Change history for Celery 1.0

• 1.0.6
• 1.0.5
  • Critical
  • Changes
• 1.0.4
• 1.0.3
  • Important notes
  • News
  • Remote control commands
  • Fixes
• 1.0.2
• 1.0.1
• 1.0.0
  • Backward incompatible changes
  • Deprecations
  • News
  • Changes
  • Bugs
  • Documentation
• 0.8.4
• 0.8.3
• 0.8.2
• 0.8.1
  • Very important note
  • Important changes
  • Changes
• 0.8.0
  • Backward incompatible changes
  • Important changes
  • News
• 0.6.0
  • Important changes
  • News
• 0.4.1
• 0.4.0
• 0.3.20
• 0.3.7
• 0.3.3
• 0.3.2
• 0.3.1
• 0.3.0
• 0.2.0
• 0.2.0-pre3
• 0.2.0-pre2
• 0.2.0-pre1
• 0.1.15
• 0.1.14
• 0.1.13
• 0.1.12
• 0.1.11
• 0.1.10
• 0.1.8
• 0.1.7
• 0.1.6
• 0.1.0

1.0.6

• RabbitMQ 1.8.0 has extended their exchange equivalence tests to include auto_delete and durable. This broke the AMQP backend.

  If you’ve already used the AMQP backend this means you have to delete the previous definitions:

  $ camqadm exchange.delete celeryresults

  or:

  $ python manage.py camqadm exchange.delete celeryresults

1.0.5

Critical

• SIGINT/Ctrl+C killed the pool, abruptly terminating the currently executing tasks.

  Fixed by making the pool worker processes ignore SIGINT.

• Should not close the consumers before the pool is terminated, just cancel the consumers.

  See issue #122.

• Now depends on billiard >= 0.3.1

• worker: Previously exceptions raised by worker components could stall startup, now it correctly logs the exceptions and shuts down.

• worker: Prefetch counts was set too late. QoS is now set as early as possible, so the worker: can’t slurp in all the messages at start-up.

Changes

• celery.contrib.abortable: Abortable tasks.

  Tasks that defines steps of execution, the task can then be aborted after each step has completed.

• EventDispatcher: No longer creates AMQP channel if events are disabled

• Added required RPM package names under [bdist_rpm] section, to support building RPMs from the sources using setup.py

• Running unit tests: NOSE_VERBOSE environment var now enables verbose output from Nose.

• celery.execute.apply(): Pass log file/log level arguments as task kwargs.

  See issue #110.

• celery.execute.apply: Should return exception, not ExceptionInfo on error.

  See issue #111.

• Added new entries to the FAQs:

  • Should I use retry or acks_late?
  • Can I call a task by name?

1.0.4

• Changelog merged with 1.0.5 as the release was never announced.

1.0.3

Important notes

• Messages are now acknowledged just before the task function is executed.

  This is the behavior we’ve wanted all along, but couldn’t have because of limitations in the multiprocessing module. The previous behavior was not good, and the situation worsened with the release of 1.0.1, so this change will definitely improve reliability, performance and operations in general.

  For more information please see http://bit.ly/9hom6T

• Database result backend: result now explicitly sets null=True as django-picklefield version 0.1.5 changed the default behavior right under our noses :(

  See: http://bit.ly/d5OwMr

  This means those who created their celery tables (via syncdb or celeryinit) with picklefield versions >= 0.1.5 has to alter their tables to allow the result field to be NULL manually.

  MySQL:

  ALTER TABLE celery_taskmeta MODIFY result TEXT NULL

  PostgreSQL:

  ALTER TABLE celery_taskmeta ALTER COLUMN result DROP NOT NULL

• Removed Task.rate_limit_queue_type, as it was not really useful and made it harder to refactor some parts.

• Now depends on carrot >= 0.10.4

• Now depends on billiard >= 0.3.0

News

• AMQP backend: Added timeout support for result.get() / result.wait().

• New task option: Task.acks_late (default: CELERY_ACKS_LATE)

  Late ack means the task messages will be acknowledged after the task has been executed, not just before, which is the default behavior.

  注解

  This means the tasks may be executed twice if the worker crashes in mid-execution. Not acceptable for most applications, but desirable for others.

• Added crontab-like scheduling to periodic tasks.

  Like a cron job, you can specify units of time of when you would like the task to execute. While not a full implementation of cron’s features, it should provide a fair degree of common scheduling needs.

  You can specify a minute (0-59), an hour (0-23), and/or a day of the week (0-6 where 0 is Sunday, or by names: sun, mon, tue, wed, thu, fri, sat).

  Examples:

  from celery.schedules import crontab
  from celery.decorators import periodic_task
  @periodic_task(run_every=crontab(hour=7, minute=30))
  def every_morning():
      print("Runs every morning at 7:30a.m")
  @periodic_task(run_every=crontab(hour=7, minute=30, day_of_week="mon"))
  def every_monday_morning():
      print("Run every monday morning at 7:30a.m")
  @periodic_task(run_every=crontab(minutes=30))
  def every_hour():
      print("Runs every hour on the clock. e.g. 1:30, 2:30, 3:30 etc.")

  注解

  This a late addition. While we have unittests, due to the nature of this feature we haven’t been able to completely test this in practice, so consider this experimental.

• TaskPool.apply_async: Now supports the accept_callback argument.

• apply_async: Now raises ValueError if task args is not a list, or kwargs is not a tuple (Issue #95).

• Task.max_retries can now be None, which means it will retry forever.

• Celerybeat: Now reuses the same connection when publishing large sets of tasks.

• Modified the task locking example in the documentation to use cache.add for atomic locking.

• Added experimental support for a started status on tasks.

  If Task.track_started is enabled the task will report its status as “started” when the task is executed by a worker.

  The default value is False as the normal behaviour is to not report that level of granularity. Tasks are either pending, finished, or waiting to be retried. Having a “started” status can be useful for when there are long running tasks and there is a need to report which task is currently running.

