/usr/lib/python2.7/dist-packages/prometheus_client/core.py is in python-prometheus-client 0.0.13-1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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from __future__ import unicode_literals
import copy
import math
import re
import time
import types
try:
from BaseHTTPServer import BaseHTTPRequestHandler
except ImportError:
# Python 3
unicode = str
from functools import wraps
from threading import Lock
_METRIC_NAME_RE = re.compile(r'^[a-zA-Z_:][a-zA-Z0-9_:]*$')
_METRIC_LABEL_NAME_RE = re.compile(r'^[a-zA-Z_:][a-zA-Z0-9_:]*$')
_RESERVED_METRIC_LABEL_NAME_RE = re.compile(r'^__.*$')
_INF = float("inf")
_MINUS_INF = float("-inf")
class CollectorRegistry(object):
'''Metric collector registry.
Collectors must have a no-argument method 'collect' that returns a list of
Metric objects. The returned metrics should be consistent with the Prometheus
exposition formats.
'''
def __init__(self):
self._collectors = set()
self._lock = Lock()
def register(self, collector):
'''Add a collector to the registry.'''
with self._lock:
self._collectors.add(collector)
def unregister(self, collector):
'''Remove a collector from the registry.'''
with self._lock:
self._collectors.remove(collector)
def collect(self):
'''Yields metrics from the collectors in the registry.'''
collectors = None
with self._lock:
collectors = copy.copy(self._collectors)
for collector in collectors:
for metric in collector.collect():
yield metric
def get_sample_value(self, name, labels=None):
'''Returns the sample value, or None if not found.
This is inefficient, and intended only for use in unittests.
'''
if labels is None:
labels = {}
for metric in self.collect():
for n, l, value in metric.samples:
if n == name and l == labels:
return value
return None
REGISTRY = CollectorRegistry()
'''The default registry.'''
_METRIC_TYPES = ('counter', 'gauge', 'summary', 'histogram', 'untyped')
class Metric(object):
'''A single metric family and its samples.
This is intended only for internal use by the instrumentation client.
Custom collectors should use GaugeMetricFamily, CounterMetricFamily
and SummaryMetricFamily instead.
'''
def __init__(self, name, documentation, typ):
self.name = name
self.documentation = documentation
if typ not in _METRIC_TYPES:
raise ValueError('Invalid metric type: ' + typ)
self.type = typ
self.samples = []
def add_sample(self, name, labels, value):
'''Add a sample to the metric.
Internal-only, do not use.'''
self.samples.append((name, labels, value))
def __eq__(self, other):
return (isinstance(other, Metric)
and self.name == other.name
and self.documentation == other.documentation
and self.type == other.type
and self.samples == other.samples)
class CounterMetricFamily(Metric):
'''A single counter and its samples.
For use by custom collectors.
'''
def __init__(self, name, documentation, value=None, labels=None):
Metric.__init__(self, name, documentation, 'counter')
if labels is not None and value is not None:
raise ValueError('Can only specify at most one of value and labels.')
if labels is None:
labels = []
self._labelnames = labels
if value is not None:
self.add_metric([], value)
def add_metric(self, labels, value):
'''Add a metric to the metric family.
Args:
labels: A list of label values
value: The value of the metric.
'''
self.samples.append((self.name, dict(zip(self._labelnames, labels)), value))
class GaugeMetricFamily(Metric):
'''A single gauge and its samples.
For use by custom collectors.
'''
def __init__(self, name, documentation, value=None, labels=None):
Metric.__init__(self, name, documentation, 'gauge')
if labels is not None and value is not None:
raise ValueError('Can only specify at most one of value and labels.')
if labels is None:
labels = []
self._labelnames = labels
if value is not None:
self.add_metric([], value)
def add_metric(self, labels, value):
'''Add a metric to the metric family.
Args:
labels: A list of label values
value: A float
'''
self.samples.append((self.name, dict(zip(self._labelnames, labels)), value))
class SummaryMetricFamily(Metric):
'''A single summary and its samples.
For use by custom collectors.
'''
def __init__(self, name, documentation, count_value=None, sum_value=None, labels=None):
Metric.__init__(self, name, documentation, 'summary')
if (sum_value is None) != (count_value is None):
raise ValueError('count_value and sum_value must be provided together.')
if labels is not None and count_value is not None:
raise ValueError('Can only specify at most one of value and labels.')
if labels is None:
labels = []
self._labelnames = labels
if count_value is not None:
self.add_metric([], count_value, sum_value)
def add_metric(self, labels, count_value, sum_value):
'''Add a metric to the metric family.
