def _get_points_proto(points):
protos = []
for point in points:
proto = metrics_pb2.Point(
timestamp=utils.proto_ts_from_datetime(point.timestamp))
if isinstance(point.value, value.ValueLong):
proto.int64_value = int(point.value.value)
elif isinstance(point.value, value.ValueDouble):
proto.double_value = float(point.value.value)
elif isinstance(point.value, value.ValueDistribution):
proto.distribution_value.MergeFrom(
metrics_pb2.DistributionValue(
sum=point.value.sum,
count=point.value.count,
sum_of_squared_deviation=point.value.
sum_of_squared_deviation,
bucket_options=_get_bucket_options_proto(
point.value.bucket_options)
if point.value.bucket_options else None,
buckets=_get_buckets_proto(point.value.buckets)))
# TODO: handle SUMMARY metrics, #567
else: # pragma: NO COVER
raise TypeError('Unsupported metric type: {}'.format(
type(point.value)))
protos.append(proto)
return protos
def test_datetime_to_proto_ts_conversion(self):
now = datetime.utcnow()
delta = now - datetime(1970, 1, 1)
expected_seconds = int(delta.total_seconds())
expected_nanos = delta.microseconds * 1000
proto_ts = utils.proto_ts_from_datetime(now)
self.assertEqual(proto_ts.seconds, int(expected_seconds))
self.assertEqual(proto_ts.nanos, expected_nanos)
def test_datetime_to_proto_ts_conversion_zero(self):
zero = datetime(1970, 1, 1)
proto_ts = utils.proto_ts_from_datetime(zero)
self.assertEqual(proto_ts.seconds, 0)
self.assertEqual(proto_ts.nanos, 0)
def test_datetime_to_proto_ts_conversion_none(self):
proto_ts = utils.proto_ts_from_datetime(None)
self.assertEqual(proto_ts.seconds, 0)
self.assertEqual(proto_ts.nanos, 0)