.. _changelog-2.0:
===============================
Change history for Celery 2.0
===============================
.. contents::
:local:
.. _version-2.0.3:
2.0.3
=====
:release-date: 2010-08-27 12:00 P.M CEST
:release-by: Ask Solem
.. _v203-fixes:
Fixes
-----
* Worker: Properly handle connection errors happening while
closing consumers.
* Worker: Events are now buffered if the connection is down,
then sent when the connection is re-established.
* No longer depends on the :pypi:`mailer` package.
This package had a name space collision with `django-mailer`,
so its functionality was replaced.
* Redis result backend: Documentation typos: Redis doesn't have
database names, but database numbers. The default database is now 0.
* :class:`~celery.task.control.inspect`:
`registered_tasks` was requesting an invalid command because of a typo.
See issue #170.
* :setting:`CELERY_ROUTES`: Values defined in the route should now have
precedence over values defined in :setting:`CELERY_QUEUES` when merging
the two.
With the follow settings:
.. code-block:: python
CELERY_QUEUES = {'cpubound': {'exchange': 'cpubound',
'routing_key': 'cpubound'}}
CELERY_ROUTES = {'tasks.add': {'queue': 'cpubound',
'routing_key': 'tasks.add',
'serializer': 'json'}}
The final routing options for `tasks.add` will become:
.. code-block:: python
{'exchange': 'cpubound',
'routing_key': 'tasks.add',
'serializer': 'json'}
This was not the case before: the values
in :setting:`CELERY_QUEUES` would take precedence.
* Worker crashed if the value of :setting:`CELERY_TASK_ERROR_WHITELIST` was
not an iterable
* :func:`~celery.execute.apply`: Make sure `kwargs['task_id']` is
always set.
* `AsyncResult.traceback`: Now returns :const:`None`, instead of raising
:exc:`KeyError` if traceback is missing.
* :class:`~celery.task.control.inspect`: Replies did not work correctly
if no destination was specified.
* Can now store result/meta-data for custom states.
* Worker: A warning is now emitted if the sending of task error
emails fails.
* ``celeryev``: Curses monitor no longer crashes if the terminal window
is resized.
See issue #160.
* Worker: On macOS it is not possible to run `os.exec*` in a process
that is threaded.
This breaks the SIGHUP restart handler,
and is now disabled on macOS, emitting a warning instead.
See issue #152.
* :mod:`celery.execute.trace`: Properly handle `raise(str)`,
which is still allowed in Python 2.4.
See issue #175.
* Using urllib2 in a periodic task on macOS crashed because
of the proxy auto detection used in macOS.
This is now fixed by using a workaround.
See issue #143.
* Debian init-scripts: Commands should not run in a sub shell
See issue #163.
* Debian init-scripts: Use the absolute path of ``celeryd`` program to allow stat
See issue #162.
.. _v203-documentation:
Documentation
-------------
* getting-started/broker-installation: Fixed typo
`set_permissions ""` -> `set_permissions ".*"`.
* Tasks User Guide: Added section on database transactions.
See issue #169.
* Routing User Guide: Fixed typo `"feed": -> {"queue": "feeds"}`.
See issue #169.
* Documented the default values for the :setting:`CELERYD_CONCURRENCY`
and :setting:`CELERYD_PREFETCH_MULTIPLIER` settings.
* Tasks User Guide: Fixed typos in the subtask example
* celery.signals: Documented worker_process_init.
* Daemonization cookbook: Need to export DJANGO_SETTINGS_MODULE in
`/etc/default/celeryd`.
* Added some more FAQs from stack overflow
* Daemonization cookbook: Fixed typo `CELERYD_LOGFILE/CELERYD_PIDFILE`
to `CELERYD_LOG_FILE` / `CELERYD_PID_FILE`
Also added troubleshooting section for the init-scripts.
.. _version-2.0.2:
2.0.2
=====
:release-date: 2010-07-22 11:31 A.M CEST
:release-by: Ask Solem
* Routes: When using the dict route syntax, the exchange for a task
could disappear making the task unroutable.
See issue #158.
* Test suite now passing on Python 2.4
* No longer have to type `PYTHONPATH=.` to use ``celeryconfig`` in the current
directory.
This is accomplished by the default loader ensuring that the current
directory is in `sys.path` when loading the config module.
`sys.path` is reset to its original state after loading.
