ffd53d8536
Change-Id: I56a884962902a0633cd6dded0c1d877a116715b9
452 lines
16 KiB
Python
452 lines
16 KiB
Python
import random
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import time
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import unittest
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import nose.tools as nt
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from monasca_agent.common.aggregator import MetricsAggregator
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class TestUnitMonascaStatsd(unittest.TestCase):
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@staticmethod
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def sort_metrics(metrics):
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def sort_by(m):
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return (m['metric'], ','.join(m['dimensions'] or []))
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return sorted(metrics, key=sort_by)
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@staticmethod
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def sort_events(metrics):
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def sort_by(m):
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return (m['title'], m['text'], ','.join(m.get('tags', None) or []))
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return sorted(metrics, key=sort_by)
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def test_counter_normalization(self):
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stats = MetricsAggregator('myhost', interval=10)
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# Assert counters are normalized.
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stats.submit_packets('int:1|c')
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stats.submit_packets('int:4|c')
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stats.submit_packets('int:15|c')
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stats.submit_packets('float:5|c')
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metrics = self.sort_metrics(stats.flush())
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assert len(metrics) == 2
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floatc, intc = metrics
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nt.assert_equal(floatc['metric'], 'float')
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nt.assert_equal(floatc['points'][0][1], 0.5)
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nt.assert_equal(floatc['host'], 'myhost')
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nt.assert_equal(intc['metric'], 'int')
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nt.assert_equal(intc['points'][0][1], 2)
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nt.assert_equal(intc['host'], 'myhost')
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def test_histogram_normalization(self):
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stats = MetricsAggregator('myhost', interval=10)
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for i in range(5):
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stats.submit_packets('h1:1|h')
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for i in range(20):
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stats.submit_packets('h2:1|h')
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metrics = self.sort_metrics(stats.flush())
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_, _, h1count, _, _, _, _, h2count, _, _ = metrics
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nt.assert_equal(h1count['points'][0][1], 0.5)
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nt.assert_equal(h2count['points'][0][1], 2)
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def test_tags(self):
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stats = MetricsAggregator('myhost')
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stats.submit_packets('gauge:1|c')
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stats.submit_packets('gauge:2|c|@1')
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stats.submit_packets('gauge:4|c|#tag1,tag2')
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stats.submit_packets('gauge:8|c|#tag2,tag1') # Should be the same as above
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stats.submit_packets('gauge:16|c|#tag3,tag4')
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metrics = self.sort_metrics(stats.flush())
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assert len(metrics) == 3
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first, second, third = metrics
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nt.assert_equal(first['metric'], 'gauge')
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nt.assert_equal(first['dimensions'], None)
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nt.assert_equal(first['points'][0][1], 3)
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nt.assert_equal(first['host'], 'myhost')
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nt.assert_equal(second['metric'], 'gauge')
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nt.assert_equal(second['dimensions'], ('tag1', 'tag2'))
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nt.assert_equal(second['points'][0][1], 12)
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nt.assert_equal(second['host'], 'myhost')
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nt.assert_equal(third['metric'], 'gauge')
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nt.assert_equal(third['dimensions'], ('tag3', 'tag4'))
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nt.assert_equal(third['points'][0][1], 16)
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nt.assert_equal(third['host'], 'myhost')
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def test_counter(self):
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stats = MetricsAggregator('myhost')
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# Track some counters.
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stats.submit_packets('my.first.counter:1|c')
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stats.submit_packets('my.first.counter:5|c')
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stats.submit_packets('my.second.counter:1|c')
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stats.submit_packets('my.third.counter:3|c')
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# Ensure they roll up nicely.
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metrics = self.sort_metrics(stats.flush())
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assert len(metrics) == 3
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first, second, third = metrics
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nt.assert_equals(first['metric'], 'my.first.counter')
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nt.assert_equals(first['points'][0][1], 6)
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nt.assert_equals(first['host'], 'myhost')
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nt.assert_equals(second['metric'], 'my.second.counter')
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nt.assert_equals(second['points'][0][1], 1)
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nt.assert_equals(third['metric'], 'my.third.counter')
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nt.assert_equals(third['points'][0][1], 3)
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# Ensure that counters reset to zero.
