async def fetch_metrics(
url: str, fmt: str = None, interval: float = 1.0, loop: BaseEventLoop = None
):
""" Fetch metrics from the service endpoint using different formats.
This coroutine runs 'n' times, with a brief interval in between, before
exiting.
"""
if fmt is None:
# Randomly choose a format to request metrics in.
choice = random.choice((TEXT, BINARY))
else:
assert fmt in header_kinds
choice = fmt
print(f"fetching metrics in {choice} format")
async with aiohttp.ClientSession() as session:
async with session.get(url, headers={ACCEPT: header_kinds[choice]}) as resp:
assert resp.status == 200
content = await resp.read()
content_type = resp.headers.get(CONTENT_TYPE)
print("Content-Type: {}".format(content_type))
print("size: {}".format(len(content)))
if choice == "text":
print(content.decode())
else:
print(content)
# Decode the binary metrics into protobuf objects
print(prometheus_metrics_proto.decode(content))
# schedule another fetch
loop.call_later(interval, fetch_task, url, fmt, interval, loop)
async def test_counter(self):
""" check counter metric export """
# Add some metrics
data = (
({
"data": 1
}, 100),
({
"data": "2"
}, 200),
({
"data": 3
}, 300),
({
"data": 1
}, 400),
)
c = Counter("test_counter", "Test Counter.", {"test": "test_counter"})
self.server.register(c)
for i in data:
c.set(i[0], i[1])
expected_data = """# HELP test_counter Test Counter.
# TYPE test_counter counter
test_counter{data="1",test="test_counter"} 400
test_counter{data="2",test="test_counter"} 200
test_counter{data="3",test="test_counter"} 300
"""
async with aiohttp.ClientSession() as session:
# Fetch as text
async with session.get(self.metrics_url,
headers={ACCEPT:
text.TEXT_CONTENT_TYPE}) as resp:
self.assertEqual(resp.status, 200)
content = await resp.read()
self.assertEqual(text.TEXT_CONTENT_TYPE,
resp.headers.get(CONTENT_TYPE))
self.assertEqual(expected_data, content.decode())
# Fetch as binary
async with session.get(self.metrics_url,
headers={
ACCEPT: binary.BINARY_CONTENT_TYPE
}) as resp:
self.assertEqual(resp.status, 200)
content = await resp.read()
self.assertEqual(binary.BINARY_CONTENT_TYPE,
resp.headers.get(CONTENT_TYPE))
metrics = pmp.decode(content)
self.assertEqual(len(metrics), 1)
mf = metrics[0]
self.assertIsInstance(mf, pmp.MetricFamily)
self.assertEqual(mf.type, pmp.COUNTER)
self.assertEqual(len(mf.metric), 3)
async def test_histogram(self):
""" check histogram metric export """
# Add some metrics
data = [3, 5.2, 13, 4]
label = {"data": 1}
h = Histogram(
"histogram_test",
"Test Histogram.",
{"type": "test_histogram"},
buckets=[5.0, 10.0, 15.0],
)
self.server.register(h)
for i in data:
h.add(label, i)
expected_data = """# HELP histogram_test Test Histogram.
# TYPE histogram_test histogram
histogram_test_bucket{data="1",le="5.0",type="test_histogram"} 2.0
histogram_test_bucket{data="1",le="10.0",type="test_histogram"} 3.0
histogram_test_bucket{data="1",le="15.0",type="test_histogram"} 4.0
histogram_test_bucket{data="1",le="+Inf",type="test_histogram"} 4.0
histogram_test_count{data="1",type="test_histogram"} 4.0
histogram_test_sum{data="1",type="test_histogram"} 25.2
"""
async with aiohttp.ClientSession() as session:
# Fetch as text
async with session.get(self.metrics_url,
headers={ACCEPT:
text.TEXT_CONTENT_TYPE}) as resp:
self.assertEqual(resp.status, 200)
content = await resp.read()
self.assertEqual(text.TEXT_CONTENT_TYPE,
resp.headers.get(CONTENT_TYPE))
self.assertEqual(expected_data, content.decode())
# Fetch as binary
async with session.get(self.metrics_url,
headers={
ACCEPT: binary.BINARY_CONTENT_TYPE
}) as resp:
self.assertEqual(resp.status, 200)
content = await resp.read()
self.assertEqual(binary.BINARY_CONTENT_TYPE,
resp.headers.get(CONTENT_TYPE))
metrics = pmp.decode(content)
self.assertEqual(len(metrics), 1)
mf = metrics[0]
self.assertIsInstance(mf, pmp.MetricFamily)
self.assertEqual(mf.type, pmp.HISTOGRAM)
self.assertEqual(len(mf.metric), 1)
self.assertEqual(len(mf.metric[0].histogram.bucket), 4)
async def test_histogram(self):
""" check histogram metric export """
# Add some metrics
data = [3, 5.2, 13, 4]
label = {"data": 1}
h = Histogram(
"histogram_test",
"Test Histogram.",
{"type": "test_histogram"},
buckets=[5.0, 10.0, 15.0],
)
self.server.register(h)
for i in data:
h.add(label, i)
expected_data = """# HELP histogram_test Test Histogram.
