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MediaCrawler/api/monitor/scheduler.py
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fix(monitor): 抖音任务的 run 永远停在「排队中」—— 我上一版把状态标记缩进错了
用户报的现象:任务一直显示「排队中」。查库确认有两批 run 卡在 pending(任务 7 的 44/45、
任务 15 的 62/63)。两个原因,一个是我上一版改坏的:

1) **`RUN_RUNNING` 被我缩进进了爬虫那条分支。** 抖音走的是另一条路,于是它**从不标记
   「运行中」** —— 建完 pending 那一行就直接进采集,中途一旦出事(异常、进程被重启),
   状态就永远停在 pending。这是我加平台分岔时把原本在两条路公共位置的一行挪进去了。

2) **`recover()` 只收 `running`,够不着 `pending`。** 那行是上一轮建的、后面的采集却
   根本没机会开始(进程重启),它永远不会自己往前走。于是重启也救不回来,界面上就是
   一个永远「排队中」的幽灵。现在 pending 一起收。

两处都补了测试:抖音路的 run 必须在**采集开始之前**就已经是 running(这条改回去就会
失败);recover 要把 pending 也标成 interrupted。
2026-10-10 17:47:41 +08:00

281 lines
12 KiB
Python

# -*- coding: utf-8 -*-
# Copyright (c) 2025 [email protected]
#
# This file is part of MediaCrawler project.
# Repository: https://github.com/NanmiCoder/MediaCrawler/blob/main/api/monitor/scheduler.py
# GitHub: https://github.com/NanmiCoder
# Licensed under NON-COMMERCIAL LEARNING LICENSE 1.1
#
# 声明:本代码仅供学习和研究目的使用。使用者应遵守以下原则:
# 1. 不得用于任何商业用途。
# 2. 使用时应遵守目标平台的使用条款和robots.txt规则。
# 3. 不得进行大规模爬取或对平台造成运营干扰。
# 4. 应合理控制请求频率,避免给目标平台带来不必要的负担。
# 5. 不得用于任何非法或不当的用途。
#
# 详细许可条款请参阅项目根目录下的LICENSE文件。
# 使用本代码即表示您同意遵守上述原则和LICENSE中的所有条款。
"""Background scheduler for monitor tasks.
One asyncio loop polls for due tasks and hands them to the runner. A plain loop
is enough here: there is exactly one process, one global crawler subprocess, and
therefore no concurrency to coordinate -- a cron-style library would add a
dependency without adding a capability.
Two families of schedule, and the difference matters:
* ``interval`` is **fixed-delay**, not fixed-rate -- ``next_run_at`` is measured
from the moment a run starts, so a slow run cannot make its task fire
back-to-back.
* the clock modes (``daily``/``weekly``) are **fixed-time** -- recomputed from the
calendar, so a run that starts late does not drag every later run with it.
The arithmetic for both lives in schedule.py.
The loop also carries the 上游更新检查: it is not a crawl, so it shares none of
the rules above (no subprocess, no active-hours gate) -- see
``_maybe_check_upstream``. It rides this loop rather than getting a thread of its
own because it is one HTTP-shaped fetch per day.
"""
import asyncio
import random
from datetime import datetime
from typing import Optional
from sqlalchemy import select
from tools.time_util import get_current_timestamp
from ..services import crawler_manager
from . import app_settings, schedule, upstream
from .db import get_session
from .models import (
RUN_INTERRUPTED,
RUN_PENDING,
RUN_RUNNING,
MonitorRun,
MonitorTask,
)
from .runner import execute_task
from .settings import get_cookie
POLL_INTERVAL_SECONDS = 20
# Spread tasks sharing an interval so they do not all come due on the same tick.
# Applied to interval mode only -- see the advance step below.
JITTER_SECONDS = 60
class MonitorScheduler:
"""Polls the task table and runs whatever is due."""
def __init__(self) -> None:
self._loop_task: Optional[asyncio.Task] = None
self._stopping = asyncio.Event()
# Avoids logging "no cookie" on every single tick. Per platform, because
# warning once for Xiaohongshu must not silence the warning for Douyin.
self._warned_no_cookie: set = set()
async def start(self) -> None:
if self._loop_task is not None and not self._loop_task.done():
return
self._stopping.clear()
self._loop_task = asyncio.create_task(self._run_loop())
async def stop(self) -> None:
self._stopping.set()
if self._loop_task is not None:
self._loop_task.cancel()
try:
await self._loop_task
except asyncio.CancelledError:
pass
self._loop_task = None
async def _run_loop(self) -> None:
try:
await self.recover()
except Exception as exc: # pragma: no cover - defensive
print(f"[monitor.scheduler] recovery failed: {exc}")
while not self._stopping.is_set():
try:
await self.tick()
except Exception as exc: # pragma: no cover - keep the loop alive
print(f"[monitor.scheduler] tick failed: {exc}")
# 独立于采集任务,因此单独一段 try:上游检查失败不该影响采集调度,
# 反过来也一样。
try:
await self._maybe_check_upstream()
except Exception as exc: # pragma: no cover - keep the loop alive
print(f"[monitor.scheduler] upstream check failed: {exc}")
await asyncio.sleep(POLL_INTERVAL_SECONDS)
async def _maybe_check_upstream(self) -> None:
"""到点就 fetch 一次上游仓库,看它有没有新提交。
与采集任务的三条规则都不同,各有理由:它不碰浏览器、也不占采集子进程,
所以不看 ``is_busy``;它只发一个 git 请求,没有被平台风控的风险,所以也不
受活跃时段限制 —— 定时检查放在半夜反而是最合适的。
"""
async with get_session() as session:
if not await app_settings.get_value(
session, "upstream_check_enabled", fallback=False
):
return
interval_minutes = int(
await app_settings.get_value(
