def test_compute_shard_distribution(self):
# Check that shard distribution isn't obviously broken.
nshards = 7
mean_samples_per_shard = 10000
nsamples = nshards * mean_samples_per_shard
distribution = [0] * nshards
for n in range(0, nsamples):
shard = Sharder.compute_shard(str(n), nshards)
distribution[shard] += 1
variance = sum([(x - mean_samples_per_shard) ** 2 for x in distribution]) / nshards
stddev = math.sqrt(variance)
# We arbitrarily assert that a stddev of less than 1% of the mean is good enough
# for sanity-checking purposes.
self.assertLess(stddev, 100)
def test_compute_shard_distribution(self):
# Check that shard distribution isn't obviously broken.
nshards = 7
mean_samples_per_shard = 10000
nsamples = nshards * mean_samples_per_shard
distribution = [0] * nshards
for n in range(0, nsamples):
shard = Sharder.compute_shard(str(n), nshards)
distribution[shard] += 1
variance = sum([(x - mean_samples_per_shard) ** 2 for x in distribution]) / nshards
stddev = math.sqrt(variance)
# We arbitrarily assert that a stddev of less than 1% of the mean is good enough
# for sanity-checking purposes.
self.assertLess(stddev, 100)
def test_compute_shard(self):
# Spot-check a couple of values, to make sure compute_shard doesn't do something
# completely degenerate.
self.assertEqual(31, Sharder.compute_shard('', 42))
self.assertEqual(35, Sharder.compute_shard('foo', 42))
self.assertEqual(5, Sharder.compute_shard('bar', 42))
def test_compute_shard(self):
# Spot-check a couple of values, to make sure compute_shard doesn't do something
# completely degenerate.
self.assertEqual(31, Sharder.compute_shard('', 42))
self.assertEqual(35, Sharder.compute_shard('foo', 42))
self.assertEqual(5, Sharder.compute_shard('bar', 42))