# TYPE histogram_test histogram
histogram_test_bucket{data="1",le="5.0",type="test_histogram"} 2.0
histogram_test_bucket{data="1",le="10.0",type="test_histogram"} 3.0
histogram_test_bucket{data="1",le="15.0",type="test_histogram"} 4.0
histogram_test_bucket{data="1",le="+Inf",type="test_histogram"} 4.0
histogram_test_count{data="1",type="test_histogram"} 4.0
histogram_test_sum{data="1",type="test_histogram"} 25.2
"""
async with aiohttp.ClientSession() as session:
# Fetch as text
async with session.get(
self.metrics_url, headers={ACCEPT: TEXT_CONTENT_TYPE}
) as resp:
self.assertEqual(resp.status, 200)
content = await resp.read()
self.assertEqual(TEXT_CONTENT_TYPE, resp.headers.get(CONTENT_TYPE))
self.assertEqual(expected_data, content.decode())
# Fetch as binary
async with session.get(
self.metrics_url, headers={ACCEPT: BINARY_CONTENT_TYPE}
) as resp:
self.assertEqual(resp.status, 200)
content = await resp.read()
self.assertEqual(BINARY_CONTENT_TYPE, resp.headers.get(CONTENT_TYPE))
metrics = pmp.decode(content)
self.assertEqual(len(metrics), 1)
mf = metrics[0]
self.assertIsInstance(mf, pmp.MetricFamily)
self.assertEqual(mf.type, pmp.HISTOGRAM)
self.assertEqual(len(mf.metric), 1)
self.assertEqual(len(mf.metric[0].histogram.bucket), 4)
async def test_summary(self):
""" check summary metric export """
# Add some metrics
data = [3, 5.2, 13, 4]
label = {"data": 1}
s = Summary("test_summary", "Test Summary.", {"test": "test_summary"})
self.server.register(s)
for i in data:
s.add(label, i)
expected_data = """# HELP test_summary Test Summary.
# TYPE test_summary summary
test_summary{data="1",quantile="0.5",test="test_summary"} 4.0
test_summary{data="1",quantile="0.9",test="test_summary"} 5.2
test_summary{data="1",quantile="0.99",test="test_summary"} 5.2
test_summary_count{data="1",test="test_summary"} 4
test_summary_sum{data="1",test="test_summary"} 25.2
"""
async with aiohttp.ClientSession() as session:
# Fetch as text
async with session.get(self.metrics_url,
headers={ACCEPT:
text.TEXT_CONTENT_TYPE}) as resp:
self.assertEqual(resp.status, 200)
content = await resp.read()
self.assertEqual(text.TEXT_CONTENT_TYPE,
resp.headers.get(CONTENT_TYPE))
self.assertEqual(expected_data, content.decode())
# Fetch as binary
async with session.get(self.metrics_url,
headers={
ACCEPT: binary.BINARY_CONTENT_TYPE
}) as resp:
self.assertEqual(resp.status, 200)
content = await resp.read()
self.assertEqual(binary.BINARY_CONTENT_TYPE,
resp.headers.get(CONTENT_TYPE))
metrics = pmp.decode(content)
self.assertEqual(len(metrics), 1)
mf = metrics[0]
self.assertIsInstance(mf, pmp.MetricFamily)
self.assertEqual(mf.type, pmp.SUMMARY)
self.assertEqual(len(mf.metric), 1)
self.assertEqual(len(mf.metric[0].summary.quantile), 3)
async def test_summary(self):
""" check summary metric export """
# Add some metrics
data = [3, 5.2, 13, 4]
label = {"data": 1}
s = Summary("test_summary", "Test Summary.", {"test": "test_summary"})
self.server.register(s)
for i in data:
s.add(label, i)
expected_data = """# HELP test_summary Test Summary.
# TYPE test_summary summary
test_summary{data="1",quantile="0.5",test="test_summary"} 4.0
test_summary{data="1",quantile="0.9",test="test_summary"} 5.2
test_summary{data="1",quantile="0.99",test="test_summary"} 5.2
test_summary_count{data="1",test="test_summary"} 4
test_summary_sum{data="1",test="test_summary"} 25.2
"""
async with aiohttp.ClientSession() as session:
# Fetch as text
async with session.get(
self.metrics_url, headers={ACCEPT: TEXT_CONTENT_TYPE}
) as resp:
self.assertEqual(resp.status, 200)
content = await resp.read()
self.assertEqual(TEXT_CONTENT_TYPE, resp.headers.get(CONTENT_TYPE))
self.assertEqual(expected_data, content.decode())
# Fetch as binary
async with session.get(
self.metrics_url, headers={ACCEPT: BINARY_CONTENT_TYPE}
) as resp:
self.assertEqual(resp.status, 200)
content = await resp.read()
self.assertEqual(BINARY_CONTENT_TYPE, resp.headers.get(CONTENT_TYPE))
metrics = pmp.decode(content)
self.assertEqual(len(metrics), 1)
mf = metrics[0]
self.assertIsInstance(mf, pmp.MetricFamily)
self.assertEqual(mf.type, pmp.SUMMARY)
self.assertEqual(len(mf.metric), 1)
self.assertEqual(len(mf.metric[0].summary.quantile), 3)
async def test_gauge(self):
""" check gauge metric export """
# Add some metrics
data = (
({"data": 1}, 100),
({"data": "2"}, 200),
({"data": 3}, 300),
({"data": 1}, 400),
)
g = Gauge("test_gauge", "Test Gauge.", {"test": "test_gauge"})
self.server.register(g)
for i in data:
g.set(i[0], i[1])
expected_data = """# HELP test_gauge Test Gauge.
