• Openstack nova-scheduler 源码分析 — Filters/Weighting


    目录

    前言

    本篇记录了 Openstack 在创建 Instances 时,nova-scheduler 作为调度器的工作原理和代码实现。
    Openstack 中会由多个的 Instance 共享同一个 Host,而不是独占。所以就需要使用调度器这种管理规则来协调和管理 Instance 之间的资源分配。

    调度器

    调度器:调度 Instance 在哪一个 Host 上运行的方式。
    目前 Nova 中实现的调度器方式由下列几种:

    • ChanceScheduler(随机调度器):从所有正常运行 nova-compute 服务的 Host Node 中随机选取来创建 Instance

    • FilterScheduler(过滤调度器):根据指定的过滤条件以及权重来挑选最佳创建 Instance 的 Host Node 。

    • Caching(缓存调度器):是 FilterScheduler 中的一种,在其基础上将 Host 资源信息缓存到本地的内存中,然后通过后台的定时任务从数据库中获取最新的 Host 资源信息。

    为了便于扩展,Nova 将一个调度器必须要实现的接口提取出来成为 nova.scheduler.driver.Scheduler,只要继承了该类并实现其中的接口,我们就可以自定义调度器。

    注意不同的调度器并不能共存,需要在 /etc/nova/nova.conf 中的选项指定使用哪一个调度器。默认为 FilterScheduler 。

    vim /etc/nova/nova.conf

    scheduler_driver = nova.scheduler.filter_scheduler.FilterScheduler

    FilterScheduler调度器的工作流程

    这里写图片描述

    FilterScheduler 首先使用指定的 Filters(过滤器) 过滤符合条件的 Host,EG. 内存使用率小于 2% 。然后对得到的 Host 列表计算 Weighting 权重并排序,获得最佳的 Host 。

    Filters 过滤器

    Filtering 就是首先根据各个 Host 当前可用的资源情况来过滤掉那些不能满足 Instance 要求的 Host,然后再使用配置文件指定的各种 Filters 去过滤掉不符合过滤条件的 Host。经过 Filters 过滤后,会得到一个 Host 列表。

    这样的话 nova-scheduler 就需要从数据库中取得当前各个 Host 最新的资源使用情况,这些资源数据的收集和存储都由 nova-compute 中定义的数据库同步机制来完成。但是 nova-compute 对数据库的更新是周期性的, nova-scheduler 在选择最佳 Host 时需要最新的资源数据。所以在 nova-scheduler 中使用了 nova.scheduler.host_manager:HostState 来维护一份数据。这份数据仅保存在当前进程的内存中,里面包含了从上次数据库更新到现在 Host 资源的变化情况,也就是最新的 Host 资源数据。nova-scheduler 为了保持自己所维护的资源数据是最新的,每创建一个 Instance ,nova-scheduler 都要将这份资源数据更新,并从 Host 可用资源中去掉虚拟机使用的部分。
    注意:nova-scheduler 所维护的数据不会同步到数据库,它只会从数据库同步数据到自身,所以 nova-scheduler 并没有写数据库的功能。

    Filters 类型

    • ALLHostsFilter:不进行任何过滤
    • RamFilter:根据内存的可用情况来进行过滤
    • ComputeFilter:选取所有处于 Active 的 Host
    • TrustedFilter:选取所有可信的 Host
    • PciPassthroughFilter:选取提供 PCI SR-IOV 支持的 Host

    所有的 Filters 实现都位于nova/scheduler/filters 目录,每个 Filter 都要继承自 nova.scheduler.filters.BaseHostFilter 。如果需要自定义一个 Filter,只需通过继承此类并实现一个函数 host_passes(),返回的结果只有 True or False 。

    在配置文件中指定 Filters

    scheduler_available_filters=
    scheduler_default_filters=

    Weighting 权重

    Weighting 表示对所有符合过滤条件(通过 Filters)的 Host 计算权重并以此排序从而得到最佳的一个 Host。计算 Host 权重的过程需要调用指定的各种 Weigher Module,得到每个 Host 的权重值。

    所有的 Weigher 的实现都位于 nova/scheduler/weights 目录下。

    源码实现

    关键文件及其意义

    • /nova/scheduler/driver.py: 文件中最重要的就是 Scheduler 类,是所有调度器实现都要继承的基类,包含了调度器必须要实现的所有接口。

