class TestAdvisoryLock(unittest.TestCase):
"""
These tests use lock aqusition as a proxy for cleanup/collect operations,
the former using exclusive locks, the latter shared locks
"""
def setUp(self):
self.tempdir = tempfile.mkdtemp()
os.environ['prometheus_multiproc_dir'] = self.tempdir
values.ValueClass = MultiProcessValue(lambda: 123)
self.registry = CollectorRegistry()
self.collector = MultiProcessCollector(self.registry, self.tempdir)
def test_cleanup_waits_for_collectors(self):
# IOError in python2, OSError in python3
with self.assertRaises(EnvironmentError):
with advisory_lock(LOCK_SH):
archive_metrics(blocking=False)
def test_collect_doesnt_block_other_collects(self):
values.ValueClass = MultiProcessValue(lambda: 0)
labels = dict((i, i) for i in 'abcd')
c = Counter('c', 'help', labelnames=labels.keys(), registry=None)
c.labels(**labels).inc(1)
with advisory_lock(LOCK_SH):
metrics = dict(
(m.name, m) for m in self.collector.collect(blocking=False))
self.assertEqual(metrics['c'].samples,
[Sample('c_total', labels, 1.0)])
def test_collect_waits_for_cleanup(self):
values.ValueClass = MultiProcessValue(lambda: 0)
labels = dict((i, i) for i in 'abcd')
c = Counter('c', 'help', labelnames=labels.keys(), registry=None)
c.labels(**labels).inc(1)
with self.assertRaises(EnvironmentError):
with advisory_lock(LOCK_EX):
self.collector.collect(blocking=False)
def test_exceptions_release_lock(self):
with self.assertRaises(ValueError):
with advisory_lock(LOCK_EX):
raise ValueError
# Do an operation which requires acquiring the lock
archive_metrics(blocking=False)
def tearDown(self):
del os.environ['prometheus_multiproc_dir']
shutil.rmtree(self.tempdir)
values.ValueClass = MutexValue
def __init__(self, app=None, export_defaults=True,
defaults_prefix='flask', group_by='path',
buckets=None, static_labels=None, registry=None):
"""
Create a new multiprocess-aware Prometheus metrics export configuration.
:param app: the Flask application (can be `None`)
:param export_defaults: expose all HTTP request latencies
and number of HTTP requests
:param defaults_prefix: string to prefix the default exported
metrics name with (when either `export_defaults=True` or
`export_defaults(..)` is called)
:param group_by: group default HTTP metrics by
this request property, like `path`, `endpoint`, `url_rule`, etc.
(defaults to `path`)
:param buckets: the time buckets for request latencies
(will use the default when `None`)
:param static_labels: static labels to attach to each of the
metrics exposed by this metrics instance
:param registry: the Prometheus Registry to use (can be `None` and it
will be registered with `prometheus_client.multiprocess.MultiProcessCollector`)
"""
_check_multiproc_env_var()
registry = registry or CollectorRegistry()
MultiProcessCollector(registry)
super(MultiprocessPrometheusMetrics, self).__init__(
app=app, path=None, export_defaults=export_defaults,
defaults_prefix=defaults_prefix, group_by=group_by,
buckets=buckets, static_labels=static_labels,
registry=registry
)
def get_metrics_reporting_registry(
process_registry: CollectorRegistry,
) -> CollectorRegistry:
"""
Get the metrics registry for reporting metrics.
If we're running under gunicorn, then each worker has its own process and
its own process collector. For reporting, we need a fresh registry with a
multiprocess collector that points to the metrics folder (created empty at
startup, with a database file for each process and metric type). It will
use the databases in this folder to generate combined metrics across the
processes, and will not double-count the reporting process's metrics.
If we're not running under gunicorn, then return the passed per-process
registry, which is the only metrics registry. In the single-process case,
We could use the default prometheus_client.REGISTRY, but it makes tests
easier to write if it is possible to replace the registry with a fresh one.
"""
try:
settings = config.Settings()
prometheus_multiproc_dir = settings.prometheus_multiproc_dir
except ValidationError:
prometheus_multiproc_dir = None
if prometheus_multiproc_dir:
registry = CollectorRegistry()
MultiProcessCollector(registry, path=prometheus_multiproc_dir)
return registry
return process_registry
def get_metrics() -> str:
"""Get collected metrics."""