  The global default can be overridden by the CELERY_TRACK_STARTED setting.

• User Guide: New section Tips and Best Practices.

  Contributions welcome!

Remote control commands

• Remote control commands can now send replies back to the caller.

  Existing commands has been improved to send replies, and the client interface in celery.task.control has new keyword arguments: reply, timeout and limit. Where reply means it will wait for replies, timeout is the time in seconds to stop waiting for replies, and limit is the maximum number of replies to get.

  By default, it will wait for as many replies as possible for one second.

  • rate_limit(task_name, destination=all, reply=False, timeout=1, limit=0)

    Worker returns {“ok”: message} on success, or {“failure”: message} on failure.

    >>> from celery.task.control import rate_limit
    >>> rate_limit("tasks.add", "10/s", reply=True)
    [{'worker1': {'ok': 'new rate limit set successfully'}},
     {'worker2': {'ok': 'new rate limit set successfully'}}]

  • ping(destination=all, reply=False, timeout=1, limit=0)

    Worker returns the simple message “pong”.

    >>> from celery.task.control import ping
    >>> ping(reply=True)
    [{'worker1': 'pong'},
     {'worker2': 'pong'},

  • revoke(destination=all, reply=False, timeout=1, limit=0)

    Worker simply returns True.

    >>> from celery.task.control import revoke
    >>> revoke("419e46eb-cf6a-4271-86a8-442b7124132c", reply=True)
    [{'worker1': True},
     {'worker2'; True}]

• You can now add your own remote control commands!

  Remote control commands are functions registered in the command registry. Registering a command is done using celery.worker.control.Panel.register():

  from celery.task.control import Panel
  @Panel.register
  def reset_broker_connection(state, **kwargs):
      state.consumer.reset_connection()
      return {"ok": "connection re-established"}

  With this module imported in the worker, you can launch the command using celery.task.control.broadcast:

  >>> from celery.task.control import broadcast
  >>> broadcast("reset_broker_connection", reply=True)
  [{'worker1': {'ok': 'connection re-established'},
   {'worker2': {'ok': 'connection re-established'}}]

  TIP You can choose the worker(s) to receive the command by using the destination argument:

  >>> broadcast("reset_broker_connection", destination=["worker1"])
  [{'worker1': {'ok': 'connection re-established'}]

• New remote control command: dump_reserved

  Dumps tasks reserved by the worker, waiting to be executed:

  >>> from celery.task.control import broadcast
  >>> broadcast("dump_reserved", reply=True)
  [{'myworker1': [<TaskRequest ....>]}]

• New remote control command: dump_schedule

  Dumps the workers currently registered ETA schedule. These are tasks with an eta (or countdown) argument waiting to be executed by the worker.

  >>> from celery.task.control import broadcast
  >>> broadcast("dump_schedule", reply=True)
  [{'w1': []},
   {'w3': []},
   {'w2': ['0. 2010-05-12 11:06:00 pri0 <TaskRequest
              {name:"opalfeeds.tasks.refresh_feed_slice",
               id:"95b45760-4e73-4ce8-8eac-f100aa80273a",
               args:"(<Feeds freq_max:3600 freq_min:60
                             start:2184.0 stop:3276.0>,)",
               kwargs:"{'page': 2}"}>']},
   {'w4': ['0. 2010-05-12 11:00:00 pri0 <TaskRequest
              {name:"opalfeeds.tasks.refresh_feed_slice",
               id:"c053480b-58fb-422f-ae68-8d30a464edfe",
               args:"(<Feeds freq_max:3600 freq_min:60
                             start:1092.0 stop:2184.0>,)",
               kwargs:"{\'page\': 1}"}>',
          '1. 2010-05-12 11:12:00 pri0 <TaskRequest
              {name:"opalfeeds.tasks.refresh_feed_slice",
               id:"ab8bc59e-6cf8-44b8-88d0-f1af57789758",
               args:"(<Feeds freq_max:3600 freq_min:60
                             start:3276.0 stop:4365>,)",
               kwargs:"{\'page\': 3}"}>']}]

Fixes

• Mediator thread no longer blocks for more than 1 second.

  With rate limits enabled and when there was a lot of remaining time, the mediator thread could block shutdown (and potentially block other jobs from coming in).

• Remote rate limits was not properly applied (Issue #98).

• Now handles exceptions with Unicode messages correctly in TaskRequest.on_failure.

• Database backend: TaskMeta.result: default value should be None not empty string.

1.0.2

• Deprecated: CELERY_BACKEND, please use CELERY_RESULT_BACKEND instead.

• We now use a custom logger in tasks. This logger supports task magic keyword arguments in formats.

  The default format for tasks (CELERYD_TASK_LOG_FORMAT) now includes the id and the name of tasks so the origin of task log messages can easily be traced.

  Example output::

  • [2010-03-25 13:11:20,317: INFO/PoolWorker-1]

    [tasks.add(a6e1c5ad-60d9-42a0-8b24-9e39363125a4)] Hello from add

  To revert to the previous behavior you can set:

  CELERYD_TASK_LOG_FORMAT = """
      [%(asctime)s: %(levelname)s/%(processName)s] %(message)s
  """.strip()

• Unit tests: Don’t disable the django test database tear down, instead fixed the underlying issue which was caused by modifications to the DATABASE_NAME setting (Issue #82).

• Django Loader: New config CELERY_DB_REUSE_MAX (max number of tasks to reuse the same database connection)

  The default is to use a new connection for every task. We would very much like to reuse the connection, but a safe number of reuses is not known, and we don’t have any way to handle the errors that might happen, which may even be database dependent.

  See: http://bit.ly/94fwdd

• worker: The worker components are now configurable: CELERYD_POOL, CELERYD_CONSUMER, CELERYD_MEDIATOR, and CELERYD_ETA_SCHEDULER.

