Exploring the mechanics of celery asynchronous tasks within a Django project: Unraveling the inner

For my Django project, I needed to run long tasks so I decided to use Celery with Redis as the broker. After installing Redis, it runs smoothly:

The server is now ready to accept connections on port 6379

Next, I installed django-celery and configured it like this:

import djcelery
djcelery.setup_loader()
BROKER_HOST = "localhost"
BROKER_PORT = 6379 #redis
BROKER_USER = "guest"
BROKER_PASSWORD = "guest"
BROKER_VHOST = "/"

After configuration, I ran the following command:

python manage.py celeryd -l DEBUG
[...]
[2011-06-18 10:31:37,913: DEBUG/MainProcess] Starting thread Timer...
[2011-06-18 10:31:37,914: DEBUG/MainProcess] Starting thread Consumer... 
[2011-06-18 10:31:37,914: WARNING/MainProcess] celery@greg... has started.
[2011-06-18 10:31:37,914: DEBUG/MainProcess] Consumer: Re-establishing connection to the broker...

Here is an example of a task I created:

from celery.decorators import task
@task()
def add(x, y):
    return x + y

When trying to run the task in the shell, I encountered a long wait time and received a traceback message at . Is there something I might be missing?

pythondjangorediscelerydjango-celery

Answer №1

If you encounter the error that the BROKER_BACKEND setting is missing, here is a sample configuration for utilizing Redis:

import djcelery
djcelery.setup_loader()

CELERY_RESULT_BACKEND = 'database'

BROKER_BACKEND = 'redis'
BROKER_HOST = 'localhost'
BROKER_PORT = 6379
BROKER_VHOST = '1'

Answer №2

Although I'm not quite sure what this entails, RabbitMQ is widely recognized as the top choice for Celery and Django integration. My experience with it has been seamless and efficient. It might be worth exploring as an alternative option!

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