registry = REGISTRY
if 'PROMETHEUS_MULTIPROC_DIR' in os.environ:
registry = CollectorRegistry()
MultiProcessCollector(registry)
return generate_latest(registry)
def metrics(request: Request) -> Response:
if "prometheus_multiproc_dir" in os.environ:
registry = CollectorRegistry()
MultiProcessCollector(registry)
else:
registry = REGISTRY
return Response(generate_latest(registry), headers={"Content-Type": CONTENT_TYPE_LATEST})
def get_registry(name):
if name not in collector_registries.keys():
collector_registries[name] = CollectorRegistry()
if prometheus_multiproc_dir is not None:
MultiProcessCollector(collector_registries[name])
return collector_registries[name]
def get_metrics():
registry = CollectorRegistry()
MultiProcessCollector(registry)
data = generate_latest(registry)
response_headers = [
('Content-type', CONTENT_TYPE_LATEST),
('Content-Length', str(len(data))),
]
return data, 200, response_headers
def collect_metrics():
registry = CollectorRegistry()
MultiProcessCollector(registry)
PlatformCollector(registry)
ExternalMetrics(registry)
data = generate_latest(registry)
return Response(data, mimetype=CONTENT_TYPE_LATEST)
def __init__(self, app, endpoint="/metrics"):
self.app = None
self.endpoint = endpoint
self.registry = CollectorRegistry()
MultiProcessCollector(self.registry)
self._metrics = {}
if app is not None:
self.init_app(app)
def test_deprecation_warning(self):
os.environ['prometheus_multiproc_dir'] = self.tempdir
with warnings.catch_warnings(record=True) as w:
values.ValueClass = get_value_class()
registry = CollectorRegistry()
collector = MultiProcessCollector(registry)
Counter('c', 'help', registry=None)
assert os.environ['PROMETHEUS_MULTIPROC_DIR'] == self.tempdir
assert len(w) == 1
assert issubclass(w[-1].category, DeprecationWarning)
assert "PROMETHEUS_MULTIPROC_DIR" in str(w[-1].message)
def metrics(request: Request) -> Response:
if "prometheus_multiproc_dir" in os.environ:
registry = CollectorRegistry()
MultiProcessCollector(registry)
logger.info(
f"Metrics multiprocess :[{os.environ['prometheus_multiproc_dir']}]"
)
else:
registry = REGISTRY
logger.info(f"Metrics no multiprocess")
return Response(generate_latest(registry), media_type=CONTENT_TYPE_LATEST)
def get_metrics(request):
"""Pyramid view that return the metrics"""
if prom.IS_MULTIPROC:
registry = CollectorRegistry()
MultiProcessCollector(registry)
else:
registry = REGISTRY
request.response.content_type = CONTENT_TYPE_LATEST
resp = Response(content_type=CONTENT_TYPE_LATEST, )
resp.body = generate_latest(registry)
return resp
def prometheus_registry():
"""
Configure prometheus_client.
This is run the first time the /metrics endpoint is used.
"""
# The multiprocess configuration makes it compatible with gunicorn.
# https://github.com/prometheus/client_python/#multiprocess-mode-eg-gunicorn
from prometheus_client import CollectorRegistry
from prometheus_client.multiprocess import MultiProcessCollector
registry = CollectorRegistry()
MultiProcessCollector(registry) # This has a side effect, apparently.
return registry
def prometheus_cleanup_worker(pid):
"""Aggregate dead worker's metrics into a single archive file."""
mark_process_dead(pid)
prom_dir = os.environ['prometheus_multiproc_dir']
worker_files = [
'histogram_{}.db'.format(pid),
'counter_{}.db'.format(pid),
]
paths = _filter_exists(os.path.join(prom_dir, f) for f in worker_files)
# check at least one worker file exists
if not paths:
return
histogram_path = os.path.join(prom_dir, histogram_archive)
counter_path = os.path.join(prom_dir, counter_archive)
archive_paths = _filter_exists([histogram_path, counter_path])
collect_paths = paths + archive_paths
collector = MultiProcessCollector(None)
try:
metrics = collector.merge(collect_paths, accumulate=False)
except AttributeError:
metrics = legacy_collect(collect_paths)
tmp_histogram = tempfile.NamedTemporaryFile(delete=False)
tmp_counter = tempfile.NamedTemporaryFile(delete=False)
write_metrics(metrics, tmp_histogram.name, tmp_counter.name)
# ensure reader does get partial state
with prometheus_lock:
os.rename(tmp_histogram.name, histogram_path)
os.rename(tmp_counter.name, counter_path)
for path in paths:
os.unlink(path)
def __init__(self, app=None, **kwargs):
"""
Create a new multiprocess-aware Prometheus metrics export configuration.
:param registry: the Prometheus Registry to use (can be `None` and it
will be registered with `prometheus_client.multiprocess.MultiProcessCollector`)
"""
_check_multiproc_env_var()
registry = kwargs.get('registry') or CollectorRegistry()
MultiProcessCollector(registry)
super(MultiprocessPrometheusMetrics, self).__init__(app=app,
path=None,
registry=registry,
**kwargs)
def set_config(self, config: ValueExtractor) -> None:
super().set_config(config)
registry = get_registry(self.config.get('registry', REGISTRY))
if MULTIPROC_DIR:
registry = MultiProcessCollector(registry)
self._registry = registry
port: int = self.config.get_int('port', default=0)
if port:
start_http_server(port=port, registry=registry)
graphite: Optional[ValueExtractor] = self.config.get('graphite')
if graphite:
address = graphite.get('address')
if isinstance(address, str):
addr = address.split(':')
address = (addr[0], int(addr[-1]))
gb = GraphiteBridge(address, registry=registry)
interval: float = graphite.get_duration('interval', 60)
prefix: str = graphite.get('prefix', '')
gb.start(interval, prefix=prefix)
def __init__(self, collectors: Iterable[Any]):
"""Builds a metric encoder using the given list of collectors. A collector is broadly
defined here as any type that implements the `collect` method.