# TYPE test_gauge gauge
test_gauge{data="1",test="test_gauge"} 400
test_gauge{data="2",test="test_gauge"} 200
test_gauge{data="3",test="test_gauge"} 300
"""
async with aiohttp.ClientSession() as session:
# Fetch as text
async with session.get(
self.metrics_url, headers={ACCEPT: TEXT_CONTENT_TYPE}
) as resp:
self.assertEqual(resp.status, 200)
content = await resp.read()
self.assertEqual(TEXT_CONTENT_TYPE, resp.headers.get(CONTENT_TYPE))
self.assertEqual(expected_data, content.decode())
# Fetch as binary
async with session.get(
self.metrics_url, headers={ACCEPT: BINARY_CONTENT_TYPE}
) as resp:
self.assertEqual(resp.status, 200)
content = await resp.read()
self.assertEqual(BINARY_CONTENT_TYPE, resp.headers.get(CONTENT_TYPE))
metrics = pmp.decode(content)
self.assertEqual(len(metrics), 1)
mf = metrics[0]
self.assertIsInstance(mf, pmp.MetricFamily)
self.assertEqual(mf.type, pmp.GAUGE)
self.assertEqual(len(mf.metric), 3)
def test_encode_histogram(self):
""" check encode of histogram matches expected output """
valid_result = (b"\x97\x01\n\x0ehistogram_test\x12\x0cA histogram."
b'\x18\x04"u\n\r\n\x08h_sample\x12\x011\n\x10\n'
b"\x0bh_subsample\x12\x01b\n\x11\n\x04type\x12\t"
b"histogram:?\x08\x06\x11\x00\x00\x00\x00\x00\x00G@"
b"\x1a\x0b\x08\x03\x11\x00\x00\x00\x00\x00\x00\x14@"
b"\x1a\x0b\x08\x02\x11\x00\x00\x00\x00\x00\x00$@\x1a"
b"\x0b\x08\x01\x11\x00\x00\x00\x00\x00\x00.@\x1a\x0b"
b"\x08\x00\x11\x00\x00\x00\x00\x00\x00\xf0\x7f")
metric_name = "histogram_test"
metric_help = "A histogram."
metric_type = pmp.HISTOGRAM
# buckets typically have a POS_INF upper bound to catch values
# beyond the largest bucket bound. Simulate this behavior.
POS_INF = float("inf")
metric_data = ((
{
"h_sample": "1",
"h_subsample": "b"
},
{
5.0: 3,
10.0: 2,
15.0: 1,
POS_INF: 0,
"count": 6,
"sum": 46.0
},
), )
mf = pmp.utils.create_metric_family(
metric_name,
metric_help,
metric_type,
metric_data,
const_labels={"type": "histogram"},
)
payload = pmp.encode(mf)
self.assertIsInstance(payload, bytes)
self.assertEqual(valid_result, payload)
# Check Histogram can be round-tripped through encode and decode
_mf = pmp.decode(payload)[0]
self.assertEqual(mf, _mf)
def test_encode_summary(self):
""" check encode of summary matches expected output """
valid_result = (b"\x99\x01\n\x0csummary_test\x12\nA summary."
b'\x18\x02"{\n\r\n\x08s_sample\x12\x011\n\x10\n'
b"\x0bs_subsample\x12\x01b\n\x0f\n\x04type\x12\x07"
b'summary"G\x08\x16\x11\x00\x00\x00\x00\x90"\xf8@'
b"\x1a\x12\t\x00\x00\x00\x00\x00\x00\xe0?\x11\x00"
b"\x00\x00\x00\x00\x8b\xb0@\x1a\x12\t\xcd\xcc\xcc"
b"\xcc\xcc\xcc\xec?\x11\x00\x00\x00\x00\x00v\xb1@"
b"\x1a\x12\t\xaeG\xe1z\x14\xae\xef?\x11\x00\x00\x00"
b"\x00\x00\xa5\xb1@")
metric_name = "summary_test"
metric_help = "A summary."
metric_type = pmp.SUMMARY
metric_data = ((
{
"s_sample": "1",
"s_subsample": "b"
},
{
0.5: 4235.0,
0.9: 4470.0,
0.99: 4517.0,
"count": 22,
"sum": 98857.0
},
), )
mf = pmp.utils.create_metric_family(
metric_name,
metric_help,
metric_type,
metric_data,
const_labels={"type": "summary"},
)
payload = pmp.encode(mf)
self.assertIsInstance(payload, bytes)
self.assertEqual(valid_result, payload)
# Check Summary can be round-tripped through encode and decode
_mf = pmp.decode(payload)[0]
self.assertEqual(mf, _mf)
def test_encode_gauge(self):
''' check encode of gauge matches expected output '''
valid_result = (b'U\n\ngauge_test\x12\x08A gauge.\x18\x01";'
b'\n\r\n\x08g_sample\x12\x011\n\x10\n\x0bg_subsample'
b'\x12\x01b\n\r\n\x04type\x12\x05gauge\x12\t\t\x00'
b'\x00\x00\x00\x00\x00\x89@')
metric_name = "gauge_test"
metric_help = "A gauge."
metric_type = pmp.GAUGE
metric_data = (({'g_sample': '1', 'g_subsample': 'b'}, 800), )
mf = pmp.utils.create_metric_family(metric_name,
metric_help,
metric_type,
metric_data,
const_labels={'type': "gauge"})
payload = pmp.encode(mf)
self.assertIsInstance(payload, bytes)
self.assertEqual(valid_result, payload)
# Check Gauge can be round-tripped through encode and decode
_mf = pmp.decode(payload)[0]
self.assertEqual(mf, _mf)
def test_encode_counter(self):
''' check encode of counter matches expected output '''
valid_result = (b'[\n\x0ccounter_test\x12\nA counter.\x18\x00"=\n\r'
b'\n\x08c_sample\x12\x011\n\x10\n\x0bc_subsample\x12'
b'\x01b\n\x0f\n\x04type\x12\x07counter\x1a\t\t\x00\x00'
b'\x00\x00\x00\x00y@')
metric_name = "counter_test"
metric_help = "A counter."
metric_type = pmp.COUNTER
metric_data = (({'c_sample': '1', 'c_subsample': 'b'}, 400), )
mf = pmp.utils.create_metric_family(metric_name,
metric_help,
metric_type,
metric_data,
const_labels={'type': "counter"})
payload = pmp.encode(mf)
self.assertIsInstance(payload, bytes)
self.assertEqual(valid_result, payload)
# Check Counter can be round-tripped through encode and decode
_mf = pmp.decode(payload)[0]
self.assertEqual(mf, _mf)
def test_histogram(self):
''' check creating histogram using utils functions '''
# Create a metrics with no metric instances
mf = pmp.utils.create_metric_family(self.histogram_metric_name,
self.histogram_metric_help,
self.histogram_metric_type, [])
self.assertIsInstance(mf, pmp.MetricFamily)
self.assertEqual(len(mf.metric), 0)
# Create it with metrics
mf = pmp.utils.create_metric_family(self.histogram_metric_name,
self.histogram_metric_help,
self.histogram_metric_type,
self.histogram_metric_data)
self.assertIsInstance(mf, pmp.MetricFamily)
self.assertEqual(mf.name, self.histogram_metric_name)
self.assertEqual(mf.help, self.histogram_metric_help)
self.assertEqual(mf.type, self.histogram_metric_type)
# Create another and check equal
mf_ = pmp.utils.create_metric_family(self.histogram_metric_name,
self.histogram_metric_help,
self.histogram_metric_type,
self.histogram_metric_data)
self.assertIsInstance(mf_, pmp.MetricFamily)
self.assertEqual(mf, mf_)
for m in mf_.metric:
self.assertEqual(m.timestamp_ms, 0)
# Create another with timestamp
mf_ = pmp.create_histogram(self.histogram_metric_name,
self.histogram_metric_help,
self.histogram_metric_data,
timestamp=True)
self.assertIsInstance(mf_, pmp.MetricFamily)
for m in mf_.metric:
self.assertNotEqual(m.timestamp_ms, 0)
self.assertNotEqual(mf, mf_)
# Create Histogram with const_labels
mf_ = pmp.utils.create_metric_family(self.histogram_metric_name,
self.histogram_metric_help,
self.histogram_metric_type,
self.histogram_metric_data,
const_labels=self.const_labels)
self.assertIsInstance(mf_, pmp.MetricFamily)
# Check that const_label is present in the LabelPair associated
# with each metric instance.
for m in mf_.metric:
labels = [lp.name for lp in m.label]
self.assertIn('app', labels)
self.assertNotEqual(mf, mf_)
# Check Histogram can be round-tripped through encode and decode
payload = pmp.encode(mf)
self.assertIsInstance(payload, bytes)
_mf = pmp.decode(payload)[0]
self.assertEqual(mf, _mf)
def main():
# Define some labels that we want added to all metrics. These labels are
# independent of the instance labels that define a metric as unique.
# These could be used to add hostname, app name, etc.
const_labels = {'host': 'examplehost', 'app': 'my_app'}
# Create a Counter metric to track logged in users. This counter has
# 5 separate instances.
# We'll make use of the optional const_labels argument to add extra
# constant labels.
# We will also add a timestamp to the metric instances.
# We will request that the labels be sorted.
cm = pmp.create_counter('logged_users_total',
'Logged users in the application.', (
({
'country': "sp",
"device": "desktop"
}, 520),
({
'country': "us",
"device": "mobile"
}, 654),
({
'country': "uk",
"device": "desktop"
}, 1001),
({
'country': "de",
"device": "desktop"
}, 995),
({
'country': "zh",
"device": "desktop"
}, 520),
),
timestamp=True,
const_labels=const_labels,
ordered=True)
# Create a Gauge metric, similar to the counter above.
gm = pmp.create_gauge('logged_users_total',
'Logged users in the application.', (
({
'country': "sp",
"device": "desktop"
}, 520),
({
'country': "us",
"device": "mobile"
}, 654),
({
'country': "uk",
"device": "desktop"
}, 1001),
({
'country': "de",
"device": "desktop"
}, 995),
({
'country': "zh",
"device": "desktop"
}, 520),
),
timestamp=True,
const_labels=const_labels,
ordered=True)
# Now lets create a Summary and Histogram metric object. These forms
# of metrics are slightly more complicated.
#
# Remember, the collection of metrics and the management of Summary
# Quantiles and Histogram Buckets are outside the scope of
# functionality provided by this package.
#
# The following examples assume they are taking the data values from
# a management library that can also emit the sum and count fields
# expected for both Summary and Histogram metrics.
# Create a Summary metric. The values for a summary are slightly
# different to a Counter or Gauge. They are composed of a dict representing
# the various quantile values of the metric. The count and sum are
# expected to be present in this dict.
sm = pmp.create_summary('request_payload_size_bytes',
'Request payload size in bytes.', (
({
'route': '/'
}, {
0.5: 4.0,
0.9: 5.2,
0.99: 5.2,
'sum': 25.2,
'count': 4
}),
({
'route': '/data'
}, {
0.5: 4.0,
0.9: 5.2,
0.99: 5.2,
'sum': 25.2,
'count': 4
}),
),
timestamp=True,
const_labels=const_labels,
ordered=True)
# Create a Histogram metric. The values for a histogram are slightly
# different to a Counter or Gauge. They are composed of a dict representing
# the various bucket values of the metric. The cumulative count and sum
# values are expected to be present in this dict.
#
# Libraries manageing buckets typically have add a POS_INF upper bound to
# catch values beyond the largest bucket bound. Simulate this behavior in
# the data below.
POS_INF = float("inf")
hm = pmp.create_histogram('request_latency_seconds',
'Request latency in seconds.', (
({
'route': '/'
}, {
5.0: 3,
10.0: 2,
15.0: 1,
POS_INF: 0,
'count': 6,
'sum': 46.0
}),
({
'route': '/data'
}, {
5.0: 3,
10.0: 2,
15.0: 1,
POS_INF: 0,
'count': 6,
'sum': 46.0
}),
),
timestamp=True,
const_labels=const_labels,
ordered=True)
# Serialize a sequence of metrics into a payload suitable for network
# transmission.
input_metrics = (cm, gm, sm, hm)
payload = pmp.encode(*input_metrics)
assert isinstance(payload, bytes)
# De-serialize the payload into a sequence of MetricsFamily objects.
recovered_metrics = pmp.decode(payload)
# Confirm that the round trip re-produced the same number of metrics
# and that the metrics are identical.
assert len(recovered_metrics) == len(input_metrics)
for recovered_metric, input_metric in zip(recovered_metrics,
input_metrics):
assert recovered_metric == input_metric
for metric in input_metrics:
print(metric)
def test_encode_decode(self):
''' check encode and decode functions '''
# check passing no metrics raises an exception
input_metrics = None
with self.assertRaises(Exception) as ctx:
payload = pmp.encode(input_metrics)
self.assertIn('Expected metrics to be instances of MetricFamily, got ',
str(ctx.exception))
cm = pmp.create_counter(self.counter_metric_name,
self.counter_metric_help,
self.counter_metric_data)
self.assertIsInstance(cm, pmp.MetricFamily)
gm = pmp.create_gauge(self.gauge_metric_name, self.gauge_metric_help,
self.gauge_metric_data)
self.assertIsInstance(gm, pmp.MetricFamily)
sm = pmp.create_summary(self.summary_metric_name,
self.summary_metric_help,
self.summary_metric_data)
self.assertIsInstance(sm, pmp.MetricFamily)
hm = pmp.create_histogram(self.histogram_metric_name,
self.histogram_metric_help,
