CKAN allows you to create tasks that run in the ‘background’, that is asynchronously and without blocking the main application (these tasks can also be automatically retried in the case of transient failures). Such tasks can be created in Extensions or in core CKAN.
Background tasks can be essential to providing certain kinds of functionality, for example:
- Creating webhooks that notify other services when certain changes occur (for example a dataset is updated)
- Performing processing or validation or on data (as done by the Archiver and DataStorer Extensions)
Enabling Background Tasks¶
To manage and run background tasks requires a job queue and CKAN uses celery (plus the CKAN database) for this purpose. Thus, to use background tasks you need to install and run celery. As of CKAN 1.7, celery is a required library and will be already installed after a default CKAN install.
Installation of celery will normally be taken care of by whichever component or extension utilizes it so we skip that here.
To run the celery daemon you have two options:
In development setup you can just use paster. This can be done as simply as:
This only works if you have a development.ini file in ckan root.
In production, the daemon should be run with a different ini file and be run as an init script. The simplest way to do this is to install supervisor:
apt-get install supervisor
Using this file as a template and copy to /etc/supservisor/conf.d:
Alternatively, you can run:
paster celeryd --config=/path/to/file.ini
Writing Background Tasks¶
These instructions should show you how to write an background task and how to call it from inside CKAN or another extension using celery.
Here are some existing real examples of writing CKAN tasks:
An entry point is required inside the setup.py for your extension, and so you should add something resembling the following that points to a function in a module. In this case the function is called task_imports in the ckanext.NAME.celery_import module:
entry_points = """ [ckan.celery_task] tasks = ckanext.NAME.celery_import:task_imports """
The function, in this case task_imports should be a function that returns fully qualified module paths to modules that contain the defined task (see the next section). In this case we will put all of our tasks in a file called tasks.py and so task_imports should be in a file called ckanext/NAME/celery_import.py:
def task_imports(): return ['ckanext.NAME.tasks']
This returns an iterable of all of the places to look to find tasks, in this example we are only putting them in one place.
Implementing the tasks¶
The most straightforward way of defining tasks in our tasks.py module, is to use the decorators provided by celery. These decorators make it easy to just define a function and then give it a name and make it accessible to celery. Make sure you import celery from ckan.lib.celery_app:
from ckan.lib.celery_app import celery
Implement your function, specifying the arguments you wish it to take. For our sample we will use a simple echo task that will print out its argument to the console:
def echo( message ): print message
Next it is important to decorate your function with the celery task decorator. You should give the task a name, which is used later on when calling the task:
@celery.task(name = "NAME.echofunction") def echo( message ): print message
That’s it, your function is ready to be run asynchronously outside of the main execution of the CKAN app. Next you should make sure you run python setup.py develop in your extensions folder and then go to your CKAN installation folder (normally pyenv/src/ckan/) to run the following command:
Once you have done this your task name NAME.echofunction should appear in the list of tasks loaded. If it is there then you are all set and ready to go. If not then you should try the following to try and resolve the problem:
- Make sure the entry point is defined correctly in your setup.py and that you have executed python setup.py develop
- Check that your task_imports function returns an iterable with valid module names in
- Ensure that the decorator marks the functions (if there is more than one decorator, make sure the celery.task is the first one - which means it will execute last).
- If none of the above helps, go into #ckan on irc.freenode.net where there should be people who can help you resolve your issue.
Calling the task¶
Now that the task is defined, and has been loaded by celery it is ready to be called. To call a background task you need to know only the name of the task, and the arguments that it expects as well as providing it a task id.:
import uuid from ckan.lib.celery_app import celery celery.send_task("NAME.echofunction", args=["Hello World"], task_id=str(uuid.uuid4()))
After executing this code you should see the message printed in the console where you ran paster celeryd.
Retrying on errors¶
Should your task fail to complete because of a transient error, it is possible to ask celery to retry the task, after some period of time. The default wait before retrying is three minutes, but you can optionally specify this in the call to retry via the countdown parameter, and you can also specify the exception that triggered the failure. For our example the call to retry would look like the following - note that it calls the function name, not the task name given in the decorator:
try: ... some work that may fail, http request? except Exception, e: # Retry again in 2 minutes echo.retry(args=(message), exc=e, countdown=120, max_retries=10)
If you don’t want to wait a period of time you can use the eta datetime parameter to specify an explicit time to run the task (i.e. 9AM tomorrow)