Kris
2e056f9bae
1. 调整默认发送延迟从800ms改为3000ms，更新配置默认值与环境变量 fallback 2. 重写Fastify代理路由，修复POST body被提前消费导致的转发超时问题 3. 新增DB校验机制，发送后轮询确认消息是否到达目标会话 4. 重构xdotool操作流程：改用鼠标点击搜索与发送，替代快捷键组合以适配微信4.x自绘UI 5. 优化窗口激活、会话搜索与输入焦点处理逻辑，提升发送稳定性
159 lines
6.0 KiB
Python
159 lines
6.0 KiB
Python
"""发送串行化队列。
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所有 xdotool 操作经此队列串行执行，避免并发 UI 操作冲突。
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内部维护最近 1 秒调用时间戳用于限流。
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"""
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from __future__ import annotations
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import asyncio
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import logging
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import time
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from typing import Any, Awaitable, Callable
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from woc_bridge.models import BridgeError
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logger = logging.getLogger("woc-bridge")
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# 工厂类型：返回一个待执行的 coroutine
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CoroFactory = Callable[[], Awaitable[Any]]
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class SendQueue:
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"""串行化发送队列 + 限流。
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通过 asyncio.Queue 串行执行所有发送任务；执行间隔可配置
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（默认 3000ms），单实例每秒调用上限可配置（默认 10）。
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"""
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def __init__(
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self,
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send_delay_ms: int = 3000,
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max_calls_per_sec: int = 10,
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) -> None:
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"""初始化队列配置。
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Args:
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send_delay_ms: 两次发送之间的最小间隔毫秒
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max_calls_per_sec: 每秒最大调用次数
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"""
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self.send_delay_ms = send_delay_ms
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self.max_calls_per_sec = max_calls_per_sec
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self._queue: asyncio.Queue[tuple[CoroFactory, asyncio.Future]] = asyncio.Queue()
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self._worker: asyncio.Task | None = None
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# 最近 1 秒内的调用时间戳
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self._recent_call_times: list[float] = []
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async def start(self) -> None:
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"""启动 worker task。"""
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if self._worker is None or self._worker.done():
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self._worker = asyncio.create_task(self._run())
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async def stop(self) -> None:
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"""取消 worker。"""
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if self._worker is not None and not self._worker.done():
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self._worker.cancel()
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try:
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await self._worker
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except asyncio.CancelledError:
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pass
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self._worker = None
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async def enqueue(self, coro_factory: CoroFactory) -> Any:
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"""将一个返回 coroutine 的工厂入队，等待执行结果。
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Args:
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coro_factory: 调用后返回 coroutine 的工厂函数
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Returns:
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coroutine 的执行结果
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Raises:
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BridgeError: 限流命中时立即抛 RATE_LIMITED；
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任务执行抛出的异常会透传给调用方
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"""
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loop = asyncio.get_running_loop()
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future: asyncio.Future = loop.create_future()
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await self._queue.put((coro_factory, future))
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logger.info("send_queue: 入队 (pending=%d)", self._queue.qsize())
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return await future
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def pending_count(self) -> int:
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"""返回当前队列中待执行任务数（供 /api/status 暴露给客户端做退避决策）。"""
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return self._queue.qsize()
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def _check_rate_limit(self) -> None:
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"""检查限流。
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清理 1 秒前的时间戳，若当前已满 max_calls_per_sec 则抛
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BridgeError(RATE_LIMITED)，并在 details 中携带 retry_after 秒数
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供上层设置 Retry-After 响应头。
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"""
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now = time.monotonic()
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# 清理 1 秒前的时间戳
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self._recent_call_times = [t for t in self._recent_call_times if now - t < 1.0]
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if len(self._recent_call_times) >= self.max_calls_per_sec:
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# 计算建议等待秒数：最早一次调用距窗口边界还差多久
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oldest = self._recent_call_times[0]
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retry_after = max(1, int(1.0 - (now - oldest)) + 1)
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logger.warning(
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"send_queue: 限流命中，拒绝执行 (recent=%d/%d, retry_after=%ds)",
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len(self._recent_call_times), self.max_calls_per_sec, retry_after,
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)
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raise BridgeError(
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code="RATE_LIMITED",
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message=f"发送限流：每秒最多 {self.max_calls_per_sec} 次",
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details={"retry_after": retry_after},
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)
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async def _run(self) -> None:
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"""worker 主循环。
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循环取出任务执行；执行前检查限流（超限则失败该任务）；
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执行前记录开始时间戳（避免长任务导致 1 秒窗口内超限）；
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执行后 sleep send_delay_ms/1000。
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"""
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while True:
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coro_factory, future = await self._queue.get()
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logger.info("send_queue: 出队，开始处理 (pending=%d)", self._queue.qsize())
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# 标记任务是否真正开始执行（用于决定 finally 是否延时）
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executed = False
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t_exec = time.perf_counter()
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try:
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# 执行前检查限流
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self._check_rate_limit()
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# 记录开始时间戳（限流窗口基于开始时刻，避免长任务后窗口偏移）
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self._recent_call_times.append(time.monotonic())
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executed = True
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# 执行任务
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logger.info("send_queue: 开始执行任务")
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result = await coro_factory()
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logger.info(
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"send_queue: 任务执行完成 (%.0fms)",
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(time.perf_counter() - t_exec) * 1000,
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)
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if not future.done():
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future.set_result(result)
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except asyncio.CancelledError:
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# worker 被取消时，把取消传播给等待的调用方
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if not future.done():
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future.cancel()
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raise
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except Exception as e:
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logger.warning(
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"send_queue: 任务执行抛异常 %s: %s (%.0fms)",
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type(e).__name__, e, (time.perf_counter() - t_exec) * 1000,
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)
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if not future.done():
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future.set_exception(e)
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finally:
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self._queue.task_done()
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# 仅在任务真正执行过时延时，限流失败的任务不延时
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if executed:
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logger.info(
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"send_queue: 延时 %dms 后处理下一个",
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self.send_delay_ms,
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)
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await asyncio.sleep(self.send_delay_ms / 1000.0)
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