def test_init_invalid(self):
time_series.TimeSeries(LABEL_VALUES, POINTS, None)
with self.assertRaises(ValueError):
time_series.TimeSeries(None, POINTS, START_TIMESTAMP)
with self.assertRaises(ValueError):
time_series.TimeSeries(LABEL_VALUES, None, START_TIMESTAMP)
with self.assertRaises(ValueError):
time_series.TimeSeries(LABEL_VALUES, [], START_TIMESTAMP)
def test_check_points_type(self):
ts = time_series.TimeSeries(LABEL_VALUES, POINTS, START_TIMESTAMP)
self.assertTrue(ts.check_points_type(value.ValueLong))
bad_points = POINTS + (point.Point(value.ValueDouble(6.0),
"2018-10-10T04:33:44.012345Z"), )
bad_time_series = time_series.TimeSeries(LABEL_VALUES, bad_points,
START_TIMESTAMP)
self.assertFalse(bad_time_series.check_points_type(value.ValueLong))
self.assertFalse(bad_time_series.check_points_type(value.ValueLong))
def view_data_to_metric(view_data, timestamp):
"""Convert a ViewData to a Metric at time `timestamp`.
:type view_data: :class: `opencensus.stats.view_data.ViewData`
:param view_data: The ViewData to convert.
:type timestamp: :class: `datetime.datetime`
:param timestamp: The time to set on the metric's point's aggregation,
usually the current time.
:rtype: :class: `opencensus.metrics.export.metric.Metric`
:return: A converted Metric.
"""
md = view_data.view.get_metric_descriptor()
# TODO: implement gauges
if is_gauge(md.type):
ts_start = None # pragma: NO COVER
else:
ts_start = view_data.start_time
ts_list = []
for tag_vals, agg_data in view_data.tag_value_aggregation_data_map.items():
label_values = get_label_values(tag_vals)
point = agg_data.to_point(timestamp)
ts_list.append(time_series.TimeSeries(label_values, [point], ts_start))
return metric.Metric(md, ts_list)
def test_export_metrics(self):
lv = label_value.LabelValue('val')
val = value.ValueLong(value=123)
dt = datetime(2019, 3, 20, 21, 34, 0, 537954)
pp = point.Point(value=val, timestamp=dt)
ts = [
time_series.TimeSeries(label_values=[lv],
points=[pp],
start_timestamp=utils.to_iso_str(dt))
]
desc = metric_descriptor.MetricDescriptor(
name='name',
description='description',
unit='unit',
type_=metric_descriptor.MetricDescriptorType.GAUGE_INT64,
label_keys=[label_key.LabelKey('key', 'description')])
mm = metric.Metric(descriptor=desc, time_series=ts)
exporter = stackdriver.StackdriverStatsExporter(client=mock.Mock())
exporter.export_metrics([mm])
self.assertEqual(exporter.client.create_time_series.call_count, 1)
sd_args = exporter.client.create_time_series.call_args[0][1]
self.assertEqual(len(sd_args), 1)
[sd_arg] = exporter.client.create_time_series.call_args[0][1]
self.assertEqual(sd_arg.points[0].value.int64_value, 123)
def _create_metric(descriptor_type=metric_descriptor.MetricDescriptorType.
CUMULATIVE_INT64,
points=[]):
return metric.Metric(
metric_descriptor.MetricDescriptor('', '', '', descriptor_type, []), [
time_series.TimeSeries([label_value.LabelValue()], points,
TEST_TIME_STR)
])
def test_check_points_type(self):
ts = time_series.TimeSeries(LABEL_VALUES, POINTS, START_TIMESTAMP)
self.assertTrue(
ts.check_points_type(
metric_descriptor.MetricDescriptorType.GAUGE_INT64))
bad_points = POINTS + (point.Point(value.Value.double_value(6.0),
"2018-10-10T04:33:44.012345Z"), )
bad_time_series = time_series.TimeSeries(LABEL_VALUES, bad_points,
START_TIMESTAMP)
self.assertFalse(
bad_time_series.check_points_type(
metric_descriptor.MetricDescriptorType.GAUGE_INT64))
self.assertFalse(
bad_time_series.check_points_type(
metric_descriptor.MetricDescriptorType.GAUGE_DOUBLE))
def test_export_single_metric(self, mock_stats, mock_client):
"""Check that we can export a set of a single metric."""
