mirror of
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161 lines
3.9 KiB
Python
161 lines
3.9 KiB
Python
# -*- coding: utf-8 -*-
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# Copyright 2015, 2016 OpenMarket Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from tests import unittest
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from synapse.metrics.metric import (
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CounterMetric, CallbackMetric, DistributionMetric, CacheMetric
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)
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class CounterMetricTestCase(unittest.TestCase):
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def test_scalar(self):
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counter = CounterMetric("scalar")
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self.assertEquals(counter.render(), [
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'scalar 0',
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])
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counter.inc()
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self.assertEquals(counter.render(), [
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'scalar 1',
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])
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counter.inc_by(2)
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self.assertEquals(counter.render(), [
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'scalar 3'
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])
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def test_vector(self):
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counter = CounterMetric("vector", labels=["method"])
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# Empty counter doesn't yet know what values it has
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self.assertEquals(counter.render(), [])
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counter.inc("GET")
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self.assertEquals(counter.render(), [
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'vector{method="GET"} 1',
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])
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counter.inc("GET")
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counter.inc("PUT")
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self.assertEquals(counter.render(), [
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'vector{method="GET"} 2',
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'vector{method="PUT"} 1',
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])
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class CallbackMetricTestCase(unittest.TestCase):
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def test_scalar(self):
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d = dict()
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metric = CallbackMetric("size", lambda: len(d))
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self.assertEquals(metric.render(), [
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'size 0',
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])
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d["key"] = "value"
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self.assertEquals(metric.render(), [
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'size 1',
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])
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def test_vector(self):
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vals = dict()
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metric = CallbackMetric("values", lambda: vals, labels=["type"])
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self.assertEquals(metric.render(), [])
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# Keys have to be tuples, even if they're 1-element
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vals[("foo",)] = 1
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vals[("bar",)] = 2
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self.assertEquals(metric.render(), [
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'values{type="bar"} 2',
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'values{type="foo"} 1',
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])
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class DistributionMetricTestCase(unittest.TestCase):
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def test_scalar(self):
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metric = DistributionMetric("thing")
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self.assertEquals(metric.render(), [
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'thing:count 0',
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'thing:total 0',
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])
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metric.inc_by(500)
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self.assertEquals(metric.render(), [
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'thing:count 1',
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'thing:total 500',
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])
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def test_vector(self):
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metric = DistributionMetric("queries", labels=["verb"])
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self.assertEquals(metric.render(), [])
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metric.inc_by(300, "SELECT")
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metric.inc_by(200, "SELECT")
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metric.inc_by(800, "INSERT")
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self.assertEquals(metric.render(), [
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'queries:count{verb="INSERT"} 1',
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'queries:count{verb="SELECT"} 2',
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'queries:total{verb="INSERT"} 800',
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'queries:total{verb="SELECT"} 500',
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])
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class CacheMetricTestCase(unittest.TestCase):
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def test_cache(self):
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d = dict()
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metric = CacheMetric("cache", lambda: len(d))
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self.assertEquals(metric.render(), [
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'cache:hits 0',
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'cache:total 0',
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'cache:size 0',
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])
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metric.inc_misses()
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d["key"] = "value"
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self.assertEquals(metric.render(), [
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'cache:hits 0',
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'cache:total 1',
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'cache:size 1',
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])
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metric.inc_hits()
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self.assertEquals(metric.render(), [
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'cache:hits 1',
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'cache:total 2',
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'cache:size 1',
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])
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