:param collectors: The collectors to fetch metrics from
:type collectors: Iterable[Any]
"""
self._registry = CollectorRegistry(auto_describe=True)
# Always use a new registry for collecting mmapped files under multiprocess mode
if "PROMETHEUS_MULTIPROC_DIR" in os.environ:
MultiProcessCollector(self._registry)
# Do not double register metrics that implement MultiProcessValue
# See: prometheus_client/values.py#L31
collectors = filter(
lambda c: not isinstance(c, LiveMetricRegistry) and
not isinstance(c, MetricWrapperBase) and hasattr(c, "collect"),
collectors,
)
for c in collectors:
self._registry.register(c)
def metrics():
return Response(
generate_latest(MultiProcessCollector(CollectorRegistry())),
mimetype=CONTENT_TYPE_LATEST,
)
def display_metrics():
registry = prometheus_client.CollectorRegistry()
MultiProcessCollector(registry)
data = prometheus_client.generate_latest(registry=registry)
return data.decode()
@contact: [email protected] @time: 2018/5/8 上午10:18 """ import os import prometheus_client from flask import Flask, Response, request from flask import jsonify from prometheus_client import CollectorRegistry, multiprocess from prometheus_client import Counter from prometheus_client.multiprocess import MultiProcessCollector # REQUEST_TIME = Summary('request_processing_seconds', 'Time spent processing request') REGISTRY = CollectorRegistry(auto_describe=False) MultiProcessCollector(REGISTRY) requests_total = Counter("app:requests_total", "Total count of requests", ["method", "url_rule"], registry=REGISTRY) app = Flask(__name__) def record(func): """ func 即为调用该函数的方法 """ def req(*args, **kwargs): requests_total.labels(method=request.method, url_rule=request.path.lower()).inc()
def test_prometheus_cleanup(registry):
pid = 1
def getpid():
return pid
# override use of os.getpid. _ValueClass is recreated after every test,
# so we don't need to clean up
from prometheus_client import core
core._ValueClass = core._MultiProcessValue(getpid)
histogram = metrics.Histogram(
name='histogram',
documentation='test histogram',
labelnames=['foo', 'bar', 'baz'],
statsd='{name}.{label}',
registry=registry,
)
counter = metrics.Counter(
name='counter',
documentation='test counter',
labelnames=['foo', 'bar', 'baz'],
statsd='{name}.{label}',
registry=registry,
)
from prometheus_client.multiprocess import MultiProcessCollector
collector = MultiProcessCollector(registry)
labels = {'foo': 'foo', 'bar': 'bar', 'baz': 'baz'}
def collect():
return {m.name: m for m in collector.collect()}
def files():
return list(sorted(os.listdir(os.environ['prometheus_multiproc_dir'])))
counter.inc(1, **labels)
histogram.observe(0.5, **labels)
histogram.observe(2.5, **labels)
assert files() == [
'counter_1.db',
'histogram_1.db',
]
before = collect()
metrics.prometheus_cleanup_worker(pid)
after = collect()
assert files() == [
'counter_archive.db',
'histogram_archive.db',
]
