steps with Celery Resources User Guide Overview Tasks Executing Tasks Workers Guide Periodic Tasks Sets of tasks, Subtasks and Callbacks HTTP Callback Tasks (Webhooks) Routing Tasks Monitoring Guide Optimizing Task Decorators - celery.decorators Defining Tasks - celery.task.base Task Sets, Subtasks and Callbacks - celery.task.sets Executing Tasks - celery.execute Task Result - celery.result Task Information celeryctl - celery.bin.celeryctl caqmadm: AMQP API Command-line Shell - celery.bin.camqadm Celeryd Multi Tool - celery.bin.celeryd_multi Internals Celery Deprecation Timeline Internals: The worker Task Message

First steps with Celery Periodic Tasks Resources User Guide Tasks Executing Tasks Workers Guide Sets of tasks, Subtasks and Callbacks HTTP Callback Tasks (Webhooks) Routing Tasks Configuration and defaults Task Decorators - celery.decorators Defining Tasks - celery.task.base Task Sets, Subtasks and Callbacks - celery.task.sets Executing Tasks - celery.execute Task Result - celery.result Task Information Viewer - celery.bin.celeryev caqmadm: AMQP API Command-line Shell - celery.bin.camqadm Celeryd Multi Tool - celery.bin.celeryd_multi Internals Celery Deprecation Timeline Internals: The worker Task Message

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 2.6 Sets of tasks, Subtasks and Callbacks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114 9.3 Task Sets, Subtasks and Callbacks - celery.task.sets . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 9.4 Executing Tasks Command-line Shell - celery.bin.camqadm . . . . . . . . . . . . . . . . . . 164 9.31 Celeryd Multi Tool - celery.bin.celeryd_multi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166 10 Internals

retried if they fail, with configurable maximum number of retries, and delays between each retry. Task Sets A Task set is a task consisting of several sub-tasks. You can find out how many, or if all of the subclass of dict used to wrap the arguments and execution options for a single task invocation. See Sets of tasks, Subtasks and Callbacks for more information about subtasks. 2.1.9 Performance and Strategies NOTE The mandatory and immediate flags are not supported by amqplib at this point. • mandatory This sets the delivery to be mandatory. An exception will be raised if there are no running workers able to

STARTED state at some point). There are also sets of states, like the set of FAILURE_STATES, and the set of READY_STATES. The client uses the membership of these sets to decide whether the exception should Celery Documentation, Release 3.1.25 This task has a signature of arity 2 (two arguments): (2, 2), and sets the countdown execution option to 10. • or you can create one using the task’s subtask method: >>> task in the chain: >>> res = chain(add.s(4, 4), mul.s(8), mul.s(10))() >>> res.get() 640 It also sets parent attributes so that you can work your way up the chain to get intermediate results: >>> res

STARTED state at some point). There are also sets of states, like the set of FAILURE_STATES, and the set of READY_STATES. The client uses the membership of these sets to decide whether the exception should countdown=10) tasks.add(2, 2) This task has a signature of arity 2 (two arguments): (2, 2), and sets the countdown execution option to 10. or you can create one using the task’s subtask method: >>> task in the chain: >>> res = chain(add.s(4, 4), mul.s(8), mul.s(10))() >>> res.get() 640 It also sets parent attributes so that you can work your way up the chain to get intermediate results: >>> res

STARTED state at some point). There are also sets of states, like the set of FAILURE_STATES, and the set of READY_STATES. The client uses the membership of these sets to decide whether the exception should countdown=10) tasks.add(2, 2) This task has a signature of arity 2 (two arguments): (2, 2), and sets the countdown execution option to 10. or you can create one using the task’s signature method: >>> task in the chain: >>> res = chain(add.s(4, 4), mul.s(8), mul.s(10))() >>> res.get() 640 It also sets parent attributes so that you can work your way up the chain to get intermediate results: >>> res

STARTED state at some point). There are also sets of states, like the set of FAILURE_STATES, and the set of READY_STATES. The client uses the membership of these sets to decide whether the exception should countdown=10) tasks.add(2, 2) This task has a signature of arity 2 (two arguments): (2, 2), and sets the countdown execution option to 10. or you can create one using the task’s signature method: >>> task in the chain: >>> res = chain(add.s(4, 4), mul.s(8), mul.s(10))() >>> res.get() 640 It also sets parent attributes so that you can work your way up the chain to get intermediate results: >>> res

STARTED state at some point). There are also sets of states, like the set of FAILURE_STATES, and the set of READY_STATES. The client uses the membership of these sets to decide whether the exception should countdown=10) tasks.add(2, 2) This task has a signature of arity 2 (two arguments): (2, 2), and sets the countdown execution option to 10. or you can create one using the task’s signature method: >>> task in the chain: >>> res = chain(add.s(4, 4), mul.s(8), mul.s(10))() >>> res.get() 640 It also sets parent attributes so that you can work your way up the chain to get intermediate results: >>> res

STARTED state at some point). There are also sets of states, like the set of FAILURE_STATES, and the set of READY_STATES. The client uses the membership of these sets to decide whether the exception should countdown=10) tasks.add(2, 2) This task has a signature of arity 2 (two arguments): (2, 2), and sets the countdown execution option to 10. or you can create one using the task’s signature method: >>> task in the chain: >>> res = chain(add.s(4, 4), mul.s(8), mul.s(10))() >>> res.get() 640 It also sets parent attributes so that you can work your way up the chain to get intermediate results: >>> res