Args:
labels: A list of label values
count_value: The count value of the metric.
sum_value: The sum value of the metric.
'''
self.samples.append((self.name + '_count', dict(zip(self._labelnames, labels)), count_value))
self.samples.append((self.name + '_sum', dict(zip(self._labelnames, labels)), sum_value))
class HistogramMetricFamily(Metric):
'''A single histogram and its samples.
For use by custom collectors.
'''
def __init__(self, name, documentation, buckets=None, sum_value=None, labels=None):
Metric.__init__(self, name, documentation, 'histogram')
if (sum_value is None) != (buckets is None):
raise ValueError('buckets and sum_value must be provided together.')
if labels is not None and buckets is not None:
raise ValueError('Can only specify at most one of buckets and labels.')
if labels is None:
labels = []
self._labelnames = labels
if buckets is not None:
self.add_metric([], buckets, sum_value)
def add_metric(self, labels, buckets, sum_value):
'''Add a metric to the metric family.
Args:
labels: A list of label values
buckets: A list of pairs of bucket names and values.
The buckets must be sorted, and +Inf present.
sum_value: The sum value of the metric.
'''
for bucket, value in buckets:
self.samples.append((self.name + '_bucket', dict(list(zip(self._labelnames, labels)) + [('le', bucket)]), value))
# +Inf is last and provides the count value.
self.samples.append((self.name + '_count', dict(zip(self._labelnames, labels)), buckets[-1][1]))
self.samples.append((self.name + '_sum', dict(zip(self._labelnames, labels)), sum_value))
class _MutexValue(object):
'''A float protected by a mutex.'''
def __init__(self, name, labelnames, labelvalues):
self._value = 0.0
self._lock = Lock()
def inc(self, amount):
with self._lock:
self._value += amount
def set(self, value):
with self._lock:
self._value = value
def get(self):
with self._lock:
return self._value
_ValueClass = _MutexValue
class _LabelWrapper(object):
'''Handles labels for the wrapped metric.'''
def __init__(self, wrappedClass, name, labelnames, **kwargs):
self._wrappedClass = wrappedClass
self._type = wrappedClass._type
self._name = name
self._labelnames = labelnames
self._kwargs = kwargs
self._lock = Lock()
self._metrics = {}
for l in labelnames:
if l.startswith('__'):
raise ValueError('Invalid label metric name: ' + l)
def labels(self, *labelvalues):
'''Return the child for the given labelset.
Labels can be provided as a tuple or as a dict:
c = Counter('c', 'counter', ['l', 'm'])
# Set labels by position
c.labels('0', '1').inc()
# Set labels by name
c.labels({'l': '0', 'm': '1'}).inc()
'''
if len(labelvalues) == 1 and type(labelvalues[0]) == dict:
if sorted(labelvalues[0].keys()) != sorted(self._labelnames):
raise ValueError('Incorrect label names')
labelvalues = tuple([unicode(labelvalues[0][l]) for l in self._labelnames])
else:
if len(labelvalues) != len(self._labelnames):
raise ValueError('Incorrect label count')
labelvalues = tuple([unicode(l) for l in labelvalues])
with self._lock:
if labelvalues not in self._metrics:
self._metrics[labelvalues] = self._wrappedClass(self._name, self._labelnames, labelvalues, **self._kwargs)
return self._metrics[labelvalues]
def remove(self, *labelvalues):
'''Remove the given labelset from the metric.'''
if len(labelvalues) != len(self._labelnames):
raise ValueError('Incorrect label count')
labelvalues = tuple([unicode(l) for l in labelvalues])
with self._lock:
del self._metrics[labelvalues]
def _samples(self):
with self._lock:
metrics = self._metrics.copy()
for labels, metric in metrics.items():
series_labels = list(dict(zip(self._labelnames, labels)).items())
for suffix, sample_labels, value in metric._samples():
yield (suffix, dict(series_labels + list(sample_labels.items())), value)
def _MetricWrapper(cls):
'''Provides common functionality for metrics.'''
def init(name, documentation, labelnames=(), namespace='', subsystem='', registry=REGISTRY, **kwargs):
full_name = ''
if namespace:
full_name += namespace + '_'
if subsystem:
full_name += subsystem + '_'
full_name += name
if labelnames:
labelnames = tuple(labelnames)
for l in labelnames:
if not _METRIC_LABEL_NAME_RE.match(l):
raise ValueError('Invalid label metric name: ' + l)
if _RESERVED_METRIC_LABEL_NAME_RE.match(l):
raise ValueError('Reserved label metric name: ' + l)
if l in cls._reserved_labelnames:
raise ValueError('Reserved label metric name: ' + l)
collector = _LabelWrapper(cls, name, labelnames, **kwargs)
else:
collector = cls(name, labelnames, (), **kwargs)
if not _METRIC_NAME_RE.match(full_name):
raise ValueError('Invalid metric name: ' + full_name)
def collect():
metric = Metric(full_name, documentation, cls._type)
for suffix, labels, value in collector._samples():
metric.add_sample(full_name + suffix, labels, value)
return [metric]
collector.collect = collect
if registry:
registry.register(collector)
return collector
return init
@_MetricWrapper
class Counter(object):
'''A Counter tracks counts of events or running totals.