Adding the current working directory to `sys.path` without the user
knowing may be a security issue, as this means someone can drop a Python module in the users
directory that executes arbitrary commands. This was the original reason
not to do this, but if done *only when loading the config module*, this
means that the behavior will only apply to the modules imported in the
config module, which I think is a good compromise (certainly better than
just explicitly setting `PYTHONPATH=.` anyway)
* Experimental Cassandra backend added.
* Worker: SIGHUP handler accidentally propagated to worker pool processes.
In combination with :sha:`7a7c44e39344789f11b5346e9cc8340f5fe4846c`
this would make each child process start a new worker instance when
the terminal window was closed :/
* Worker: Do not install SIGHUP handler if running from a terminal.
This fixes the problem where the worker is launched in the background
when closing the terminal.
* Worker: Now joins threads at shutdown.
See issue #152.
* Test tear down: Don't use `atexit` but nose's `teardown()` functionality
instead.
See issue #154.
* Debian worker init-script: Stop now works correctly.
* Task logger: `warn` method added (synonym for `warning`)
* Can now define a white list of errors to send error emails for.
Example:
.. code-block:: python
CELERY_TASK_ERROR_WHITELIST = ('myapp.MalformedInputError',)
See issue #153.
* Worker: Now handles overflow exceptions in `time.mktime` while parsing
the ETA field.
* LoggerWrapper: Try to detect loggers logging back to stderr/stdout making
an infinite loop.
* Added :class:`celery.task.control.inspect`: Inspects a running worker.
Examples:
.. code-block:: pycon
# Inspect a single worker
>>> i = inspect('myworker.example.com')
# Inspect several workers
>>> i = inspect(['myworker.example.com', 'myworker2.example.com'])
# Inspect all workers consuming on this vhost.
>>> i = inspect()
### Methods
# Get currently executing tasks
>>> i.active()
# Get currently reserved tasks
>>> i.reserved()
# Get the current eta schedule
>>> i.scheduled()
# Worker statistics and info
>>> i.stats()
# List of currently revoked tasks
>>> i.revoked()
# List of registered tasks
>>> i.registered_tasks()
* Remote control commands `dump_active`/`dump_reserved`/`dump_schedule`
now replies with detailed task requests.
Containing the original arguments and fields of the task requested.
In addition the remote control command `set_loglevel` has been added,
this only changes the log level for the main process.
* Worker control command execution now catches errors and returns their
string representation in the reply.
* Functional test suite added
:mod:`celery.tests.functional.case` contains utilities to start
and stop an embedded worker process, for use in functional testing.
.. _version-2.0.1:
2.0.1
=====
:release-date: 2010-07-09 03:02 P.M CEST
:release-by: Ask Solem
* multiprocessing.pool: Now handles encoding errors, so that pickling errors
doesn't crash the worker processes.
* The remote control command replies was not working with RabbitMQ 1.8.0's
stricter equivalence checks.
If you've already hit this problem you may have to delete the
declaration:
.. code-block:: console
$ camqadm exchange.delete celerycrq
or:
.. code-block:: console
$ python manage.py camqadm exchange.delete celerycrq
* A bug sneaked in the ETA scheduler that made it only able to execute
one task per second(!)
The scheduler sleeps between iterations so it doesn't consume too much CPU.
It keeps a list of the scheduled items sorted by time, at each iteration
it sleeps for the remaining time of the item with the nearest deadline.
If there are no eta tasks it will sleep for a minimum amount of time, one
second by default.
A bug sneaked in here, making it sleep for one second for every task
that was scheduled. This has been fixed, so now it should move
tasks like hot knife through butter.
In addition a new setting has been added to control the minimum sleep
interval; :setting:`CELERYD_ETA_SCHEDULER_PRECISION`. A good
value for this would be a float between 0 and 1, depending
on the needed precision. A value of 0.8 means that when the ETA of a task
is met, it will take at most 0.8 seconds for the task to be moved to the
ready queue.
* Pool: Supervisor did not release the semaphore.
This would lead to a deadlock if all workers terminated prematurely.
* Added Python version trove classifiers: 2.4, 2.5, 2.6 and 2.7
* Tests now passing on Python 2.7.
* Task.__reduce__: Tasks created using the task decorator can now be pickled.
* :file:`setup.py`: :pypi:`nose` added to `tests_require`.
