def test_histogram_percentiles(self):
dog = DogStatsApi()
dog.start(roll_up_interval=10, flush_in_thread=False)
reporter = dog.reporter = MemoryReporter()
# Sample all numbers between 1-100 many times. This
# means our percentiles should be relatively close to themselves.
percentiles = list(range(100))
random.shuffle(percentiles) # in place
for i in percentiles:
for j in range(20):
dog.histogram('percentiles', i, 1000.0)
dog.flush(2000.0)
metrics = reporter.metrics
def assert_almost_equal(i, j, e=1):
# Floating point math?
assert abs(i - j) <= e, "%s %s %s" % (i, j, e)
nt.assert_equal(len(metrics), 8)
p75, p85, p95, p99, _, _, _, _ = self.sort_metrics(metrics)
nt.assert_equal(p75['metric'], 'percentiles.75percentile')
nt.assert_equal(p75['points'][0][0], 1000.0)
assert_almost_equal(p75['points'][0][1], 75, 8)
assert_almost_equal(p85['points'][0][1], 85, 8)
assert_almost_equal(p95['points'][0][1], 95, 8)
assert_almost_equal(p99['points'][0][1], 99, 8)
def test_timed_decorator(self):
dog = DogStatsApi()
dog.start(roll_up_interval=1, flush_in_thread=False)
reporter = dog.reporter = MemoryReporter()
@dog.timed('timed.test')
def func(a, b, c=1, d=1):
"""docstring"""
return (a, b, c, d)
nt.assert_equal(func.__name__, 'func')
nt.assert_equal(func.__doc__, 'docstring')
result = func(1, 2, d=3)
# Assert it handles args and kwargs correctly.
nt.assert_equal(result, (1, 2, 1, 3))
time.sleep(1) # Argh. I hate this.
dog.flush()
metrics = self.sort_metrics(reporter.metrics)
nt.assert_equal(len(metrics), 8)
(_, _, _, _, avg, count, max_, min_) = metrics
nt.assert_equal(avg['metric'], 'timed.test.avg')
nt.assert_equal(count['metric'], 'timed.test.count')
nt.assert_equal(max_['metric'], 'timed.test.max')
nt.assert_equal(min_['metric'], 'timed.test.min')
def test_disabled_mode(self):
dog = DogStatsApi()
reporter = dog.reporter = MemoryReporter()
dog.start(disabled=True, flush_interval=1, roll_up_interval=1)
dog.gauge('testing', 1, timestamp=1000)
dog.gauge('testing', 2, timestamp=1000)
dog.flush(2000.0)
assert not reporter.metrics
def test_custom_host_and_device(self):
dog = DogStatsApi()
dog.start(roll_up_interval=1, flush_in_thread=False, host='host', device='dev')
reporter = dog.reporter = MemoryReporter()
dog.gauge('my.gauge', 1, 100.0)
dog.flush(1000)
metric = reporter.metrics[0]
nt.assert_equal(metric['device'], 'dev')
nt.assert_equal(metric['host'], 'host')
def test_default_host_and_device(self):
dog = DogStatsApi()
dog.start(roll_up_interval=1, flush_in_thread=False)
reporter = dog.reporter = MemoryReporter()
dog.gauge('my.gauge', 1, 100.0)
dog.flush(1000)
metric = reporter.metrics[0]
assert not metric['device']
assert metric['host']
def test_host(self):
dog = DogStatsApi()
dog.start(roll_up_interval=10, flush_in_thread=False, host='default')
reporter = dog.reporter = MemoryReporter()
