图片解析应用
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from __future__ import absolute_import
import logging
import threading
from kafka.metrics.metrics_reporter import AbstractMetricsReporter
logger = logging.getLogger(__name__)
class DictReporter(AbstractMetricsReporter):
"""A basic dictionary based metrics reporter.
Store all metrics in a two level dictionary of category > name > metric.
"""
def __init__(self, prefix=''):
self._lock = threading.Lock()
self._prefix = prefix if prefix else '' # never allow None
self._store = {}
def snapshot(self):
"""
Return a nested dictionary snapshot of all metrics and their
values at this time. Example:
{
'category': {
'metric1_name': 42.0,
'metric2_name': 'foo'
}
}
"""
return dict((category, dict((name, metric.value())
for name, metric in list(metrics.items())))
for category, metrics in
list(self._store.items()))
def init(self, metrics):
for metric in metrics:
self.metric_change(metric)
def metric_change(self, metric):
with self._lock:
category = self.get_category(metric)
if category not in self._store:
self._store[category] = {}
self._store[category][metric.metric_name.name] = metric
def metric_removal(self, metric):
with self._lock:
category = self.get_category(metric)
metrics = self._store.get(category, {})
removed = metrics.pop(metric.metric_name.name, None)
if not metrics:
self._store.pop(category, None)
return removed
def get_category(self, metric):
"""
Return a string category for the metric.
The category is made up of this reporter's prefix and the
metric's group and tags.
Examples:
prefix = 'foo', group = 'bar', tags = {'a': 1, 'b': 2}
returns: 'foo.bar.a=1,b=2'
prefix = 'foo', group = 'bar', tags = None
returns: 'foo.bar'
prefix = None, group = 'bar', tags = None
returns: 'bar'
"""
tags = ','.join('%s=%s' % (k, v) for k, v in
sorted(metric.metric_name.tags.items()))
return '.'.join(x for x in
[self._prefix, metric.metric_name.group, tags] if x)
def configure(self, configs):
pass
def close(self):
pass