self.histogram_metric_data)
self.assertIsInstance(hm, pmp.MetricFamily)
# check encode can take a single valid metric
input_metrics = [cm]
payload = pmp.encode(input_metrics[0])
self.assertIsInstance(payload, bytes)
# check round-trip
metrics = pmp.decode(payload)
self.assertIsInstance(metrics, list)
self.assertEqual(len(metrics), len(input_metrics))
for m_in, m_out in zip(input_metrics, metrics):
self.assertEqual(m_in, m_out)
# check passing invalid type raises an exception
input_metrics = ['a']
with self.assertRaises(Exception) as ctx:
payload = pmp.encode(*input_metrics)
self.assertIn('Expected metrics to be instances of MetricFamily, got ',
str(ctx.exception))
# check parser can take multiple valid metrics
input_metrics = (cm, gm, sm, hm)
payload = pmp.encode(*input_metrics)
self.assertIsInstance(payload, bytes)
# check round-trip
metrics = pmp.decode(payload)
self.assertIsInstance(metrics, list)
self.assertEqual(len(metrics), len(input_metrics))
for m_in, m_out in zip(input_metrics, metrics):
self.assertEqual(m_in, m_out)
# check decoding empty bytes returns empty list
metrics = pmp.decode(b'')
self.assertIsInstance(metrics, list)
self.assertEqual(len(metrics), 0)
async def test_all(self):
counter_data = (
({"c_sample": "1"}, 100),
({"c_sample": "2"}, 200),
({"c_sample": "3"}, 300),
({"c_sample": "1", "c_subsample": "b"}, 400),
)
gauge_data = (
({"g_sample": "1"}, 500),
({"g_sample": "2"}, 600),
({"g_sample": "3"}, 700),
({"g_sample": "1", "g_subsample": "b"}, 800),
)
summary_data = (
({"s_sample": "1"}, range(1000, 2000, 4)),
({"s_sample": "2"}, range(2000, 3000, 20)),
({"s_sample": "3"}, range(3000, 4000, 13)),
({"s_sample": "1", "s_subsample": "b"}, range(4000, 5000, 47)),
)
histogram_data = (
({"h_sample": "1"}, [3, 14]),
({"h_sample": "2"}, range(1, 20, 2)),
({"h_sample": "3"}, range(1, 20, 2)),
({"h_sample": "1", "h_subsample": "b"}, range(1, 20, 2)),
)
counter = Counter("counter_test", "A counter.", {"type": "counter"})
gauge = Gauge("gauge_test", "A gauge.", {"type": "gauge"})
summary = Summary("summary_test", "A summary.", {"type": "summary"})
histogram = Histogram(
"histogram_test",
"A histogram.",
{"type": "histogram"},
buckets=[5.0, 10.0, 15.0],
)
self.server.register(counter)
self.server.register(gauge)
self.server.register(summary)
self.server.register(histogram)
# Add data
[counter.set(c[0], c[1]) for c in counter_data]
[gauge.set(g[0], g[1]) for g in gauge_data]
[summary.add(i[0], s) for i in summary_data for s in i[1]]
[histogram.observe(i[0], h) for i in histogram_data for h in i[1]]
expected_data = """# HELP counter_test A counter.
# TYPE counter_test counter
counter_test{c_sample="1",type="counter"} 100
counter_test{c_sample="2",type="counter"} 200
counter_test{c_sample="3",type="counter"} 300
counter_test{c_sample="1",c_subsample="b",type="counter"} 400
# HELP gauge_test A gauge.
# TYPE gauge_test gauge
gauge_test{g_sample="1",type="gauge"} 500
gauge_test{g_sample="2",type="gauge"} 600
gauge_test{g_sample="3",type="gauge"} 700
gauge_test{g_sample="1",g_subsample="b",type="gauge"} 800
# HELP histogram_test A histogram.
# TYPE histogram_test histogram
histogram_test_bucket{h_sample="1",le="5.0",type="histogram"} 1.0
histogram_test_bucket{h_sample="1",le="10.0",type="histogram"} 1.0
histogram_test_bucket{h_sample="1",le="15.0",type="histogram"} 2.0
histogram_test_bucket{h_sample="1",le="+Inf",type="histogram"} 2.0
histogram_test_count{h_sample="1",type="histogram"} 2.0
histogram_test_sum{h_sample="1",type="histogram"} 17.0
histogram_test_bucket{h_sample="2",le="5.0",type="histogram"} 3.0
histogram_test_bucket{h_sample="2",le="10.0",type="histogram"} 5.0
histogram_test_bucket{h_sample="2",le="15.0",type="histogram"} 8.0
histogram_test_bucket{h_sample="2",le="+Inf",type="histogram"} 10.0
histogram_test_count{h_sample="2",type="histogram"} 10.0
histogram_test_sum{h_sample="2",type="histogram"} 100.0
histogram_test_bucket{h_sample="3",le="5.0",type="histogram"} 3.0
histogram_test_bucket{h_sample="3",le="10.0",type="histogram"} 5.0
histogram_test_bucket{h_sample="3",le="15.0",type="histogram"} 8.0
histogram_test_bucket{h_sample="3",le="+Inf",type="histogram"} 10.0
histogram_test_count{h_sample="3",type="histogram"} 10.0
histogram_test_sum{h_sample="3",type="histogram"} 100.0
histogram_test_bucket{h_sample="1",h_subsample="b",le="5.0",type="histogram"} 3.0
histogram_test_bucket{h_sample="1",h_subsample="b",le="10.0",type="histogram"} 5.0
histogram_test_bucket{h_sample="1",h_subsample="b",le="15.0",type="histogram"} 8.0
histogram_test_bucket{h_sample="1",h_subsample="b",le="+Inf",type="histogram"} 10.0
