def resource(type_, labels):
"""Factory for constructing monitored resource objects.
A monitored resource object (
:class:`~google.cloud.monitoring.resource.Resource`) is
typically used to create a
:class:`~google.cloud.monitoring.timeseries.TimeSeries` object.
For a list of possible monitored resource types and their associated
labels, see:
https://cloud.google.com/monitoring/api/resources
:type type_: str
:param type_: The monitored resource type name.
:type labels: dict
:param labels: A mapping from label names to values for all labels
enumerated in the associated
:class:`~.resource.ResourceDescriptor`,
except that ``project_id`` can and should be omitted
when writing time series data.
:rtype: :class:`~google.cloud.monitoring.resource.Resource`
:returns: A monitored resource object.
"""
return Resource(type_, labels)
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 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 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],
)