  The default configuration is as follows:

  CELERYD_POOL = "celery.concurrency.processes.TaskPool"
  CELERYD_MEDIATOR = "celery.worker.controllers.Mediator"
  CELERYD_ETA_SCHEDULER = "celery.worker.controllers.ScheduleController"
  CELERYD_CONSUMER = "celery.worker.consumer.Consumer"

  The CELERYD_POOL setting makes it easy to swap out the multiprocessing pool with a threaded pool, or how about a twisted/eventlet pool?

  Consider the competition for the first pool plug-in started!

• Debian init scripts: Use -a not && (Issue #82).

• Debian init scripts: Now always preserves $CELERYD_OPTS from the /etc/default/celeryd and /etc/default/celerybeat.

• celery.beat.Scheduler: Fixed a bug where the schedule was not properly flushed to disk if the schedule had not been properly initialized.

• celerybeat: Now syncs the schedule to disk when receiving the SIGTERM and SIGINT signals.

• Control commands: Make sure keywords arguments are not in Unicode.

• ETA scheduler: Was missing a logger object, so the scheduler crashed when trying to log that a task had been revoked.

• management.commands.camqadm: Fixed typo camqpadm -> camqadm (Issue #83).

• PeriodicTask.delta_resolution: Was not working for days and hours, now fixed by rounding to the nearest day/hour.

• Fixed a potential infinite loop in BaseAsyncResult.__eq__, although there is no evidence that it has ever been triggered.

• worker: Now handles messages with encoding problems by acking them and emitting an error message.

1.0.1

• Tasks are now acknowledged early instead of late.

  This is done because messages can only be acknowledged within the same connection channel, so if the connection is lost we would have to refetch the message again to acknowledge it.

  This might or might not affect you, but mostly those running tasks with a really long execution time are affected, as all tasks that has made it all the way into the pool needs to be executed before the worker can safely terminate (this is at most the number of pool workers, multiplied by the CELERYD_PREFETCH_MULTIPLIER setting.)

  We multiply the prefetch count by default to increase the performance at times with bursts of tasks with a short execution time. If this doesn’t apply to your use case, you should be able to set the prefetch multiplier to zero, without sacrificing performance.

  注解

  A patch to multiprocessing is currently being worked on, this patch would enable us to use a better solution, and is scheduled for inclusion in the 2.0.0 release.

• The worker now shutdowns cleanly when receiving the SIGTERM signal.

• The worker now does a cold shutdown if the SIGINT signal is received (Ctrl+C), this means it tries to terminate as soon as possible.

• Caching of results now moved to the base backend classes, so no need to implement this functionality in the base classes.

• Caches are now also limited in size, so their memory usage doesn’t grow out of control.

  You can set the maximum number of results the cache can hold using the CELERY_MAX_CACHED_RESULTS setting (the default is five thousand results). In addition, you can refetch already retrieved results using backend.reload_task_result + backend.reload_taskset_result (that’s for those who want to send results incrementally).

• The worker now works on Windows again.

  警告

  If you’re using Celery with Django, you can’t use project.settings as the settings module name, but the following should work:

  $ python manage.py celeryd --settings=settings

• Execution: .messaging.TaskPublisher.send_task now incorporates all the functionality apply_async previously did.

  Like converting countdowns to eta, so celery.execute.apply_async() is now simply a convenient front-end to celery.messaging.TaskPublisher.send_task(), using the task classes default options.

  Also celery.execute.send_task() has been introduced, which can apply tasks using just the task name (useful if the client does not have the destination task in its task registry).

  Example:

  >>> from celery.execute import send_task
  >>> result = send_task("celery.ping", args=[], kwargs={})
  >>> result.get()
  'pong'

• camqadm: This is a new utility for command-line access to the AMQP API.

  Excellent for deleting queues/bindings/exchanges, experimentation and testing:

  $ camqadm
  1> help

  Gives an interactive shell, type help for a list of commands.

  When using Django, use the management command instead:

  $ python manage.py camqadm
  1> help

• Redis result backend: To conform to recent Redis API changes, the following settings has been deprecated:

  • REDIS_TIMEOUT
  • REDIS_CONNECT_RETRY

  These will emit a DeprecationWarning if used.

  A REDIS_PASSWORD setting has been added, so you can use the new simple authentication mechanism in Redis.

• The redis result backend no longer calls SAVE when disconnecting, as this is apparently better handled by Redis itself.

• If settings.DEBUG is on, the worker now warns about the possible memory leak it can result in.

• The ETA scheduler now sleeps at most two seconds between iterations.

• The ETA scheduler now deletes any revoked tasks it might encounter.

  As revokes are not yet persistent, this is done to make sure the task is revoked even though it’s currently being hold because its eta is e.g. a week into the future.

• The task_id argument is now respected even if the task is executed eagerly (either using apply, or CELERY_ALWAYS_EAGER).

• The internal queues are now cleared if the connection is reset.

• New magic keyword argument: delivery_info.

  Used by retry() to resend the task to its original destination using the same exchange/routing_key.

• Events: Fields was not passed by .send() (fixes the UUID key errors in celerymon)

• Added –schedule/-s option to the worker, so it is possible to specify a custom schedule filename when using an embedded celerybeat server (the -B/–beat) option.

• Better Python 2.4 compatibility. The test suite now passes.

• task decorators: Now preserve docstring as cls.__doc__, (was previously copied to cls.run.__doc__)

• The testproj directory has been renamed to tests and we’re now using nose + django-nose for test discovery, and unittest2 for test cases.

• New pip requirements files available in requirements.

• TaskPublisher: Declarations are now done once (per process).

• Added Task.delivery_mode and the CELERY_DEFAULT_DELIVERY_MODE setting.

  These can be used to mark messages non-persistent (i.e. so they are lost if the broker is restarted).

