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#
# -------------------------------------------------------------------------
# Copyright (c) 2015-2017 AT&T Intellectual Property
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
# -------------------------------------------------------------------------
#
from oslo_log import log
from conductor.solver.optimizer import decision_path as dpath
from conductor.solver.optimizer import search
from random import randint
LOG = log.getLogger(__name__)
class RandomPick(search.Search):
def __init__(self, conf):
search.Search.__init__(self, conf)
def search(self, _demand_list, _request):
decision_path = dpath.DecisionPath()
decision_path.set_decisions({})
return self._find_current_best(_demand_list, decision_path, _request)
def _find_current_best(self, _demand_list, _decision_path, _request):
self.triageSolver.getSortedDemand(_demand_list)
for demand in _demand_list:
# apply the constraints on all candidates first
_decision_path.current_demand = demand
candidate_list = self._solve_constraints(_decision_path, _request)
# When you have two demands and for one there are no candidates left after filtering by constraints
# the code tries to randomly choose index randint(0, -1) what raises an exception. None is returned
# in order to prevent that and this case is considered in the Optimizer respectively
if len(candidate_list) > 0:
# random pick one candidate
r_index = randint(0, len(candidate_list) - 1)
best_resource = candidate_list[r_index]
_decision_path.decisions[demand.name] = best_resource
else:
return None
return _decision_path
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