def test_histogram_protected(context, registry):
histogram = metrics.Histogram(
name='test_histogram_protected',
documentation='test histogram',
labelnames=['label'],
statsd='{name}.{label}',
registry=registry,
)
histogram.prometheus = 'THIS WILL RAISE'
histogram.observe(1.0, label='label')
assert context.logs.exists(msg='Failed to collect histogram metric')
def test_histogram(context, registry):
histogram = metrics.Histogram(
name='test_histogram',
documentation='test histogram',
labelnames=['label'],
statsd='{name}.{label}',
registry=registry,
)
labels = {'label': 'value'}
count = registry.get_metric('test_histogram_count', **labels)
sum_ = registry.get_metric('test_histogram_sum', **labels)
bucket = registry.get_metric('test_histogram_bucket', le='2.5', **labels)
histogram.observe(2.0, **labels)
assert context.statsd[0] == 'test.histogram.value:2.000000|ms'
assert registry.get_metric('test_histogram_count', **labels) - count == 1.0
assert registry.get_metric('test_histogram_sum', **labels) - sum_ == 2.0
after_bucket = registry.get_metric(
'test_histogram_bucket', le='2.5', **labels)
assert after_bucket - bucket == 1.0
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