Documentation, Release 2.3.5 2.2.1 Basics A task is a class that encapsulates a function and its execution options. Given a function create_user‘, that takes two arguments: username and password, you can create registered, but any task inheriting from it will be. When tasks are sent, we don’t send any actual function code, just the name of the task to execute. When the worker then receives the message it can look and the shortcut: delay(). delay is simple and convenient, as it looks like calling a regular function: Task.delay(arg1, arg2, kwarg1="x", kwarg2="y") The same using apply_async is written like this:

another function, for which Celery uses something called signatures. A signature wraps the arguments and execution options of a single task invocation in such a way that it can be passed to functions or even host names work on the internet: every worker maintains a mapping of task names to their actual functions, called the task registry. Whenever you define a task, that task will also be added to the local add> and there you see that __main__ again; whenever Celery isn’t able to detect what module the function belongs to, it uses the main module name to generate the beginning of the task name. This is only

another function, for which Celery uses something called signatures. A signature wraps the arguments and execution options of a single task invocation in such a way that it can be passed to functions or even host names work on the internet: every worker maintains a mapping of task names to their actual functions, called the task registry. Whenever you define a task, that task will also be added to the local add> and there you see that __main__ again; whenever Celery isn’t able to detect what module the function belongs to, it uses the main module name to generate the beginning of the task name. This is only

another function, for which Celery uses something called signatures. A signature wraps the arguments and execution options of a single task invocation in such a way that it can be passed to functions or even host names work on the internet: every worker maintains a mapping of task names to their actual functions, called the task registry. Whenever you define a task, that task will also be added to the local add> and there you see that __main__ again; whenever Celery isn’t able to detect what module the function belongs to, it uses the main module name to generate the beginning of the task name. This is only

another function, for which Celery uses something called signatures. A signature wraps the arguments and execution options of a single task invocation in such a way that it can be passed to functions or even host names work on the internet: every worker maintains a mapping of task names to their actual functions, called the task registry. Whenever you define a task, that task will also be added to the local add> and there you see that __main__ again; whenever Celery isn’t able to detect what module the function belongs to, it uses the main module name to generate the beginning of the task name. This is only

please see the API reference. Basics A task is a class that encapsulates a function and its execution options. Given a function create_user`, that takes two arguments: username and password, you can create executed. Can be either int [http://docs.python.org/dev/library/functions.html#int] or float [http://docs.python.org/dev/library/functions.html#float]. Default is a 3 minute delay. Task.rate_limit Set registered, but any task inheriting from it will be. When tasks are sent, we don’t send any actual function code, just the name of the task to execute. When the worker then receives the message it can look

see the API reference. 2.2.1 Basics A task is a class that encapsulates a function and its execution options. Given a function create_user‘, that takes two arguments: username and password, you can create registered, but any task inheriting from it will be. When tasks are sent, we don’t send any actual function code, just the name of the task to execute. When the worker then receives the message it can look and the shortcut: delay(). delay is simple and convenient, as it looks like calling a regular function: 2.3. Executing Tasks 37 Celery Documentation, Release 2.5.5 Task.delay(arg1, arg2, kwarg1="x"

please see the API reference. Basics A task is a class that encapsulates a function and its execution options. Given a function create_user`, that takes two arguments: username and password, you can create registered, but any task inheriting from it will be. When tasks are sent, we don’t send any actual function code, just the name of the task to execute. When the worker then receives the message it can look and the shortcut: delay(). delay is simple and convenient, as it looks like calling a regular function: Task.delay(arg1, arg2, kwarg1="x", kwarg2="y") The same using apply_async is written like this:

please see the API reference. Basics A task is a class that encapsulates a function and its execution options. Given a function create_user`, that takes two arguments: username and password, you can create registered, but any task inheriting from it will be. When tasks are sent, we don’t send any actual function code, just the name of the task to execute. When the worker then receives the message it can look and the shortcut: delay(). delay is simple and convenient, as it looks like calling a regular function: Task.delay(arg1, arg2, kwarg1="x", kwarg2="y") The same using apply_async is written like this:

see the API reference. 2.2.1 Basics A task is a class that encapsulates a function and its execution options. Given a function create_user‘, that takes two arguments: username and password, you can create registered, but any task inheriting from it will be. When tasks are sent, we don’t send any actual function code, just the name of the task to execute. When the worker then receives the message it can look and the shortcut: delay(). delay is simple and convenient, as it looks like calling a regular function: Task.delay(arg1, arg2, kwarg1="x", kwarg2="y") The same using apply_async is written like this: