Running “unique” tasks with celery

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后悔当初
后悔当初 2020-11-28 03:40

I use celery to update RSS feeds in my news aggregation site. I use one @task for each feed, and things seem to work nicely.

There\'s a detail that I\'m not sure to

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  • 2020-11-28 04:22

    Based on MattH's answer, you could use a decorator like this:

    def single_instance_task(timeout):
        def task_exc(func):
            @functools.wraps(func)
            def wrapper(*args, **kwargs):
                lock_id = "celery-single-instance-" + func.__name__
                acquire_lock = lambda: cache.add(lock_id, "true", timeout)
                release_lock = lambda: cache.delete(lock_id)
                if acquire_lock():
                    try:
                        func(*args, **kwargs)
                    finally:
                        release_lock()
            return wrapper
        return task_exc
    

    then, use it like so...

    @periodic_task(run_every=timedelta(minutes=1))
    @single_instance_task(60*10)
    def fetch_articles()
        yada yada...
    
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  • 2020-11-28 04:36

    Using https://pypi.python.org/pypi/celery_once seems to do the job really nice, including reporting errors and testing against some parameters for uniqueness.

    You can do things like:

    from celery_once import QueueOnce
    from myapp.celery import app
    from time import sleep
    
    @app.task(base=QueueOnce, once=dict(keys=('customer_id',)))
    def start_billing(customer_id, year, month):
        sleep(30)
        return "Done!"
    

    which just needs the following settings in your project:

    ONCE_REDIS_URL = 'redis://localhost:6379/0'
    ONCE_DEFAULT_TIMEOUT = 60 * 60  # remove lock after 1 hour in case it was stale
    
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  • 2020-11-28 04:37

    If you're looking for an example that doesn't use Django, then try this example (caveat: uses Redis instead, which I was already using).

    The decorator code is as follows (full credit to the author of the article, go read it)

    import redis
    
    REDIS_CLIENT = redis.Redis()
    
    def only_one(function=None, key="", timeout=None):
        """Enforce only one celery task at a time."""
    
        def _dec(run_func):
            """Decorator."""
    
            def _caller(*args, **kwargs):
                """Caller."""
                ret_value = None
                have_lock = False
                lock = REDIS_CLIENT.lock(key, timeout=timeout)
                try:
                    have_lock = lock.acquire(blocking=False)
                    if have_lock:
                        ret_value = run_func(*args, **kwargs)
                finally:
                    if have_lock:
                        lock.release()
    
                return ret_value
    
            return _caller
    
        return _dec(function) if function is not None else _dec
    
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  • 2020-11-28 04:40

    This solution for celery working at single host with concurency greater 1. Other kinds (without dependencies like redis) of locks difference file-based don't work with concurrency greater 1.

    class Lock(object):
        def __init__(self, filename):
            self.f = open(filename, 'w')
    
        def __enter__(self):
            try:
                flock(self.f.fileno(), LOCK_EX | LOCK_NB)
                return True
            except IOError:
                pass
            return False
    
        def __exit__(self, *args):
            self.f.close()
    
    
    class SinglePeriodicTask(PeriodicTask):
        abstract = True
        run_every = timedelta(seconds=1)
    
        def __call__(self, *args, **kwargs):
            lock_filename = join('/tmp',
                                 md5(self.name).hexdigest())
            with Lock(lock_filename) as is_locked:
                if is_locked:
                    super(SinglePeriodicTask, self).__call__(*args, **kwargs)
                else:
                    print 'already working'
    
    
    class SearchTask(SinglePeriodicTask):
        restart_delay = timedelta(seconds=60)
    
        def run(self, *args, **kwargs):
            print self.name, 'start', datetime.now()
            sleep(5)
            print self.name, 'end', datetime.now()
    
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  • 2020-11-28 04:41

    From the official documentation: Ensuring a task is only executed one at a time.

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