session, "upstream_check_interval_minutes", fallback=1440
)
)
state = await upstream.load_state(session)
checked_at = int(state.get("checked_at") or 0)
now = get_current_timestamp()
# 失败也会写 checked_at,所以不通的时候同样是每个间隔重试一次,
# 而不是每个 tick(20 秒)都去撞一次墙。
if checked_at and now - checked_at < max(1, interval_minutes) * 60_000:
return
result = await upstream.run_check()
if result.get("behind"):
print(
f"[monitor.scheduler] 上游 {result.get('branch')} 领先 "
f"{result['behind']} 个提交"
)
elif not result.get("ok"):
print(f"[monitor.scheduler] 上游检查失败:{result.get('error')}")
async def recover(self) -> None:
"""Clean up state left behind by a server restart.
A run still marked ``running`` cannot be running -- its subprocess died
with the previous process. Marking it interrupted stops it from blocking
the UI as a phantom in-flight run.
**``pending`` 同样是残留**:那一行是上一轮建的,可它后面的采集根本没机会开始
(进程被重启,或者采集那条路抛了异常),所以它永远不会自己往前走。只清 running
的话,它会永远挂在界面上显示「排队中」—— 用户看到的就是任务卡住了。
"""
async with get_session() as session:
stale = (
await session.scalars(
select(MonitorRun).where(
MonitorRun.status.in_((RUN_RUNNING, RUN_PENDING))
)
)
).all()
for run in stale:
run.status = RUN_INTERRUPTED
run.finished_at = get_current_timestamp()
if stale:
print(
f"[monitor.scheduler] marked {len(stale)} interrupted run(s) "
f"left over from a previous process"
)
async def tick(self) -> None:
"""Run one due task, if the crawler is free and we are in the active window."""
# The crawler subprocess is a global singleton, so a manual crawl and a
# monitor run cannot overlap. Returning without advancing next_run_at
# leaves the task due, and it is picked up on a later tick.
if crawler_manager.is_busy():
return
async with get_session() as session:
if not await self._within_active_hours(session):
# Deliberately does not advance next_run_at: the task simply runs
# when the window next opens, rather than being skipped for a day.
return
await self._run_due_task()
async def _within_active_hours(self, session) -> bool:
"""Whether scheduled runs are allowed right now (local time)."""
start, end = await app_settings.active_hours(session)
hour = datetime.now().hour
if start <= end:
return start <= hour <= end
# Window wraps past midnight, e.g. 22 -> 6.
return hour >= start or hour <= end
async def _run_due_task(self) -> None:
async with get_session() as session:
task = await session.scalar(
select(MonitorTask)
.where(
MonitorTask.enabled.is_(True),
MonitorTask.next_run_at.is_not(None),
MonitorTask.next_run_at <= get_current_timestamp(),
)
.order_by(MonitorTask.next_run_at)
.limit(1)
)
if task is None:
return
# 没有 cookie 就跳过,是为了不让任务每轮白跑一趟出个认证失败。任务留在
# due 状态而不推进 —— 用户一粘上 cookie 它就能自己跑起来。
#
# **但开着 CDP 时必须放行**:那种模式下登录态来自被接管的那个浏览器,
# 粘不粘 cookie 根本轮不到它决定成败。不放行的话,选了「接管已有 Chrome」
# 却没粘 cookie 的用户会发现任务永远不被触发,而且什么错都不报。
cookie = await get_cookie(session, task.platform)
if not cookie:
cdp_enabled = await app_settings.get_value(
session, "cdp_enabled", fallback=False
)
if not cdp_enabled:
if task.platform not in self._warned_no_cookie:
print(
f"[monitor.scheduler] no {task.platform} cookie configured; "
"scheduled tasks will not run until one is set or CDP is enabled"
)
self._warned_no_cookie.add(task.platform)
return
self._warned_no_cookie.discard(task.platform)
# Advance before running so a crash mid-run cannot cause an immediate
# re-fire, and so a long outage coalesces into a single run instead
# of one run per missed interval.
now = get_current_timestamp()
following = schedule.next_occurrence(
mode=task.schedule_mode,
interval_minutes=task.interval_minutes,
hours=schedule.parse_hours(task.schedule_hours),
days=schedule.parse_days(task.schedule_days),
minute=task.schedule_minute,
after_ms=now,
)
if following is None:
# A clock schedule with no times can never fire. The API rejects
# that shape, so this guards against a hand-edited row: park the
# task with no next run rather than leaving it permanently due and
# re-running it on every tick.
task.next_run_at = None
print(
f"[monitor.scheduler] task {task.id} has no usable schedule "
f"and will not run until one is set"
)
elif task.schedule_mode == schedule.MODE_INTERVAL:
# Jitter belongs to the interval mode only. Spreading identical
# intervals apart is the point; nudging a time the operator
# explicitly picked is not -- it just looks like a broken clock.
task.next_run_at = following + random.randint(0, JITTER_SECONDS) * 1000
else:
task.next_run_at = following
task_id = task.id
try:
await execute_task(task_id, trigger="scheduled")
except Exception as exc:
print(f"[monitor.scheduler] task {task_id} failed: {exc}")
# Global singleton, mirroring the crawler_manager pattern.
monitor_scheduler = MonitorScheduler()