    • /nova/scheduler/manager.py: 主要实现了 SchedulerManager 类,定义了 Host 的管理操作函数,如:删除 Host 中的 Instance — delete_instance_info

    • /nova/scheduler/host_manager.py: 有两个类的实现,都是描述了跟调度器相关的 Host 的操作实现,类 HostState 维护了一份最新的 Host 资源数据。类 HostManager 描述了调度器相关的操作函数, EG._choose_host_filters/get_filtered_hosts/get_weighed_hosts

    • /nova/scheduler/chance.py: 只有 ChanceScheduler 类(随机调度器),继承自 Scheduler 类,实现随机选取 Host Node 的调度器

    • /nova/scheduler/client: 客户端调用程序的入口

    • /nova/scheduler/filter_scheduler.py: 只有 FilterScheduler 类(过滤调度器),继承自 Scheduler 类,实现了根据指定的过滤条件来选取 Host Node 的调度器

    • /nova/scheduler/filters 和 /nova/scheduler/weights: 这两个目录下的内容分别对应 过滤器权重 的实现 。

    阶段一:nova-scheduler 接收 build_instances RPC 远程调用

    这里写图片描述

    nova-conductor ==> RPC scheduler_client.select_destinations() ==> nova-sechduler

    #nova.conductor.manager.ComputeTaskManager:build_instances()
    
        def build_instances(self, context, instances, image, filter_properties,
                admin_password, injected_files, requested_networks,
                security_groups, block_device_mapping=None, legacy_bdm=True):
            # TODO(ndipanov): Remove block_device_mapping and legacy_bdm in version
            #                 2.0 of the RPC API.
    
            # 获取需要创建的 Instance 的参数信息
            request_spec = scheduler_utils.build_request_spec(context, image,
                                                              instances)
    
            # TODO(danms): Remove this in version 2.0 of the RPC API
            if (requested_networks and
                    not isinstance(requested_networks,
                                   objects.NetworkRequestList)):
                # 请求 network 信息
                requested_networks = objects.NetworkRequestList(
                    objects=[objects.NetworkRequest.from_tuple(t)
                             for t in requested_networks])
            # TODO(melwitt): Remove this in version 2.0 of the RPC API
    
            # 获取 flavor 信息
            flavor = filter_properties.get('instance_type')
            if flavor and not isinstance(flavor, objects.Flavor):
                # Code downstream may expect extra_specs to be populated since it
                # is receiving an object, so lookup the flavor to ensure this.
                flavor = objects.Flavor.get_by_id(context, flavor['id'])
                filter_properties = dict(filter_properties, instance_type=flavor)
    
            try:
                scheduler_utils.setup_instance_group(context, request_spec,
                                                     filter_properties)
                # check retry policy. Rather ugly use of instances[0]...
                # but if we've exceeded max retries... then we really only
                # have a single instance.
                scheduler_utils.populate_retry(filter_properties,
                    instances[0].uuid)
    
                # 获取 Hosts 列表
                hosts = self.scheduler_client.select_destinations(context,
                        request_spec, filter_properties)
    
            except Exception as exc:
                updates = {'vm_state': vm_states.ERROR, 'task_state': None}
                for instance in instances:
                    self._set_vm_state_and_notify(
                        context, instance.uuid, 'build_instances', updates,
                        exc, request_spec)
                return
    
            for (instance, host) in itertools.izip(instances, hosts):
                try:
                    instance.refresh()
                except (exception.InstanceNotFound,
                        exception.InstanceInfoCacheNotFound):
                    LOG.debug('Instance deleted during build', instance=instance)
                    continue
                local_filter_props = copy.deepcopy(filter_properties)
                scheduler_utils.populate_filter_properties(local_filter_props,
                    host)
                # The block_device_mapping passed from the api doesn't contain
                # instance specific information
                bdms = objects.BlockDeviceMappingList.get_by_instance_uuid(
                        context, instance.uuid)
    
    
                self.compute_rpcapi.build_and_run_instance(context,
                        instance=instance, host=host['host'], image=image,
                        request_spec=request_spec,
                        filter_properties=local_filter_props,
                        admin_password=admin_password,
                        injected_files=injected_files,
                        requested_networks=requested_networks,
                        security_groups=security_groups,
                        block_device_mapping=bdms, node=host['nodename'],
                        limits=host['limits'])

    nova-conductor 在调用 nova-scheduler 来获取能够创建 Instance 的 Host 的同时也获取了:requested_networks/flavor 等信息。

