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_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_flushing_in_thread(self):
dog = DogStatsApi()
dog.start(roll_up_interval=1,
flush_interval=1,
flush_in_greenlet=True,
api_key=API_KEY)
now = time.time()
dog.gauge('test.dogapi.greenlet.gauge.%s' % now, 3)
dog.increment('test.dogapi.greenlet.counter.%s' % now)
dog.increment('test.dogapi.greenlet.counter.%s' % now)
dog.histogram('test.dogapi.greenlet.histogram.%s' % now, 20)
dog.histogram('test.dogapi.greenlet.histogram.%s' % now, 30)
time.sleep(3)
assert 1 <= dog.flush_count <= 5
def test_flushing_in_thread(self):
dog = DogStatsApi()
dog.start(roll_up_interval=1,
flush_interval=1,
flush_in_greenlet=True,
api_key=API_KEY)
now = time.time()
dog.gauge('test.dogapi.greenlet.gauge.%s' % now , 3)
dog.increment('test.dogapi.greenlet.counter.%s' % now)
dog.increment('test.dogapi.greenlet.counter.%s' % now)
dog.histogram('test.dogapi.greenlet.histogram.%s' % now, 20)
dog.histogram('test.dogapi.greenlet.histogram.%s' % now, 30)
time.sleep(3)
assert 1 <= dog.flush_count <= 5
def measure_thousands_of_metrics():
dog = DogStatsApi()
dog.start(api_key='apikey_3', api_host="https://app.datad0g.com")
yappi.start()
@dog.timed('timed')
def timed():
pass
for i in range(100):
for j in range(1000):
name = j % 100
dog.gauge('gauge.%s' % name, j)
dog.increment('counter.%s' % name, j)
dog.histogram('histogram.%s' % name, j)
timed()
print('run %s' % i)
yappi.print_stats(sort_type=yappi.SORTTYPE_TSUB, sort_order=yappi.SORTORDER_DESC)
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 measure_thousands_of_metrics():
dog = DogStatsApi()
dog.start(api_key='apikey_3', api_host="https://app.datad0g.com")
yappi.start()
@dog.timed('timed')
def timed():
pass
for i in range(100):
for j in range(1000):
name = j % 100
dog.gauge('gauge.%s' % name, j)
dog.increment('counter.%s' % name, j)
dog.histogram('histogram.%s' % name, j)
timed()
print('run %s' % i)
yappi.print_stats(sort_type=yappi.SORTTYPE_TSUB,
sort_order=yappi.SORTORDER_DESC)
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)