• Now have our own ImproperlyConfigured exception, instead of using the Django one.

• Improvements to the Debian init scripts: Shows an error if the program is not executable. Does not modify CELERYD when using django with virtualenv.

1.0.0

Backward incompatible changes

• Celery does not support detaching anymore, so you have to use the tools available on your platform, or something like Supervisord to make celeryd/celerybeat/celerymon into background processes.

  We’ve had too many problems with the worker daemonizing itself, so it was decided it has to be removed. Example startup scripts has been added to the extra/ directory:

  • Debian, Ubuntu, (start-stop-daemon)

    extra/debian/init.d/celeryd extra/debian/init.d/celerybeat

  • Mac OS X launchd

    extra/mac/org.celeryq.celeryd.plist extra/mac/org.celeryq.celerybeat.plist extra/mac/org.celeryq.celerymon.plist

  • Supervisord (http://supervisord.org)

    extra/supervisord/supervisord.conf

  In addition to –detach, the following program arguments has been removed: –uid, –gid, –workdir, –chroot, –pidfile, –umask. All good daemonization tools should support equivalent functionality, so don’t worry.

  Also the following configuration keys has been removed: CELERYD_PID_FILE, CELERYBEAT_PID_FILE, CELERYMON_PID_FILE.

• Default worker loglevel is now WARN, to enable the previous log level start the worker with –loglevel=INFO.

• Tasks are automatically registered.

  This means you no longer have to register your tasks manually. You don’t have to change your old code right away, as it doesn’t matter if a task is registered twice.

  If you don’t want your task to be automatically registered you can set the abstract attribute

  class MyTask(Task):
      abstract = True

  By using abstract only tasks subclassing this task will be automatically registered (this works like the Django ORM).

  If you don’t want subclasses to be registered either, you can set the autoregister attribute to False.

  Incidentally, this change also fixes the problems with automatic name assignment and relative imports. So you also don’t have to specify a task name anymore if you use relative imports.

• You can no longer use regular functions as tasks.

  This change was added because it makes the internals a lot more clean and simple. However, you can now turn functions into tasks by using the @task decorator:

  from celery.decorators import task
  @task()
  def add(x, y):
      return x + y

  参见

  Tasks for more information about the task decorators.

• The periodic task system has been rewritten to a centralized solution.

  This means the worker no longer schedules periodic tasks by default, but a new daemon has been introduced: celerybeat.

  To launch the periodic task scheduler you have to run celerybeat:

  $ celerybeat

  Make sure this is running on one server only, if you run it twice, all periodic tasks will also be executed twice.

  If you only have one worker server you can embed it into the worker like this:

  $ celeryd --beat # Embed celerybeat in celeryd.

• The supervisor has been removed.

  This means the -S and –supervised options to celeryd is no longer supported. Please use something like http://supervisord.org instead.

• TaskSet.join has been removed, use TaskSetResult.join instead.

• The task status “DONE” has been renamed to “SUCCESS”.

• AsyncResult.is_done has been removed, use AsyncResult.successful instead.

• The worker no longer stores errors if Task.ignore_result is set, to revert to the previous behaviour set CELERY_STORE_ERRORS_EVEN_IF_IGNORED to True.

• The statistics functionality has been removed in favor of events, so the -S and –statistics` switches has been removed.

• The module celery.task.strategy has been removed.

• celery.discovery has been removed, and it’s autodiscover function is now in celery.loaders.djangoapp. Reason: Internal API.

• The CELERY_LOADER environment variable now needs loader class name in addition to module name,

  E.g. where you previously had: “celery.loaders.default”, you now need “celery.loaders.default.Loader”, using the previous syntax will result in a DeprecationWarning.

• Detecting the loader is now lazy, and so is not done when importing celery.loaders.

  To make this happen celery.loaders.settings has been renamed to load_settings and is now a function returning the settings object. celery.loaders.current_loader is now also a function, returning the current loader.

  So:

  loader = current_loader

  needs to be changed to:

  loader = current_loader()

Deprecations

• The following configuration variables has been renamed and will be deprecated in v2.0:

  • CELERYD_DAEMON_LOG_FORMAT -> CELERYD_LOG_FORMAT
  • CELERYD_DAEMON_LOG_LEVEL -> CELERYD_LOG_LEVEL
  • CELERY_AMQP_CONNECTION_TIMEOUT -> CELERY_BROKER_CONNECTION_TIMEOUT
  • CELERY_AMQP_CONNECTION_RETRY -> CELERY_BROKER_CONNECTION_RETRY
  • CELERY_AMQP_CONNECTION_MAX_RETRIES -> CELERY_BROKER_CONNECTION_MAX_RETRIES
  • SEND_CELERY_TASK_ERROR_EMAILS -> CELERY_SEND_TASK_ERROR_EMAILS

• The public API names in celery.conf has also changed to a consistent naming scheme.

• We now support consuming from an arbitrary number of queues.

  To do this we had to rename the configuration syntax. If you use any of the custom AMQP routing options (queue/exchange/routing_key, etc.), you should read the new FAQ entry: Can I send some tasks to only some servers?.

  The previous syntax is deprecated and scheduled for removal in v2.0.

• TaskSet.run has been renamed to TaskSet.apply_async.

  TaskSet.run has now been deprecated, and is scheduled for removal in v2.0.

News

• Rate limiting support (per task type, or globally).

• New periodic task system.

• Automatic registration.

• New cool task decorator syntax.

• worker: now sends events if enabled with the -E argument.

  Excellent for monitoring tools, one is already in the making (http://github.com/celery/celerymon).

  Current events include: worker-heartbeat, task-[received/succeeded/failed/retried], worker-online, worker-offline.

• You can now delete (revoke) tasks that has already been applied.

• You can now set the hostname the worker identifies as using the –hostname argument.

• Cache backend now respects the CELERY_TASK_RESULT_EXPIRES setting.