* Pickle should now work with SQLAlchemy 0.5.x
* New homepage design by Jan Henrik Helmers: http://celeryproject.org
* New Sphinx theme by Armin Ronacher: http://docs.celeryproject.org/
* Fixed "pending_xref" errors shown in the HTML rendering of the
documentation. Apparently this was caused by new changes in Sphinx 1.0b2.
* Router classes in :setting:`CELERY_ROUTES` are now imported lazily.
Importing a router class in a module that also loads the Celery
environment would cause a circular dependency. This is solved
by importing it when needed after the environment is set up.
* :setting:`CELERY_ROUTES` was broken if set to a single dict.
This example in the docs should now work again:
.. code-block:: python
CELERY_ROUTES = {'feed.tasks.import_feed': 'feeds'}
* `CREATE_MISSING_QUEUES` was not honored by apply_async.
* New remote control command: `stats`
Dumps information about the worker, like pool process ids, and
total number of tasks executed by type.
Example reply:
.. code-block:: python
[{'worker.local':
'total': {'tasks.sleeptask': 6},
'pool': {'timeouts': [None, None],
'processes': [60376, 60377],
'max-concurrency': 2,
'max-tasks-per-child': None,
'put-guarded-by-semaphore': True}}]
* New remote control command: `dump_active`
Gives a list of tasks currently being executed by the worker.
By default arguments are passed through repr in case there
are arguments that is not JSON encodable. If you know
the arguments are JSON safe, you can pass the argument `safe=True`.
Example reply:
.. code-block:: pycon
>>> broadcast('dump_active', arguments={'safe': False}, reply=True)
[{'worker.local': [
{'args': '(1,)',
'time_start': 1278580542.6300001,
'name': 'tasks.sleeptask',
'delivery_info': {
'consumer_tag': '30',
'routing_key': 'celery',
'exchange': 'celery'},
'hostname': 'casper.local',
'acknowledged': True,
'kwargs': '{}',
'id': '802e93e9-e470-47ed-b913-06de8510aca2',
}
]}]
* Added experimental support for persistent revokes.
Use the `-S|--statedb` argument to the worker to enable it:
.. code-block:: console
$ celeryd --statedb=/var/run/celeryd
This will use the file: `/var/run/celeryd.db`,
as the `shelve` module automatically adds the `.db` suffix.
.. _version-2.0.0:
2.0.0
=====
:release-date: 2010-07-02 02:30 P.M CEST
:release-by: Ask Solem
Foreword
--------
Celery 2.0 contains backward incompatible changes, the most important
being that the Django dependency has been removed so Celery no longer
supports Django out of the box, but instead as an add-on package
called `django-celery`_.
We're very sorry for breaking backwards compatibility, but there's
also many new and exciting features to make up for the time you lose
upgrading, so be sure to read the :ref:`News <v200-news>` section.
Quite a lot of potential users have been upset about the Django dependency,
so maybe this is a chance to get wider adoption by the Python community as
well.
Big thanks to all contributors, testers and users!
.. _v200-django-upgrade:
Upgrading for Django-users
--------------------------
Django integration has been moved to a separate package: `django-celery`_.
* To upgrade you need to install the `django-celery`_ module and change:
.. code-block:: python
INSTALLED_APPS = 'celery'
to:
.. code-block:: python
INSTALLED_APPS = 'djcelery'
* If you use `mod_wsgi` you need to add the following line to your `.wsgi`
file:
.. code-block:: python
import os
os.environ['CELERY_LOADER'] = 'django'
* The following modules has been moved to `django-celery`_:
===================================== =====================================
**Module name** **Replace with**
===================================== =====================================
`celery.models` `djcelery.models`
`celery.managers` `djcelery.managers`
`celery.views` `djcelery.views`
`celery.urls` `djcelery.urls`
`celery.management` `djcelery.management`
`celery.loaders.djangoapp` `djcelery.loaders`
`celery.backends.database` `djcelery.backends.database`
`celery.backends.cache` `djcelery.backends.cache`
===================================== =====================================
Importing :mod:`djcelery` will automatically setup Celery to use Django loader.
loader. It does this by setting the :envvar:`CELERY_LOADER` environment variable to
`"django"` (it won't change it if a loader is already set.)
When the Django loader is used, the "database" and "cache" result backend
aliases will point to the :mod:`djcelery` backends instead of the built-in backends,
and configuration will be read from the Django settings.