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metrics = self.sort_metrics(stats.flush())
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first, second, third = metrics
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nt.assert_equals(first['metric'], 'my.first.counter')
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nt.assert_equals(first['points'][0][1], 0)
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nt.assert_equals(second['metric'], 'my.second.counter')
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nt.assert_equals(second['points'][0][1], 0)
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nt.assert_equals(third['metric'], 'my.third.counter')
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nt.assert_equals(third['points'][0][1], 0)
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def test_sampled_counter(self):
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# Submit a sampled counter.
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stats = MetricsAggregator('myhost')
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stats.submit_packets('sampled.counter:1|c|@0.5')
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metrics = stats.flush()
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assert len(metrics) == 1
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m = metrics[0]
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assert m['metric'] == 'sampled.counter'
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nt.assert_equal(m['points'][0][1], 2)
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def test_gauge(self):
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stats = MetricsAggregator('myhost')
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# Track some counters.
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stats.submit_packets('my.first.gauge:1|g')
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stats.submit_packets('my.first.gauge:5|g')
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stats.submit_packets('my.second.gauge:1.5|g')
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# Ensure that gauges roll up correctly.
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metrics = self.sort_metrics(stats.flush())
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assert len(metrics) == 2
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first, second = metrics
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nt.assert_equals(first['metric'], 'my.first.gauge')
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nt.assert_equals(first['points'][0][1], 5)
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nt.assert_equals(first['host'], 'myhost')
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nt.assert_equals(second['metric'], 'my.second.gauge')
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nt.assert_equals(second['points'][0][1], 1.5)
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# Ensure that old gauges get dropped due to old timestamps
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stats.gauge('my.first.gauge', 5)
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stats.gauge('my.first.gauge', 1, timestamp=1000000000)
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stats.gauge('my.second.gauge', 20, timestamp=1000000000)
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metrics = self.sort_metrics(stats.flush())
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assert len(metrics) == 1
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first = metrics[0]
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nt.assert_equals(first['metric'], 'my.first.gauge')
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nt.assert_equals(first['points'][0][1], 5)
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nt.assert_equals(first['host'], 'myhost')
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def test_sets(self):
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stats = MetricsAggregator('myhost')
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stats.submit_packets('my.set:10|s')
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stats.submit_packets('my.set:20|s')
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stats.submit_packets('my.set:20|s')
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stats.submit_packets('my.set:30|s')
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stats.submit_packets('my.set:30|s')
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stats.submit_packets('my.set:30|s')
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# Assert that it's treated normally.
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metrics = stats.flush()
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nt.assert_equal(len(metrics), 1)
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m = metrics[0]
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nt.assert_equal(m['metric'], 'my.set')
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nt.assert_equal(m['points'][0][1], 3)
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# Assert there are no more sets
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assert not stats.flush()
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def test_string_sets(self):
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stats = MetricsAggregator('myhost')
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stats.submit_packets('my.set:string|s')
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stats.submit_packets('my.set:sets|s')
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stats.submit_packets('my.set:sets|s')
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stats.submit_packets('my.set:test|s')
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stats.submit_packets('my.set:test|s')
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stats.submit_packets('my.set:test|s')
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# Assert that it's treated normally.
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metrics = stats.flush()
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nt.assert_equal(len(metrics), 1)
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m = metrics[0]
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nt.assert_equal(m['metric'], 'my.set')
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nt.assert_equal(m['points'][0][1], 3)
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# Assert there are no more sets
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assert not stats.flush()
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def test_rate(self):
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stats = MetricsAggregator('myhost')
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stats.submit_packets('my.rate:10|_dd-r')
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# Sleep 1 second so the time interval > 0
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time.sleep(1)
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stats.submit_packets('my.rate:40|_dd-r')
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# Check that the rate is calculated correctly
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metrics = stats.flush()
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nt.assert_equal(len(metrics), 1)
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m = metrics[0]
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nt.assert_equals(m['metric'], 'my.rate')
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nt.assert_equals(m['points'][0][1], 30)
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# Assert that no more rates are given
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assert not stats.flush()
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def test_gauge_sample_rate(self):
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stats = MetricsAggregator('myhost')
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# Submit a sampled gauge metric.
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stats.submit_packets('sampled.gauge:10|g|@0.1')
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# Assert that it's treated normally.
