10000 initial commit with some tests and replaced _metrics with pandas Data… · engFelipeMonteiro/client_python@ea13dac · GitHub
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initial commit with some tests and replaced _metrics with pandas DataFrame
Signed-off-by: Felipe Monteiro Jácome <fmj1988@gmail.com>
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‎prometheus_client/metrics.py

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@@ -15,6 +15,8 @@
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from .samples import Exemplar, Sample
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from .utils import floatToGoString, INF
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import pandas as pd
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T = TypeVar('T', bound='MetricWrapperBase')
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F = TypeVar("F", bound=Callable[..., Any])
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@@ -714,3 +716,299 @@ def _child_samples(self) -> Iterable[Sample]:
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for i, s
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in enumerate(self._states)
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]
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class MetricPandasWrapperBase:
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_type: Optional[str] = None
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_reserved_labelnames: Sequence[str] = ()
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def _is_observable(self):
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# Whether this metric is observable, i.e.
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# * a metric without label names and values, or
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# * the child of a labelled metric.
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return not self._labelnames or (self._labelnames and self._labelvalues)
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def _raise_if_not_observable(self):
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# Functions that mutate the state of the metric, for example incrementing
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# a counter, will fail if the metric is not observable, because only if a
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# metric is observable will the value be initialized.
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if not self._is_observable():
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raise ValueError('%s metric is missing label values' % str(self._type))
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def _is_parent(self):
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return self._labelnames and not self._labelvalues
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def _get_metric(self):
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return Metric(self._name, self._documentation, self._type, self._unit)
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def describe(self):
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return [self._get_metric()]
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def collect(self):
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metric = self._get_metric()
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for suffix, labels, value, timestamp, exemplar in self._samples():
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metric.add_sample(self._name + suffix, labels, value, timestamp, exemplar)
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return [metric]
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def __str__(self):
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return f"{self._type}:{self._name}"
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def __repr__(self):
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metric_type = type(self)
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return f"{metric_type.__module__}.{metric_type.__name__}({self._name})"
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def __init__(self: T,
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name: str,
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documentation: str,
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labelnames: Iterable[str] = (),
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namespace: str = '',
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subsystem: str = '',
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unit: str = '',
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registry: Optional[CollectorRegistry] = REGISTRY,
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_labelvalues: Optional[Sequence[str]] = None,
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) -> None:
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self._name = _build_full_name(self._type, name, namespace, subsystem, unit)
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self._labelnames = _validate_labelnames(self, labelnames)
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self._labelvalues = tuple(_labelvalues or ())
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self._kwargs: Dict[str, Any] = {}
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self._documentation = documentation
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self._unit = unit
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if not METRIC_NAME_RE.match(self._name):
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raise ValueError('Invalid metric name: ' + self._name)
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if self._is_parent():
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# Prepare the fields needed for child metrics.
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self._lock = Lock()< F438 /div>
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self._metrics = pd.DataFrame(columns=labelnames)
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if self._is_observable():
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self._metric_init()
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if not self._labelvalues:
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# Register the multi-wrapper parent metric, or if a label-less metric, the whole shebang.
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if registry:
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registry.register(self)
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def labels(self: T, *labelvalues: Any, **labelkwargs: Any) -> T:
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"""Return the child for the given labelset.
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All metrics can have labels, allowing grouping of related time series.
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Taking a counter as an example:
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from prometheus_client import Counter
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c = Counter('my_requests_total', 'HTTP Failures', ['method', 'endpoint'])
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c.labels('get', '/').inc()
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c.labels('post', '/submit').inc()
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Labels can also be provided as keyword arguments:
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from prometheus_client import Counter
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c = Counter('my_requests_total', 'HTTP Failures', ['method', 'endpoint'])
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c.labels(method='get', endpoint='/').inc()
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c.labels(method='post', endpoint='/submit').inc()
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See the best practices on [naming](http://prometheus.io/docs/practices/naming/)
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and [labels](http://prometheus.io/docs/practices/instrumentation/#use-labels).