assert before == after
# magic!
pid += 1
# new worker, create some new metrics, check they are all combined
counter.inc(2, **labels)
histogram.observe(0.5, **labels)
histogram.observe(2.5, **labels)
later = collect()
assert files() == [
'counter_2.db',
'counter_archive.db',
'histogram_2.db',
'histogram_archive.db',
]
# check counter is correct
assert later['counter'].samples == [
Sample(counter_name('counter_total'), labels, 3.0),
]
expected_histogram = [
Sample('histogram_bucket', dict(le='0.005', **labels), 0.0),
Sample('histogram_bucket', dict(le='0.01', **labels), 0.0),
Sample('histogram_bucket', dict(le='0.025', **labels), 0.0),
Sample('histogram_bucket', dict(le='0.05', **labels), 0.0),
Sample('histogram_bucket', dict(le='0.075', **labels), 0.0),
Sample('histogram_bucket', dict(le='0.1', **labels), 0.0),
Sample('histogram_bucket', dict(le='0.25', **labels), 0.0),
Sample('histogram_bucket', dict(le='0.5', **labels), 2.0),
Sample('histogram_bucket', dict(le='0.75', **labels), 2.0),
Sample('histogram_bucket', dict(le='1.0', **labels), 2.0),
Sample('histogram_bucket', dict(le='2.5', **labels), 4.0),
Sample('histogram_bucket', dict(le='5.0', **labels), 4.0),
Sample('histogram_bucket', dict(le='7.5', **labels), 4.0),
Sample('histogram_bucket', dict(le='10.0', **labels), 4.0),
Sample('histogram_bucket', dict(le='+Inf', **labels), 4.0),
Sample('histogram_count', labels, 4.0),
Sample('histogram_sum', labels, 6.0),
]
# check histogram is correct
later['histogram'].samples.sort(key=metrics.histogram_sorter)
assert later['histogram'].samples == expected_histogram
# check the final files produce the correct numbers
metrics.prometheus_cleanup_worker(pid)
final = collect()
assert files() == [
'counter_archive.db',
'histogram_archive.db',
]
final['histogram'].samples.sort(key=metrics.histogram_sorter)
assert later == final
def metrics(request):
log.info('Serving metrics')
registry = CollectorRegistry()
MultiProcessCollector(registry)
data = generate_latest(registry)
return Response(data, content_type='text/plain')
def setUp(self):
self.tempdir = tempfile.mkdtemp()
os.environ['PROMETHEUS_MULTIPROC_DIR'] = self.tempdir
values.ValueClass = MultiProcessValue(lambda: 123)
self.registry = CollectorRegistry()
self.collector = MultiProcessCollector(self.registry)
class TestMultiProcess(unittest.TestCase):
def setUp(self):
self.tempdir = tempfile.mkdtemp()
os.environ['PROMETHEUS_MULTIPROC_DIR'] = self.tempdir
values.ValueClass = MultiProcessValue(lambda: 123)
self.registry = CollectorRegistry()
self.collector = MultiProcessCollector(self.registry)
@property
def _value_class(self):
return
def tearDown(self):
del os.environ['PROMETHEUS_MULTIPROC_DIR']
shutil.rmtree(self.tempdir)
values.ValueClass = MutexValue
def test_counter_adds(self):
c1 = Counter('c', 'help', registry=None)
values.ValueClass = MultiProcessValue(lambda: 456)
c2 = Counter('c', 'help', registry=None)
self.assertEqual(0, self.registry.get_sample_value('c_total'))
c1.inc(1)
c2.inc(2)
self.assertEqual(3, self.registry.get_sample_value('c_total'))
def test_summary_adds(self):
s1 = Summary('s', 'help', registry=None)
values.ValueClass = MultiProcessValue(lambda: 456)
s2 = Summary('s', 'help', registry=None)
self.assertEqual(0, self.registry.get_sample_value('s_count'))
self.assertEqual(0, self.registry.get_sample_value('s_sum'))
s1.observe(1)
s2.observe(2)
self.assertEqual(2, self.registry.get_sample_value('s_count'))
self.assertEqual(3, self.registry.get_sample_value('s_sum'))
def test_histogram_adds(self):
h1 = Histogram('h', 'help', registry=None)
values.ValueClass = MultiProcessValue(lambda: 456)
h2 = Histogram('h', 'help', registry=None)
self.assertEqual(0, self.registry.get_sample_value('h_count'))
self.assertEqual(0, self.registry.get_sample_value('h_sum'))
self.assertEqual(
0, self.registry.get_sample_value('h_bucket', {'le': '5.0'}))
h1.observe(1)
h2.observe(2)
self.assertEqual(2, self.registry.get_sample_value('h_count'))
self.assertEqual(3, self.registry.get_sample_value('h_sum'))
self.assertEqual(
2, self.registry.get_sample_value('h_bucket', {'le': '5.0'}))
def test_gauge_all(self):
g1 = Gauge('g', 'help', registry=None)
values.ValueClass = MultiProcessValue(lambda: 456)
g2 = Gauge('g', 'help', registry=None)
self.assertEqual(0,