• Message format has been standardized and now uses ISO-8601 format for dates instead of datetime.

• worker now responds to the SIGHUP signal by restarting itself.

• Periodic tasks are now scheduled on the clock.

  I.e. timedelta(hours=1) means every hour at :00 minutes, not every hour from the server starts. To revert to the previous behaviour you can set PeriodicTask.relative = True.

• Now supports passing execute options to a TaskSets list of args, e.g.:

  >>> ts = TaskSet(add, [([2, 2], {}, {"countdown": 1}),
  ...                   ([4, 4], {}, {"countdown": 2}),
  ...                   ([8, 8], {}, {"countdown": 3})])
  >>> ts.run()

• Got a 3x performance gain by setting the prefetch count to four times the concurrency, (from an average task round-trip of 0.1s to 0.03s!).

  A new setting has been added: CELERYD_PREFETCH_MULTIPLIER, which is set to 4 by default.

• Improved support for webhook tasks.

  celery.task.rest is now deprecated, replaced with the new and shiny celery.task.http. With more reflective names, sensible interface, and it’s possible to override the methods used to perform HTTP requests.

• The results of task sets are now cached by storing it in the result backend.

Changes

• Now depends on carrot >= 0.8.1

• New dependencies: billiard, python-dateutil, django-picklefield

• No longer depends on python-daemon

• The uuid distribution is added as a dependency when running Python 2.4.

• Now remembers the previously detected loader by keeping it in the CELERY_LOADER environment variable.

  This may help on windows where fork emulation is used.

• ETA no longer sends datetime objects, but uses ISO 8601 date format in a string for better compatibility with other platforms.

• No longer sends error mails for retried tasks.

• Task can now override the backend used to store results.

• Refactored the ExecuteWrapper, apply and CELERY_ALWAYS_EAGER now also executes the task callbacks and signals.

• Now using a proper scheduler for the tasks with an ETA.

  This means waiting eta tasks are sorted by time, so we don’t have to poll the whole list all the time.

• Now also imports modules listed in CELERY_IMPORTS when running with django (as documented).

• Log level for stdout/stderr changed from INFO to ERROR

• ImportErrors are now properly propagated when autodiscovering tasks.

• You can now use celery.messaging.establish_connection to establish a connection to the broker.

• When running as a separate service the periodic task scheduler does some smart moves to not poll too regularly.

  If you need faster poll times you can lower the value of CELERYBEAT_MAX_LOOP_INTERVAL.

• You can now change periodic task intervals at runtime, by making run_every a property, or subclassing PeriodicTask.is_due.

• The worker now supports control commands enabled through the use of a broadcast queue, you can remotely revoke tasks or set the rate limit for a task type. See celery.task.control.

• The services now sets informative process names (as shown in ps listings) if the setproctitle module is installed.

• NotRegistered now inherits from KeyError, and TaskRegistry.__getitem__`+`pop raises NotRegistered instead

• You can set the loader via the CELERY_LOADER environment variable.

• You can now set CELERY_IGNORE_RESULT to ignore task results by default (if enabled, tasks doesn’t save results or errors to the backend used).

• The worker now correctly handles malformed messages by throwing away and acknowledging the message, instead of crashing.

Bugs

• Fixed a race condition that could happen while storing task results in the database.

Documentation

• Reference now split into two sections; API reference and internal module reference.

0.8.4

• Now emits a warning if the –detach argument is used. –detach should not be used anymore, as it has several not easily fixed bugs related to it. Instead, use something like start-stop-daemon, Supervisord or launchd (os x).
• Make sure logger class is process aware, even if running Python >= 2.6.
• Error emails are not sent anymore when the task is retried.

0.8.3

• Fixed a possible race condition that could happen when storing/querying task results using the database backend.
• Now has console script entry points in the setup.py file, so tools like Buildout will correctly install the programs celeryd and celeryinit.

0.8.2

• QOS Prefetch count was not applied properly, as it was set for every message received (which apparently behaves like, “receive one more”), instead of only set when our wanted value changed.

0.8.1

Very important note

This release (with carrot 0.8.0) enables AMQP QoS (quality of service), which means the workers will only receive as many messages as it can handle at a time. As with any release, you should test this version upgrade on your development servers before rolling it out to production!

Important changes

• If you’re using Python < 2.6 and you use the multiprocessing backport, then multiprocessing version 2.6.2.1 is required.

• All AMQP_* settings has been renamed to BROKER_*, and in addition AMQP_SERVER has been renamed to BROKER_HOST, so before where you had:

  AMQP_SERVER = "localhost"
  AMQP_PORT = 5678
  AMQP_USER = "myuser"
  AMQP_PASSWORD = "mypassword"
  AMQP_VHOST = "celery"

  You need to change that to:

  BROKER_HOST = "localhost"
  BROKER_PORT = 5678
  BROKER_USER = "myuser"
  BROKER_PASSWORD = "mypassword"
  BROKER_VHOST = "celery"

• Custom carrot backends now need to include the backend class name, so before where you had:

  CARROT_BACKEND = "mycustom.backend.module"

  you need to change it to:

  CARROT_BACKEND = "mycustom.backend.module.Backend"

  where Backend is the class name. This is probably “Backend”, as that was the previously implied name.

• New version requirement for carrot: 0.8.0

Changes

• Incorporated the multiprocessing backport patch that fixes the processName error.
• Ignore the result of PeriodicTask’s by default.
• Added a Redis result store backend
• Allow /etc/default/celeryd to define additional options for the celeryd init script.
• MongoDB periodic tasks issue when using different time than UTC fixed.
• Windows specific: Negate test for available os.fork (thanks miracle2k)
• Now tried to handle broken PID files.
• Added a Django test runner to contrib that sets CELERY_ALWAYS_EAGER = True for testing with the database backend.
• Added a CELERY_CACHE_BACKEND setting for using something other than the django-global cache backend.
• Use custom implementation of functools.partial (curry) for Python 2.4 support (Probably still problems with running on 2.4, but it will eventually be supported)
• Prepare exception to pickle when saving RETRY status for all backends.
• SQLite no concurrency limit should only be effective if the database backend is used.

