This document describes the current stable version of Celery (5.5). For development docs, go here.
What’s new in Celery 2.5¶
Celery aims to be a flexible and reliable, best-of-breed solution to process vast amounts of messages in a distributed fashion, while providing operations with the tools to maintain such a system.
Celery has a large and diverse community of users and contributors, you should come join us on IRC or our mailing-list.
To read more about Celery you should visit our website.
While this version is backward compatible with previous versions it’s important that you read the following section.
If you use Celery in combination with Django you must also read the django-celery changelog <djcelery:version-2.5.0> and upgrade to django-celery 2.5.
This version is officially supported on CPython 2.5, 2.6, 2.7, 3.2 and 3.3, as well as PyPy and Jython.
Important Notes¶
Broker connection pool now enabled by default¶
The default limit is 10 connections, if you have many threads/green-threads using connections at the same time you may want to tweak this limit to avoid contention.
See the BROKER_POOL_LIMIT
setting for more information.
Also note that publishing tasks will be retried by default, to change
this default or the default retry policy see
CELERY_TASK_PUBLISH_RETRY
and
CELERY_TASK_PUBLISH_RETRY_POLICY
.
Rabbit Result Backend: Exchange is no longer auto delete¶
The exchange used for results in the Rabbit (AMQP) result backend used to have the auto_delete flag set, which could result in a race condition leading to an annoying warning.
For RabbitMQ users
Old exchanges created with the auto_delete flag enabled has to be removed.
The camqadm command can be used to delete the previous exchange:
$ camqadm exchange.delete celeryresults
As an alternative to deleting the old exchange you can configure a new name for the exchange:
CELERY_RESULT_EXCHANGE = 'celeryresults2'
But you have to make sure that all clients and workers use this new setting, so they’re updated to use the same exchange name.
Solution for hanging workers (but must be manually enabled)¶
The CELERYD_FORCE_EXECV setting has been added to solve a problem with deadlocks that originate when threads and fork is mixed together:
CELERYD_FORCE_EXECV = True
This setting is recommended for all users using the prefork pool, but especially users also using time limits or a max tasks per child setting.
See Python Issue 6721 to read more about this issue, and why resorting to
execv`()
is the only safe solution.
Enabling this option will result in a slight performance penalty when new child worker processes are started, and it will also increase memory usage (but many platforms are optimized, so the impact may be minimal). Considering that it ensures reliability when replacing lost worker processes, it should be worth it.
It’s already the default behavior on Windows.
It will be the default behavior for all platforms in a future version.
Optimization¶
The code path used when the worker executes a task has been heavily optimized, meaning the worker is able to process a great deal more tasks/second compared to previous versions. As an example the solo pool can now process up to 15000 tasks/second on a 4 core MacBook Pro when using the https://pypi.org/project/pylibrabbitmq/ transport, where it previously could only do 5000 tasks/second.
The task error tracebacks are now much shorter.
Fixed a noticeable delay in task processing when rate limits are enabled.
Deprecation Time-line Changes¶
Removals¶
The old
TaskSet
signature of(task_name, list_of_tasks)
can no longer be used (originally scheduled for removal in 2.4). The deprecated.task_name
and.task
attributes has also been removed.The functions
celery.execute.delay_task
,celery.execute.apply
, andcelery.execute.apply_async
has been removed (originally) scheduled for removal in 2.3).The built-in
ping
task has been removed (originally scheduled for removal in 2.3). Please use the ping broadcast command instead.It’s no longer possible to import
subtask
andTaskSet
fromcelery.task.base
, please import them fromcelery.task
instead (originally scheduled for removal in 2.4).
Deprecated modules¶
The
celery.decorators
module has changed status from pending deprecation to deprecated, and is scheduled for removal in version 4.0. Thecelery.task
module must be used instead.
News¶
Timezone support¶
Celery can now be configured to treat all incoming and outgoing dates as UTC, and the local timezone can be configured.
This isn’t yet enabled by default, since enabling time zone support means workers running versions pre-2.5 will be out of sync with upgraded workers.
To enable UTC you have to set CELERY_ENABLE_UTC
:
CELERY_ENABLE_UTC = True
When UTC is enabled, dates and times in task messages will be converted to UTC, and then converted back to the local timezone when received by a worker.