# Post the same metric with different tags.
dog.gauge('gauge', 12, timestamp=100.0, host='') # unset the host
dog.gauge('gauge', 10, timestamp=100.0)
dog.gauge('gauge', 15, timestamp=100.0, host='test')
dog.gauge('gauge', 15, timestamp=100.0, host='test')
dog.increment('counter', timestamp=100.0)
dog.increment('counter', timestamp=100.0)
dog.increment('counter', timestamp=100.0, host='test')
dog.increment('counter', timestamp=100.0, host='test', tags=['tag'])
dog.increment('counter', timestamp=100.0, host='test', tags=['tag'])
dog.flush(200.0)
metrics = self.sort_metrics(reporter.metrics)
nt.assert_equal(len(metrics), 6)
[c1, c2, c3, g1, g2, g3] = metrics
(nt.assert_equal(c['metric'], 'counter') for c in [c1, c2, c3])
nt.assert_equal(c1['host'], 'default')
nt.assert_equal(c1['tags'], None)
nt.assert_equal(c1['points'][0][1], 2)
nt.assert_equal(c2['host'], 'test')
nt.assert_equal(c2['tags'], None)
nt.assert_equal(c2['points'][0][1], 1)
nt.assert_equal(c3['host'], 'test')
nt.assert_equal(c3['tags'], ['tag'])
nt.assert_equal(c3['points'][0][1], 2)
(nt.assert_equal(g['metric'], 'gauge') for g in [g1, g2, g3])
nt.assert_equal(g1['host'], '')
nt.assert_equal(g1['points'][0][1], 12)
nt.assert_equal(g2['host'], 'default')
nt.assert_equal(g2['points'][0][1], 10)
nt.assert_equal(g3['host'], 'test')
nt.assert_equal(g3['points'][0][1], 15)
# Ensure histograms work as well.
@dog.timed('timed', host='test')
def test():
pass
test()
dog.histogram('timed', 20, timestamp=300.0, host='test')
reporter.metrics = []
dog.flush(400)
for metric in reporter.metrics:
assert metric['host'] == 'test'
def test_tags(self):
dog = DogStatsApi()
dog.start(roll_up_interval=10, flush_in_thread=False)
reporter = dog.reporter = MemoryReporter()
# Post the same metric with different tags.
dog.gauge('gauge', 10, timestamp=100.0)
dog.gauge('gauge', 15, timestamp=100.0, tags=['env:production', 'db'])
dog.gauge('gauge', 20, timestamp=100.0, tags=['env:staging'])
dog.increment('counter', timestamp=100.0)
dog.increment('counter',
timestamp=100.0,
tags=['env:production', 'db'])
dog.increment('counter', timestamp=100.0, tags=['env:staging'])
dog.flush(200.0)
metrics = self.sort_metrics(reporter.metrics)
nt.assert_equal(len(metrics), 6)
[c1, c2, c3, g1, g2, g3] = metrics
(nt.assert_equal(c['metric'], 'counter') for c in [c1, c2, c3])
nt.assert_equal(c1['tags'], None)
nt.assert_equal(c1['points'][0][1], 1)
nt.assert_equal(c2['tags'], ['env:production', 'db'])
nt.assert_equal(c2['points'][0][1], 1)
nt.assert_equal(c3['tags'], ['env:staging'])
nt.assert_equal(c3['points'][0][1], 1)
(nt.assert_equal(c['metric'], 'gauge') for c in [g1, g2, g3])
nt.assert_equal(g1['tags'], None)
nt.assert_equal(g1['points'][0][1], 10)
nt.assert_equal(g2['tags'], ['env:production', 'db'])
nt.assert_equal(g2['points'][0][1], 15)
nt.assert_equal(g3['tags'], ['env:staging'])
nt.assert_equal(g3['points'][0][1], 20)
# Ensure histograms work as well.
@dog.timed('timed', tags=['version:1'])
def test():
pass
test()
dog.histogram('timed', 20, timestamp=300.0, tags=['db', 'version:2'])
reporter.metrics = []
dog.flush(400)
for metric in reporter.metrics:
assert metric['tags'] # this is enough
def test_tags(self):
dog = DogStatsApi()
dog.start(roll_up_interval=10, flush_in_thread=False)
reporter = dog.reporter = MemoryReporter()
