# Copyright 2011 OpenStack Foundation # All Rights Reserved. # # 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. """ Fakes For Scheduler tests. """ import six from nova import objects from nova.scheduler import driver from nova.scheduler import host_manager NUMA_TOPOLOGY = objects.NUMATopology( cells=[objects.NUMACell( id=0, cpuset=set([1, 2]), memory=512, cpu_usage=0, memory_usage=0, mempages=[], siblings=[], pinned_cpus=set([])), objects.NUMACell( id=1, cpuset=set([3, 4]), memory=512, cpu_usage=0, memory_usage=0, mempages=[], siblings=[], pinned_cpus=set([]))]) NUMA_TOPOLOGY_W_HT = objects.NUMATopology(cells=[ objects.NUMACell( id=0, cpuset=set([1, 2, 5, 6]), memory=512, cpu_usage=0, memory_usage=0, mempages=[], siblings=[set([1, 5]), set([2, 6])], pinned_cpus=set([])), objects.NUMACell( id=1, cpuset=set([3, 4, 7, 8]), memory=512, cpu_usage=0, memory_usage=0, mempages=[], siblings=[set([3, 4]), set([7, 8])], pinned_cpus=set([])) ]) COMPUTE_NODES = [ objects.ComputeNode( id=1, local_gb=1024, memory_mb=1024, vcpus=1, disk_available_least=None, free_ram_mb=512, vcpus_used=1, free_disk_gb=512, local_gb_used=0, updated_at=None, host='host1', hypervisor_hostname='node1', host_ip='127.0.0.1', hypervisor_version=0, numa_topology=None, hypervisor_type='foo', supported_hv_specs=[], pci_device_pools=None, cpu_info=None, stats=None, metrics=None, cpu_allocation_ratio=16.0, ram_allocation_ratio=1.5), objects.ComputeNode( id=2, local_gb=2048, memory_mb=2048, vcpus=2, disk_available_least=1024, free_ram_mb=1024, vcpus_used=2, free_disk_gb=1024, local_gb_used=0, updated_at=None, host='host2', hypervisor_hostname='node2', host_ip='127.0.0.1', hypervisor_version=0, numa_topology=None, hypervisor_type='foo', supported_hv_specs=[], pci_device_pools=None, cpu_info=None, stats=None, metrics=None, cpu_allocation_ratio=16.0, ram_allocation_ratio=1.5), objects.ComputeNode( id=3, local_gb=4096, memory_mb=4096, vcpus=4, disk_available_least=3333, free_ram_mb=3072, vcpus_used=1, free_disk_gb=3072, local_gb_used=0, updated_at=None, host='host3', hypervisor_hostname='node3', host_ip='127.0.0.1', hypervisor_version=0, numa_topology=NUMA_TOPOLOGY._to_json(), hypervisor_type='foo', supported_hv_specs=[], pci_device_pools=None, cpu_info=None, stats=None, metrics=None, cpu_allocation_ratio=16.0, ram_allocation_ratio=1.5), objects.ComputeNode( id=4, local_gb=8192, memory_mb=8192, vcpus=8, disk_available_least=8192, free_ram_mb=8192, vcpus_used=0, free_disk_gb=8888, local_gb_used=0, updated_at=None, host='host4', hypervisor_hostname='node4', host_ip='127.0.0.1', hypervisor_version=0, numa_topology=None, hypervisor_type='foo', supported_hv_specs=[], pci_device_pools=None, cpu_info=None, stats=None, metrics=None, cpu_allocation_ratio=16.0, ram_allocation_ratio=1.5), # Broken entry objects.ComputeNode( id=5, local_gb=1024, memory_mb=1024, vcpus=1, host='fake', hypervisor_hostname='fake-hyp'), ] SERVICES = [ objects.Service(host='host1', disabled=False), objects.Service(host='host2', disabled=True), objects.Service(host='host3', disabled=False), objects.Service(host='host4', disabled=False), ] def get_service_by_host(host): services = [service for service in SERVICES if service.host == host] return services[0] class FakeHostState(host_manager.HostState): def __init__(self, host, node, attribute_dict, instances=None): super(FakeHostState, self).__init__(host, node) if instances: self.instances = {inst.uuid: inst for inst in instances} else: self.instances = {} for (key, val) in six.iteritems(attribute_dict): setattr(self, key, val) class FakeScheduler(driver.Scheduler): def select_destinations(self, context, request_spec, filter_properties): return []