63 lines
2.0 KiB
Python
63 lines
2.0 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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"""Tests for stochastic weight handler."""
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import random
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import ddt
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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.tests.unit 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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