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  • 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
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    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:
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    How to run celery worker on Windows without creating Windows Service? Is there any analogy to $ celery -A your_application worker?
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    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
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    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)
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    I set up Celery in tasks py to complete a selenium webdriver request (which takes about 20 seconds) My goal is to simply return the result of that request to app py Running the Celery worker on another terminal, I can see in the console that the Celery task completes successfully and prints all the data I need from the selenium request





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