# Post the same metric with different tags.
dog.gauge('gauge', 10, timestamp=100.0)
dog.gauge('gauge', 15, timestamp=100.0, tags=['env:production', 'db'])
dog.gauge('gauge', 20, timestamp=100.0, tags=['env:staging'])
dog.increment('counter', timestamp=100.0)
dog.increment('counter', timestamp=100.0, tags=['env:production', 'db'])
dog.increment('counter', timestamp=100.0, tags=['env:staging'])
dog.flush(200.0)
metrics = self.sort_metrics(reporter.metrics)
nt.assert_equal(len(metrics), 6)
[c1, c2, c3, g1, g2, g3] = metrics
(nt.assert_equal(c['metric'], 'counter') for c in [c1, c2, c3])
nt.assert_equal(c1['tags'], None)
nt.assert_equal(c1['points'][0][1], 1)
nt.assert_equal(c2['tags'], ['env:production', 'db'])
nt.assert_equal(c2['points'][0][1], 1)
nt.assert_equal(c3['tags'], ['env:staging'])
nt.assert_equal(c3['points'][0][1], 1)
(nt.assert_equal(c['metric'], 'gauge') for c in [g1, g2, g3])
nt.assert_equal(g1['tags'], None)
nt.assert_equal(g1['points'][0][1], 10)
nt.assert_equal(g2['tags'], ['env:production', 'db'])
nt.assert_equal(g2['points'][0][1], 15)
nt.assert_equal(g3['tags'], ['env:staging'])
nt.assert_equal(g3['points'][0][1], 20)
# Ensure histograms work as well.
@dog.timed('timed', tags=['version:1'])
def test():
pass
test()
dog.histogram('timed', 20, timestamp=300.0, tags=['db', 'version:2'])
reporter.metrics = []
dog.flush(400)
for metric in reporter.metrics:
assert metric['tags'] # this is enough
def test_counter(self):
# Create some fake metrics.
dog = DogStatsApi()
dog.start(roll_up_interval=10, flush_in_thread=False)
reporter = dog.reporter = MemoryReporter()
dog.increment('test.counter.1', timestamp=1000.0)
dog.increment('test.counter.1', value=2, timestamp=1005.0)
dog.increment('test.counter.2', timestamp=1015.0)
dog.increment('test.counter.3', timestamp=1025.0)
dog.flush(1021.0)
# Assert they've been properly flushed.
metrics = self.sort_metrics(reporter.metrics)
nt.assert_equal(len(metrics), 2)
(first, second) = metrics
nt.assert_equal(first['metric'], 'test.counter.1')
nt.assert_equal(first['points'][0][0], 1000.0)
nt.assert_equal(first['points'][0][1], 3)
nt.assert_equal(second['metric'], 'test.counter.2')
# Flush again and make sure we're progressing.
reporter.metrics = []
dog.flush(1030.0)
nt.assert_equal(len(reporter.metrics), 1)
# Finally, make sure we've flushed all metrics.
reporter.metrics = []
dog.flush(1050.0)
nt.assert_equal(len(reporter.metrics), 0)
def test_gauge(self):
# Create some fake metrics.
dog = DogStatsApi()
dog.start(roll_up_interval=10, flush_in_thread=False)
reporter = dog.reporter = MemoryReporter()
dog.gauge('test.gauge.1', 20, 100.0)
dog.gauge('test.gauge.1', 22, 105.0)
dog.gauge('test.gauge.2', 30, 115.0)
dog.gauge('test.gauge.3', 30, 125.0)
dog.flush(120.0)
# Assert they've been properly flushed.
metrics = self.sort_metrics(reporter.metrics)
nt.assert_equal(len(metrics), 2)
(first, second) = metrics
nt.assert_equal(first['metric'], 'test.gauge.1')
nt.assert_equal(first['points'][0][0], 100.0)
nt.assert_equal(first['points'][0][1], 22)
nt.assert_equal(second['metric'], 'test.gauge.2')
# Flush again and make sure we're progressing.
reporter.metrics = []
dog.flush(130.0)
nt.assert_equal(len(reporter.metrics), 1)
# Finally, make sure we've flushed all metrics.
reporter.metrics = []
dog.flush(150.0)
nt.assert_equal(len(reporter.metrics), 0)
def test_histogram_percentiles(self):
dog = DogStatsApi()
dog.start(roll_up_interval=10, flush_in_thread=False)
reporter = dog.reporter = MemoryReporter()
# Sample all numbers between 1-100 many times. This
# means our percentiles should be relatively close to themselves.
percentiles = list(range(100))
random.shuffle(percentiles) # in place
for i in percentiles:
for j in range(20):
dog.histogram('percentiles', i, 1000.0)
dog.flush(2000.0)
metrics = reporter.metrics
def assert_almost_equal(i, j, e=1):