self.registry.get_sample_value('g', {'pid': '123'}))
self.assertEqual(0,
self.registry.get_sample_value('g', {'pid': '456'}))
g1.set(1)
g2.set(2)
mark_process_dead(123)
self.assertEqual(1,
self.registry.get_sample_value('g', {'pid': '123'}))
self.assertEqual(2,
self.registry.get_sample_value('g', {'pid': '456'}))
def test_gauge_liveall(self):
g1 = Gauge('g', 'help', registry=None, multiprocess_mode='liveall')
values.ValueClass = MultiProcessValue(lambda: 456)
g2 = Gauge('g', 'help', registry=None, multiprocess_mode='liveall')
self.assertEqual(0,
self.registry.get_sample_value('g', {'pid': '123'}))
self.assertEqual(0,
self.registry.get_sample_value('g', {'pid': '456'}))
g1.set(1)
g2.set(2)
self.assertEqual(1,
self.registry.get_sample_value('g', {'pid': '123'}))
self.assertEqual(2,
self.registry.get_sample_value('g', {'pid': '456'}))
mark_process_dead(123, os.environ['PROMETHEUS_MULTIPROC_DIR'])
self.assertEqual(None,
self.registry.get_sample_value('g', {'pid': '123'}))
self.assertEqual(2,
self.registry.get_sample_value('g', {'pid': '456'}))
def test_gauge_min(self):
g1 = Gauge('g', 'help', registry=None, multiprocess_mode='min')
values.ValueClass = MultiProcessValue(lambda: 456)
g2 = Gauge('g', 'help', registry=None, multiprocess_mode='min')
self.assertEqual(0, self.registry.get_sample_value('g'))
g1.set(1)
g2.set(2)
self.assertEqual(1, self.registry.get_sample_value('g'))
def test_gauge_max(self):
g1 = Gauge('g', 'help', registry=None, multiprocess_mode='max')
values.ValueClass = MultiProcessValue(lambda: 456)
g2 = Gauge('g', 'help', registry=None, multiprocess_mode='max')
self.assertEqual(0, self.registry.get_sample_value('g'))
g1.set(1)
g2.set(2)
self.assertEqual(2, self.registry.get_sample_value('g'))
def test_gauge_livesum(self):
g1 = Gauge('g', 'help', registry=None, multiprocess_mode='livesum')
values.ValueClass = MultiProcessValue(lambda: 456)
g2 = Gauge('g', 'help', registry=None, multiprocess_mode='livesum')
self.assertEqual(0, self.registry.get_sample_value('g'))
g1.set(1)
g2.set(2)
self.assertEqual(3, self.registry.get_sample_value('g'))
mark_process_dead(123, os.environ['PROMETHEUS_MULTIPROC_DIR'])
self.assertEqual(2, self.registry.get_sample_value('g'))
def test_namespace_subsystem(self):
c1 = Counter('c',
'help',
registry=None,
namespace='ns',
subsystem='ss')
c1.inc(1)
self.assertEqual(1, self.registry.get_sample_value('ns_ss_c_total'))
def test_counter_across_forks(self):
pid = 0
values.ValueClass = MultiProcessValue(lambda: pid)
c1 = Counter('c', 'help', registry=None)
self.assertEqual(0, self.registry.get_sample_value('c_total'))
c1.inc(1)
c1.inc(1)
pid = 1
c1.inc(1)
self.assertEqual(3, self.registry.get_sample_value('c_total'))
self.assertEqual(1, c1._value.get())
def test_initialization_detects_pid_change(self):
pid = 0
values.ValueClass = MultiProcessValue(lambda: pid)
# can not inspect the files cache directly, as it's a closure, so we
# check for the actual files themselves
def files():
fs = os.listdir(os.environ['PROMETHEUS_MULTIPROC_DIR'])
fs.sort()
return fs
c1 = Counter('c1', 'c1', registry=None)
self.assertEqual(files(), ['counter_0.db'])
c2 = Counter('c2', 'c2', registry=None)
self.assertEqual(files(), ['counter_0.db'])
pid = 1
c3 = Counter('c3', 'c3', registry=None)
self.assertEqual(files(), ['counter_0.db', 'counter_1.db'])
def test_collect(self):
pid = 0
values.ValueClass = MultiProcessValue(lambda: pid)
labels = dict((i, i) for i in 'abcd')
def add_label(key, value):
l = labels.copy()
l[key] = value
return l
c = Counter('c', 'help', labelnames=labels.keys(), registry=None)
g = Gauge('g', 'help', labelnames=labels.keys(), registry=None)
h = Histogram('h', 'help', labelnames=labels.keys(), registry=None)
c.labels(**labels).inc(1)
g.labels(**labels).set(1)
h.labels(**labels).observe(1)
pid = 1
c.labels(**labels).inc(1)
g.labels(**labels).set(1)
h.labels(**labels).observe(5)
metrics = dict((m.name, m) for m in self.collector.collect())
self.assertEqual(metrics['c'].samples,
[Sample('c_total', labels, 2.0)])
metrics['g'].samples.sort(key=lambda x: x[1]['pid'])
self.assertEqual(metrics['g'].samples, [
Sample('g', add_label('pid', '0'), 1.0),
Sample('g', add_label('pid', '1'), 1.0),
])
metrics['h'].samples.sort(
key=lambda x: (x[0], float(x[1].get('le', 0))))
expected_histogram = [
