45d350e80d
Instead of having a pretty restrictive module based api for saving logbook objects it is much more friendly and extensible to move toward a more ceilometer-influenced engine and connection based storage backend using stevedore to do the backend loading instead of a custom registration/fetching mechanism. This allows us to provide a base object oriented backend api that can be easily inherited from to allow for customized & pluggable backend storage modules. Implements blueprint stevedore-based-backends Implements blueprint ceilometer-influenced-backends Change-Id: Ib5868d3d9018b7aa1a3354858dcb90ca1a04055d
137 lines
4.1 KiB
Python
137 lines
4.1 KiB
Python
# -*- coding: utf-8 -*-
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# vim: tabstop=4 shiftwidth=4 softtabstop=4
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# Copyright (C) 2012-2013 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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from taskflow import decorators
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from taskflow.patterns import linear_flow
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from taskflow import test
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from taskflow.engines.action_engine import engine as eng
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class WrapableObjectsTest(test.TestCase):
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def _make_engine(self, flow):
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e = eng.SingleThreadedActionEngine(flow)
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e.compile()
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return e
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def test_simple_function(self):
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values = []
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def revert_one(*args, **kwargs):
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values.append('revert one')
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@decorators.task(revert=revert_one)
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def run_one(*args, **kwargs):
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values.append('one')
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@decorators.task
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def run_fail(*args, **kwargs):
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values.append('fail')
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raise RuntimeError('Woot!')
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flow = linear_flow.Flow('test')
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flow.add(
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run_one,
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run_fail
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)
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with self.assertRaisesRegexp(RuntimeError, '^Woot'):
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e = self._make_engine(flow)
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e.run()
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self.assertEquals(values, ['one', 'fail', 'revert one'])
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def test_simple_method(self):
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class MyTasks(object):
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def __init__(self):
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# NOTE(imelnikov): that's really *bad thing* to pass
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# data between task like this; though, its good enough
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# for our testing here
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self.values = []
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@decorators.task
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def run_one(self, *args, **kwargs):
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self.values.append('one')
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@decorators.task
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def run_fail(self, *args, **kwargs):
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self.values.append('fail')
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raise RuntimeError('Woot!')
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tasks = MyTasks()
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flow = linear_flow.Flow('test')
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flow.add(
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tasks.run_one,
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tasks.run_fail
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)
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with self.assertRaisesRegexp(RuntimeError, '^Woot'):
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e = self._make_engine(flow)
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e.run()
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self.assertEquals(tasks.values, ['one', 'fail'])
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def test_static_method(self):
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values = []
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class MyTasks(object):
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@decorators.task
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@staticmethod
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def run_one(*args, **kwargs):
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values.append('one')
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# NOTE(imelnikov): decorators should work in any order:
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@staticmethod
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@decorators.task
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def run_fail(*args, **kwargs):
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values.append('fail')
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raise RuntimeError('Woot!')
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flow = linear_flow.Flow('test')
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flow.add(
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MyTasks.run_one,
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MyTasks.run_fail
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)
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with self.assertRaisesRegexp(RuntimeError, '^Woot'):
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e = self._make_engine(flow)
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e.run()
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self.assertEquals(values, ['one', 'fail'])
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def test_class_method(self):
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class MyTasks(object):
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values = []
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@decorators.task
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@classmethod
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def run_one(cls, *args, **kwargs):
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cls.values.append('one')
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# NOTE(imelnikov): decorators should work in any order:
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@classmethod
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@decorators.task
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def run_fail(cls, *args, **kwargs):
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cls.values.append('fail')
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raise RuntimeError('Woot!')
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flow = linear_flow.Flow('test')
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flow.add(
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MyTasks.run_one,
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MyTasks.run_fail
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)
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with self.assertRaisesRegexp(RuntimeError, '^Woot'):
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e = self._make_engine(flow)
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e.run()
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self.assertEquals(MyTasks.values, ['one', 'fail'])
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