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metrics = stats.flush()
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nt.assert_equal(len(metrics), 1)
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m = metrics[0]
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nt.assert_equal(m['metric'], 'sampled.gauge')
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nt.assert_equal(m['points'][0][1], 10)
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def test_histogram(self):
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stats = MetricsAggregator('myhost')
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# Sample all numbers between 1-100 many times. This
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# means our percentiles should be relatively close to themselves.
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percentiles = range(100)
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random.shuffle(percentiles) # in place
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for i in percentiles:
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for j in xrange(20):
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for type_ in ['h', 'ms']:
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m = 'my.p:%s|%s' % (i, type_)
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stats.submit_packets(m)
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metrics = self.sort_metrics(stats.flush())
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def assert_almost_equal(i, j, e=1):
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# Floating point math?
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assert abs(i - j) <= e, "%s %s %s" % (i, j, e)
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nt.assert_equal(len(metrics), 5)
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p95, pavg, pcount, pmax, pmed = self.sort_metrics(metrics)
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nt.assert_equal(p95['metric'], 'my.p.95percentile')
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assert_almost_equal(p95['points'][0][1], 95, 10)
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assert_almost_equal(pmax['points'][0][1], 99, 1)
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assert_almost_equal(pmed['points'][0][1], 50, 2)
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assert_almost_equal(pavg['points'][0][1], 50, 2)
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assert_almost_equal(pcount['points'][0][1], 4000, 0) # 100 * 20 * 2
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nt.assert_equals(p95['host'], 'myhost')
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# Ensure that histograms are reset.
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metrics = self.sort_metrics(stats.flush())
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assert not metrics
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def test_sampled_histogram(self):
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# Submit a sampled histogram.
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stats = MetricsAggregator('myhost')
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stats.submit_packets('sampled.hist:5|h|@0.5')
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# Assert we scale up properly.
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metrics = self.sort_metrics(stats.flush())
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p95, pavg, pcount, pmax, pmed = self.sort_metrics(metrics)
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nt.assert_equal(pcount['points'][0][1], 2)
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for p in [p95, pavg, pmed, pmax]:
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nt.assert_equal(p['points'][0][1], 5)
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def test_batch_submission(self):
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# Submit a sampled histogram.
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stats = MetricsAggregator('myhost')
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metrics = [
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'counter:1|c',
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'counter:1|c',
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'gauge:1|g'
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]
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packet = "\n".join(metrics)
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stats.submit_packets(packet)
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metrics = self.sort_metrics(stats.flush())
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nt.assert_equal(2, len(metrics))
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counter, gauge = metrics
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assert counter['points'][0][1] == 2
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assert gauge['points'][0][1] == 1
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def test_bad_packets_throw_errors(self):
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packets = [
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'missing.value.and.type',
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'missing.type:2',
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'missing.value|c',
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'2|c',
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'unknown.type:2|z',
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'string.value:abc|c',
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'string.sample.rate:0|c|@abc',
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# Bad event-like packets
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'_ev{1,2}:bad_header'
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'_e{1,}:invalid|headers',
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'_e:missing|size|headers',
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'_e:{1,1}:t|t|t:bad_meta|h',
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]
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stats = MetricsAggregator('myhost')
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for packet in packets:
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try:
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stats.submit_packets(packet)
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except Exception:
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assert True
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else:
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assert False, 'invalid : %s' % packet
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def test_metrics_expiry(self):
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# Ensure metrics eventually expire and stop submitting.
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stats = MetricsAggregator('myhost', expiry_seconds=1)
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stats.submit_packets('test.counter:123|c')
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# Ensure points keep submitting
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assert stats.flush()
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assert stats.flush()
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time.sleep(0.5)
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assert stats.flush()
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# Now sleep for longer than the expiry window and ensure
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# no points are submitted
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time.sleep(2)
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m = stats.flush()
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assert not m, str(m)
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# If we submit again, we're all good.