histogram_test_count{h_sample="1",h_subsample="b",type="histogram"} 10.0
histogram_test_sum{h_sample="1",h_subsample="b",type="histogram"} 100.0
# HELP summary_test A summary.
# TYPE summary_test summary
summary_test{quantile="0.5",s_sample="1",type="summary"} 1272.0
summary_test{quantile="0.9",s_sample="1",type="summary"} 1452.0
summary_test{quantile="0.99",s_sample="1",type="summary"} 1496.0
summary_test_count{s_sample="1",type="summary"} 250
summary_test_sum{s_sample="1",type="summary"} 374500.0
summary_test{quantile="0.5",s_sample="2",type="summary"} 2260.0
summary_test{quantile="0.9",s_sample="2",type="summary"} 2440.0
summary_test{quantile="0.99",s_sample="2",type="summary"} 2500.0
summary_test_count{s_sample="2",type="summary"} 50
summary_test_sum{s_sample="2",type="summary"} 124500.0
summary_test{quantile="0.5",s_sample="3",type="summary"} 3260.0
summary_test{quantile="0.9",s_sample="3",type="summary"} 3442.0
summary_test{quantile="0.99",s_sample="3",type="summary"} 3494.0
summary_test_count{s_sample="3",type="summary"} 77
summary_test_sum{s_sample="3",type="summary"} 269038.0
summary_test{quantile="0.5",s_sample="1",s_subsample="b",type="summary"} 4235.0
summary_test{quantile="0.9",s_sample="1",s_subsample="b",type="summary"} 4470.0
summary_test{quantile="0.99",s_sample="1",s_subsample="b",type="summary"} 4517.0
summary_test_count{s_sample="1",s_subsample="b",type="summary"} 22
summary_test_sum{s_sample="1",s_subsample="b",type="summary"} 98857.0
"""
async with aiohttp.ClientSession() as session:
# Fetch as text
async with session.get(
self.metrics_url, headers={ACCEPT: TEXT_CONTENT_TYPE}
) as resp:
self.assertEqual(resp.status, 200)
content = await resp.read()
self.assertEqual(TEXT_CONTENT_TYPE, resp.headers.get(CONTENT_TYPE))
self.assertEqual(expected_data, content.decode())
# Fetch as binary
async with session.get(
self.metrics_url, headers={ACCEPT: BINARY_CONTENT_TYPE}
) as resp:
self.assertEqual(resp.status, 200)
content = await resp.read()
self.assertEqual(BINARY_CONTENT_TYPE, resp.headers.get(CONTENT_TYPE))
metrics = pmp.decode(content)
self.assertEqual(len(metrics), 4)
for mf in metrics:
self.assertIsInstance(mf, pmp.MetricFamily)
if mf.type == pmp.COUNTER:
self.assertEqual(len(mf.metric), 4)
elif mf.type == pmp.GAUGE:
self.assertEqual(len(mf.metric), 4)
elif mf.type == pmp.SUMMARY:
self.assertEqual(len(mf.metric), 4)
self.assertEqual(len(mf.metric[0].summary.quantile), 3)
elif mf.type == pmp.HISTOGRAM:
self.assertEqual(len(mf.metric), 4)
self.assertEqual(len(mf.metric[0].histogram.bucket), 4)
async def test_all(self):
counter_data = (
({
"c_sample": "1"
}, 100),
({
"c_sample": "2"
}, 200),
({
"c_sample": "3"
}, 300),
({
"c_sample": "1",
"c_subsample": "b"
}, 400),
)
gauge_data = (
({
"g_sample": "1"
}, 500),
({
"g_sample": "2"
}, 600),
({
"g_sample": "3"
}, 700),
({
"g_sample": "1",
"g_subsample": "b"
}, 800),
)
summary_data = (
({
"s_sample": "1"
}, range(1000, 2000, 4)),
({
"s_sample": "2"
}, range(2000, 3000, 20)),
({
"s_sample": "3"
}, range(3000, 4000, 13)),
({
"s_sample": "1",
"s_subsample": "b"
}, range(4000, 5000, 47)),
)
histogram_data = (
({
"h_sample": "1"
}, [3, 14]),
({
"h_sample": "2"
}, range(1, 20, 2)),
({
"h_sample": "3"
}, range(1, 20, 2)),
({
"h_sample": "1",
"h_subsample": "b"
}, range(1, 20, 2)),
)
counter = Counter("counter_test", "A counter.", {"type": "counter"})
gauge = Gauge("gauge_test", "A gauge.", {"type": "gauge"})
summary = Summary("summary_test", "A summary.", {"type": "summary"})
histogram = Histogram(
"histogram_test",
"A histogram.",
{"type": "histogram"},
buckets=[5.0, 10.0, 15.0],
)
self.server.register(counter)
self.server.register(gauge)
self.server.register(summary)
self.server.register(histogram)
# Add data
[counter.set(c[0], c[1]) for c in counter_data]
[gauge.set(g[0], g[1]) for g in gauge_data]
[summary.add(i[0], s) for i in summary_data for s in i[1]]
[histogram.observe(i[0], h) for i in histogram_data for h in i[1]]
expected_data = """# HELP counter_test A counter.
