def _InitializeMetric(self, metadata):
"""See base class."""
field_defs = stats_utils.FieldDefinitionTuplesFromProtos(
metadata.fields_defs)
if metadata.metric_type == rdf_stats.MetricMetadata.MetricType.COUNTER:
self._counter_metrics[metadata.varname] = _CounterMetric(field_defs)
elif metadata.metric_type == rdf_stats.MetricMetadata.MetricType.EVENT:
self._event_metrics[metadata.varname] = _EventMetric(
list(metadata.bins), field_defs)
elif metadata.metric_type == rdf_stats.MetricMetadata.MetricType.GAUGE:
value_type = stats_utils.PythonTypeFromMetricValueType(
metadata.value_type)
self._gauge_metrics[metadata.varname] = _GaugeMetric(
value_type, field_defs)
else:
raise ValueError("Unknown metric type: %s." % metadata.metric_type)
def __init__(self, metadata,
registry):
"""Instantiates a new _Metric.
Args:
metadata: An rdf_stats.MetricMetadata instance describing this _Metric.
registry: A prometheus_client.Registry instance.
Raises:
ValueError: metadata contains an unknown metric_type.
"""
self.metadata = metadata
self.fields = stats_utils.FieldDefinitionTuplesFromProtos(
metadata.fields_defs)
field_names = [name for name, _ in self.fields]
if metadata.metric_type == rdf_stats.MetricMetadata.MetricType.COUNTER:
self.metric = prometheus_client.Counter(
metadata.varname,
metadata.docstring,
labelnames=field_names,
registry=registry)
elif metadata.metric_type == rdf_stats.MetricMetadata.MetricType.EVENT:
bins = metadata.bins or [
0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.75, 1, 1.5, 2, 2.5, 3, 4, 5, 6, 7, 8,
9, 10, 15, 20, 50, 100
]
self.metric = prometheus_client.Histogram(
metadata.varname,
metadata.docstring,
labelnames=field_names,
buckets=bins,
registry=registry)
elif metadata.metric_type == rdf_stats.MetricMetadata.MetricType.GAUGE:
self.metric = prometheus_client.Gauge(
metadata.varname,
metadata.docstring,
labelnames=field_names,
registry=registry)
else:
raise ValueError("Unknown metric type: {!r}".format(metadata.metric_type))