23dfff4105
In order to move away from the existing flows having their own implementation of running, start moving the existing flows to be patterns that only structure tasks (and impose constraints about how the group of tasks can run) in useful ways. Let the concept of running those patterns be handled by an engine instead of being handled by the flow itself. This will allow for varying engines to be able to run flows in whichever way the engine chooses (as long as the constraints set up by the flow are observed). Currently threaded flow and graph flow are broken by this commit, since they have not been converted to being a structure of tasks + constraints. The existing engine has not yet been modified to run those structures either, work is underway to remediate this. Part of: blueprint patterns-and-engines Followup bugs that must be addressed: Bug: 1221448 Bug: 1221505 Change-Id: I3a8b96179f336d1defe269728ebae0caa3d832d7
59 lines
1.7 KiB
Python
59 lines
1.7 KiB
Python
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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my_dir_path = os.path.dirname(os.path.abspath(__file__))
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sys.path.insert(0, os.path.join(os.path.join(my_dir_path, os.pardir),
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os.pardir))
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from taskflow.engines.action_engine import engine as eng
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from taskflow.patterns import linear_flow as lf
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from taskflow.patterns import unordered_flow as uf
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from taskflow import task
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# This examples shows how LinearFlow and ParallelFlow can be used
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# together to execute calculations in parallel and then use the
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# result for the next task. Adder task is used for all calculations
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# and arguments' bindings are used to set correct parameters to the task.
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class Provider(task.Task):
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def __init__(self, name, *args, **kwargs):
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super(Provider, self).__init__(name=name, **kwargs)
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self._provide = args
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def execute(self):
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return self._provide
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class Adder(task.Task):
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def __init__(self, name, provides, rebind):
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super(Adder, self).__init__(name=name, provides=provides,
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rebind=rebind)
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def execute(self, x, y):
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return x + y
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flow = lf.Flow('root').add(
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# x1 = 2, y1 = 3, x2 = 5, x3 = 8
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Provider("provide-adder", 2, 3, 5, 8,
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provides=('x1', 'y1', 'x2', 'y2')),
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uf.Flow('adders').add(
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# z1 = x1+y1 = 5
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Adder(name="add", provides='z1', rebind=['x1', 'y1']),
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# z2 = x2+y2 = 13
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Adder(name="add-2", provides='z2', rebind=['x2', 'y2']),
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),
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# r = z1+z2 = 18
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Adder(name="sum-1", provides='r', rebind=['z1', 'z2']))
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engine = eng.MultiThreadedActionEngine(flow)
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engine.run()
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print engine.storage.fetch_all()
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