cde0dee14e
Previously to run a flow client code had to put together the flow,
an engine, logbook, flowdetail, and storage backend. This commit
adds two helper functions, run() and load(), so that simplest usecase
now looks like
taskflow.engines.run(flow)
Client code may also provide configuration for storage and engine if
needed, but if not needed it just works with defaults.
Engines are loaded via stevedore, as drivers in 'taskflow.engines'
backend. Now three entry points are defined in that namespace:
- 'default', for SingleThreadedActionEngine, used by default;
- 'serial', as another synonym for SingleThreadedActionEngine;
- 'parallel', for MultiThreadedActionEngine.
Closes-bug: #1224726
Change-Id: I7f4cb5c8ff7f5f12831ddd0952c202d2fd8cd6ef
67 lines
1.7 KiB
Python
67 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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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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# In this example there are complex dependencies between
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# tasks. User shouldn't care about ordering the Tasks.
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# GraphFlow resolves dependencies automatically using tasks'
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# requirements and provided values.
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# Flows of any types can be nested into Graph flow. Subflows
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# dependencies will be resolved too.
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class Adder(task.Task):
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def execute(self, x, y):
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return x + y
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flow = gf.Flow('root').add(
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lf.Flow('nested_linear').add(
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# x2 = y3+y4 = 12
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Adder("add2", provides='x2', rebind=['y3', 'y4']),
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# x1 = y1+y2 = 4
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Adder("add1", provides='x1', rebind=['y1', 'y2'])
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),
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# x5 = x1+x3 = 20
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Adder("add5", provides='x5', rebind=['x1', 'x3']),
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# x3 = x1+x2 = 16
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Adder("add3", provides='x3', rebind=['x1', 'x2']),
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# x4 = x2+y5 = 21
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Adder("add4", provides='x4', rebind=['x2', 'y5']),
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# x6 = x5+x4 = 41
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Adder("add6", provides='x6', rebind=['x5', 'x4']),
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# x7 = x6+x6 = 82
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Adder("add7", provides='x7', rebind=['x6', 'x6']))
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store = {
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"y1": 1,
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"y2": 3,
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"y3": 5,
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"y4": 7,
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"y5": 9,
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}
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result = taskflow.engines.run(
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flow, engine_conf='serial', store=store)
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print("Single threaded engine result %s" % result)
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result = taskflow.engines.run(
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flow, engine_conf='parallel', store=store)
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print("Multi threaded engine result %s" % result)
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