Example use cases for Counters:
- Number of requests processed
- Number of items that were inserted into a queue
- Total amount of data that a system has processed
Counters can only go up (and be reset when the process restarts). If your use case can go down,
you should use a Gauge instead.
An example for a Counter:
from prometheus_client import Counter
c = Counter('my_failures_total', 'Description of counter')
c.inc() # Increment by 1
c.inc(1.6) # Increment by given value
'''
_type = 'counter'
_reserved_labelnames = []
def __init__(self, name, labelnames, labelvalues):
self._value = _ValueClass(name, labelnames, labelvalues)
def inc(self, amount=1):
'''Increment counter by the given amount.'''
if amount < 0:
raise ValueError('Counters can only be incremented by non-negative amounts.')
self._value.inc(amount)
def count_exceptions(self, exception=Exception):
'''Count exceptions in a block of code or function.
Can be used as a function decorator or context manager.
Increments the counter when an exception of the given
type is raised up out of the code.
'''
class ExceptionCounter(object):
def __init__(self, counter):
self._counter = counter
def __enter__(self):
pass
def __exit__(self, typ, value, traceback):
if isinstance(value, exception):
self._counter.inc()
def __call__(self, f):
@wraps(f)
def wrapped(*args, **kwargs):
with self:
return f(*args, **kwargs)
return wrapped
return ExceptionCounter(self)
def _samples(self):
return (('', {}, self._value.get()), )
@_MetricWrapper
class Gauge(object):
'''Gauge metric, to report instantaneous values.
Examples of Gauges include:
Inprogress requests
Number of items in a queue
Free memory
Total memory
Temperature
Gauges can go both up and down.
from prometheus_client import Gauge
g = Gauge('my_inprogress_requests', 'Description of gauge')
g.inc() # Increment by 1
g.dec(10) # Decrement by given value
g.set(4.2) # Set to a given value
'''
_type = 'gauge'
_reserved_labelnames = []
def __init__(self, name, labelnames, labelvalues):
self._value = _ValueClass(name, labelnames, labelvalues)
def inc(self, amount=1):
'''Increment gauge by the given amount.'''
self._value.inc(amount)
def dec(self, amount=1):
'''Decrement gauge by the given amount.'''
self._value.inc(-amount)
def set(self, value):
'''Set gauge to the given value.'''
self._value.set(float(value))
def set_to_current_time(self):
'''Set gauge to the current unixtime.'''
self.set(time.time())
def track_inprogress(self):
'''Track inprogress blocks of code or functions.
Can be used as a function decorator or context manager.
Increments the gauge when the code is entered,
and decrements when it is exited.
'''
class InprogressTracker(object):
def __init__(self, gauge):
self._gauge = gauge
def __enter__(self):
self._gauge.inc()
def __exit__(self, typ, value, traceback):
self._gauge.dec()
def __call__(self, f):
@wraps(f)
def wrapped(*args, **kwargs):
with self:
return f(*args, **kwargs)
return wrapped
return InprogressTracker(self)
def time(self):
'''Time a block of code or function, and set the duration in seconds.
Can be used as a function decorator or context manager.
'''
class Timer(object):
def __init__(self, gauge):
self._gauge = gauge
def __enter__(self):
self._start = time.time()
def __exit__(self, typ, value, traceback):
# Time can go backwards.
self._gauge.set(max(time.time() - self._start, 0))
def __call__(self, f):
@wraps(f)
def wrapped(*args, **kwargs):
with self:
return f(*args, **kwargs)
return wrapped
return Timer(self)
def set_function(self, f):
'''Call the provided function to return the Gauge value.
The function must return a float, and may be called from
multiple threads.
All other methods of the Gauge become NOOPs.
'''
def samples(self):
return (('', {}, float(f())), )
self._samples = types.MethodType(samples, self)
def _samples(self):
return (('', {}, self._value.get()), )
@_MetricWrapper
class Summary(object):
'''A Summary tracks the size and number of events.