0.8.0

Backward incompatible changes

• Add traceback to result value on failure.

  注解

  If you use the database backend you have to re-create the database table celery_taskmeta.

  Contact the Mailing list or IRC channel for help doing this.

• Database tables are now only created if the database backend is used, so if you change back to the database backend at some point, be sure to initialize tables (django: syncdb, python: celeryinit).

  注解

  This is only applies if using Django version 1.1 or higher.

• Now depends on carrot version 0.6.0.

• Now depends on python-daemon 1.4.8

Important changes

• Celery can now be used in pure Python (outside of a Django project).

  This means celery is no longer Django specific.

  For more information see the FAQ entry Is Celery for Django only?.

• Celery now supports task retries.

  See Retrying for more information.

• We now have an AMQP result store backend.

  It uses messages to publish task return value and status. And it’s incredibly fast!

  See issue #6 for more info!

• AMQP QoS (prefetch count) implemented:

  This to not receive more messages than we can handle.

• Now redirects stdout/stderr to the workers log file when detached

• Now uses inspect.getargspec to only pass default arguments

  the task supports.

• Add Task.on_success, .on_retry, .on_failure handlers

  • See celery.task.base.Task.on_success(),

    celery.task.base.Task.on_retry(), celery.task.base.Task.on_failure(),

• celery.utils.gen_unique_id: Workaround for

  http://bugs.python.org/issue4607

• You can now customize what happens at worker start, at process init, etc.,

  by creating your own loaders. (see celery.loaders.default, celery.loaders.djangoapp, celery.loaders.)

• Support for multiple AMQP exchanges and queues.

  This feature misses documentation and tests, so anyone interested is encouraged to improve this situation.

• The worker now survives a restart of the AMQP server!

  Automatically re-establish AMQP broker connection if it’s lost.

  New settings:

  • AMQP_CONNECTION_RETRY

    Set to True to enable connection retries.

  • AMQP_CONNECTION_MAX_RETRIES.

    Maximum number of restarts before we give up. Default: 100.

News

• Fix an incompatibility between python-daemon and multiprocessing,

  which resulted in the [Errno 10] No child processes problem when detaching.

• Fixed a possible DjangoUnicodeDecodeError being raised when saving pickled

  data to Django`s memcached cache backend.

• Better Windows compatibility.

• New version of the pickled field (taken from

  http://www.djangosnippets.org/snippets/513/)

• New signals introduced: task_sent, task_prerun and

  task_postrun, see celery.signals for more information.

• TaskSetResult.join caused TypeError when timeout=None.

  Thanks Jerzy Kozera. Closes #31

• views.apply should return HttpResponse instance.

  Thanks to Jerzy Kozera. Closes #32

• PeriodicTask: Save conversion of run_every from int

  to timedelta to the class attribute instead of on the instance.

• Exceptions has been moved to celery.exceptions, but are still

  available in the previous module.

• Try to rollback transaction and retry saving result if an error happens

  while setting task status with the database backend.

• jail() refactored into celery.execute.ExecuteWrapper.

• views.apply now correctly sets mime-type to “application/json”

• views.task_status now returns exception if state is RETRY

• views.task_status now returns traceback if state is FAILURE

  or RETRY

• Documented default task arguments.

• Add a sensible __repr__ to ExceptionInfo for easier debugging

• Fix documentation typo .. import map -> .. import dmap.

  Thanks to mikedizon

0.6.0

Important changes

• Fixed a bug where tasks raising unpickleable exceptions crashed pool

  workers. So if you’ve had pool workers mysteriously disappearing, or problems with the worker stopping working, this has been fixed in this version.

• Fixed a race condition with periodic tasks.

• The task pool is now supervised, so if a pool worker crashes,

  goes away or stops responding, it is automatically replaced with a new one.

• Task.name is now automatically generated out of class module+name, e.g.

  “djangotwitter.tasks.UpdateStatusesTask”. Very convenient. No idea why we didn’t do this before. Some documentation is updated to not manually specify a task name.

News

• Tested with Django 1.1

• New Tutorial: Creating a click counter using carrot and celery

• Database entries for periodic tasks are now created at the workers

  startup instead of for each check (which has been a forgotten TODO/XXX in the code for a long time)

• New settings variable: CELERY_TASK_RESULT_EXPIRES

  Time (in seconds, or a datetime.timedelta object) for when after stored task results are deleted. For the moment this only works for the database backend.

• The worker now emits a debug log message for which periodic tasks

  has been launched.

• The periodic task table is now locked for reading while getting

  periodic task status. (MySQL only so far, seeking patches for other engines)

• A lot more debugging information is now available by turning on the

  DEBUG log level (–loglevel=DEBUG).

• Functions/methods with a timeout argument now works correctly.

• New: celery.strategy.even_time_distribution:

  With an iterator yielding task args, kwargs tuples, evenly distribute the processing of its tasks throughout the time window available.

• Log message Unknown task ignored… now has log level ERROR

• Log message when task is received is now emitted for all tasks, even if

  the task has an ETA (estimated time of arrival). Also the log message now includes the ETA for the task (if any).

• Acknowledgement now happens in the pool callback. Can’t do ack in the job

  target, as it’s not pickleable (can’t share AMQP connection, etc.)).

• Added note about .delay hanging in README

• Tests now passing in Django 1.1

• Fixed discovery to make sure app is in INSTALLED_APPS

• Previously overridden pool behavior (process reap, wait until pool worker

  available, etc.) is now handled by multiprocessing.Pool itself.

• Convert statistics data to Unicode for use as kwargs. Thanks Lucy!

