synapse-old/tests/metrics/test_metric.py

162 lines
3.9 KiB
Python

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