Example use cases for Summaries:
- Response latency
- Request size
Example for a Summary:
from prometheus_client import Summary
s = Summary('request_size_bytes', 'Request size (bytes)')
s.observe(512) # Observe 512 (bytes)
Example for a Summary using time:
from prometheus_client import Summary
REQUEST_TIME = Summary('response_latency_seconds', 'Response latency (seconds)')
@REQUEST_TIME.time()
def create_response(request):
"""A dummy function"""
time.sleep(1)
'''
_type = 'summary'
_reserved_labelnames = ['quantile']
def __init__(self, name, labelnames, labelvalues):
self._count = _ValueClass(name + '_count', labelnames, labelvalues)
self._sum = _ValueClass(name + '_sum', labelnames, labelvalues)
def observe(self, amount):
'''Observe the given amount.'''
self._count.inc(1)
self._sum.inc(amount)
def time(self):
'''Time a block of code or function, and observe the duration in seconds.
Can be used as a function decorator or context manager.
'''
class Timer(object):
def __init__(self, summary):
self._summary = summary
def __enter__(self):
self._start = time.time()
def __exit__(self, typ, value, traceback):
# Time can go backwards.
self._summary.observe(max(time.time() - self._start, 0))
def __call__(self, f):
@wraps(f)
def wrapped(*args, **kwargs):
with self:
return f(*args, **kwargs)
return wrapped
return Timer(self)
def _samples(self):
return (
('_count', {}, self._count.get()),
('_sum', {}, self._sum.get()))
def _floatToGoString(d):
if d == _INF:
return '+Inf'
elif d == _MINUS_INF:
return '-Inf'
elif math.isnan(d):
return 'NaN'
else:
return repr(float(d))
@_MetricWrapper
class Histogram(object):
'''A Histogram tracks the size and number of events in buckets.
You can use Histograms for aggregatable calculation of quantiles.
Example use cases:
- Response latency
- Request size
Example for a Histogram:
from prometheus_client import Histogram
h = Histogram('request_size_bytes', 'Request size (bytes)')
h.observe(512) # Observe 512 (bytes)
Example for a Histogram using time:
from prometheus_client import Histogram
REQUEST_TIME = Histogram('response_latency_seconds', 'Response latency (seconds)')
@REQUEST_TIME.time()
def create_response(request):
"""A dummy function"""
time.sleep(1)
The default buckets are intended to cover a typical web/rpc request from milliseconds to seconds.
They can be overridden by passing `buckets` keyword argument to `Histogram`.
'''
_type = 'histogram'
_reserved_labelnames = ['histogram']
def __init__(self, name, labelnames, labelvalues, buckets=(.005, .01, .025, .05, .075, .1, .25, .5, .75, 1.0, 2.5, 5.0, 7.5, 10.0, _INF)):
self._sum = _ValueClass(name + '_sum', labelnames, labelvalues)
buckets = [float(b) for b in buckets]
if buckets != sorted(buckets):
# This is probably an error on the part of the user,
# so raise rather than sorting for them.
raise ValueError('Buckets not in sorted order')
if buckets and buckets[-1] != _INF:
buckets.append(_INF)
if len(buckets) < 2:
raise ValueError('Must have at least two buckets')
self._upper_bounds = buckets
self._buckets = []
bucket_labelnames = labelnames + ('le',)
for b in buckets:
self._buckets.append(_ValueClass(name + '_bucket', bucket_labelnames, labelvalues + (_floatToGoString(b),)))
def observe(self, amount):
'''Observe the given amount.'''
self._sum.inc(amount)
for i, bound in enumerate(self._upper_bounds):
if amount <= bound:
self._buckets[i].inc(1)
break
def time(self):
'''Time a block of code or function, and observe the duration in seconds.
Can be used as a function decorator or context manager.
'''
class Timer(object):
def __init__(self, histogram):
self._histogram = histogram
def __enter__(self):
self._start = time.time()
def __exit__(self, typ, value, traceback):
# Time can go backwards.
self._histogram.observe(max(time.time() - self._start, 0))
def __call__(self, f):
@wraps(f)
def wrapped(*args, **kwargs):
with self:
return f(*args, **kwargs)
return wrapped
return Timer(self)
def _samples(self):
samples = []
acc = 0
for i, bound in enumerate(self._upper_bounds):
acc += self._buckets[i].get()
samples.append(('_bucket', {'le': _floatToGoString(bound)}, acc))
samples.append(('_count', {}, acc))
samples.append(('_sum', {}, self._sum.get()))
return tuple(samples)
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