12. Celery Based Background Tasks¶

12.1. Installing Celery¶

Celery is on the Python Package Index (PyPI), so it can be installed with standard Python tools like pip or easy_install:

$ pip install celery

12.2. Configuring Celery¶

The first thing you need is a Celery instance, this is called the celery application. It serves the same purpose as the Flask object in Flask, just for Celery. Since this instance is used as the entry-point for everything you want to do in Celery, like creating tasks and managing workers, it must be possible for other modules to import it.

For instance you can place this in a tasks module. While you can use Celery without any reconfiguration with Flask, it becomes a bit nicer by subclassing tasks and adding support for Flask’s application contexts and hooking it up with the Flask configuration.

This is all that is necessary to properly integrate Celery with Flask:

from celery import Celery

def make_celery(app):
    celery = Celery(app.import_name, backend=app.config['CELERY_RESULT_BACKEND'],
                    broker=app.config['CELERY_BROKER_URL'])
    celery.conf.update(app.config)
    TaskBase = celery.Task
    class ContextTask(TaskBase):
        abstract = True
        def __call__(self, *args, **kwargs):
            with app.app_context():
                return TaskBase.__call__(self, *args, **kwargs)
    celery.Task = ContextTask
    return celery

The function creates a new Celery object, configures it with the broker from the application config, updates the rest of the Celery config from the Flask config and then creates a subclass of the task that wraps the task execution in an application context.

12.3. Minimal Example¶

With what we have above this is the minimal example of using Celery with Flask:

from flask import Flask

flask_app = Flask(__name__)
flask_app.config.update(
    CELERY_BROKER_URL='redis://localhost:6379',
    CELERY_RESULT_BACKEND='redis://localhost:6379'
)
celery = make_celery(flask_app)


@celery.task()
def add_together(a, b):
    return a + b

This task can now be called in the background:

>>> result = add_together.delay(23, 42)
>>> result.wait()
65

12.4. Running the Celery Worker¶

Now if you jumped in and already executed the above code you will be disappointed to learn that your .wait() will never actually return. That’s because you also need to run celery. You can do that by running celery as a worker:

$ celery -A your_application.celery worker

The your_application string has to point to your application’s package or module that creates the celery object.