9a239a0a2e
This commit makes a set of small adjustments to examples. - Rework some of the comments to be more clear. - Add links to the original source tree file. - Rename some of the examples to make it clear the concept the example is intented to show. - Move some common example functionality to the example utility file. Change-Id: I858e0dbf72fe8cb40a05bfdbb0857720ffb71c7f
187 lines
6.3 KiB
Python
187 lines
6.3 KiB
Python
# -*- coding: utf-8 -*-
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# Copyright (C) 2012-2013 Yahoo! Inc. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License"); you may
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# not use this file except in compliance with the License. You may obtain
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# a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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# License for the specific language governing permissions and limitations
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# under the License.
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import logging
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import os
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import sys
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logging.basicConfig(level=logging.ERROR)
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top_dir = os.path.abspath(os.path.join(os.path.dirname(__file__),
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os.pardir,
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os.pardir))
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sys.path.insert(0, top_dir)
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import taskflow.engines
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from taskflow.patterns import graph_flow as gf
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from taskflow.patterns import linear_flow as lf
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from taskflow import task
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import example_utils as eu # noqa
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# INTRO: This examples shows how a graph flow and linear flow can be used
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# together to execute dependent & non-dependent tasks by going through the
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# steps required to build a simplistic car (an assembly line if you will). It
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# also shows how raw functions can be wrapped into a task object instead of
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# being forced to use the more *heavy* task base class. This is useful in
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# scenarios where pre-existing code has functions that you easily want to
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# plug-in to taskflow, without requiring a large amount of code changes.
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def build_frame():
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return 'steel'
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def build_engine():
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return 'honda'
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def build_doors():
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return '2'
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def build_wheels():
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return '4'
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# These just return true to indiciate success, they would in the real work
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# do more than just that.
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def install_engine(frame, engine):
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return True
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def install_doors(frame, windows_installed, doors):
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return True
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def install_windows(frame, doors):
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return True
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def install_wheels(frame, engine, engine_installed, wheels):
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return True
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def trash(**kwargs):
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eu.print_wrapped("Throwing away pieces of car!")
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def startup(**kwargs):
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# If you want to see the rollback function being activated try uncommenting
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# the following line.
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#
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# raise ValueError("Car not verified")
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return True
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def verify(spec, **kwargs):
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# If the car is not what we ordered throw away the car (trigger reversion).
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for key, value in kwargs.items():
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if spec[key] != value:
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raise Exception("Car doesn't match spec!")
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return True
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# These two functions connect into the state transition notification emission
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# points that the engine outputs, they can be used to log state transitions
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# that are occurring, or they can be used to suspend the engine (or perform
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# other useful activities).
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def flow_watch(state, details):
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print('Flow => %s' % state)
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def task_watch(state, details):
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print('Task %s => %s' % (details.get('task_name'), state))
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flow = lf.Flow("make-auto").add(
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task.FunctorTask(startup, revert=trash, provides='ran'),
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# A graph flow allows automatic dependency based ordering, the ordering
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# is determined by analyzing the symbols required and provided and ordering
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# execution based on a functioning order (if one exists).
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gf.Flow("install-parts").add(
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task.FunctorTask(build_frame, provides='frame'),
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task.FunctorTask(build_engine, provides='engine'),
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task.FunctorTask(build_doors, provides='doors'),
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task.FunctorTask(build_wheels, provides='wheels'),
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# These *_installed outputs allow for other tasks to depend on certain
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# actions being performed (aka the components were installed), another
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# way to do this is to link() the tasks manually instead of creating
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# an 'artificial' data dependency that accomplishes the same goal the
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# manual linking would result in.
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task.FunctorTask(install_engine, provides='engine_installed'),
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task.FunctorTask(install_doors, provides='doors_installed'),
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task.FunctorTask(install_windows, provides='windows_installed'),
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task.FunctorTask(install_wheels, provides='wheels_installed')),
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task.FunctorTask(verify, requires=['frame',
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'engine',
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'doors',
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'wheels',
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'engine_installed',
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'doors_installed',
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'windows_installed',
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'wheels_installed']))
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# This dictionary will be provided to the tasks as a specification for what
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# the tasks should produce, in this example this specification will influence
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# what those tasks do and what output they create. Different tasks depend on
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# different information from this specification, all of which will be provided
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# automatically by the engine to those tasks.
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spec = {
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"frame": 'steel',
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"engine": 'honda',
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"doors": '2',
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"wheels": '4',
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# These are used to compare the result product, a car without the pieces
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# installed is not a car after all.
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"engine_installed": True,
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"doors_installed": True,
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"windows_installed": True,
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"wheels_installed": True,
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}
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engine = taskflow.engines.load(flow, store={'spec': spec.copy()})
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# This registers all (*) state transitions to trigger a call to the flow_watch
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# function for flow state transitions, and registers the same all (*) state
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# transitions for task state transitions.
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engine.notifier.register('*', flow_watch)
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engine.task_notifier.register('*', task_watch)
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eu.print_wrapped("Building a car")
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engine.run()
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# Alter the specification and ensure that the reverting logic gets triggered
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# since the resultant car that will be built by the build_wheels function will
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# build a car with 4 doors only (not 5), this will cause the verification
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# task to mark the car that is produced as not matching the desired spec.
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spec['doors'] = 5
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engine = taskflow.engines.load(flow, store={'spec': spec.copy()})
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engine.notifier.register('*', flow_watch)
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engine.task_notifier.register('*', task_watch)
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eu.print_wrapped("Building a wrong car that doesn't match specification")
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try:
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engine.run()
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except Exception as e:
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eu.print_wrapped("Flow failed: %s" % e)
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