Celery integration with pyramid

## Getting Started

Include pyramid_celery either by setting your includes in your .ini, or by calling config.include('pyramid_celery'):

pyramid.includes = pyramid_celery

Then you just need to tell pyramid_celery what ini file your [celery] section is in:

config.configure_celery('development.ini')

Then you are free to use celery, for example class based:

from pyramid_celery import celery_app as app

def run(self, x, y):
print x+y

or decorator based:

from pyramid_celery import celery_app as app

print x+y

To get pyramid settings you may access them in app.conf['PYRAMID_REGISTRY'].

## Configuration

By default pyramid_celery assumes you want to configure celery via an ini settings. You can do this by calling config.configure_celery(‘development.ini’) but if you are already in the main of your application and want to use the ini used to configure the app you can do the following:

config.configure_celery(global_config['__file__'])

If you want to use the standard celeryconfig python file you can set the USE_CELERYCONFIG = True like this:

[celery]
USE_CELERYCONFIG = True

An example ini configuration looks like this:

[celery]
BROKER_URL = redis://localhost:1337/0

type = crontab
schedule = {"minute": 0}

To use celerybeat (periodic tasks) you need to declare 1 celerybeat config section per task. The options are:

• type - The type of scheduling your configuration uses, options are crontab, timedelta, and integer.

• schedule - The actual schedule for your type of configuration.

• args - Additional positional arguments.

• kwargs - Additional keyword arguments.

Example configuration for this:

type = crontab
schedule = {"minute": 0}

type = timedelta
schedule = {"seconds": 30}
args = [16, 16]

type = crontab
schedule = {"hour": 0, "minute": 0}
kwargs = {"boom": "shaka"}

type = integer
schedule = 30

### Routing

If you would like to route a task to a specific queue you can define a route per task by declaring their queue and/or routing_key in a celeryroute section.

An example configuration for this:

routing_key = turtle

## Running the worker

To run the worker we just use the standard celery command with an additional argument:

celery worker -A pyramid_celery.celery_app --ini development.ini

If you’ve defined variables in your .ini like %(database_username)s you can use the –ini-var argument, which is a comma separated list of key value pairs:

The values in ini-var cannot have spaces in them, this will break celery’s parser.

The reason it is a csv instead of using –ini-var multiple times is because of a bug in celery itself. When they fix the bug we will re-work the API. Ticket is here:

https://github.com/celery/celery/pull/2435

If you use celerybeat scheduler you need to run with the -B flag to run beat and worker at the same time or you can launch it separately like this:

celery beat -A pyramid_celery.celery_app --ini development.ini

## Logging

If you use the .ini configuration (i.e don’t use celeryconfig.py) then the logging configuration will be loaded from the .ini and will not use the default celery loggers.

You most likely want to add a logging section to your ini for celery as well:

[logger_celery]
level = INFO
handlers =
qualname = celery

and then update your [loggers] section to include it.

If you want use the default celery loggers then you can set CELERYD_HIJACK_ROOT_LOGGER=True in the [celery] section of your .ini

## Demo

To see it all in action check out examples/long_running_with_tm, run redis-server and then do:

$python setup.py develop$ populate_long_running_with_tm development.ini
$pserve ./development.ini$ celery worker -A pyramid_celery.celery_app --ini development.ini