Sample('h_bucket', add_label('le', '0.005'), 0.0),
Sample('h_bucket', add_label('le', '0.01'), 0.0),
Sample('h_bucket', add_label('le', '0.025'), 0.0),
Sample('h_bucket', add_label('le', '0.05'), 0.0),
Sample('h_bucket', add_label('le', '0.075'), 0.0),
Sample('h_bucket', add_label('le', '0.1'), 0.0),
Sample('h_bucket', add_label('le', '0.25'), 0.0),
Sample('h_bucket', add_label('le', '0.5'), 0.0),
Sample('h_bucket', add_label('le', '0.75'), 0.0),
Sample('h_bucket', add_label('le', '1.0'), 1.0),
Sample('h_bucket', add_label('le', '2.5'), 1.0),
Sample('h_bucket', add_label('le', '5.0'), 2.0),
Sample('h_bucket', add_label('le', '7.5'), 2.0),
Sample('h_bucket', add_label('le', '10.0'), 2.0),
Sample('h_bucket', add_label('le', '+Inf'), 2.0),
Sample('h_count', labels, 2.0),
Sample('h_sum', labels, 6.0),
]
self.assertEqual(metrics['h'].samples, expected_histogram)
def test_merge_no_accumulate(self):
pid = 0
values.ValueClass = MultiProcessValue(lambda: pid)
labels = dict((i, i) for i in 'abcd')
def add_label(key, value):
l = labels.copy()
l[key] = value
return l
h = Histogram('h', 'help', labelnames=labels.keys(), registry=None)
h.labels(**labels).observe(1)
pid = 1
h.labels(**labels).observe(5)
path = os.path.join(os.environ['PROMETHEUS_MULTIPROC_DIR'], '*.db')
files = glob.glob(path)
metrics = dict(
(m.name, m) for m in self.collector.merge(files, accumulate=False))
metrics['h'].samples.sort(
key=lambda x: (x[0], float(x[1].get('le', 0))))
expected_histogram = [
Sample('h_bucket', add_label('le', '0.005'), 0.0),
Sample('h_bucket', add_label('le', '0.01'), 0.0),
Sample('h_bucket', add_label('le', '0.025'), 0.0),
Sample('h_bucket', add_label('le', '0.05'), 0.0),
Sample('h_bucket', add_label('le', '0.075'), 0.0),
Sample('h_bucket', add_label('le', '0.1'), 0.0),
Sample('h_bucket', add_label('le', '0.25'), 0.0),
Sample('h_bucket', add_label('le', '0.5'), 0.0),
Sample('h_bucket', add_label('le', '0.75'), 0.0),
Sample('h_bucket', add_label('le', '1.0'), 1.0),
Sample('h_bucket', add_label('le', '2.5'), 0.0),
Sample('h_bucket', add_label('le', '5.0'), 1.0),
Sample('h_bucket', add_label('le', '7.5'), 0.0),
Sample('h_bucket', add_label('le', '10.0'), 0.0),
Sample('h_bucket', add_label('le', '+Inf'), 0.0),
Sample('h_sum', labels, 6.0),
]
self.assertEqual(metrics['h'].samples, expected_histogram)
def test_missing_gauge_file_during_merge(self):
# These files don't exist, just like if mark_process_dead(9999999) had been
# called during self.collector.collect(), after the glob found it
# but before the merge actually happened.
# This should not raise and return no metrics
self.assertFalse(
self.collector.merge([
os.path.join(self.tempdir, 'gauge_liveall_9999999.db'),
os.path.join(self.tempdir, 'gauge_livesum_9999999.db'),
]))
def create_registry():
registry = CollectorRegistry()
MultiProcessCollector(registry)
return registry
def setUp(self):
self.tempdir = tempfile.mkdtemp()
os.environ['prometheus_multiproc_dir'] = self.tempdir
core._ValueClass = core._MultiProcessValue(lambda: 123)
self.registry = CollectorRegistry()
MultiProcessCollector(self.registry, self.tempdir)
class TestMultiProcess(unittest.TestCase):
def setUp(self):
self.tempdir = tempfile.mkdtemp()
os.environ['prometheus_multiproc_dir'] = self.tempdir
core._ValueClass = core._MultiProcessValue(lambda: 123)
self.registry = CollectorRegistry()
self.collector = MultiProcessCollector(self.registry, self.tempdir)
def tearDown(self):
del os.environ['prometheus_multiproc_dir']
shutil.rmtree(self.tempdir)
core._ValueClass = core._MutexValue
def test_counter_adds(self):
c1 = Counter('c', 'help', registry=None)
core._ValueClass = core._MultiProcessValue(lambda: 456)
c2 = Counter('c', 'help', registry=None)
self.assertEqual(0, self.registry.get_sample_value('c_total'))
c1.inc(1)
c2.inc(2)
self.assertEqual(3, self.registry.get_sample_value('c_total'))
def test_summary_adds(self):
s1 = Summary('s', 'help', registry=None)
core._ValueClass = core._MultiProcessValue(lambda: 456)
s2 = Summary('s', 'help', registry=None)
self.assertEqual(0, self.registry.get_sample_value('s_count'))
self.assertEqual(0, self.registry.get_sample_value('s_sum'))
s1.observe(1)
s2.observe(2)
self.assertEqual(2, self.registry.get_sample_value('s_count'))
self.assertEqual(3, self.registry.get_sample_value('s_sum'))