    其中获取 Hosts 列表的代码块:

    # 获取 Hosts 列表
                hosts = self.scheduler_client.select_destinations(context,
                        request_spec, filter_properties)

    下面列出了一系列为了获取 Hosts 列表的函数调用跳转

    # nova.scheduler.client.query.SchedulerQueryClient:select_destinations()
    
    from nova.scheduler import rpcapi as scheduler_rpcapi
    
    class SchedulerQueryClient(object):
        """Client class for querying to the scheduler."""
    
        def __init__(self):
            self.scheduler_rpcapi = scheduler_rpcapi.SchedulerAPI()
    
        def select_destinations(self, context, request_spec, filter_properties):
            """Returns destinations(s) best suited for this request_spec and
            filter_properties.
    
            The result should be a list of dicts with 'host', 'nodename' and
            'limits' as keys.
            """
            # 
            return self.scheduler_rpcapi.select_destinations(
                context, request_spec, filter_properties)
    
    
    # nova.scheduler.rpcapi.SchedulerAPI:select_destinations()
    
        def select_destinations(self, ctxt, request_spec, filter_properties):
            cctxt = self.client.prepare(version='4.0')
            return cctxt.call(ctxt, 'select_destinations',
                request_spec=request_spec, filter_properties=filter_properties)

    阶段二:从 scheduler.rpcapi.SchedulerAPI 到 scheduler.manager.SchedulerManager

    rpcapi.py 中的接口函数会在 manager.py 中实现实际操作函数。
    所以跳转到 nova.scheduler.manager.SchedulerManager:select_destinations()

    # nova.scheduler.manager.SchedulerManager:select_destinations()
    class SchedulerManager(manager.Manager):
        """Chooses a host to run instances on."""
    
        target = messaging.Target(version='4.2')
    
        def __init__(self, scheduler_driver=None, *args, **kwargs):
            if not scheduler_driver:
                scheduler_driver = CONF.scheduler_driver
            # 可以看出这里的 driver 是通过配置文件中的选项值指定的类来返回的对象 EG.nova.scheduler.filter_scheduler.FilterScheduler
            self.driver = importutils.import_object(scheduler_driver)
            super(SchedulerManager, self).__init__(service_name='scheduler',
                                                   *args, **kwargs)
    
    
        def select_destinations(self, context, request_spec, filter_properties):
            """Returns destinations(s) best suited for this request_spec and
            filter_properties.
    
            The result should be a list of dicts with 'host', 'nodename' and
            'limits' as keys.
            """
            dests = self.driver.select_destinations(context, request_spec,
                filter_properties)
            return jsonutils.to_primitive(dests)

    阶段三:从 scheduler.manager.SchedulerManager 到调度器 FilterScheduler

    vim /etc/nova/nova.conf

    scheduler_driver = nova.scheduler.filter_scheduler.FilterScheduler

    从配置文件选项 scheduler_driver 的值可以知道,nova.scheduler.manager.SchedulerManager:driver
    nova.scheduler.filter_scheduler.FilterScheduler 的实例化对象。
    所以跳转到 nova.scheduler.filter_scheduler.FilterScheduler:select_destinations()

    # nova.scheduler.filter_scheduler.FilterScheduler:select_destinations()
    
    class FilterScheduler(driver.Scheduler):
        """Scheduler that can be used for filtering and weighing."""
        def __init__(self, *args, **kwargs):
            super(FilterScheduler, self).__init__(*args, **kwargs)
            self.options = scheduler_options.SchedulerOptions()
            self.notifier = rpc.get_notifier('scheduler')
    
        def select_destinations(self, context, request_spec, filter_properties):
            """Selects a filtered set of hosts and nodes."""
            self.notifier.info(context, 'scheduler.select_destinations.start',
                               dict(request_spec=request_spec))
    
            # 需要创建的 Instances 的数量
            num_instances = request_spec['num_instances']
    
            # 获取满足笫一次过滤条件的主机列表 List (详见上述的调度器过滤原理)
            # nova.scheduler.filter_scheduler.FilterScheduler:_schedule() ==> return selected_hosts
            selected_hosts = self._schedule(context, request_spec,
                                            filter_properties)
    