# TYPE counter_test counter
counter_test{c_sample="1",type="counter"} 100
counter_test{c_sample="2",type="counter"} 200
counter_test{c_sample="3",type="counter"} 300
counter_test{c_sample="1",c_subsample="b",type="counter"} 400
# HELP gauge_test A gauge.
# TYPE gauge_test gauge
gauge_test{g_sample="1",type="gauge"} 500
gauge_test{g_sample="2",type="gauge"} 600
gauge_test{g_sample="3",type="gauge"} 700
gauge_test{g_sample="1",g_subsample="b",type="gauge"} 800
# HELP histogram_test A histogram.
# TYPE histogram_test histogram
histogram_test_bucket{h_sample="1",le="5.0",type="histogram"} 1.0
histogram_test_bucket{h_sample="1",le="10.0",type="histogram"} 1.0
histogram_test_bucket{h_sample="1",le="15.0",type="histogram"} 2.0
histogram_test_bucket{h_sample="1",le="+Inf",type="histogram"} 2.0
histogram_test_count{h_sample="1",type="histogram"} 2.0
histogram_test_sum{h_sample="1",type="histogram"} 17.0
histogram_test_bucket{h_sample="2",le="5.0",type="histogram"} 3.0
histogram_test_bucket{h_sample="2",le="10.0",type="histogram"} 5.0
histogram_test_bucket{h_sample="2",le="15.0",type="histogram"} 8.0
histogram_test_bucket{h_sample="2",le="+Inf",type="histogram"} 10.0
histogram_test_count{h_sample="2",type="histogram"} 10.0
histogram_test_sum{h_sample="2",type="histogram"} 100.0
histogram_test_bucket{h_sample="3",le="5.0",type="histogram"} 3.0
histogram_test_bucket{h_sample="3",le="10.0",type="histogram"} 5.0
histogram_test_bucket{h_sample="3",le="15.0",type="histogram"} 8.0
histogram_test_bucket{h_sample="3",le="+Inf",type="histogram"} 10.0
histogram_test_count{h_sample="3",type="histogram"} 10.0
histogram_test_sum{h_sample="3",type="histogram"} 100.0
histogram_test_bucket{h_sample="1",h_subsample="b",le="5.0",type="histogram"} 3.0
histogram_test_bucket{h_sample="1",h_subsample="b",le="10.0",type="histogram"} 5.0
histogram_test_bucket{h_sample="1",h_subsample="b",le="15.0",type="histogram"} 8.0
histogram_test_bucket{h_sample="1",h_subsample="b",le="+Inf",type="histogram"} 10.0
histogram_test_count{h_sample="1",h_subsample="b",type="histogram"} 10.0
histogram_test_sum{h_sample="1",h_subsample="b",type="histogram"} 100.0
# HELP summary_test A summary.
# TYPE summary_test summary
summary_test{quantile="0.5",s_sample="1",type="summary"} 1272.0
summary_test{quantile="0.9",s_sample="1",type="summary"} 1452.0
summary_test{quantile="0.99",s_sample="1",type="summary"} 1496.0
summary_test_count{s_sample="1",type="summary"} 250
summary_test_sum{s_sample="1",type="summary"} 374500.0
summary_test{quantile="0.5",s_sample="2",type="summary"} 2260.0
summary_test{quantile="0.9",s_sample="2",type="summary"} 2440.0
summary_test{quantile="0.99",s_sample="2",type="summary"} 2500.0
summary_test_count{s_sample="2",type="summary"} 50
summary_test_sum{s_sample="2",type="summary"} 124500.0
summary_test{quantile="0.5",s_sample="3",type="summary"} 3260.0
summary_test{quantile="0.9",s_sample="3",type="summary"} 3442.0
summary_test{quantile="0.99",s_sample="3",type="summary"} 3494.0
summary_test_count{s_sample="3",type="summary"} 77
summary_test_sum{s_sample="3",type="summary"} 269038.0
summary_test{quantile="0.5",s_sample="1",s_subsample="b",type="summary"} 4235.0
summary_test{quantile="0.9",s_sample="1",s_subsample="b",type="summary"} 4470.0
summary_test{quantile="0.99",s_sample="1",s_subsample="b",type="summary"} 4517.0
summary_test_count{s_sample="1",s_subsample="b",type="summary"} 22
summary_test_sum{s_sample="1",s_subsample="b",type="summary"} 98857.0
"""
async with aiohttp.ClientSession() as session:
# Fetch as text
async with session.get(self.metrics_url,
headers={ACCEPT:
text.TEXT_CONTENT_TYPE}) as resp:
self.assertEqual(resp.status, 200)
content = await resp.read()
self.assertEqual(text.TEXT_CONTENT_TYPE,
resp.headers.get(CONTENT_TYPE))
self.assertEqual(expected_data, content.decode())
# Fetch as binary
async with session.get(self.metrics_url,
headers={
ACCEPT: binary.BINARY_CONTENT_TYPE
}) as resp:
self.assertEqual(resp.status, 200)
content = await resp.read()
self.assertEqual(binary.BINARY_CONTENT_TYPE,
resp.headers.get(CONTENT_TYPE))
metrics = pmp.decode(content)
self.assertEqual(len(metrics), 4)
for mf in metrics:
self.assertIsInstance(mf, pmp.MetricFamily)
if mf.type == pmp.COUNTER:
self.assertEqual(len(mf.metric), 4)
elif mf.type == pmp.GAUGE:
self.assertEqual(len(mf.metric), 4)
elif mf.type == pmp.SUMMARY:
self.assertEqual(len(mf.metric), 4)
self.assertEqual(len(mf.metric[0].summary.quantile), 3)
elif mf.type == pmp.HISTOGRAM:
self.assertEqual(len(mf.metric), 4)
self.assertEqual(len(mf.metric[0].histogram.bucket), 4)