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"""
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if not self._labelnames:
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raise ValueError('No label names were set when constructing %s' % self)
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if self._labelvalues:
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raise ValueError('{} already has labels set ({}); can not chain calls to .labels()'.format(
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self,
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dict(zip(self._labelnames, self._labelvalues))
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))
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10000 825+
if labelvalues and labelkwargs:
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raise ValueError("Can't pass both *args and **kwargs")
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if labelkwargs:
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if sorted(labelkwargs) != sorted(self._labelnames):
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raise ValueError('Incorrect label names')
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labelvalues = tuple(str(labelkwargs[l]) for l in self._labelnames)
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else:
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if len(labelvalues) != len(self._labelnames):
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raise ValueError('Incorrect label count')
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labelvalues = tuple(str(l) for l in labelvalues)
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with self._lock:
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if labelvalues not in self._metrics:
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self._metrics[labelvalues] = self.__class__(
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self._name,
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documentation=self._documentation,
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labelnames=self._labelnames,
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unit=self._unit,
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_labelvalues=labelvalues,
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**self._kwargs
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)
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return self._metrics[labelvalues]
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def remove(self, *labelvalues):
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if not self._labelnames:
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raise ValueError('No label names were set when constructing %s' % self)
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"""Remove the given labelset from the metric."""
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if len(labelvalues) != len(self._labelnames):
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raise ValueError('Incorrect label count (expected %d, got %s)' % (len(self._labelnames), labelvalues))
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labelvalues = tuple(str(l) for l in labelvalues)
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with self._lock:
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del self._metrics[labelvalues]
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def clear(self) -> None:
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"""Remove all labelsets from the metric"""
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with self._lock:
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self._metrics = {}
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def _samples(self) -> Iterable[Sample]:
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if self._is_parent():
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return self._multi_samples()
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else:
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return self._child_samples()
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def _multi_samples(self) -> Iterable[Sample]:
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with self._lock:
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metrics = self._metrics.copy()
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for labels, metric in metrics.items():
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series_labels = list(zip(self._labelnames, labels))
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for suffix, sample_labels, value, timestamp, exemplar in metric._samples():
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yield Sample(suffix, dict(series_labels + list(sample_labels.items())), value, timestamp, exemplar)
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def _child_samples(self) -> Iterable[Sample]: # pragma: no cover
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raise NotImplementedError('_child_samples() must be implemented by %r' % self)
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def _metric_init(self): # pragma: no cover
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"""
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Initialize the metric object as a child, i.e. when it has labels (if any) set.
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This is factored as a separate function to allow for deferred initialization.
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"""
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raise NotImplementedError('_metric_init() must be implemented by %r' % self)
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class GaugePandas(MetricPandasWrapperBase):
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"""Gauge metric, to report instantaneous values.
892+
893+
Examples of Gauges include:
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- Inprogress requests
895+
- Number of items in a queue
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- Free memory
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- Total memory
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- Temperature
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Gauges can go both up and down.
901+
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from prometheus_client import Gauge
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904+
g = Gauge('my_inprogress_requests', 'Description of gauge')
905+
g.inc() # Increment by 1
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g.dec(10) # Decrement by given value
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g.set(4.2) # Set to a given value
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There are utilities for common use cases:
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g.set_to_current_time() # Set to current unixtime
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# Increment when entered, decrement when exited.
