成果与技术栈同级保护 - 简历导入：DOCX/PDF 解析、结构归一、手机号脱敏 - PostgreSQL 运行时 + Alembic 迁移链 Co-Authored-By: Claude <noreply@anthropic.com>
38 lines
1.1 KiB
Python
38 lines
1.1 KiB
Python
"""In-process sliding-window rate limiting for single-process deployments."""
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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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from typing import Callable
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class SlidingWindowRateLimiter:
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"""Allow at most ``limit`` requests per key during a sliding time window."""
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def __init__(
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self,
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*,
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limit: int,
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window_seconds: float,
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clock: Callable[[], float] = time.monotonic,
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) -> None:
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if limit < 1:
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raise ValueError("limit must be positive")
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if window_seconds <= 0:
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raise ValueError("window_seconds must be positive")
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self.limit = limit
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self.window_seconds = window_seconds
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self.clock = clock
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self._hits: dict[str, deque[float]] = {}
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def allow(self, key: str) -> bool:
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now = self.clock()
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hits = self._hits.setdefault(key, deque())
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while hits and now - hits[0] >= self.window_seconds:
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hits.popleft()
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if len(hits) >= self.limit:
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return False
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hits.append(now)
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return True
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