I use celery to update RSS feeds in my news aggregation site. I use one @task for each feed, and things seem to work nicely.
There's a detail that I'm not sure to handle well though: all feeds are updated once every minute with a @periodic_task, but what if a feed is still updating from the last periodic task when a new one is started ? (for example if the feed is really slow, or offline and the task is held in a retry loop)
Currently I store tasks results and check their status like this:
import socket
from datetime import timedelta
from celery.decorators import task, periodic_task
from aggregator.models import Feed
_results = {}
@periodic_task(run_every=timedelta(minutes=1))
def fetch_articles():
for feed in Feed.objects.all():
if feed.pk in _results:
if not _results[feed.pk].ready():
# The task is not finished yet
continue
_results[feed.pk] = update_feed.delay(feed)
@task()
def update_feed(feed):
try:
feed.fetch_articles()
except socket.error, exc:
update_feed.retry(args=[feed], exc=exc)
Maybe there is a more sophisticated/robust way of achieving the same result using some celery mechanism that I missed ?
Based on MattH's answer, you could use a decorator like this:
def single_instance_task(timeout):
def task_exc(func):
@functools.wraps(func)
def wrapper(*args, **kwargs):
lock_id = "celery-single-instance-" + func.__name__
acquire_lock = lambda: cache.add(lock_id, "true", timeout)
release_lock = lambda: cache.delete(lock_id)
if acquire_lock():
try:
func(*args, **kwargs)
finally:
release_lock()
return wrapper
return task_exc
then, use it like so...
@periodic_task(run_every=timedelta(minutes=1))
@single_instance_task(60*10)
def fetch_articles()
yada yada...