def test_small_scale(self):
with self.assertRaises(ValueError):
distribution.GeometricBucketer(growth_factor=-1)
with self.assertRaises(ValueError):
distribution.GeometricBucketer(growth_factor=0)
with self.assertRaises(ValueError):
distribution.GeometricBucketer(growth_factor=1)
def test_populate_canonical(self):
pb = metrics_pb2.MetricsData()
m = metrics.DistributionMetric('test')
m._populate_value(pb,
distribution.Distribution(distribution.GeometricBucketer()))
self.assertEquals(pb.distribution.spec_type,
metrics_pb2.PrecomputedDistribution.CANONICAL_POWERS_OF_10_P_0_2)
m._populate_value(pb,
distribution.Distribution(distribution.GeometricBucketer(2)))
self.assertEquals(pb.distribution.spec_type,
metrics_pb2.PrecomputedDistribution.CANONICAL_POWERS_OF_2)
m._populate_value(pb,
distribution.Distribution(distribution.GeometricBucketer(10)))
self.assertEquals(pb.distribution.spec_type,
metrics_pb2.PrecomputedDistribution.CANONICAL_POWERS_OF_10)
def __init__(self,
name,
is_cumulative=True,
bucketer=None,
target=None,
fields=None,
start_time=None,
time_fn=time.time):
super(DistributionMetric, self).__init__(name, target, fields)
self._start_time = start_time or int(
time_fn() * MICROSECONDS_PER_SECOND)
if bucketer is None:
bucketer = distribution.GeometricBucketer()
self.is_cumulative = is_cumulative
self.bucketer = bucketer
def test_populate_custom(self):
pb = metrics_pb2.MetricsData()
m = metrics.DistributionMetric('test')
m._populate_value(pb,
distribution.Distribution(distribution.GeometricBucketer(4)))
self.assertEquals(pb.distribution.spec_type,
metrics_pb2.PrecomputedDistribution.CUSTOM_PARAMETERIZED)
self.assertEquals(0, pb.distribution.width)
self.assertEquals(4, pb.distribution.growth_factor)
self.assertEquals(100, pb.distribution.num_buckets)
m._populate_value(pb,
distribution.Distribution(distribution.FixedWidthBucketer(10)))
self.assertEquals(pb.distribution.spec_type,
metrics_pb2.PrecomputedDistribution.CUSTOM_PARAMETERIZED)
self.assertEquals(10, pb.distribution.width)
self.assertEquals(0, pb.distribution.growth_factor)
self.assertEquals(100, pb.distribution.num_buckets)
def test_add(self):
d = distribution.Distribution(distribution.GeometricBucketer())
self.assertEqual(0, d.sum)
self.assertEqual(0, d.count)
self.assertEqual({}, d.buckets)
d.add(1)
d.add(10)
d.add(100)
self.assertEqual(111, d.sum)
self.assertEqual(3, d.count)
self.assertEqual({2: 1, 6: 1, 11: 1}, d.buckets)
d.add(50)
self.assertEqual(161, d.sum)
self.assertEqual(4, d.count)
self.assertEqual({2: 1, 6: 1, 10: 1, 11: 1}, d.buckets)
def test_large_size(self):
b = distribution.GeometricBucketer(growth_factor=4,
num_finite_buckets=4)
self.assertBucketCounts(b, 6)
self.assertBoundaries(b, [1, 4, 16, 64])
def test_zero_size(self):
b = distribution.GeometricBucketer(num_finite_buckets=0)
self.assertBucketCounts(b, 2)
self.assertBoundaries(b, [])
def test_negative_size(self):
with self.assertRaises(ValueError):
distribution.GeometricBucketer(num_finite_buckets=-1)