lv = label_value.LabelValue('val')
val = value.ValueLong(value=123)
dt = datetime(2019, 3, 20, 21, 34, 0, 537954)
pp = point.Point(value=val, timestamp=dt)
ts = [
time_series.TimeSeries(label_values=[lv],
points=[pp],
start_timestamp=utils.to_iso_str(dt))
]
desc = metric_descriptor.MetricDescriptor(
name='name2',
description='description2',
unit='unit2',
type_=metric_descriptor.MetricDescriptorType.GAUGE_INT64,
label_keys=[label_key.LabelKey('key', 'description')])
mm = metric.Metric(descriptor=desc, time_series=ts)
mock_stats.get_metrics.return_value = [mm]
with MockGetExporterThread() as mget:
exporter = stackdriver.new_stats_exporter(
stackdriver.Options(project_id=1))
mget.transport.step()
exporter.client.create_metric_descriptor.assert_called()
self.assertEqual(exporter.client.create_metric_descriptor.call_count,
1)
md_call_arg =\
exporter.client.create_metric_descriptor.call_args[0][1]
self.assertEqual(md_call_arg.metric_kind,
monitoring_v3.enums.MetricDescriptor.MetricKind.GAUGE)
self.assertEqual(md_call_arg.value_type,
monitoring_v3.enums.MetricDescriptor.ValueType.INT64)
exporter.client.create_time_series.assert_called()
self.assertEqual(exporter.client.create_time_series.call_count, 1)
ts_call_arg = exporter.client.create_time_series.call_args[0][1]
self.assertEqual(len(ts_call_arg), 1)
self.assertEqual(len(ts_call_arg[0].points), 1)
self.assertEqual(ts_call_arg[0].points[0].value.int64_value, 123)
def create_metric():
lv = label_value.LabelValue('val')
val = value.ValueLong(value=123)
dt = datetime(2019, 3, 20, 21, 34, 0, 537954)
pp = point.Point(value=val, timestamp=dt)
ts = [
time_series.TimeSeries(label_values=[lv],
points=[pp],
start_timestamp=utils.to_iso_str(dt))
]
desc = metric_descriptor.MetricDescriptor(
name='name',
description='description',
unit='unit',
type_=metric_descriptor.MetricDescriptorType.GAUGE_INT64,
label_keys=[label_key.LabelKey('key', 'description')])
return metric.Metric(descriptor=desc, time_series=ts)
def get_timeseries_list(points, timestamp):
"""Convert a list of `GaugePoint`s into a list of `TimeSeries`.
Get a :class:`opencensus.metrics.export.time_series.TimeSeries` for each
measurement in `points`. Each series contains a single
:class:`opencensus.metrics.export.point.Point` that represents the last
recorded value of the measurement.
:type points: list(:class:`GaugePoint`)
:param points: The list of measurements to convert.
:type timestamp: :class:`datetime.datetime`
:param timestamp: Recording time to report, usually the current time.
:rtype: list(:class:`opencensus.metrics.export.time_series.TimeSeries`)
:return: A list of one `TimeSeries` for each point in `points`.
"""
ts_list = []
for lv, gp in points.items():
point = point_module.Point(gp.to_point_value(), timestamp)
ts_list.append(time_series.TimeSeries(lv, [point], timestamp))
return ts_list
def get_metric(self, timestamp):
"""Get a metric including all current time series.
Get a :class:`opencensus.metrics.export.metric.Metric` with one
:class:`opencensus.metrics.export.time_series.TimeSeries` for each
set of label values with a recorded measurement. Each `TimeSeries`
has a single point that represents the last recorded value.
:type timestamp: :class:`datetime.datetime`
:param timestamp: Recording time to report, usually the current time.
:rtype: :class:`opencensus.metrics.export.metric.Metric` or None
:return: A converted metric for all current measurements.
"""
if not self.points:
return None
ts_list = []
with self._points_lock:
for lv, gp in self.points.items():
point = point_module.Point(
self.value_type(gp.value), timestamp)
ts_list.append(time_series.TimeSeries(lv, [point], timestamp))
return metric.Metric(self.descriptor, ts_list)
def test_init(self):
ts = time_series.TimeSeries(LABEL_VALUES, POINTS, START_TIMESTAMP)
self.assertEqual(ts.start_timestamp, START_TIMESTAMP)
self.assertEqual(ts.label_values, LABEL_VALUES)
self.assertEqual(ts.points, POINTS)
