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deb-python-taskflow/doc/source/notifications.rst
Joshua Harlow 1de8bbd838 Add a claims listener that connects job claims to engines
To make it easily possible to stop running a engine that was
created from a job, add a claims listener that will be called
on state changes that an engine progresses through. During those
state changes the jobboard will be queried to determine if the
job is still claimed by the respective owner; if not the engine
will be suspended and further work will stop.

Change-Id: I8bbc6a3e03746ba0a7c74139cf9e230631d80d8f
2014-12-01 21:39:23 -08:00

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5.3 KiB
ReStructuredText

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