32e8c3da61
* Implemented Worker to be started on remote host for handling tasks request. * Implemented WorkerTaskExecutor that proxies tasks requests to remote workers. * Implemented Proxy that is used for consuming and publishing messages by Worker and Executor. * Added worker-based engine and worker task executor. * Added kombu dependency to requirements. * Added worker-based flow example. * Added unit-tests for worker-based flow components. Implements: blueprint worker-based-engine Change-Id: I8c6859ba4a1a56c2592e3d67cdfb8968b13ee99c
69 lines
2.0 KiB
Python
69 lines
2.0 KiB
Python
# -*- coding: utf-8 -*-
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# vim: tabstop=4 shiftwidth=4 softtabstop=4
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# Copyright (C) 2014 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 json
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import logging
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import sys
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import taskflow.engines
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from taskflow.patterns import linear_flow as lf
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from taskflow.tests import utils
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LOG = logging.getLogger(__name__)
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if __name__ == "__main__":
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logging.basicConfig(level=logging.ERROR)
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engine_conf = {
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'engine': 'worker-based',
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'exchange': 'taskflow',
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'workers_info': {
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'topic': [
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'taskflow.tests.utils.TaskOneArgOneReturn',
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'taskflow.tests.utils.TaskMultiArgOneReturn'
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]
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}
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}
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# parse command line
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try:
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arg = sys.argv[1]
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except IndexError:
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pass
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else:
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try:
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cfg = json.loads(arg)
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except ValueError:
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engine_conf.update(url=arg)
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else:
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engine_conf.update(cfg)
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finally:
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LOG.debug("Worker configuration: %s\n" %
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json.dumps(engine_conf, sort_keys=True, indent=4))
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# create and run flow
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flow = lf.Flow('simple-linear').add(
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utils.TaskOneArgOneReturn(provides='result1'),
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utils.TaskMultiArgOneReturn(provides='result2')
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)
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eng = taskflow.engines.load(flow,
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store=dict(x=111, y=222, z=333),
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engine_conf=engine_conf)
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eng.run()
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print(json.dumps(eng.storage.fetch_all(), sort_keys=True))
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