python - Celery : understanding the big picture - Stack Overflow Celery seems to be a great tool, but I have hard time understanding how the various Celery components work together: The workers The apps The tasks The message Broker (like RabbitMQ) From what I
python - Retrieve list of tasks in a queue in Celery - Stack Overflow The celery inspect module appears to only be aware of the tasks from the workers perspective If you want to view the messages that are in the queue (yet to be pulled by the workers) I suggest to use pyrabbit, which can interface with the rabbitmq http api to retrieve all kinds of information from the queue
python - how to see the celery messages in redis? - Stack Overflow Even if I set a long timer on my tasks (sleep(60)) the tasks will take 60 seconds to run, but I still don't see anything in my redis container mget <key> returns nil for all keys above I was expecting to see messages incoming in form of ID or something into Redis (I can see messages if I use SQS as broker, but not for redis)
python 3. x - How to route tasks to different queues with Celery and . . . Python 3 6 Celery v4 2 1 (Broker: RabbitMQ v3 6 0) Django v2 0 4 According Celery's documentation, running scheduled tasks on different queues should be as easy as defining the corresponding queues for the tasks on CELERY_ROUTES, nonetheless all tasks seem to be executed on Celery's default queue This is the configuration on my_app settings py:
python - How to structure celery tasks - Stack Overflow Asking about "how to structure celery tasks" is irrelevant premature unless you know that your file layout is the cause of things not working Also, please provide more detail on what "it does not work" and "cannot accept the task from celerybeat" mean In other words, what do you expect to happen, and what happens instead? Specifically
python - How can I use Celerys apply_async () delay () as a non . . . In general, the celery is geared towards multi-processing not towards coroutines and async The key thing to remember when trying to integrate with asyncio is that calling delay or apply_async is a "relatively" non-blocking call (each call will kick off the task by placing a message on the celery broker, like redis or rabbitmq)
python - event loop is closed in a celery worker - Stack Overflow After many investigation using flower for monitoring workers and logging the workers Id ( processes ids) it turns out that Celery worker itself does not process any tasks, it spawns other child processes ( this is my case because i am using the default executor pool which is prefork), while the signal ( worker_ready connect ) is only run on the