            # Couldn't fulfill the request_spec
            # 当请求的 Instance 数量大于合适的主机数量时,不会创建 Instance 且输出 'There are not enough hosts available.'
            if len(selected_hosts) < num_instances:
                # NOTE(Rui Chen): If multiple creates failed, set the updated time
                # of selected HostState to None so that these HostStates are
                # refreshed according to database in next schedule, and release
                # the resource consumed by instance in the process of selecting
                # host.
                for host in selected_hosts:
                    host.obj.updated = None
    
                # Log the details but don't put those into the reason since
                # we don't want to give away too much information about our
                # actual environment.
                LOG.debug('There are %(hosts)d hosts available but '
                          '%(num_instances)d instances requested to build.',
                          {'hosts': len(selected_hosts),
                           'num_instances': num_instances})
    
                reason = _('There are not enough hosts available.')
                raise exception.NoValidHost(reason=reason)
    
            dests = [dict(host=host.obj.host, nodename=host.obj.nodename,
                          limits=host.obj.limits) for host in selected_hosts]
    
            self.notifier.info(context, 'scheduler.select_destinations.end',
                               dict(request_spec=request_spec))
            return dests
    
    
     def _schedule(self, context, request_spec, filter_properties):
            # 获取所有 Hosts 的状态
            hosts = self._get_all_host_states(elevated)
    
            selected_hosts = []
    
            # 获取需要创建的 Instances 数目
            num_instances = request_spec.get('num_instances', 1)
    
            # 遍历 num_instances,为每个 Instance 选取合适的主机
            for num in range(num_instances):
                # Filter local hosts based on requirements ...
    
                # 在 for 循环里,_schedule 的两个关键操作,get_filtered_hosts() 和 get_weighed_hosts()
                hosts = self.host_manager.get_filtered_hosts(hosts,
                        filter_properties, index=num)
                if not hosts:
                    # Can't get any more locally.
                    break
    
                LOG.debug("Filtered %(hosts)s", {'hosts': hosts})
    
                weighed_hosts = self.host_manager.get_weighed_hosts(hosts,
                        filter_properties)
    
                LOG.debug("Weighed %(hosts)s", {'hosts': weighed_hosts})
    
                scheduler_host_subset_size = CONF.scheduler_host_subset_size
    
                # 下面两个 if,主要为了防止 random.choice 调用越界
                if scheduler_host_subset_size > len(weighed_hosts):
                    scheduler_host_subset_size = len(weighed_hosts)
                if scheduler_host_subset_size < 1:
                    scheduler_host_subset_size = 1
    
                # 在符合要求的weigh过的host里进行随机选取
                chosen_host = random.choice(
                    weighed_hosts[0:scheduler_host_subset_size])
                LOG.debug("Selected host: %(host)s", {'host': chosen_host})
                selected_hosts.append(chosen_host)
    
                # Now consume the resources so the filter/weights
                # will change for the next instance.
                chosen_host.obj.consume_from_instance(instance_properties)
                if update_group_hosts is True:
                    if isinstance(filter_properties['group_hosts'], list):
                        filter_properties['group_hosts'] = set(
                            filter_properties['group_hosts'])
                    filter_properties['group_hosts'].add(chosen_host.obj.host)
            # 循环为每一个实例获取合适的主机后,返回选择的主机列表
            return selected_hosts

    上述的函数有三个非常关键的操作函数:

    • _get_all_host_states: 获取所有的 Host 状态,并且将初步满足条件的 Hosts 过滤出来。
    • get_filtered_hosts:使用 Filters 过滤器将第一个函数返回的 hosts 进行再一次过滤。
    • get_weighed_hosts:通过 Weighed 选取最优 Host。

    这三个关键函数在后面会继续介绍。

    首先看看host_manager.get_filtered_hosts() 中,host_manager 是 nova.scheduler.driver.Scheduler 的成员变量 。如下:

    # nova.scheduler.driver.Scheduler:__init__()
    
    # nova.scheduler.filter_scheduler.FilterScheduler 继承了 nova.scheduler.driver.Scheduler
     class Scheduler(object):
         """The base class that all Scheduler classes should inherit from."""
    
         def __init__(self):
             # 从这里知道 host_manager 会根据配置文件动态导入
             self.host_manager = importutils.import_object(
                     CONF.scheduler_host_manager)
             self.servicegroup_api = servicegroup.API()
    

