WechatOnCloud/bridge/woc_bridge/messaging/send_queue.py

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"""发送串行化队列。
所有 xdotool 操作经此队列串行执行避免并发 UI 操作冲突
内部维护最近 1 秒调用时间戳用于限流
"""
from __future__ import annotations
import asyncio
import logging
import time
from typing import Any, Awaitable, Callable, Optional
from woc_bridge.models import BridgeError
logger = logging.getLogger("woc-bridge")
# 工厂类型:返回一个待执行的 coroutine
CoroFactory = Callable[[], Awaitable[Any]]
class SendQueue:
"""串行化发送队列 + 限流。
通过 asyncio.Queue 串行执行所有发送任务执行间隔可配置
默认 3000ms单实例每秒调用上限可配置默认 10
"""
def __init__(
self,
send_delay_ms: int = 3000,
max_calls_per_sec: int = 10,
max_queue_size: int = 100,
) -> None:
"""初始化队列配置。
Args:
send_delay_ms: 两次发送之间的最小间隔毫秒
max_calls_per_sec: 每秒最大调用次数
max_queue_size: 队列最大深度满时入队抛 RATE_LIMITED
"""
self.send_delay_ms = send_delay_ms
self.max_calls_per_sec = max_calls_per_sec
self._queue: asyncio.Queue[tuple[CoroFactory, asyncio.Future, Optional[int]]] = asyncio.Queue(maxsize=max_queue_size)
self._worker: asyncio.Task | None = None
# 最近 1 秒内的调用时间戳
self._recent_call_times: list[float] = []
async def start(self) -> None:
"""启动 worker task。"""
if self._worker is None or self._worker.done():
self._worker = asyncio.create_task(self._run())
async def stop(self) -> None:
"""取消 worker。"""
if self._worker is not None and not self._worker.done():
self._worker.cancel()
try:
await self._worker
except asyncio.CancelledError:
pass
self._worker = None
async def enqueue(
self,
coro_factory: CoroFactory,
delay_ms: Optional[int] = None,
wait_timeout_ms: Optional[int] = None,
) -> Any:
"""将一个返回 coroutine 的工厂入队,等待执行结果。
Args:
coro_factory: 调用后返回 coroutine 的工厂函数
delay_ms: 自定义延时毫秒None 用默认 send_delay_ms
wait_timeout_ms: 队列等待超时毫秒None 表示无限等待
超时抛出 BridgeError(TIMEOUT)
Returns:
coroutine 的执行结果
Raises:
BridgeError: 限流命中队列满或等待超时时抛错
任务执行抛出的异常会透传给调用方
"""
loop = asyncio.get_running_loop()
future: asyncio.Future = loop.create_future()
# 队列满时立即拒绝,避免无界增长 OOM
if self._queue.maxsize > 0 and self._queue.qsize() >= self._queue.maxsize:
logger.warning(
"send_queue: 队列已满 (size=%d/%d),拒绝入队",
self._queue.qsize(), self._queue.maxsize,
)
raise BridgeError(
code="RATE_LIMITED",
message=f"发送队列已满({self._queue.qsize()}/{self._queue.maxsize}),请稍后重试",
details={"retry_after": 3},
)
await self._queue.put((coro_factory, future, delay_ms))
pending = self._queue.qsize()
logger.info("send_queue: 入队 (pending=%d)", pending)
if wait_timeout_ms is not None and wait_timeout_ms > 0:
try:
return await asyncio.wait_for(
future, timeout=wait_timeout_ms / 1000.0
)
except asyncio.TimeoutError:
# 竞争窗口worker 可能刚好在此时完成并 set_result。
# 若 future 已完成且未被取消,直接取结果;否则取消 future 并抛 TIMEOUT。
if future.done() and not future.cancelled():
logger.info(
"send_queue: 等待超时但任务刚好完成,取结果 (pending=%d)",
pending,
)
return future.result()
# 取消 futureworker 出队时发现 cancelled 会跳过执行
future.cancel()
wait_sec = wait_timeout_ms / 1000.0
logger.warning(
"send_queue: 等待超时 (pending=%d, wait_timeout=%.1fs)",
pending, wait_sec,
)
raise BridgeError(
code="TIMEOUT",
message=f"发送队列等待超时({pending} 个待处理,已等 {wait_sec:.1f}s",
details={"retry_after": max(1, int(self.send_delay_ms / 1000))},
)
return await future
def pending_count(self) -> int:
"""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)。"""
return self._queue.qsize()
def _check_rate_limit(self) -> None:
"""检查限流。
清理 1 秒前的时间戳若当前已满 max_calls_per_sec 则抛
BridgeError(RATE_LIMITED)并在 details 中携带 retry_after 秒数
供上层设置 Retry-After 响应头
"""
now = time.monotonic()
# 清理 1 秒前的时间戳
self._recent_call_times = [t for t in self._recent_call_times if now - t < 1.0]
if len(self._recent_call_times) >= self.max_calls_per_sec:
# 计算建议等待秒数:最早一次调用距窗口边界还差多久
oldest = self._recent_call_times[0]
retry_after = max(1, int(1.0 - (now - oldest)) + 1)
logger.warning(
"send_queue: 限流命中,拒绝执行 (recent=%d/%d, retry_after=%ds)",
len(self._recent_call_times), self.max_calls_per_sec, retry_after,
)
raise BridgeError(
code="RATE_LIMITED",
message=f"发送限流:每秒最多 {self.max_calls_per_sec}",
details={"retry_after": retry_after},
)
logger.debug(
"send_queue: 限流通过 (recent=%d/%d)",
len(self._recent_call_times), self.max_calls_per_sec,
)
async def _run(self) -> None:
"""worker 主循环。
循环取出任务执行执行前检查限流超限则失败该任务
执行前记录开始时间戳避免长任务导致 1 秒窗口内超限
执行后 sleep delay_ms/1000自定义延时优先于默认 send_delay_ms
"""
while True:
coro_factory, future, custom_delay_ms = await self._queue.get()
# 调用方已超时取消:跳过执行与延时
if future.cancelled():
self._queue.task_done()
logger.info(
"send_queue: 出队任务已取消,跳过 (pending=%d)",
self._queue.qsize(),
)
continue
logger.info("send_queue: 出队,开始处理 (pending=%d)", self._queue.qsize())
# 标记任务是否真正开始执行(用于决定 finally 是否延时)
executed = False
t_exec = time.perf_counter()
try:
# 执行前检查限流
self._check_rate_limit()
# 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)
self._recent_call_times.append(time.monotonic())
executed = True
# 执行任务
logger.info("send_queue: 开始执行任务")
result = await coro_factory()
logger.info(
"send_queue: 任务执行完成 (%.0fms)",
(time.perf_counter() - t_exec) * 1000,
)
if not future.done():
future.set_result(result)
except asyncio.CancelledError:
# worker 被取消时,把取消传播给等待的调用方
if not future.done():
future.cancel()
raise
except Exception as e:
logger.warning(
"send_queue: 任务执行抛异常 %s: %s (%.0fms)",
type(e).__name__, e, (time.perf_counter() - t_exec) * 1000,
)
if not future.done():
future.set_exception(e)
finally:
self._queue.task_done()
# 仅在任务真正执行过时延时,限流失败/已取消的任务不延时
if executed:
delay = custom_delay_ms if custom_delay_ms is not None else self.send_delay_ms
logger.info(
"send_queue: 延时 %dms 后处理下一个",
delay,
)
await asyncio.sleep(delay / 1000.0)