0.4.1

• Fixed a bug with parsing the message options (mandatory, routing_key, priority, immediate)

0.4.0

• Adds eager execution. celery.execute.apply`|`Task.apply executes the function blocking until the task is done, for API compatibility it returns an celery.result.EagerResult instance. You can configure celery to always run tasks locally by setting the CELERY_ALWAYS_EAGER setting to True.
• Now depends on anyjson.
• 99% coverage using python coverage 3.0.

0.3.20

• New arguments to apply_async (the advanced version of delay_task), countdown and eta;

  >>> # Run 10 seconds into the future.
  >>> res = apply_async(MyTask, countdown=10);

  >>> # Run 1 day from now
  >>> res = apply_async(MyTask,
  ...                   eta=datetime.now() + timedelta(days=1))

• Now unlinks stale PID files

• Lots of more tests.

• Now compatible with carrot >= 0.5.0.

• IMPORTANT The subtask_ids attribute on the TaskSetResult instance has been removed. To get this information instead use:

  >>> subtask_ids = [subtask.id for subtask in ts_res.subtasks]

• Taskset.run() now respects extra message options from the task class.

• Task: Add attribute ignore_result: Don’t store the status and return value. This means you can’t use the celery.result.AsyncResult to check if the task is done, or get its return value. Only use if you need the performance and is able live without these features. Any exceptions raised will store the return value/status as usual.

• Task: Add attribute disable_error_emails to disable sending error emails for that task.

• Should now work on Windows (although running in the background won’t work, so using the –detach argument results in an exception being raised.)

• Added support for statistics for profiling and monitoring. To start sending statistics start the worker with the –statistics option. Then after a while you can dump the results by running `python manage.py celerystats. See celery.monitoring for more information.

• The celery daemon can now be supervised (i.e. it is automatically restarted if it crashes). To use this start the worker with the –supervised` option (or alternatively -S).

• views.apply: View calling a task. Example

  http://e.com/celery/apply/task_name/arg1/arg2//?kwarg1=a&kwarg2=b

  警告

  Use with caution! Do not expose this URL to the public without first ensuring that your code is safe!

• Refactored celery.task. It’s now split into three modules:

  • celery.task

    Contains apply_async, delay_task, discard_all, and task shortcuts, plus imports objects from celery.task.base and celery.task.builtins

  • celery.task.base

    Contains task base classes: Task, PeriodicTask, TaskSet, AsynchronousMapTask, ExecuteRemoteTask.

  • celery.task.builtins

    Built-in tasks: PingTask, DeleteExpiredTaskMetaTask.

0.3.7

• IMPORTANT Now uses AMQP`s basic.consume instead of basic.get. This means we’re no longer polling the broker for new messages.

• IMPORTANT Default concurrency limit is now set to the number of CPUs available on the system.

• IMPORTANT tasks.register: Renamed task_name argument to name, so

  >>> tasks.register(func, task_name="mytask")

  has to be replaced with:

  >>> tasks.register(func, name="mytask")

• The daemon now correctly runs if the pidlock is stale.

• Now compatible with carrot 0.4.5

• Default AMQP connection timeout is now 4 seconds.

• AsyncResult.read() was always returning True.

• Only use README as long_description if the file exists so easy_install doesn’t break.

• celery.view: JSON responses now properly set its mime-type.

• apply_async now has a connection keyword argument so you can re-use the same AMQP connection if you want to execute more than one task.

• Handle failures in task_status view such that it won’t throw 500s.

• Fixed typo AMQP_SERVER in documentation to AMQP_HOST.

• Worker exception emails sent to administrators now works properly.

• No longer depends on django, so installing celery won’t affect the preferred Django version installed.

• Now works with PostgreSQL (psycopg2) again by registering the PickledObject field.

• Worker: Added –detach option as an alias to –daemon, and it’s the term used in the documentation from now on.

• Make sure the pool and periodic task worker thread is terminated properly at exit. (So Ctrl-C works again).

• Now depends on python-daemon.

• Removed dependency to simplejson

• Cache Backend: Re-establishes connection for every task process if the Django cache backend is memcached/libmemcached.

• Tyrant Backend: Now re-establishes the connection for every task executed.

0.3.3

• The PeriodicWorkController now sleeps for 1 second between checking for periodic tasks to execute.

0.3.2

• worker: Added option –discard: Discard (delete!) all waiting messages in the queue.
• Worker: The –wakeup-after option was not handled as a float.

0.3.1

• The PeriodicTask worker is now running in its own thread instead of blocking the TaskController loop.
• Default QUEUE_WAKEUP_AFTER has been lowered to 0.1 (was 0.3)

0.3.0

警告

This is a development version, for the stable release, please see versions 0.2.x.

VERY IMPORTANT: Pickle is now the encoder used for serializing task arguments, so be sure to flush your task queue before you upgrade.

• IMPORTANT TaskSet.run() now returns a celery.result.TaskSetResult instance, which lets you inspect the status and return values of a taskset as it was a single entity.

• IMPORTANT Celery now depends on carrot >= 0.4.1.

• The celery daemon now sends task errors to the registered admin emails. To turn off this feature, set SEND_CELERY_TASK_ERROR_EMAILS to False in your settings.py. Thanks to Grégoire Cachet.

• You can now run the celery daemon by using manage.py:

  $ python manage.py celeryd

  Thanks to Grégoire Cachet.

• Added support for message priorities, topic exchanges, custom routing keys for tasks. This means we have introduced celery.task.apply_async, a new way of executing tasks.

  You can use celery.task.delay and celery.Task.delay like usual, but if you want greater control over the message sent, you want celery.task.apply_async and celery.Task.apply_async.

