ef44589948
mock_object method in TestCase class now accepts keyword arguments that
will be properly handled when no new object is provided, so we can now
simplify calls in our tests.
This patch changes calls like
self.mock_object(os.path, 'exists', mock.Mock(return_value=True))
into
self.mock_object(os.path, 'exists', return_value=True)
Change-Id: I904ab4956a081c0292e2c982320e5005b055d3d5
64 lines
1.9 KiB
Python
64 lines
1.9 KiB
Python
#
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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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"""
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Tests for stochastic weight handler
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"""
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import ddt
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import random
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from cinder.scheduler import base_weight
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from cinder.scheduler.weights.stochastic import StochasticHostWeightHandler
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from cinder import test
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@ddt.ddt
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class StochasticWeightHandlerTestCase(test.TestCase):
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"""Test case for StochasticHostWeightHandler."""
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@ddt.data(
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(0.0, 'A'),
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(0.1, 'A'),
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(0.2, 'B'),
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(0.3, 'B'),
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(0.4, 'B'),
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(0.5, 'B'),
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(0.6, 'B'),
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(0.7, 'C'),
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(0.8, 'C'),
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(0.9, 'C'),
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)
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@ddt.unpack
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def test_get_weighed_objects_correct(self, rand_value, expected_obj):
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self.mock_object(random,
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'random',
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return_value=rand_value)
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class MapWeigher(base_weight.BaseWeigher):
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minval = 0
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maxval = 100
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def _weigh_object(self, obj, weight_map):
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return weight_map[obj]
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weight_map = {'A': 1, 'B': 3, 'C': 2}
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objs = sorted(weight_map.keys())
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weigher_classes = [MapWeigher]
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handler = StochasticHostWeightHandler('fake_namespace')
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weighted_objs = handler.get_weighed_objects(weigher_classes,
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objs,
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weight_map)
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winner = weighted_objs[0].obj
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self.assertEqual(expected_obj, winner)
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