.. _`django-celery`: http://pypi.python.org/pypi/django-celery
.. _v200-upgrade:
Upgrading for others
--------------------
.. _v200-upgrade-database:
Database result backend
~~~~~~~~~~~~~~~~~~~~~~~
The database result backend is now using `SQLAlchemy`_ instead of the
Django ORM, see `Supported Databases`_ for a table of supported databases.
The `DATABASE_*` settings has been replaced by a single setting:
:setting:`CELERY_RESULT_DBURI`. The value here should be an
`SQLAlchemy Connection String`_, some examples include:
.. code-block:: python
# sqlite (filename)
CELERY_RESULT_DBURI = 'sqlite:///celerydb.sqlite'
# mysql
CELERY_RESULT_DBURI = 'mysql://scott:tiger@localhost/foo'
# postgresql
CELERY_RESULT_DBURI = 'postgresql://scott:tiger@localhost/mydatabase'
# oracle
CELERY_RESULT_DBURI = 'oracle://scott:tiger@127.0.0.1:1521/sidname'
See `SQLAlchemy Connection Strings`_ for more information about connection
strings.
To specify additional SQLAlchemy database engine options you can use
the :setting:`CELERY_RESULT_ENGINE_OPTIONS` setting:
.. code-block:: python
# echo enables verbose logging from SQLAlchemy.
CELERY_RESULT_ENGINE_OPTIONS = {'echo': True}
.. _`SQLAlchemy`:
http://www.sqlalchemy.org
.. _`Supported Databases`:
http://www.sqlalchemy.org/docs/core/engines.html#supported-databases
.. _`SQLAlchemy Connection String`:
http://www.sqlalchemy.org/docs/core/engines.html#database-urls
.. _`SQLAlchemy Connection Strings`:
http://www.sqlalchemy.org/docs/core/engines.html#database-urls
.. _v200-upgrade-cache:
Cache result backend
~~~~~~~~~~~~~~~~~~~~
The cache result backend is no longer using the Django cache framework,
but it supports mostly the same configuration syntax:
.. code-block:: python
CELERY_CACHE_BACKEND = 'memcached://A.example.com:11211;B.example.com'
To use the cache backend you must either have the `pylibmc`_ or
`python-memcached`_ library installed, of which the former is regarded
as the best choice.
.. _`pylibmc`: http://pypi.python.org/pypi/pylibmc
.. _`python-memcached`: http://pypi.python.org/pypi/python-memcached
The support backend types are `memcached://` and `memory://`,
we haven't felt the need to support any of the other backends
provided by Django.
.. _v200-incompatible:
Backward incompatible changes
-----------------------------
* Default (python) loader now prints warning on missing `celeryconfig.py`
instead of raising :exc:`ImportError`.
The worker raises :exc:`~@ImproperlyConfigured` if the configuration
is not set up. This makes it possible to use `--help` etc., without having a
working configuration.
Also this makes it possible to use the client side of celery without being
configured:
.. code-block:: pycon
>>> from carrot.connection import BrokerConnection
>>> conn = BrokerConnection('localhost', 'guest', 'guest', '/')
>>> from celery.execute import send_task
>>> r = send_task('celery.ping', args=(), kwargs={}, connection=conn)
>>> from celery.backends.amqp import AMQPBackend
>>> r.backend = AMQPBackend(connection=conn)
>>> r.get()
'pong'
* The following deprecated settings has been removed (as scheduled by
the :ref:`deprecation-timeline`):
===================================== =====================================
**Setting name** **Replace with**
===================================== =====================================
`CELERY_AMQP_CONSUMER_QUEUES` `CELERY_QUEUES`
`CELERY_AMQP_EXCHANGE` `CELERY_DEFAULT_EXCHANGE`
`CELERY_AMQP_EXCHANGE_TYPE` `CELERY_DEFAULT_EXCHANGE_TYPE`
`CELERY_AMQP_CONSUMER_ROUTING_KEY` `CELERY_QUEUES`
`CELERY_AMQP_PUBLISHER_ROUTING_KEY` `CELERY_DEFAULT_ROUTING_KEY`
===================================== =====================================
* The `celery.task.rest` module has been removed, use :mod:`celery.task.http`
instead (as scheduled by the :ref:`deprecation-timeline`).
* It's no longer allowed to skip the class name in loader names.
(as scheduled by the :ref:`deprecation-timeline`):
Assuming the implicit `Loader` class name is no longer supported,
if you use e.g.:
.. code-block:: python
CELERY_LOADER = 'myapp.loaders'
You need to include the loader class name, like this:
.. code-block:: python
CELERY_LOADER = 'myapp.loaders.Loader'
* :setting:`CELERY_TASK_RESULT_EXPIRES` now defaults to 1 day.