# Floating point math?
assert abs(i - j) <= e, "%s %s %s" % (i, j, e)
nt.assert_equal(len(metrics), 8)
p75, p85, p95, p99, _, _, _, _ = self.sort_metrics(metrics)
nt.assert_equal(p75['metric'], 'percentiles.75percentile')
nt.assert_equal(p75['points'][0][0], 1000.0)
assert_almost_equal(p75['points'][0][1], 75, 8)
assert_almost_equal(p85['points'][0][1], 85, 8)
assert_almost_equal(p95['points'][0][1], 95, 8)
assert_almost_equal(p99['points'][0][1], 99, 8)
def test_histogram(self):
dog = DogStatsApi()
dog.start(roll_up_interval=10, flush_in_thread=False)
reporter = dog.reporter = MemoryReporter()
# Add some histogram metrics.
dog.histogram('histogram.1', 20, 100.0)
dog.histogram('histogram.1', 30, 105.0)
dog.histogram('histogram.1', 40, 106.0)
dog.histogram('histogram.1', 50, 106.0)
dog.histogram('histogram.1', 30, 110.0)
dog.histogram('histogram.1', 50, 115.0)
dog.histogram('histogram.1', 40, 116.0)
dog.histogram('histogram.2', 40, 100.0)
dog.histogram('histogram.3', 50, 134.0)
# Flush and ensure they roll up properly.
dog.flush(120.0)
metrics = self.sort_metrics(reporter.metrics)
nt.assert_equal(len(metrics), 24)
# Test histograms elsewhere.
(h1751, h1851, h1951, h1991, h1avg1, h1cnt1, h1max1, h1min1,
_, _, _, _, h2avg1, h2cnt1, h2max1, h2min1,
h1752, _, _, h1992, h1avg2, h1cnt2, h1max2, h1min2) = metrics
nt.assert_equal(h1avg1['metric'], 'histogram.1.avg')
nt.assert_equal(h1avg1['points'][0][0], 100.0)
nt.assert_equal(h1avg1['points'][0][1], 35)
nt.assert_equal(h1cnt1['metric'], 'histogram.1.count')
nt.assert_equal(h1cnt1['points'][0][0], 100.0)
nt.assert_equal(h1cnt1['points'][0][1], 4)
nt.assert_equal(h1min1['metric'], 'histogram.1.min')
nt.assert_equal(h1min1['points'][0][1], 20)
nt.assert_equal(h1max1['metric'], 'histogram.1.max')
nt.assert_equal(h1max1['points'][0][1], 50)
nt.assert_equal(h1751['metric'], 'histogram.1.75percentile')
nt.assert_equal(h1751['points'][0][1], 40)
nt.assert_equal(h1991['metric'], 'histogram.1.99percentile')
nt.assert_equal(h1991['points'][0][1], 50)
nt.assert_equal(h1avg2['metric'], 'histogram.1.avg')
nt.assert_equal(h1avg2['points'][0][0], 110.0)
nt.assert_equal(h1avg2['points'][0][1], 40)
nt.assert_equal(h1cnt2['metric'], 'histogram.1.count')
nt.assert_equal(h1cnt2['points'][0][0], 110.0)
nt.assert_equal(h1cnt2['points'][0][1], 3)
nt.assert_equal(h1752['metric'], 'histogram.1.75percentile')
nt.assert_equal(h1752['points'][0][0], 110.0)
nt.assert_equal(h1752['points'][0][1], 40.0)
nt.assert_equal(h1992['metric'], 'histogram.1.99percentile')
nt.assert_equal(h1992['points'][0][0], 110.0)
nt.assert_equal(h1992['points'][0][1], 50.0)
nt.assert_equal(h2avg1['metric'], 'histogram.2.avg')
nt.assert_equal(h2avg1['points'][0][0], 100.0)
nt.assert_equal(h2avg1['points'][0][1], 40)
nt.assert_equal(h2cnt1['metric'], 'histogram.2.count')
nt.assert_equal(h2cnt1['points'][0][0], 100.0)
nt.assert_equal(h2cnt1['points'][0][1], 1)
# Flush again ensure they're gone.
dog.reporter.metrics = []
dog.flush(140.0)
nt.assert_equal(len(dog.reporter.metrics), 8)
dog.reporter.metrics = []
dog.flush(200.0)
nt.assert_equal(len(dog.reporter.metrics), 0)