4e514f41e5
The reflection module is now part of oslo.utils so we should remove our local version and use that version instead; this also goes for the uuidutils module which is now part of oslo.utils as well so we no longer need our local version copied from the incubator... Note that one reflection method `find_subclasses` which was to specific to taskflow is now moved to the misc utility module instead of its prior home in the reflection module. Change-Id: I069881c80b0b2916cc0c414992b80171f7eeb79f
113 lines
4.2 KiB
Python
113 lines
4.2 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 contextlib
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import logging
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import os
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import random
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import sys
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import time
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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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from oslo.utils import reflection
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from taskflow import engines
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from taskflow.listeners import printing
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from taskflow.patterns import unordered_flow as uf
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from taskflow import task
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# INTRO: This examples shows how unordered_flow can be used to create a large
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# number of fake volumes in parallel (or serially, depending on a constant that
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# can be easily changed).
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@contextlib.contextmanager
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def show_time(name):
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start = time.time()
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yield
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end = time.time()
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print(" -- %s took %0.3f seconds" % (name, end - start))
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# This affects how many volumes to create and how much time to *simulate*
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# passing for that volume to be created.
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MAX_CREATE_TIME = 3
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VOLUME_COUNT = 5
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# This will be used to determine if all the volumes are created in parallel
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# or whether the volumes are created serially (in an undefined ordered since
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# a unordered flow is used). Note that there is a disconnection between the
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# ordering and the concept of parallelism (since unordered items can still be
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# ran in a serial ordering). A typical use-case for offering both is to allow
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# for debugging using a serial approach, while when running at a larger scale
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# one would likely want to use the parallel approach.
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#
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# If you switch this flag from serial to parallel you can see the overall
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# time difference that this causes.
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SERIAL = False
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if SERIAL:
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engine = 'serial'
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else:
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engine = 'parallel'
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class VolumeCreator(task.Task):
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def __init__(self, volume_id):
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# Note here that the volume name is composed of the name of the class
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# along with the volume id that is being created, since a name of a
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# task uniquely identifies that task in storage it is important that
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# the name be relevant and identifiable if the task is recreated for
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# subsequent resumption (if applicable).
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#
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# UUIDs are *not* used as they can not be tied back to a previous tasks
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# state on resumption (since they are unique and will vary for each
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# task that is created). A name based off the volume id that is to be
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# created is more easily tied back to the original task so that the
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# volume create can be resumed/revert, and is much easier to use for
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# audit and tracking purposes.
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base_name = reflection.get_callable_name(self)
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super(VolumeCreator, self).__init__(name="%s-%s" % (base_name,
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volume_id))
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self._volume_id = volume_id
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def execute(self):
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print("Making volume %s" % (self._volume_id))
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time.sleep(random.random() * MAX_CREATE_TIME)
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print("Finished making volume %s" % (self._volume_id))
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# Assume there is no ordering dependency between volumes.
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flow = uf.Flow("volume-maker")
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for i in range(0, VOLUME_COUNT):
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flow.add(VolumeCreator(volume_id="vol-%s" % (i)))
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# Show how much time the overall engine loading and running takes.
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with show_time(name=flow.name.title()):
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eng = engines.load(flow, engine=engine)
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# This context manager automatically adds (and automatically removes) a
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# helpful set of state transition notification printing helper utilities
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# that show you exactly what transitions the engine is going through
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# while running the various volume create tasks.
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with printing.PrintingListener(eng):
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eng.run()
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