def test_histogram_adds(self):
h1 = Histogram('h', 'help', registry=None)
core._ValueClass = core._MultiProcessValue(lambda: 456)
h2 = Histogram('h', 'help', registry=None)
self.assertEqual(0, self.registry.get_sample_value('h_count'))
self.assertEqual(0, self.registry.get_sample_value('h_sum'))
self.assertEqual(0, self.registry.get_sample_value('h_bucket', {'le': '5.0'}))
h1.observe(1)
h2.observe(2)
self.assertEqual(2, self.registry.get_sample_value('h_count'))
self.assertEqual(3, self.registry.get_sample_value('h_sum'))
self.assertEqual(2, self.registry.get_sample_value('h_bucket', {'le': '5.0'}))
def test_gauge_all(self):
g1 = Gauge('g', 'help', registry=None)
core._ValueClass = core._MultiProcessValue(lambda: 456)
g2 = Gauge('g', 'help', registry=None)
self.assertEqual(0, self.registry.get_sample_value('g', {'pid': '123'}))
self.assertEqual(0, self.registry.get_sample_value('g', {'pid': '456'}))
g1.set(1)
g2.set(2)
mark_process_dead(123, os.environ['prometheus_multiproc_dir'])
self.assertEqual(1, self.registry.get_sample_value('g', {'pid': '123'}))
self.assertEqual(2, self.registry.get_sample_value('g', {'pid': '456'}))
def test_gauge_liveall(self):
g1 = Gauge('g', 'help', registry=None, multiprocess_mode='liveall')
core._ValueClass = core._MultiProcessValue(lambda: 456)
g2 = Gauge('g', 'help', registry=None, multiprocess_mode='liveall')
self.assertEqual(0, self.registry.get_sample_value('g', {'pid': '123'}))
self.assertEqual(0, self.registry.get_sample_value('g', {'pid': '456'}))
g1.set(1)
g2.set(2)
self.assertEqual(1, self.registry.get_sample_value('g', {'pid': '123'}))
self.assertEqual(2, self.registry.get_sample_value('g', {'pid': '456'}))
mark_process_dead(123, os.environ['prometheus_multiproc_dir'])
self.assertEqual(None, self.registry.get_sample_value('g', {'pid': '123'}))
self.assertEqual(2, self.registry.get_sample_value('g', {'pid': '456'}))
def test_gauge_min(self):
g1 = Gauge('g', 'help', registry=None, multiprocess_mode='min')
core._ValueClass = core._MultiProcessValue(lambda: 456)
g2 = Gauge('g', 'help', registry=None, multiprocess_mode='min')
self.assertEqual(0, self.registry.get_sample_value('g'))
g1.set(1)
g2.set(2)
self.assertEqual(1, self.registry.get_sample_value('g'))
def test_gauge_max(self):
g1 = Gauge('g', 'help', registry=None, multiprocess_mode='max')
core._ValueClass = core._MultiProcessValue(lambda: 456)
g2 = Gauge('g', 'help', registry=None, multiprocess_mode='max')
self.assertEqual(0, self.registry.get_sample_value('g'))
g1.set(1)
g2.set(2)
self.assertEqual(2, self.registry.get_sample_value('g'))
def test_gauge_livesum(self):
g1 = Gauge('g', 'help', registry=None, multiprocess_mode='livesum')
core._ValueClass = core._MultiProcessValue(lambda: 456)
g2 = Gauge('g', 'help', registry=None, multiprocess_mode='livesum')
self.assertEqual(0, self.registry.get_sample_value('g'))
g1.set(1)
g2.set(2)
self.assertEqual(3, self.registry.get_sample_value('g'))
mark_process_dead(123, os.environ['prometheus_multiproc_dir'])
self.assertEqual(2, self.registry.get_sample_value('g'))
def test_namespace_subsystem(self):
c1 = Counter('c', 'help', registry=None, namespace='ns', subsystem='ss')
c1.inc(1)
self.assertEqual(1, self.registry.get_sample_value('ns_ss_c_total'))
def test_counter_across_forks(self):
pid = 0
core._ValueClass = core._MultiProcessValue(lambda: pid)
c1 = Counter('c', 'help', registry=None)
self.assertEqual(0, self.registry.get_sample_value('c_total'))
c1.inc(1)
c1.inc(1)
pid = 1
c1.inc(1)
self.assertEqual(3, self.registry.get_sample_value('c_total'))
self.assertEqual(1, c1._value.get())
def test_initialization_detects_pid_change(self):
pid = 0
core._ValueClass = core._MultiProcessValue(lambda: pid)
# can not inspect the files cache directly, as it's a closure, so we
# check for the actual files themselves
def files():
fs = os.listdir(os.environ['prometheus_multiproc_dir'])
fs.sort()
return fs
c1 = Counter('c1', 'c1', registry=None)
self.assertEqual(files(), ['counter_0.db'])
c2 = Counter('c2', 'c2', registry=None)
self.assertEqual(files(), ['counter_0.db'])
pid = 1
c3 = Counter('c3', 'c3', registry=None)
self.assertEqual(files(), ['counter_0.db', 'counter_1.db'])
@unittest.skipIf(sys.version_info < (2, 7), "Test requires Python 2.7+.")