Previous default setting was to expire in 5 days.
* AMQP backend: Don't use different values for `auto_delete`.
This bug became visible with RabbitMQ 1.8.0, which no longer
allows conflicting declarations for the auto_delete and durable settings.
If you've already used celery with this backend chances are you
have to delete the previous declaration:
.. code-block:: console
$ camqadm exchange.delete celeryresults
* Now uses pickle instead of cPickle on Python versions <= 2.5
cPickle is broken in Python <= 2.5.
It unsafely and incorrectly uses relative instead of absolute imports,
so e.g.:
.. code-block:: python
exceptions.KeyError
becomes:
.. code-block:: python
celery.exceptions.KeyError
Your best choice is to upgrade to Python 2.6,
as while the pure pickle version has worse performance,
it is the only safe option for older Python versions.
.. _v200-news:
News
----
* **celeryev**: Curses Celery Monitor and Event Viewer.
This is a simple monitor allowing you to see what tasks are
executing in real-time and investigate tracebacks and results of ready
tasks. It also enables you to set new rate limits and revoke tasks.
Screenshot:
.. figure:: ../images/celeryevshotsm.jpg
If you run `celeryev` with the `-d` switch it will act as an event
dumper, simply dumping the events it receives to standard out:
.. code-block:: console
$ celeryev -d
-> celeryev: starting capture...
casper.local [2010-06-04 10:42:07.020000] heartbeat
casper.local [2010-06-04 10:42:14.750000] task received:
tasks.add(61a68756-27f4-4879-b816-3cf815672b0e) args=[2, 2] kwargs={}
eta=2010-06-04T10:42:16.669290, retries=0
casper.local [2010-06-04 10:42:17.230000] task started
tasks.add(61a68756-27f4-4879-b816-3cf815672b0e) args=[2, 2] kwargs={}
casper.local [2010-06-04 10:42:17.960000] task succeeded:
tasks.add(61a68756-27f4-4879-b816-3cf815672b0e)
args=[2, 2] kwargs={} result=4, runtime=0.782663106918
The fields here are, in order: *sender hostname*, *timestamp*, *event type* and
*additional event fields*.
* AMQP result backend: Now supports `.ready()`, `.successful()`,
`.result`, `.status`, and even responds to changes in task state
* New user guides:
* :ref:`guide-workers`
* :ref:`guide-canvas`
* :ref:`guide-routing`
* Worker: Standard out/error is now being redirected to the log file.
* :pypi:`billiard` has been moved back to the celery repository.
===================================== =====================================
**Module name** **celery equivalent**
===================================== =====================================
`billiard.pool` `celery.concurrency.processes.pool`
`billiard.serialization` `celery.serialization`
`billiard.utils.functional` `celery.utils.functional`
===================================== =====================================
The :pypi:`billiard` distribution may be maintained, depending on interest.
* now depends on :pypi:`carrot` >= 0.10.5
* now depends on :pypi:`pyparsing`
* Worker: Added `--purge` as an alias to `--discard`.
* Worker: :kbd:`Control-c` (SIGINT) once does warm shutdown,
hitting :kbd:`Control-c` twice forces termination.
* Added support for using complex Crontab-expressions in periodic tasks. For
example, you can now use:
.. code-block:: pycon
>>> crontab(minute='*/15')
or even:
.. code-block:: pycon
>>> crontab(minute='*/30', hour='8-17,1-2', day_of_week='thu-fri')
See :ref:`guide-beat`.
* Worker: Now waits for available pool processes before applying new
tasks to the pool.
This means it doesn't have to wait for dozens of tasks to finish at shutdown
because it has applied prefetched tasks without having any pool
processes available to immediately accept them.
See issue #122.
* New built-in way to do task callbacks using
:class:`~celery.subtask`.
See :ref:`guide-canvas` for more information.
* TaskSets can now contain several types of tasks.
:class:`~celery.task.sets.TaskSet` has been refactored to use
a new syntax, please see :ref:`guide-canvas` for more information.
The previous syntax is still supported, but will be deprecated in
version 1.4.
* TaskSet failed() result was incorrect.
See issue #132.
* Now creates different loggers per task class.
See issue #129.
* Missing queue definitions are now created automatically.