  This also means the AMQP configuration has changed. Some settings has been renamed, while others are new:

  CELERY_AMQP_EXCHANGE
  CELERY_AMQP_PUBLISHER_ROUTING_KEY
  CELERY_AMQP_CONSUMER_ROUTING_KEY
  CELERY_AMQP_CONSUMER_QUEUE
  CELERY_AMQP_EXCHANGE_TYPE

  See the entry Can I send some tasks to only some servers? in the FAQ for more information.

• Task errors are now logged using log level ERROR instead of INFO, and stacktraces are dumped. Thanks to Grégoire Cachet.

• Make every new worker process re-establish it’s Django DB connection, this solving the “MySQL connection died?” exceptions. Thanks to Vitaly Babiy and Jirka Vejrazka.

• IMPORTANT Now using pickle to encode task arguments. This means you now can pass complex python objects to tasks as arguments.

• Removed dependency to yadayada.

• Added a FAQ, see docs/faq.rst.

• Now converts any Unicode keys in task kwargs to regular strings. Thanks Vitaly Babiy.

• Renamed the TaskDaemon to WorkController.

• celery.datastructures.TaskProcessQueue is now renamed to celery.pool.TaskPool.

• The pool algorithm has been refactored for greater performance and stability.

0.2.0

• Final release of 0.2.0
• Compatible with carrot version 0.4.0.
• Fixes some syntax errors related to fetching results from the database backend.

0.2.0-pre3

• Internal release. Improved handling of unpickleable exceptions, get_result now tries to recreate something looking like the original exception.

0.2.0-pre2

• Now handles unpickleable exceptions (like the dynamically generated subclasses of django.core.exception.MultipleObjectsReturned).

0.2.0-pre1

• It’s getting quite stable, with a lot of new features, so bump version to 0.2. This is a pre-release.
• celery.task.mark_as_read() and celery.task.mark_as_failure() has been removed. Use celery.backends.default_backend.mark_as_read(), and celery.backends.default_backend.mark_as_failure() instead.

0.1.15

• The celery daemon was leaking AMQP connections, this should be fixed, if you have any problems with too many files open (like emfile errors in rabbit.log, please contact us!

0.1.14

• Fixed a syntax error in the TaskSet class. (No such variable TimeOutError).

0.1.13

• Forgot to add yadayada to install requirements.

• Now deletes all expired task results, not just those marked as done.

• Able to load the Tokyo Tyrant backend class without django configuration, can specify tyrant settings directly in the class constructor.

• Improved API documentation

• Now using the Sphinx documentation system, you can build the html documentation by doing:

  $ cd docs
  $ make html

  and the result will be in docs/.build/html.

0.1.12

• delay_task() etc. now returns celery.task.AsyncResult object, which lets you check the result and any failure that might have happened. It kind of works like the multiprocessing.AsyncResult class returned by multiprocessing.Pool.map_async.

• Added dmap() and dmap_async(). This works like the multiprocessing.Pool versions except they are tasks distributed to the celery server. Example:

  >>> from celery.task import dmap
  >>> import operator
  >>> dmap(operator.add, [[2, 2], [4, 4], [8, 8]])
  >>> [4, 8, 16]

  >>> from celery.task import dmap_async
  >>> import operator
  >>> result = dmap_async(operator.add, [[2, 2], [4, 4], [8, 8]])
  >>> result.ready()
  False
  >>> time.sleep(1)
  >>> result.ready()
  True
  >>> result.result
  [4, 8, 16]

• Refactored the task metadata cache and database backends, and added a new backend for Tokyo Tyrant. You can set the backend in your django settings file. E.g.:

  CELERY_RESULT_BACKEND = "database"; # Uses the database
  CELERY_RESULT_BACKEND = "cache"; # Uses the django cache framework
  CELERY_RESULT_BACKEND = "tyrant"; # Uses Tokyo Tyrant
  TT_HOST = "localhost"; # Hostname for the Tokyo Tyrant server.
  TT_PORT = 6657; # Port of the Tokyo Tyrant server.

0.1.11

• The logging system was leaking file descriptors, resulting in servers stopping with the EMFILES (too many open files) error. (fixed)

0.1.10

• Tasks now supports both positional arguments and keyword arguments.
• Requires carrot 0.3.8.
• The daemon now tries to reconnect if the connection is lost.

0.1.8

• Better test coverage
• More documentation
• The worker doesn’t emit Queue is empty message if settings.CELERYD_EMPTY_MSG_EMIT_EVERY is 0.

0.1.7

• Added some unit tests
• Can now use the database for task metadata (like if the task has been executed or not). Set settings.CELERY_TASK_META
• Can now run python setup.py test to run the unit tests from within the tests project.
• Can set the AMQP exchange/routing key/queue using settings.CELERY_AMQP_EXCHANGE, settings.CELERY_AMQP_ROUTING_KEY, and settings.CELERY_AMQP_CONSUMER_QUEUE.

0.1.6

• Introducing TaskSet. A set of subtasks is executed and you can find out how many, or if all them, are done (excellent for progress bars and such)

• Now catches all exceptions when running Task.__call__, so the daemon doesn’t die. This doesn’t happen for pure functions yet, only Task classes.

• autodiscover() now works with zipped eggs.

• Worker: Now adds current working directory to sys.path for convenience.

• The run_every attribute of PeriodicTask classes can now be a datetime.timedelta() object.

• Worker: You can now set the DJANGO_PROJECT_DIR variable for the worker and it will add that to sys.path for easy launching.

• Can now check if a task has been executed or not via HTTP.

• You can do this by including the celery urls.py into your project,

  >>> url(r'^celery/$', include("celery.urls"))

  then visiting the following url,:

  http://mysite/celery/$task_id/done/

  this will return a JSON dictionary like e.g:

  >>> {"task": {"id": $task_id, "executed": true}}

• delay_task now returns string id, not uuid.UUID instance.

• Now has PeriodicTasks, to have cron like functionality.

• Project changed name from crunchy to celery. The details of the name change request is in docs/name_change_request.txt.

0.1.0

• Initial release