Instead of just recording them it can also be quite useful (especially for debugging) to print the start and stop timings as they occur. Also adds an example that shows how this can be used and an explanation of why it is useful to have this type of capability. Part of blueprint more-examples Change-Id: Id2dc3f8dc9ac94e511470e39f499f325b33537ee
170 lines
5.3 KiB
ReStructuredText
170 lines
5.3 KiB
ReStructuredText
===========================
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Notifications and Listeners
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===========================
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.. testsetup::
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from taskflow import task
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from taskflow.patterns import linear_flow
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from taskflow import engines
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--------
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Overview
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--------
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Engines provide a way to receive notification on task and flow state
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transitions, which is useful for monitoring, logging, metrics, debugging
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and plenty of other tasks.
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To receive these notifications you should register a callback with
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an instance of the the :py:class:`notifier <taskflow.utils.misc.Notifier>`
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class that is attached
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to :py:class:`engine <taskflow.engines.base.EngineBase>`
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attributes ``task_notifier`` and ``notifier``.
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TaskFlow also comes with a set of predefined :ref:`listeners <listeners>`, and
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provides means to write your own listeners, which can be more convenient than
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using raw callbacks.
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--------------------------------------
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Receiving notifications with callbacks
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--------------------------------------
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To manage notifications instances of
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:py:class:`~taskflow.utils.misc.Notifier` are used.
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.. autoclass:: taskflow.utils.misc.Notifier
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Flow notifications
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------------------
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To receive notification on flow state changes use
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:py:class:`~taskflow.utils.misc.Notifier` available as
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``notifier`` property of the engine. A basic example is:
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.. doctest::
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>>> class CatTalk(task.Task):
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... def execute(self, meow):
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... print(meow)
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... return "cat"
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...
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>>> class DogTalk(task.Task):
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... def execute(self, woof):
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... print(woof)
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... return 'dog'
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...
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>>> def flow_transition(state, details):
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... print("Flow '%s' transition to state %s" % (details['flow_name'], state))
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...
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>>>
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>>> flo = linear_flow.Flow("cat-dog").add(
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... CatTalk(), DogTalk(provides="dog"))
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>>> eng = engines.load(flo, store={'meow': 'meow', 'woof': 'woof'})
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>>> eng.notifier.register("*", flow_transition)
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>>> eng.run()
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Flow 'cat-dog' transition to state RUNNING
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meow
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woof
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Flow 'cat-dog' transition to state SUCCESS
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Task notifications
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------------------
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To receive notification on task state changes use
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:py:class:`~taskflow.utils.misc.Notifier` available as
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``task_notifier`` property of the engine. A basic example is:
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.. doctest::
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>>> class CatTalk(task.Task):
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... def execute(self, meow):
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... print(meow)
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... return "cat"
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...
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>>> class DogTalk(task.Task):
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... def execute(self, woof):
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... print(woof)
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... return 'dog'
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...
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>>> def task_transition(state, details):
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... print("Task '%s' transition to state %s" % (details['task_name'], state))
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...
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>>>
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>>> flo = linear_flow.Flow("cat-dog")
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>>> flo.add(CatTalk(), DogTalk(provides="dog"))
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<taskflow.patterns.linear_flow.Flow object at 0x...>
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>>> eng = engines.load(flo, store={'meow': 'meow', 'woof': 'woof'})
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>>> eng.task_notifier.register("*", task_transition)
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>>> eng.run()
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Task 'CatTalk' transition to state RUNNING
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meow
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Task 'CatTalk' transition to state SUCCESS
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Task 'DogTalk' transition to state RUNNING
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woof
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Task 'DogTalk' transition to state SUCCESS
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.. _listeners:
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---------
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Listeners
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---------
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TaskFlow comes with a set of predefined listeners -- helper classes that can be
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used to do various actions on flow and/or tasks transitions. You can also
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create your own listeners easily, which may be more convenient than using raw
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callbacks for some use cases.
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For example, this is how you can use
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:py:class:`~taskflow.listeners.printing.PrintingListener`:
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.. doctest::
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>>> from taskflow.listeners import printing
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>>> class CatTalk(task.Task):
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... def execute(self, meow):
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... print(meow)
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... return "cat"
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...
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>>> class DogTalk(task.Task):
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... def execute(self, woof):
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... print(woof)
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... return 'dog'
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...
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>>>
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>>> flo = linear_flow.Flow("cat-dog").add(
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... CatTalk(), DogTalk(provides="dog"))
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>>> eng = engines.load(flo, store={'meow': 'meow', 'woof': 'woof'})
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>>> with printing.PrintingListener(eng):
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... eng.run()
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...
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taskflow.engines.action_engine.engine.SingleThreadedActionEngine: ... has moved flow 'cat-dog' (...) into state 'RUNNING'
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taskflow.engines.action_engine.engine.SingleThreadedActionEngine: ... has moved task 'CatTalk' (...) into state 'RUNNING'
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meow
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taskflow.engines.action_engine.engine.SingleThreadedActionEngine: ... has moved task 'CatTalk' (...) into state 'SUCCESS' with result 'cat' (failure=False)
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taskflow.engines.action_engine.engine.SingleThreadedActionEngine: ... has moved task 'DogTalk' (...) into state 'RUNNING'
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woof
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taskflow.engines.action_engine.engine.SingleThreadedActionEngine: ... has moved task 'DogTalk' (...) into state 'SUCCESS' with result 'dog' (failure=False)
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taskflow.engines.action_engine.engine.SingleThreadedActionEngine: ... has moved flow 'cat-dog' (...) into state 'SUCCESS'
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Basic listener
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--------------
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.. autoclass:: taskflow.listeners.base.ListenerBase
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Printing and logging listeners
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------------------------------
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.. autoclass:: taskflow.listeners.base.LoggingBase
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.. autoclass:: taskflow.listeners.logging.LoggingListener
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.. autoclass:: taskflow.listeners.printing.PrintingListener
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Timing listener
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---------------
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.. autoclass:: taskflow.listeners.timing.TimingListener
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.. autoclass:: taskflow.listeners.timing.PrintingTimingListener
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