You can change the local timezone using the CELERY_TIMEZONE
setting. Installing the https://pypi.org/project/pytz/ library is recommended when
using a custom timezone, to keep timezone definition up-to-date,
but it will fallback to a system definition of the timezone if available.
UTC will enabled by default in version 3.0.
Note
https://pypi.org/project/django-celery/ will use the local timezone as specified by the
TIME_ZONE
setting, it will also honor the new USE_TZ setting
introduced in Django 1.4.
New security serializer using cryptographic signing¶
A new serializer has been added that signs and verifies the signature of messages.
The name of the new serializer is auth
, and needs additional
configuration to work (see Security).
See also
Contributed by Mher Movsisyan.
New CELERY_ANNOTATIONS
setting¶
This new setting enables the configuration to modify task classes and their attributes.
The setting can be a dict, or a list of annotation objects that filter for tasks and return a map of attributes to change.
As an example, this is an annotation to change the rate_limit
attribute
for the tasks.add
task:
CELERY_ANNOTATIONS = {'tasks.add': {'rate_limit': '10/s'}}
or change the same for all tasks:
CELERY_ANNOTATIONS = {'*': {'rate_limit': '10/s'}}
You can change methods too, for example the on_failure
handler:
def my_on_failure(self, exc, task_id, args, kwargs, einfo):
print('Oh no! Task failed: %r' % (exc,))
CELERY_ANNOTATIONS = {'*': {'on_failure': my_on_failure}}
If you need more flexibility then you can also create objects that filter for tasks to annotate:
class MyAnnotate(object):
def annotate(self, task):
if task.name.startswith('tasks.'):
return {'rate_limit': '10/s'}
CELERY_ANNOTATIONS = (MyAnnotate(), {other_annotations,})
current
provides the currently executing task¶
The new celery.task.current
proxy will always give the currently
executing task.
Example:
from celery.task import current, task
@task
def update_twitter_status(auth, message):
twitter = Twitter(auth)
try:
twitter.update_status(message)
except twitter.FailWhale, exc:
# retry in 10 seconds.
current.retry(countdown=10, exc=exc)
Previously you’d’ve to type update_twitter_status.retry(…)
here, which can be annoying for long task names.
Note
This won’t work if the task function is called directly (i.e.,
update_twitter_status(a, b)
). For that to work apply
must
be used: update_twitter_status.apply((a, b))
.
In Other News¶
Now depends on Kombu 2.1.0.
Efficient Chord support for the Memcached backend (Issue #533)
This means Memcached joins Redis in the ability to do non-polling chords.
Contributed by Dan McGee.
Adds Chord support for the Rabbit result backend (amqp)
The Rabbit result backend can now use the fallback chord solution.
Sending
QUIT
toceleryd
will now cause it cold terminate.That is, it won’t finish executing the tasks it’s currently working on.
Contributed by Alec Clowes.
New “detailed” mode for the Cassandra backend.
Allows to have a “detailed” mode for the Cassandra backend. Basically the idea is to keep all states using Cassandra wide columns. New states are then appended to the row as new columns, the last state being the last column.
See the
CASSANDRA_DETAILED_MODE
setting.Contributed by Steeve Morin.
The Crontab parser now matches Vixie Cron behavior when parsing ranges with steps (e.g., 1-59/2).
Contributed by Daniel Hepper.
celerybeat
can now be configured on the command-line likeceleryd
.Additional configuration must be added at the end of the argument list followed by
--
, for example:$ celerybeat -l info -- celerybeat.max_loop_interval=10.0
Now limits the number of frames in a traceback so that
celeryd
doesn’t crash on maximum recursion limit exceeded exceptions (Issue #615).The limit is set to the current recursion limit divided by 8 (which is 125 by default).
To get or set the current recursion limit use
sys.getrecursionlimit()
andsys.setrecursionlimit()
.More information is now preserved in the pickleable traceback.
This has been added so that Sentry can show more details.
Contributed by Sean O’Connor.
CentOS init-script has been updated and should be more flexible.
Contributed by Andrew McFague.
MongoDB result backend now supports
forget()
.Contributed by Andrew McFague
task.retry()
now re-raises the original exception keeping the original stack trace.Suggested by @ojii.
The –uid argument to daemons now uses
initgroups()
to set groups to all the groups the user is a member of.Contributed by Łukasz Oleś.
celeryctl
: Addedshell
command.The shell will have the current_app (
celery
) and all tasks automatically added to locals.celeryctl
: Addedmigrate
command.The migrate command moves all tasks from one broker to another. Note that this is experimental and you should have a backup of the data before proceeding.
Examples:
$ celeryctl migrate redis://localhost amqp://localhost $ celeryctl migrate amqp://localhost//v1 amqp://localhost//v2 $ python manage.py celeryctl migrate django:// redis://
Routers can now override the
exchange
androuting_key
used to create missing queues (Issue #577).By default this will always use the name of the queue, but you can now have a router return exchange and routing_key keys to set them.
This is useful when using routing classes which decides a destination at run-time.
Contributed by Akira Matsuzaki.
Redis result backend: Adds support for a
max_connections
parameter.It’s now possible to configure the maximum number of simultaneous connections in the Redis connection pool used for results.
The default max connections setting can be configured using the
CELERY_REDIS_MAX_CONNECTIONS
setting, or it can be changed individually byRedisBackend(max_connections=int)
.Contributed by Steeve Morin.
Redis result backend: Adds the ability to wait for results without polling.
Contributed by Steeve Morin.
MongoDB result backend: Now supports save and restore
taskset
.Contributed by Julien Poissonnier.
There’s a new Security guide in the documentation.
The init-scripts have been updated, and many bugs fixed.
Contributed by Chris Streeter.
User (tilde) is now expanded in command-line arguments.
Can now configure
CELERYCTL
environment variable in/etc/default/celeryd
.While not necessary for operation, celeryctl is used for the
celeryd status
command, and the path to celeryctl must be configured for that to work.The daemonization cookbook contains examples.
Contributed by Jude Nagurney.
The MongoDB result backend can now use Replica Sets.
Contributed by Ivan Metzlar.
gevent: Now supports autoscaling (Issue #599).
Contributed by Mark Lavin.
multiprocessing: Mediator thread is now always enabled, even though rate limits are disabled, as the pool semaphore is known to block the main thread, causing broadcast commands and shutdown to depend on the semaphore being released.
Fixes¶
Exceptions that are re-raised with a new exception object now keeps the original stack trace.
Windows: Fixed the
no handlers found for multiprocessing
warning.Windows: The
celeryd
program can now be used.Previously Windows users had to launch
celeryd
usingpython -m celery.bin.celeryd
.Redis result backend: Now uses
SETEX
command to set result key, and expiry atomically.Suggested by @yaniv-aknin.
celeryd
: Fixed a problem where shutdown hanged when Control-c was used to terminate.celeryd
: No longer crashes when channel errors occur.Fix contributed by Roger Hu.
Fixed memory leak in the eventlet pool, caused by the use of
greenlet.getcurrent
.Fix contributed by Ignas Mikalajūnas.
Cassandra backend: No longer uses
pycassa.connect()
which is deprecated since https://pypi.org/project/pycassa/ 1.4.Fix contributed by Jeff Terrace.
Fixed unicode decode errors that could occur while sending error emails.
Fix contributed by Seong Wun Mun.
celery.bin
programs now always defines__package__
as recommended by PEP-366.send_task
now emits a warning when used in combination withCELERY_ALWAYS_EAGER
(Issue #581).Contributed by Mher Movsisyan.
apply_async
now forwards the original keyword arguments toapply
whenCELERY_ALWAYS_EAGER
is enabled.celeryev
now tries to re-establish the connection if the connection to the broker is lost (Issue #574).celeryev
: Fixed a crash occurring if a task has no associated worker information.Fix contributed by Matt Williamson.
The current date and time is now consistently taken from the current loaders
now
method.Now shows helpful error message when given a configuration module ending in
.py
that can’t be imported.celeryctl
: The--expires
and--eta
arguments to the apply command can now be an ISO-8601 formatted string.celeryctl
now exits with exit statusEX_UNAVAILABLE
(69) if no replies have been received.