359cc490bd
To make it easily possible to change the retry atom execution from being in the engine thread this creates a retry executor (which is similar to the task executor) and provide that a serial executor (which it will use to execute with). This makes the retry and task actions closer to being the same and makes the surrounding code that much similar (which makes understanding it easier). Change-Id: I993e938280df3bd97f8076293183ef21989e2dba
103 lines
3.7 KiB
Python
103 lines
3.7 KiB
Python
# -*- coding: utf-8 -*-
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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 futurist
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from oslo_utils import uuidutils
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from taskflow.engines.action_engine import executor as base_executor
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from taskflow.engines.worker_based import endpoint
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from taskflow.engines.worker_based import executor as worker_executor
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from taskflow.engines.worker_based import server as worker_server
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from taskflow import test
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from taskflow.tests import utils as test_utils
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from taskflow.types import failure
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from taskflow.utils import async_utils
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from taskflow.utils import threading_utils
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TEST_EXCHANGE, TEST_TOPIC = ('test-exchange', 'test-topic')
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WAIT_TIMEOUT = 1.0
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POLLING_INTERVAL = 0.01
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class TestPipeline(test.TestCase):
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def _fetch_server(self, task_classes):
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endpoints = []
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for cls in task_classes:
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endpoints.append(endpoint.Endpoint(cls))
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server = worker_server.Server(
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TEST_TOPIC, TEST_EXCHANGE,
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futurist.ThreadPoolExecutor(max_workers=1), endpoints,
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transport='memory',
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transport_options={
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'polling_interval': POLLING_INTERVAL,
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})
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server_thread = threading_utils.daemon_thread(server.start)
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return (server, server_thread)
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def _fetch_executor(self):
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executor = worker_executor.WorkerTaskExecutor(
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uuidutils.generate_uuid(),
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TEST_EXCHANGE,
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[TEST_TOPIC],
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transport='memory',
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transport_options={
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'polling_interval': POLLING_INTERVAL,
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})
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return executor
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def _start_components(self, task_classes):
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server, server_thread = self._fetch_server(task_classes)
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executor = self._fetch_executor()
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self.addCleanup(executor.stop)
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self.addCleanup(server_thread.join)
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self.addCleanup(server.stop)
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executor.start()
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server_thread.start()
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server.wait()
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return (executor, server)
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def test_execution_pipeline(self):
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executor, server = self._start_components([test_utils.TaskOneReturn])
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self.assertEqual(0, executor.wait_for_workers(timeout=WAIT_TIMEOUT))
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t = test_utils.TaskOneReturn()
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progress_callback = lambda *args, **kwargs: None
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f = executor.execute_task(t, uuidutils.generate_uuid(), {},
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progress_callback=progress_callback)
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async_utils.wait_for_any([f])
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event, result = f.result()
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self.assertEqual(1, result)
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self.assertEqual(base_executor.EXECUTED, event)
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def test_execution_failure_pipeline(self):
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task_classes = [
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test_utils.TaskWithFailure,
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]
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executor, server = self._start_components(task_classes)
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t = test_utils.TaskWithFailure()
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progress_callback = lambda *args, **kwargs: None
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f = executor.execute_task(t, uuidutils.generate_uuid(), {},
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progress_callback=progress_callback)
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async_utils.wait_for_any([f])
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action, result = f.result()
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self.assertIsInstance(result, failure.Failure)
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self.assertEqual(RuntimeError, result.check(RuntimeError))
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self.assertEqual(base_executor.EXECUTED, action)
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