    还需要注意:scheduler.filter_scheduler.FilterScheduler:_schedule() 中获取 Hosts 状态的函数 _get_all_host_states() 实现如下:

    # nova.scheduler.host_manager.HostManager:get_all_host_states()
    
     def get_all_host_states(self, context):
    
            service_refs = {service.host: service
                            for service in objects.ServiceList.get_by_binary(
                                context, 'nova-compute')}
    
            # 获取 Compute Node 资源
            compute_nodes = objects.ComputeNodeList.get_all(context)
            # nova.object.__init__()
            #     ==> nova.object.compute_node.ComputeNodeList:get_all
            seen_nodes = set()
            for compute in compute_nodes:
                service = service_refs.get(compute.host)
    
                if not service:
                    LOG.warning(_LW(
                        "No compute service record found for host %(host)s"),
                        {'host': compute.host})
                    continue
                host = compute.host
                node = compute.hypervisor_hostname
                state_key = (host, node)
                host_state = self.host_state_map.get(state_key)
    
                # 更新主机信息
                if host_state:
                    host_state.update_from_compute_node(compute)
                else:
                    host_state = self.host_state_cls(host, node, compute=compute)
                    self.host_state_map[state_key] = host_state
                # We force to update the aggregates info each time a new request
                # comes in, because some changes on the aggregates could have been
                # happening after setting this field for the first time
                host_state.aggregates = [self.aggs_by_id[agg_id] for agg_id in
                                         self.host_aggregates_map[
                                             host_state.host]]
                host_state.update_service(dict(service))
                self._add_instance_info(context, compute, host_state)
                seen_nodes.add(state_key)
    
            # remove compute nodes from host_state_map if they are not active
            # * 移除 not active 的节点
            dead_nodes = set(self.host_state_map.keys()) - seen_nodes
    
    
    for state_key in dead_nodes:
                host, node = state_key
                LOG.info(_LI("Removing dead compute node %(host)s:%(node)s "
                             "from scheduler"), {'host': host, 'node': node})
                del self.host_state_map[state_key]
    
            return six.itervalues(self.host_state_map)
    # get_all_host_states主要用来去除不活跃的节点

    继续往下看获取 Compute Node 资源信息函数 objects.ComputeNodeList.get_all(context) 的实现。

    # nova.object.compute_node:get_all()
    
        @base.remotable_classmethod
        def get_all(cls, context):
            # 调到了 nova.db.api.compute_node_get_all()
            db_computes = db.compute_node_get_all(context)
    
    
            return base.obj_make_list(context, cls(context), objects.ComputeNode,
                                      db_computes)
    
    
    
    #nova.db.api:compute_node_get_all()
    
    def compute_node_get_all(context):
        """Get all computeNodes.
    
        :param context: The security context
    
        :returns: List of dictionaries each containing compute node properties
        """
        return IMPL.compute_node_get_all(context)

    至此,说明 liberty 版本的 nova-scheduler 还是能够访问数据库的。

    问题是: nova-scheduler 是怎么更新主机信息的,能够直接数据库进行写操作吗?
    答案是:不能,nova-scheduler 不能够对数据库进行写操作,但是却可以从数据库中读取 Host 资源数据并缓存在进程的内存中。如下:

    # nova.scheduler.host_manager.HostState:__init__()
    class HostState(object):
        """Mutable and immutable information tracked for a host.
        This is an attempt to remove the ad-hoc data structures
        previously used and lock down access.
        """
    
        def __init__(self, host, node, compute=None):
            self.host = host
            self.nodename = node
    
            # Mutable available resources.
            # These will change as resources are virtually "consumed".
            self.total_usable_ram_mb = 0
            self.total_usable_disk_gb = 0
            self.disk_mb_used = 0
            self.free_ram_mb = 0
            self.free_disk_mb = 0
            self.vcpus_total = 0
            self.vcpus_used = 0
            self.pci_stats = None
            self.numa_topology = None
    
            # Additional host information from the compute node stats:
            self.num_instances = 0
            self.num_io_ops = 0
    