You can disable this using the :setting:`CELERY_CREATE_MISSING_QUEUES`
setting.
The missing queues are created with the following options:
.. code-block:: python
CELERY_QUEUES[name] = {'exchange': name,
'exchange_type': 'direct',
'routing_key': 'name}
This feature is added for easily setting up routing using the `-Q`
option to the worker:
.. code-block:: console
$ celeryd -Q video, image
See the new routing section of the User Guide for more information:
:ref:`guide-routing`.
* New Task option: `Task.queue`
If set, message options will be taken from the corresponding entry
in :setting:`CELERY_QUEUES`. `exchange`, `exchange_type` and `routing_key`
will be ignored
* Added support for task soft and hard time limits.
New settings added:
* :setting:`CELERYD_TASK_TIME_LIMIT`
Hard time limit. The worker processing the task will be killed and
replaced with a new one when this is exceeded.
* :setting:`CELERYD_TASK_SOFT_TIME_LIMIT`
Soft time limit. The :exc:`~@SoftTimeLimitExceeded`
exception will be raised when this is exceeded. The task can catch
this to e.g. clean up before the hard time limit comes.
New command-line arguments to ``celeryd`` added:
`--time-limit` and `--soft-time-limit`.
What's left?
This won't work on platforms not supporting signals (and specifically
the `SIGUSR1` signal) yet. So an alternative the ability to disable
the feature all together on nonconforming platforms must be implemented.
Also when the hard time limit is exceeded, the task result should
be a `TimeLimitExceeded` exception.
* Test suite is now passing without a running broker, using the carrot
in-memory backend.
* Log output is now available in colors.
===================================== =====================================
**Log level** **Color**
===================================== =====================================
`DEBUG` Blue
`WARNING` Yellow
`CRITICAL` Magenta
`ERROR` Red
===================================== =====================================
This is only enabled when the log output is a tty.
You can explicitly enable/disable this feature using the
:setting:`CELERYD_LOG_COLOR` setting.
* Added support for task router classes (like the django multi-db routers)
* New setting: :setting:`CELERY_ROUTES`
This is a single, or a list of routers to traverse when
sending tasks. Dictionaries in this list converts to a
:class:`celery.routes.MapRoute` instance.
Examples:
>>> CELERY_ROUTES = {'celery.ping': 'default',
'mytasks.add': 'cpu-bound',
'video.encode': {
'queue': 'video',
'exchange': 'media'
'routing_key': 'media.video.encode'}}
>>> CELERY_ROUTES = ('myapp.tasks.Router',
{'celery.ping': 'default})
Where `myapp.tasks.Router` could be:
.. code-block:: python
class Router(object):
def route_for_task(self, task, args=None, kwargs=None):
if task == 'celery.ping':
return 'default'
route_for_task may return a string or a dict. A string then means
it's a queue name in :setting:`CELERY_QUEUES`, a dict means it's a custom route.
When sending tasks, the routers are consulted in order. The first
router that doesn't return `None` is the route to use. The message options
is then merged with the found route settings, where the routers settings
have priority.
Example if :func:`~celery.execute.apply_async` has these arguments:
.. code-block:: pycon
>>> Task.apply_async(immediate=False, exchange='video',
... routing_key='video.compress')
and a router returns:
.. code-block:: python
{'immediate': True,
'exchange': 'urgent'}
the final message options will be:
.. code-block:: pycon
>>> task.apply_async(
... immediate=True,
... exchange='urgent',
... routing_key='video.compress',
... )
(and any default message options defined in the
:class:`~celery.task.base.Task` class)
* New Task handler called after the task returns:
:meth:`~celery.task.base.Task.after_return`.
* :class:`~celery.datastructures.ExceptionInfo` now passed to
:meth:`~celery.task.base.Task.on_retry`/
:meth:`~celery.task.base.Task.on_failure` as ``einfo`` keyword argument.
* Worker: Added :setting:`CELERYD_MAX_TASKS_PER_CHILD` /
:option:`celery worker --maxtasksperchild`
Defines the maximum number of tasks a pool worker can process before
the process is terminated and replaced by a new one.
* Revoked tasks now marked with state :state:`REVOKED`, and `result.get()`
will now raise :exc:`~@TaskRevokedError`.
* :func:`celery.task.control.ping` now works as expected.
* `apply(throw=True)` / :setting:`CELERY_EAGER_PROPAGATES_EXCEPTIONS`:
Makes eager execution re-raise task errors.
