Celery is an asynchronous task queue/job queue based on distributed message passing. It is focused on real-time operation, but supports scheduling as well. The execution units, called tasks, are executed concurrently on a single or more worker servers using multiprocessing, Eventlet, or gevent. Tasks can execute asynchronously (in the background) or synchronously (wait until ready). Celery is used in production systems to process millions of tasks a day.
ENV CELERY_BROKER_URL amqp://guest@rabbit so linking
with a RabbitMQ container works by default.$ docker run --name some-rabbitmq -d tklx/rabbitmq
$ docker run --link some-rabbitmq:rabbit --name some-celery -d tklx/celery
...
### Check the status of the cluster (RabbitMQ)
```console
$ docker run --link some-rabbitmq:rabbit --rm celery python -m celery status
$ docker run --name some-redis -d tklx/redis
$ docker run --link some-redis:redis -e CELERY_BROKER_URL=redis://redis --name some-celery -d tklx/celery
...
### Check the status of the cluster (Redis)
```console
$ docker run --link some-rabbitmq:rabbit -e CELERY_BROKER_URL=redis://redis --rm tklx/celery python -m celery status
The Docker image is built, tested and pushed by CircleCI from source hosted on GitHub.
x.y.z refers to a release (recommended).latest refers to the master branch.Currently on major version zero (0.y.z). Per Semantic Versioning, major version zero is for initial development, and should not be considered stable. Anything may change at any time.
TKLX uses a central issue tracker on GitHub for reporting and tracking of bugs, issues and feature requests.
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docker pull tklx/celery