本文整理汇总了Python中marathon.MarathonClient.list_queue方法的典型用法代码示例。如果您正苦于以下问题：Python MarathonClient.list_queue方法的具体用法？Python MarathonClient.list_queue怎么用？Python MarathonClient.list_queue使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类marathon.MarathonClient的用法示例。
在下文中一共展示了MarathonClient.list_queue方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: MarathonAppCollector
# 需要导入模块: from marathon import MarathonClient [as 别名]
# 或者: from marathon.MarathonClient import list_queue [as 别名]
class MarathonAppCollector(object):
APP_ATTIBUTES = (
"instances",
"cpus",
"mem",
"disk",
"backoffSeconds",
"backoffFactor",
"maxLaunchDelaySeconds",
"container.docker.privileged",
"container.docker.forcePullImage",
"healthChecks.gracePeriodSeconds",
"healthChecks.intervalSeconds",
"healthChecks.maxConsecutiveFailures",
"healthChecks.timeoutSeconds",
"upgradeStrategy.minimumHealthCapacity",
"upgradeStrategy.maximumOverCapacity",
"tasksStaged",
"tasksRunning",
"tasksHealthy",
"tasksUnhealthy",
"taskStats.startedAfterLastScaling.stats.counts.staged",
"taskStats.startedAfterLastScaling.stats.counts.running",
"taskStats.startedAfterLastScaling.stats.counts.healthy",
"taskStats.startedAfterLastScaling.stats.lifeTime.averageSeconds",
"taskStats.startedAfterLastScaling.stats.lifeTime.medianSeconds",
"taskStats.withLatestConfig.stats.counts.staged",
"taskStats.withLatestConfig.stats.counts.running",
"taskStats.withLatestConfig.stats.counts.healthy",
"taskStats.withLatestConfig.stats.lifeTime.averageSeconds",
"taskStats.withLatestConfig.stats.lifeTime.medianSeconds",
"taskStats.totalSummary.stats.counts.staged",
"taskStats.totalSummary.stats.counts.running",
"taskStats.totalSummary.stats.counts.healthy",
"taskStats.totalSummary.stats.lifeTime.averageSeconds",
"taskStats.totalSummary.stats.lifeTime.medianSeconds",
)
QUEUE_ATTRIBUTES = (
"count",
"delay.overdue",
"delay.timeLeftSeconds",
)
def __init__(self, marathon_url=None):
self.client = MarathonClient(marathon_url)
def collect(self):
result_dict = {}
apps = self.client.list_apps(embed_task_stats=True)
for app_attribute in self.APP_ATTIBUTES:
metric_family = GaugeMetricFamily(
self.get_metric_key(app_attribute, 'apps'),
documentation='from v2/apps?embed=apps.taskStats value of %s' % app_attribute,
labels=["id"])
for app in apps:
labels = [app.id]
value = self.get_metric_value(app_attribute, app)
if value is None:
continue
metric_family.add_metric(labels, value)
yield metric_family
queue = self.client.list_queue()
for queue_attribute in self.QUEUE_ATTRIBUTES:
metric_family = GaugeMetricFamily(
self.get_metric_key(queue_attribute, 'queue'),
documentation='from v2/queue value of %s' % queue_attribute,
labels=["id"])
for queue_item in queue:
labels = [queue_item.app.id]
value = self.get_metric_value(queue_attribute, queue_item)
if value is None:
continue
metric_family.add_metric(labels, value)
yield metric_family
@classmethod
def get_metric_value(cls, key, obj):
if '.' in key:
key_current, key_rest = key.split('.', 1)
sub_obj = getattr(obj, to_snake_case(key_current), None)
if sub_obj is None:
return None
return cls.get_metric_value(key_rest, sub_obj)
return getattr(obj, to_snake_case(key), None)
@classmethod
def get_metric_key(cls, key, obj_type):
return "marathon_%s_%s" % (obj_type, key.replace('.', '_'))
@classmethod
def generate_metric(cls, key, obj, obj_type, labels, value):
return metric_family