MatrixSynapse/tests/metrics/test_metric.py

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# -*- coding: utf-8 -*-
# Copyright 2015 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, 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()
counter.inc()
self.assertEquals(counter.render(), [
"scalar 3"
])
def test_vector(self):
counter = CounterMetric("vector", keys=["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):
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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",
])
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def test_vector(self):
vals = dict()
metric = CallbackMetric("values", lambda: vals, keys=["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 CacheMetricTestCase(unittest.TestCase):
def test_cache(self):
d = dict()
metric = CacheMetric("cache", lambda: len(d))
self.assertEquals(metric.render(), [
"cache:hits 0",
"cache:misses 0",
"cache:size 0",
])
metric.inc_misses()
d["key"] = "value"
self.assertEquals(metric.render(), [
"cache:hits 0",
"cache:misses 1",
"cache:size 1",
])
metric.inc_hits()
self.assertEquals(metric.render(), [
"cache:hits 1",
"cache:misses 1",
"cache:size 1",
])