* New signal: :signal:`~celery.signals.worker_process_init`: Sent inside the
pool worker process at init.
* Worker: :option:`celery worker -Q` option: Ability to specify list of queues
to use, disabling other configured queues.
For example, if :setting:`CELERY_QUEUES` defines four
queues: `image`, `video`, `data` and `default`, the following
command would make the worker only consume from the `image` and `video`
queues:
.. code-block:: console
$ celeryd -Q image,video
* Worker: New return value for the `revoke` control command:
Now returns:
.. code-block:: python
{'ok': 'task $id revoked'}
instead of :const:`True`.
* Worker: Can now enable/disable events using remote control
Example usage:
>>> from celery.task.control import broadcast
>>> broadcast('enable_events')
>>> broadcast('disable_events')
* Removed top-level tests directory. Test config now in celery.tests.config
This means running the unit tests doesn't require any special setup.
`celery/tests/__init__` now configures the :envvar:`CELERY_CONFIG_MODULE`
and :envvar:`CELERY_LOADER` environment variables, so when `nosetests`
imports that, the unit test environment is all set up.
Before you run the tests you need to install the test requirements:
.. code-block:: console
$ pip install -r requirements/test.txt
Running all tests:
.. code-block:: console
$ nosetests
Specifying the tests to run:
.. code-block:: console
$ nosetests celery.tests.test_task
Producing HTML coverage:
.. code-block:: console
$ nosetests --with-coverage3
The coverage output is then located in `celery/tests/cover/index.html`.
* Worker: New option `--version`: Dump version info and exit.
* :mod:`celeryd-multi <celeryd.bin.multi>`: Tool for shell scripts
to start multiple workers.
Some examples:
- Advanced example with 10 workers:
* Three of the workers processes the images and video queue
* Two of the workers processes the data queue with loglevel DEBUG
* the rest processes the default' queue.
.. code-block:: console
$ celeryd-multi start 10 -l INFO -Q:1-3 images,video -Q:4,5:data -Q default -L:4,5 DEBUG
- Get commands to start 10 workers, with 3 processes each
.. code-block:: console
$ celeryd-multi start 3 -c 3
celeryd -n celeryd1.myhost -c 3
celeryd -n celeryd2.myhost -c 3
celeryd -n celeryd3.myhost -c 3
- Start 3 named workers
.. code-block:: console
$ celeryd-multi start image video data -c 3
celeryd -n image.myhost -c 3
celeryd -n video.myhost -c 3
celeryd -n data.myhost -c 3
- Specify custom hostname
.. code-block:: console
$ celeryd-multi start 2 -n worker.example.com -c 3
celeryd -n celeryd1.worker.example.com -c 3
celeryd -n celeryd2.worker.example.com -c 3
Additional options are added to each ``celeryd``,
but you can also modify the options for ranges of or single workers
- 3 workers: Two with 3 processes, and one with 10 processes.
.. code-block:: console
$ celeryd-multi start 3 -c 3 -c:1 10
celeryd -n celeryd1.myhost -c 10
celeryd -n celeryd2.myhost -c 3
celeryd -n celeryd3.myhost -c 3
- Can also specify options for named workers
.. code-block:: console
$ celeryd-multi start image video data -c 3 -c:image 10
celeryd -n image.myhost -c 10
celeryd -n video.myhost -c 3
celeryd -n data.myhost -c 3
- Ranges and lists of workers in options is also allowed:
(``-c:1-3`` can also be written as ``-c:1,2,3``)
.. code-block:: console
$ celeryd-multi start 5 -c 3 -c:1-3 10
celeryd-multi -n celeryd1.myhost -c 10
celeryd-multi -n celeryd2.myhost -c 10
celeryd-multi -n celeryd3.myhost -c 10
celeryd-multi -n celeryd4.myhost -c 3
celeryd-multi -n celeryd5.myhost -c 3
- Lists also work with named workers:
.. code-block:: console
$ celeryd-multi start foo bar baz xuzzy -c 3 -c:foo,bar,baz 10
celeryd-multi -n foo.myhost -c 10
celeryd-multi -n bar.myhost -c 10
celeryd-multi -n baz.myhost -c 10
celeryd-multi -n xuzzy.myhost -c 3
* The worker now calls the result backends `process_cleanup` method
*after* task execution instead of before.
* AMQP result backend now supports Pika.