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@g.track_inprogress()
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def f():
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pass
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with g.track_inprogress():
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pass
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A Gauge can also take its value from a callback:
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923+
d = Gauge('data_objects', 'Number of objects')
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my_dict = {}
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d.set_function(lambda: len(my_dict))
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"""
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_type = 'gauge'
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_MULTIPROC_MODES = frozenset(('min', 'max', 'livesum', 'liveall', 'all'))
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930+
def __init__(self,
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name: str,
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documentation: str,
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labelnames: Iterable[str] = (),
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namespace: str = '',
935+
subsystem: str = '',
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unit: str = '',
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registry: Optional[CollectorRegistry] = REGISTRY,
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_labelvalues: Optional[Sequence[str]] = None,
939+
multiprocess_mode: str = 'all',
940+
):
941+
self._multiprocess_mode = multiprocess_mode
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if multiprocess_mode not in self._MULTIPROC_MODES:
943+
raise ValueError('Invalid multiprocess mode: ' + multiprocess_mode)
944+
super().__init__(
945+
name=name,
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documentation=documentation,
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labelnames=labelnames,
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namespace=namespace,
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subsystem=subsystem,
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unit=unit,
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registry=registry,
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_labelvalues=_labelvalues,
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)
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self._kwargs['multiprocess_mode'] = self._multiprocess_mode
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def _metric_init(self) -> None:
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self._value = values.ValueClass(
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self._type, self._name, self._name, self._labelnames, self._labelvalues,
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multiprocess_mode=self._multiprocess_mode
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)
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def inc(self, amount: float = 1) -> None:
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"""Increment gauge by the given amount."""
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self._raise_if_not_observable()
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self._value.inc(amount)
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def dec(self, amount: float = 1) -> None:
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"""Decrement gauge by the given amount."""
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self._raise_if_not_observable()
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self._value.inc(-amount)
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def set(self, value: float) -> None:
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"""Set gauge to the given value."""
974+
self._raise_if_not_observable()
975+
self._value.set(float(value))
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def set_to_current_time(self) -> None:
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"""Set gauge to the current unixtime."""
979+
self.set(time.time())
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def track_inprogress(self) -> InprogressTracker:
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"""Track inprogress blocks of code or functions.
983+
984+
Can be used as a function decorator or context manager.
985+
Increments the gauge when the code is entered,
986+
and decrements when it is exited.
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"""
988+
self._raise_if_not_observable()
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return InprogressTracker(self)
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def time(self) -> Timer:
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"""Time a block of code or function, and set the duration in seconds.
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Can be used as a function decorator or context manager.
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"""
996+
return Timer(self, 'set')
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def set_function(self, f: Callable[[], float]) -> None:
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"""Call the provided function to return the Gauge value.
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The function must return a float, and may be called from
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multiple threads. All other methods of the Gauge become NOOPs.
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"""
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self._raise_if_not_observable()
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def samples(_: Gauge) -> Iterable[Sample]:
1008+
return (Sample('', {}, float(f()), None, None),)
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1010+
self._child_samples = types.MethodType(samples, self) # type: ignore
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def _child_samples(self) -> Iterable[Sample]:
1013+
return (Sample('', {}, self._value.get(), None, None),)
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‎tests/test_registry.py

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from prometheus_client.registry import CollectorRegistry
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from prometheus_client.metrics import Gauge, GaugePandas
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import pandas as pd
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5+
def test_collector_registry_init():
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registry = CollectorRegistry()
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assert registry._collector_to_names == {}
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assert registry._names_to_collectors == {}
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assert registry._auto_describe == False
10+
assert str(type(registry._lock)) == "<class '_thread.lock'>"
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assert registry._target_info == None
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13+
def test_collector_registry_gauge():
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registry = CollectorRegistry()
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g = Gauge('raid_status', '1 if raid array is okay', registry=registry)
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g.set(1)
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assert registry._names_to_collectors['raid_status'] == g
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assert registry._names_to_collectors['raid_status']._documentation == '1 if raid array is okay'
20+
assert '_metrics' not in vars(registry._names_to_collectors['raid_status'])
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G = Gauge('raid_status2', '1 if raid array is okay', ['label1'], registry=registry)
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#G.labels('a').set(10)
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#G.labels('b').set(11)
25 6BA7 +
#G.labels('c').set(12)
26+
#G.labels('c').set(13)
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assert registry._names_to_collectors['raid_status2']._labelnames == ('label1',)
29+
'_metrics' in vars(registry._names_to_collectors['raid_status2'])
30+
31+
registry2 = CollectorRegistry()
32+
GP = GaugePandas('raid_status2', '1 if raid array is okay', ['label1'], registry=registry2)
33+
assert type(GP._metrics) == pd.core.frame.DataFrame
34+
import pdb; pdb.set_trace()

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