def metric(type_, labels):
"""Factory for constructing metric objects.
:class:`~google.cloud.monitoring.metric.Metric` objects are typically
created to write custom metric values. The type should match the
metric type specified in the
:class:`~google.cloud.monitoring.metric.MetricDescriptor` used to
create the custom metric::
>>> metric = client.metric('custom.googleapis.com/my_metric',
... labels={
... 'status': 'successful',
... })
:type type_: str
:param type_: The metric type name.
:type labels: dict
:param labels: A mapping from label names to values for all labels
enumerated in the associated
:class:`~.metric.MetricDescriptor`.
:rtype: :class:`~google.cloud.monitoring.metric.Metric`
:returns: The metric object.
"""
return Metric(type=type_, labels=labels)
def test_constructor(self):
from google.cloud.monitoring.metric import Metric
from google.cloud.monitoring.resource import Resource
from google.cloud.monitoring.timeseries import Point
VALUE = 60 # seconds
METRIC = Metric(type=METRIC_TYPE, labels=METRIC_LABELS)
RESOURCE = Resource(type=RESOURCE_TYPE, labels=RESOURCE_LABELS)
POINTS = [
Point(start_time=TS0, end_time=TS1, value=VALUE),
Point(start_time=TS1, end_time=TS2, value=VALUE),
]
series = self._makeOne(metric=METRIC,
resource=RESOURCE,
metric_kind=METRIC_KIND,
value_type=VALUE_TYPE,
points=POINTS)
self.assertEqual(series.metric, METRIC)
self.assertEqual(series.resource, RESOURCE)
self.assertEqual(series.metric_kind, METRIC_KIND)
self.assertEqual(series.value_type, VALUE_TYPE)
self.assertEqual(series.points, POINTS)
def test_to_dict(self):
import datetime
from google.cloud._helpers import _datetime_to_rfc3339
from google.cloud.monitoring.metric import Metric
from google.cloud.monitoring.resource import Resource
from google.cloud.monitoring.timeseries import Point
VALUE = 42
end_time = datetime.datetime.now()
end_time_str = _datetime_to_rfc3339(end_time, ignore_zone=False)
METRIC = Metric(type=METRIC_TYPE, labels=METRIC_LABELS)
RESOURCE = Resource(type=RESOURCE_TYPE, labels=RESOURCE_LABELS)
POINT = Point(start_time=None, end_time=end_time_str, value=VALUE)
info = {
'metric': {'type': METRIC_TYPE, 'labels': METRIC_LABELS},
'resource': {'type': RESOURCE_TYPE, 'labels': RESOURCE_LABELS},
'points': [{
'interval': {
'endTime': end_time_str},
'value': {'int64Value': str(VALUE)},
}]
}
series = self._makeOne(metric=METRIC, resource=RESOURCE,
metric_kind=None, value_type=None,
points=[POINT])
series_dict = series._to_dict()
self.assertEqual(info, series_dict)
def _from_dict(cls, info):
"""Construct a time series from the parsed JSON representation.
:type info: dict
:param info:
A ``dict`` parsed from the JSON wire-format representation.
:rtype: :class:`TimeSeries`
:returns: A time series object.
"""
metric = Metric._from_dict(info['metric'])
resource = Resource._from_dict(info['resource'])
metric_kind = info['metricKind']
value_type = info['valueType']
points = [Point._from_dict(p) for p in info.get('points', ())]
return cls(metric, resource, metric_kind, value_type, points)
def generate_query_results(): # pragma: NO COVER
from google.cloud.monitoring.metric import Metric
from google.cloud.monitoring.resource import Resource
from google.cloud.monitoring.timeseries import Point
from google.cloud.monitoring.timeseries import TimeSeries
def P(timestamp, value):
return Point(
start_time=timestamp,
end_time=timestamp,
value=value,
)
for metric_labels, resource_labels, value in zip(
METRIC_LABELS, RESOURCE_LABELS, VALUES):
yield TimeSeries(
metric=Metric(type=METRIC_TYPE, labels=metric_labels),
resource=Resource(type=RESOURCE_TYPE, labels=resource_labels),
metric_kind=METRIC_KIND,
value_type=VALUE_TYPE,
points=[P(t, value) for t in TIMESTAMPS],
)