def test_collect(self):
pid = 0
core._ValueClass = core._MultiProcessValue(lambda: pid)
labels = dict((i, i) for i in 'abcd')
def add_label(key, value):
l = labels.copy()
l[key] = value
return l
c = Counter('c', 'help', labelnames=labels.keys(), registry=None)
g = Gauge('g', 'help', labelnames=labels.keys(), registry=None)
h = Histogram('h', 'help', labelnames=labels.keys(), registry=None)
c.labels(**labels).inc(1)
g.labels(**labels).set(1)
h.labels(**labels).observe(1)
pid = 1
c.labels(**labels).inc(1)
g.labels(**labels).set(1)
h.labels(**labels).observe(5)
metrics = dict((m.name, m) for m in self.collector.collect())
self.assertEqual(
metrics['c'].samples, [Sample('c_total', labels, 2.0)]
)
metrics['g'].samples.sort(key=lambda x: x[1]['pid'])
self.assertEqual(metrics['g'].samples, [
Sample('g', add_label('pid', '0'), 1.0),
Sample('g', add_label('pid', '1'), 1.0),
])
metrics['h'].samples.sort(
key=lambda x: (x[0], float(x[1].get('le', 0)))
)
expected_histogram = [
Sample('h_bucket', add_label('le', '0.005'), 0.0),
Sample('h_bucket', add_label('le', '0.01'), 0.0),
Sample('h_bucket', add_label('le', '0.025'), 0.0),
Sample('h_bucket', add_label('le', '0.05'), 0.0),
Sample('h_bucket', add_label('le', '0.075'), 0.0),
Sample('h_bucket', add_label('le', '0.1'), 0.0),
Sample('h_bucket', add_label('le', '0.25'), 0.0),
Sample('h_bucket', add_label('le', '0.5'), 0.0),
Sample('h_bucket', add_label('le', '0.75'), 0.0),
Sample('h_bucket', add_label('le', '1.0'), 1.0),
Sample('h_bucket', add_label('le', '2.5'), 1.0),
Sample('h_bucket', add_label('le', '5.0'), 2.0),
Sample('h_bucket', add_label('le', '7.5'), 2.0),
Sample('h_bucket', add_label('le', '10.0'), 2.0),
Sample('h_bucket', add_label('le', '+Inf'), 2.0),
Sample('h_count', labels, 2.0),
Sample('h_sum', labels, 6.0),
]
self.assertEqual(metrics['h'].samples, expected_histogram)
@unittest.skipIf(sys.version_info < (2, 7), "Test requires Python 2.7+.")
def test_merge_no_accumulate(self):
pid = 0
core._ValueClass = core._MultiProcessValue(lambda: pid)
labels = dict((i, i) for i in 'abcd')
def add_label(key, value):
l = labels.copy()
l[key] = value
return l
h = Histogram('h', 'help', labelnames=labels.keys(), registry=None)
h.labels(**labels).observe(1)
pid = 1
h.labels(**labels).observe(5)
path = os.path.join(os.environ['prometheus_multiproc_dir'], '*.db')
files = glob.glob(path)
metrics = dict(
(m.name, m) for m in self.collector.merge(files, accumulate=False)
)
metrics['h'].samples.sort(
key=lambda x: (x[0], float(x[1].get('le', 0)))
)
expected_histogram = [
Sample('h_bucket', add_label('le', '0.005'), 0.0),
Sample('h_bucket', add_label('le', '0.01'), 0.0),
Sample('h_bucket', add_label('le', '0.025'), 0.0),
Sample('h_bucket', add_label('le', '0.05'), 0.0),
Sample('h_bucket', add_label('le', '0.075'), 0.0),
Sample('h_bucket', add_label('le', '0.1'), 0.0),
Sample('h_bucket', add_label('le', '0.25'), 0.0),
Sample('h_bucket', add_label('le', '0.5'), 0.0),
Sample('h_bucket', add_label('le', '0.75'), 0.0),
Sample('h_bucket', add_label('le', '1.0'), 1.0),
Sample('h_bucket', add_label('le', '2.5'), 0.0),
Sample('h_bucket', add_label('le', '5.0'), 1.0),
Sample('h_bucket', add_label('le', '7.5'), 0.0),
Sample('h_bucket', add_label('le', '10.0'), 0.0),
Sample('h_bucket', add_label('le', '+Inf'), 0.0),
Sample('h_sum', labels, 6.0),
]
self.assertEqual(metrics['h'].samples, expected_histogram)