            # Other information
            self.host_ip = None
            self.hypervisor_type = None
            self.hypervisor_version = None
            self.hypervisor_hostname = None
            self.cpu_info = None
            self.supported_instances = None
    

    nova-scheduler 并没有写数据库的操作函数,但是 nova-scheduler 会将数据库的数据缓存到进程内存中。这样就可以在保证了 nova-scheduler 能使用最新的 Host 资源信息,同时下降低了对数据库的 I/O 请求。

    阶段四:从调度器 FilterScheduler 到过滤器 Filters

    上面的代码中调用了 Filters 函数:get_filtered_hosts(),实现如下:

    # nova.scheduler.host_manager.HostManager:get_filtered_hosts()
        def get_filtered_hosts(self, hosts, filter_properties,
                filter_class_names=None, index=0):
            """Filter hosts and return only ones passing all filters."""
            # 下面定义了若干局部函数,先省略掉
            def _strip_ignore_hosts(host_map, hosts_to_ignore):
                ignored_hosts = []
                for host in hosts_to_ignore:
    
            。。。。
            # 返回经过验证的可用的过滤器;
            filter_classes = self._choose_host_filters(filter_class_names)
            。。。。
                # 调用了get_filtered_objects
                return self.filter_handler.get_filtered_objects(filters,
                            hosts, filter_properties, index)
    
    
    
    # 继续跳转到 get_filtered_objects()
     def get_filtered_objects(self, filters, objs, filter_properties, index=0):
            list_objs = list(objs)
            LOG.debug("Starting with %d host(s)", len(list_objs))
            part_filter_results = []
            full_filter_results = []
            log_msg = "%(cls_name)s: (start: %(start)s, end: %(end)s)"
            for filter_ in filters:
                if filter_.run_filter_for_index(index):
                    cls_name = filter_.__class__.__name__
                    start_count = len(list_objs)
                    # 关键的一句话
                    objs = filter_.filter_all(list_objs, filter_properties)
                    if objs is None:
                        LOG.debug("Filter %s says to stop filtering", cls_name)
                        return
                    list_objs = list(objs)
                    end_count = len(list_objs)
                    part_filter_results.append(log_msg % {"cls_name": cls_name,
                            "start": start_count, "end": end_count})
                    if list_objs:
                        remaining = [(getattr(obj, "host", obj),
                                      getattr(obj, "nodename", ""))
                                     for obj in list_objs]
                        full_filter_results.append((cls_name, remaining))
    
            return list_objs
    
    
    
    # objs 的 return 又调用了 filter_.filter_all(list_objs, filter_properties)
    def filter_all(self, filter_obj_list, filter_properties):
            for obj in filter_obj_list:
                if self._filter_one(obj, filter_properties):
                    # 符合规则 生产一个obj
                    yield obj
    
    
    
    # 继续调用 _filter_one()
    def _filter_one(self, obj, filter_properties):
    
            # 如果符合 Filter 过滤器,就返回 TRUE,否则返回 FALSE
    
            return self.host_passes(obj, filter_properties)

    经过一连串的调用跳转,Filter 的过滤工作就完成了。

    阶段五:Filters 到权重计算与排序

    # nova.scheduler.host_manager.HostManager:get_weighed_hosts()
        def get_weighed_hosts(self, hosts, weight_properties):
            """Weigh the hosts."""
            return self.weight_handler.get_weighed_objects(self.weighers,
                    hosts, weight_properties)
    
    
    # nova.weights.BaseWeightHandler:get_weighed_objects()
    class BaseWeightHandler(loadables.BaseLoader):
        object_class = WeighedObject
    
        def get_weighed_objects(self, weighers, obj_list, weighing_properties):
            """Return a sorted (descending), normalized list of WeighedObjects."""
            weighed_objs = [self.object_class(obj, 0.0) for obj in obj_list]
    
            if len(weighed_objs) <= 1:
                return weighed_objs
    
            for weigher in weighers:
                weights = weigher.weigh_objects(weighed_objs, weighing_properties)
    
                # Normalize the weights
                weights = normalize(weights,
                                    minval=weigher.minval,
                                    maxval=weigher.maxval)
    
                for i, weight in enumerate(weights):
                    obj = weighed_objs[i]
                    obj.weight += weigher.weight_multiplier() * weight
    
            # 进行排序
            return sorted(weighed_objs, key=lambda x: x.weight, reverse=True)
    
    
    

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  • 原文地址:https://www.cnblogs.com/hzcya1995/p/13310761.html
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