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stats.submit_packets('test.counter:123|c')
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assert stats.flush()
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def test_histogram_counter(self):
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# Test whether histogram.count == increment
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# same deal with a sample rate
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cnt = 100000
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for run in [1, 2]:
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stats = MetricsAggregator('myhost')
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for i in xrange(cnt):
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if run == 2:
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stats.submit_packets('test.counter:1|c|@0.5')
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stats.submit_packets('test.hist:1|ms|@0.5')
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else:
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stats.submit_packets('test.counter:1|c')
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stats.submit_packets('test.hist:1|ms')
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metrics = self.sort_metrics(stats.flush())
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assert len(metrics) > 0
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nt.assert_equal([m['points'][0][1]
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for m in metrics if m['metric'] == 'test.counter'], [cnt * run])
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nt.assert_equal([m['points'][0][1]
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for m in metrics if m['metric'] == 'test.hist.count'], [cnt * run])
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def test_scientific_notation(self):
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stats = MetricsAggregator('myhost', interval=10)
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stats.submit_packets('test.scinot:9.512901e-05|g')
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metrics = self.sort_metrics(stats.flush())
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assert len(metrics) == 1
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ts, val = metrics[0].get('points')[0]
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nt.assert_almost_equal(val, 9.512901e-05)
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def test_event_tags(self):
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stats = MetricsAggregator('myhost')
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stats.submit_packets('_e{6,4}:title1|text')
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stats.submit_packets('_e{6,4}:title2|text|#t1')
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stats.submit_packets('_e{6,4}:title3|text|#t1,t2:v2,t3,t4')
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stats.submit_packets('_e{6,4}:title4|text|k:key|p:normal|#t1,t2')
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events = self.sort_events(stats.flush_events())
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assert len(events) == 4
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first, second, third, fourth = events
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try:
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first['dimensions']
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except Exception:
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assert True
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else:
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assert False, "event['tags'] shouldn't be defined when no tags aren't explicited in the packet"
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nt.assert_equal(first['title'], 'title1')
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nt.assert_equal(first['text'], 'text')
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nt.assert_equal(second['title'], 'title2')
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nt.assert_equal(second['text'], 'text')
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nt.assert_equal(second['dimensions'], sorted(['t1']))
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nt.assert_equal(third['title'], 'title3')
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nt.assert_equal(third['text'], 'text')
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nt.assert_equal(third['dimensions'], sorted(['t1', 't2:v2', 't3', 't4']))
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nt.assert_equal(fourth['title'], 'title4')
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nt.assert_equal(fourth['text'], 'text')
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nt.assert_equal(fourth['aggregation_key'], 'key')
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nt.assert_equal(fourth['priority'], 'normal')
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nt.assert_equal(fourth['dimensions'], sorted(['t1', 't2']))
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def test_event_title(self):
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stats = MetricsAggregator('myhost')
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stats.submit_packets('_e{0,4}:|text')
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stats.submit_packets(u'_e{9,4}:2intitul<75><6C>|text')
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stats.submit_packets('_e{14,4}:3title content|text')
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stats.submit_packets('_e{14,4}:4title|content|text')
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stats.submit_packets('_e{13,4}:5title\\ntitle|text') # \n stays escaped
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events = self.sort_events(stats.flush_events())
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assert len(events) == 5
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first, second, third, fourth, fifth = events
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nt.assert_equal(first['title'], '')
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nt.assert_equal(second['title'], u'2intitul<EFBFBD><EFBFBD>')
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nt.assert_equal(third['title'], '3title content')
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nt.assert_equal(fourth['title'], '4title|content')
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nt.assert_equal(fifth['title'], '5title\\ntitle')
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def test_event_text(self):
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stats = MetricsAggregator('myhost')
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stats.submit_packets('_e{2,0}:t1|')
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stats.submit_packets('_e{2,12}:t2|text|content')
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stats.submit_packets('_e{2,23}:t3|First line\\nSecond line') # \n is a newline
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stats.submit_packets(u'_e{2,19}:t4|<7C><><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD>U <20><><EFBFBD><EFBFBD><EFBFBD>U <20><><EFBFBD><EFBFBD>u T0<54><30> <20><><EFBFBD>') # utf-8 compliant
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events = self.sort_events(stats.flush_events())
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assert len(events) == 4
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first, second, third, fourth = events
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nt.assert_equal(first['text'], '')
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nt.assert_equal(second['text'], 'text|content')
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nt.assert_equal(third['text'], 'First line\nSecond line')
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nt.assert_equal(fourth['text'], u'<EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD>U <20><><EFBFBD><EFBFBD><EFBFBD>U <20><><EFBFBD><EFBFBD>u T0<54><30> <20><><EFBFBD>')
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if __name__ == "__main__":
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unittest.main()
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