celery conf

• pip list|grep celery

celery                5.5.1
celery-types          0.23.0

• app/celery_app.py

import functools
from redis import StrictRedis
from celery import Celery
MQ_URL = "amqp://celery:123456@localhost:5672/app"
REDIS_URL = "redis://localhost:6379"
MAX_LIVE_SECONDS = 1.5 * 60 * 60  # 最大推流时长（超过这个时间就自动关闭ffmpeg进程）
app = Celery(__name__, broker=MQ_URL, backend=DB_URL)
app.autodiscover_tasks()
app.conf.broker_connection_retry_on_startup = True

# 同一个 Worker 在执行了大量任务后，会有几率出现内存泄漏的情况。
# 这里建议全局设置 Worker 最大的任务执行数，Worker 在完成了最大的任务执行数后就主动退出。
# https://www.cnblogs.com/jmilkfan-fanguiju/p/10589785.html
app.conf.worker_max_tasks_per_child = 100

app.conf.task_time_limit = 65 * 60  # 全局设置任务超时时间

@functools.cache
def get_sync_redis_client(url=REDIS_URL) -> StrictRedis:
    return StrictRedis.from_url(url)

@app.on_after_configure.connect
def setup_periodic_tasks(sender, **kwargs):
    # Auto close outdate ffmpeg processes every 1.5 hours
    sender.add_periodic_task(MAX_LIVE_SECONDS, close_outdate_ffmpeg.s())

@app.task()
def close_outdate_ffmpeg():
    now = datetime.now()
    delta = timedelta(seconds=MAX_LIVE_SECONDS)
    for p in get_ffmpeg_processes():
        nums = re.findall(r"\d+", p.started.split(".")[0])[:6]
        start_time = datetime(*map(int, nums))  # type:ignore[arg-type]
        if (now - start_time) > delta:
            close_process(p.pid, raises=False)