58a5a0932d
- Convert the various functions that take a task detail into
ones that take atom details (since this is now the generic
type they should take).
- Don't expose the detail type strings as part of the atom
detail api, leave those as private hidden strings and provide
conversion functions from string<->class instead.
- Have the logbook objects contain the following new methods
to reduce the dependence on persistence_utils to do the same.
- to_dict() which converts the current object into a dict
- from_dict() which converts the provided dict into a object
- merge() which merges a incoming objects data with the current
objects
- Have the persistence backends + storage + action engine use these
new methods instead of there current usage.
- Don't compare to logbook.RETRY_DETAIL or logbook.TASK_DETAIL since
python has the isinstance function just use it (ideally we should
fix the code so that this isn't even needed, usage of isinstance
means something is not designed/structured right).
- In storage tests we can't assume that failures will be non-lossy
since under certain backends when a failure is stored information
about the internally held exc_info is lost, so take this into
account when testing by using matches() where applicable.
Change-Id: Ie8a274cfd4cb4e64e87c355dc99d466d74a4e82c
143 lines
4.9 KiB
Python
143 lines
4.9 KiB
Python
# -*- coding: utf-8 -*-
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# Copyright (C) 2012 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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from taskflow import task
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from taskflow import test
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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.persistence.backends import impl_memory
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from taskflow.utils import persistence_utils as p_utils
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class ProgressTask(task.Task):
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def __init__(self, name, segments):
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super(ProgressTask, self).__init__(name=name)
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self._segments = segments
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def execute(self):
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if self._segments <= 0:
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return
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for i in range(1, self._segments):
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progress = float(i) / self._segments
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self.update_progress(progress)
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class ProgressTaskWithDetails(task.Task):
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def execute(self):
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self.update_progress(0.5, test='test data', foo='bar')
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class TestProgress(test.TestCase):
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def _make_engine(self, flow, flow_detail=None, backend=None):
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e = taskflow.engines.load(flow,
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flow_detail=flow_detail,
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backend=backend)
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e.compile()
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return e
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def tearDown(self):
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super(TestProgress, self).tearDown()
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with contextlib.closing(impl_memory.MemoryBackend({})) as be:
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with contextlib.closing(be.get_connection()) as conn:
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conn.clear_all()
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def test_sanity_progress(self):
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fired_events = []
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def notify_me(task, event_data, progress):
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fired_events.append(progress)
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ev_count = 5
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t = ProgressTask("test", ev_count)
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t.bind('update_progress', notify_me)
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flo = lf.Flow("test")
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flo.add(t)
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e = self._make_engine(flo)
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e.run()
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self.assertEqual(ev_count + 1, len(fired_events))
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self.assertEqual(1.0, fired_events[-1])
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self.assertEqual(0.0, fired_events[0])
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def test_no_segments_progress(self):
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fired_events = []
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def notify_me(task, event_data, progress):
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fired_events.append(progress)
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t = ProgressTask("test", 0)
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t.bind('update_progress', notify_me)
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flo = lf.Flow("test")
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flo.add(t)
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e = self._make_engine(flo)
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e.run()
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# 0.0 and 1.0 should be automatically fired
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self.assertEqual(2, len(fired_events))
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self.assertEqual(1.0, fired_events[-1])
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self.assertEqual(0.0, fired_events[0])
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def test_storage_progress(self):
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with contextlib.closing(impl_memory.MemoryBackend({})) as be:
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flo = lf.Flow("test")
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flo.add(ProgressTask("test", 3))
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b, fd = p_utils.temporary_flow_detail(be)
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e = self._make_engine(flo, flow_detail=fd, backend=be)
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e.run()
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end_progress = e.storage.get_task_progress("test")
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self.assertEqual(1.0, end_progress)
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task_uuid = e.storage.get_atom_uuid("test")
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td = fd.find(task_uuid)
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self.assertEqual(1.0, td.meta['progress'])
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self.assertFalse(td.meta['progress_details'])
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def test_storage_progress_detail(self):
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flo = ProgressTaskWithDetails("test")
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e = self._make_engine(flo)
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e.run()
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end_progress = e.storage.get_task_progress("test")
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self.assertEqual(1.0, end_progress)
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end_details = e.storage.get_task_progress_details("test")
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self.assertEqual(end_details.get('at_progress'), 0.5)
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self.assertEqual(end_details.get('details'), {
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'test': 'test data',
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'foo': 'bar'
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})
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def test_dual_storage_progress(self):
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fired_events = []
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def notify_me(task, event_data, progress):
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fired_events.append(progress)
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with contextlib.closing(impl_memory.MemoryBackend({})) as be:
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t = ProgressTask("test", 5)
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t.bind('update_progress', notify_me)
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flo = lf.Flow("test")
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flo.add(t)
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b, fd = p_utils.temporary_flow_detail(be)
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e = self._make_engine(flo, flow_detail=fd, backend=be)
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e.run()
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end_progress = e.storage.get_task_progress("test")
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self.assertEqual(1.0, end_progress)
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task_uuid = e.storage.get_atom_uuid("test")
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td = fd.find(task_uuid)
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self.assertEqual(1.0, td.meta['progress'])
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self.assertFalse(td.meta['progress_details'])
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self.assertEqual(6, len(fired_events))
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