def test_get_collector_point(self):
aggregator = aggregate.SumAggregator()
int_counter = self._meter.create_metric(
"testName", "testDescription", "unit", int, Counter
)
float_counter = self._meter.create_metric(
"testName", "testDescription", "unit", float, Counter
)
valuerecorder = self._meter.create_metric(
"testName", "testDescription", "unit", float, ValueRecorder
)
result = metrics_exporter.get_collector_point(
MetricRecord(int_counter, self._key_labels, aggregator)
)
self.assertIsInstance(result, metrics_pb2.Point)
self.assertIsInstance(result.timestamp, Timestamp)
self.assertEqual(result.int64_value, 0)
aggregator.update(123.5)
aggregator.take_checkpoint()
result = metrics_exporter.get_collector_point(
MetricRecord(float_counter, self._key_labels, aggregator)
)
self.assertEqual(result.double_value, 123.5)
self.assertRaises(
TypeError,
metrics_exporter.get_collector_point(
MetricRecord(valuerecorder, self._key_labels, aggregator)
),
)
def test_export(self):
mock_client = mock.MagicMock()
mock_export = mock.MagicMock()
mock_client.Export = mock_export
host_name = "testHostName"
collector_exporter = metrics_exporter.OpenCensusMetricsExporter(
client=mock_client, host_name=host_name
)
test_metric = self._meter.create_counter(
"testname", "testdesc", "unit", int, self._labels.keys(),
)
record = MetricRecord(
test_metric,
self._key_labels,
aggregate.SumAggregator(),
metrics.get_meter_provider().resource,
)
result = collector_exporter.export([record])
self.assertIs(result, MetricsExportResult.SUCCESS)
# pylint: disable=unsubscriptable-object
export_arg = mock_export.call_args[0]
service_request = next(export_arg[0])
output_metrics = getattr(service_request, "metrics")
output_node = getattr(service_request, "node")
self.assertEqual(len(output_metrics), 1)
self.assertIsNotNone(getattr(output_node, "library_info"))
self.assertIsNotNone(getattr(output_node, "service_info"))
output_identifier = getattr(output_node, "identifier")
self.assertEqual(
getattr(output_identifier, "host_name"), "testHostName"
)
def test_translate_to_collector(self):
test_metric = self._meter.create_metric(
"testname", "testdesc", "unit", int, Counter,
)
aggregator = aggregate.SumAggregator()
aggregator.update(123)
aggregator.take_checkpoint()
record = MetricRecord(test_metric, self._key_labels, aggregator,)
output_metrics = metrics_exporter.translate_to_collector([record])
self.assertEqual(len(output_metrics), 1)
self.assertIsInstance(output_metrics[0], metrics_pb2.Metric)
self.assertEqual(output_metrics[0].metric_descriptor.name, "testname")
self.assertEqual(
output_metrics[0].metric_descriptor.description, "testdesc"
)
self.assertEqual(output_metrics[0].metric_descriptor.unit, "unit")
self.assertEqual(
output_metrics[0].metric_descriptor.type,
metrics_pb2.MetricDescriptor.CUMULATIVE_INT64,
)
self.assertEqual(
len(output_metrics[0].metric_descriptor.label_keys), 1
)
self.assertEqual(
output_metrics[0].metric_descriptor.label_keys[0].key,
"environment",
)
self.assertEqual(len(output_metrics[0].timeseries), 1)
self.assertEqual(len(output_metrics[0].timeseries[0].label_values), 1)
self.assertEqual(
output_metrics[0].timeseries[0].label_values[0].has_value, True
)
self.assertEqual(
output_metrics[0].timeseries[0].label_values[0].value, "staging"
)
self.assertEqual(len(output_metrics[0].timeseries[0].points), 1)
self.assertEqual(
output_metrics[0].timeseries[0].points[0].timestamp.seconds,
record.aggregator.last_update_timestamp // 1000000000,
)
self.assertEqual(
output_metrics[0].timeseries[0].points[0].timestamp.nanos,
record.aggregator.last_update_timestamp % 1000000000,
)
self.assertEqual(
output_metrics[0].timeseries[0].points[0].int64_value, 123
)
def test_translate_to_collector(self):
test_metric = self._meter.create_counter(
"testname", "testdesc", "unit", int, self._labels.keys()
)
aggregator = aggregate.SumAggregator()
aggregator.update(123)
aggregator.take_checkpoint()
record = MetricRecord(
test_metric,
self._key_labels,
aggregator,
metrics.get_meter_provider().resource,
)
start_timestamp = Timestamp()
output_metrics = metrics_exporter.translate_to_collector(
[record], start_timestamp,
)
self.assertEqual(len(output_metrics), 1)
self.assertIsInstance(output_metrics[0], metrics_pb2.Metric)
self.assertEqual(output_metrics[0].metric_descriptor.name, "testname")
self.assertEqual(
output_metrics[0].metric_descriptor.description, "testdesc"
)
self.assertEqual(output_metrics[0].metric_descriptor.unit, "unit")
self.assertEqual(
output_metrics[0].metric_descriptor.type,
metrics_pb2.MetricDescriptor.CUMULATIVE_INT64,
)
self.assertEqual(
len(output_metrics[0].metric_descriptor.label_keys), 2
)
self.assertEqual(
output_metrics[0].metric_descriptor.label_keys[0].key,
"environment",
)
self.assertEqual(
output_metrics[0].metric_descriptor.label_keys[1].key, "number",
)
self.assertIsNotNone(output_metrics[0].resource)
self.assertEqual(
output_metrics[0].resource.type, "",
)
self.assertEqual(
output_metrics[0].resource.labels["key_with_str_value"],
self._resource_labels["key_with_str_value"],
)
self.assertIsInstance(
output_metrics[0].resource.labels["key_with_int_val"], str,
)
self.assertEqual(
output_metrics[0].resource.labels["key_with_int_val"],
str(self._resource_labels["key_with_int_val"]),
)
self.assertIsInstance(
output_metrics[0].resource.labels["key_with_true"], str,
)
self.assertEqual(
output_metrics[0].resource.labels["key_with_true"],
str(self._resource_labels["key_with_true"]),
)
self.assertEqual(len(output_metrics[0].timeseries), 1)
self.assertEqual(len(output_metrics[0].timeseries[0].label_values), 2)
self.assertEqual(
output_metrics[0].timeseries[0].start_timestamp, start_timestamp
)
self.assertEqual(
output_metrics[0].timeseries[0].label_values[0].has_value, True
)
self.assertEqual(
output_metrics[0].timeseries[0].label_values[0].value, "staging"
)
self.assertEqual(len(output_metrics[0].timeseries[0].points), 1)
self.assertEqual(
output_metrics[0].timeseries[0].points[0].timestamp.seconds,
record.aggregator.last_update_timestamp // 1000000000,
)
self.assertEqual(
output_metrics[0].timeseries[0].points[0].timestamp.nanos,
record.aggregator.last_update_timestamp % 1000000000,
)
self.assertEqual(
output_metrics[0].timeseries[0].points[0].int64_value, 123
)
