/usr/lib/python2.7/dist-packages/nagiosplugin/context.py is in python-nagiosplugin 1.2.2-1.
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# See also LICENSE.txt
"""Metadata about metrics to perform data :term:`evaluation`.
This module contains the :class:`Context` class, which is the base for
all contexts. :class:`ScalarContext` is an important specialization to
cover numeric contexts with warning and critical thresholds. The
:class:`~.check.Check` controller selects a context for each
:class:`~.metric.Metric` by matching the metric's `context` attribute with the
context's `name`. The same context may be used for several metrics.
Plugin authors may just use to :class:`ScalarContext` in the majority of cases.
Sometimes is better to subclass :class:`Context` instead to implement custom
evaluation or performance data logic.
"""
from .performance import Performance
from .range import Range
from .result import Result
from .state import Ok, Warn, Critical
class Context(object):
def __init__(self, name, fmt_metric=None, result_cls=Result):
"""Creates generic context identified by `name`.
Generic contexts just format associated metrics and evaluate
always to :obj:`~nagiosplugin.state.Ok`. Metric formatting is
controlled with the :attr:`fmt_metric` attribute. It can either
be a string or a callable. See the :meth:`describe` method for
how formatting is done.
:param name: context name that is matched by the context
attribute of :class:`~nagiosplugin.metric.Metric`
:param fmt_metric: string or callable to convert
context and associated metric to a human readable string
:param result_cls: use this class (usually a
:class:`~.result.Result` subclass) to represent the
evaluation outcome
"""
self.name = name
self.fmt_metric = fmt_metric
self.result_cls = result_cls
def evaluate(self, metric, resource):
"""Determines state of a given metric.
This base implementation returns :class:`~nagiosplugin.state.Ok`
in all cases. Plugin authors may override this method in
subclasses to specialize behaviour.
:param metric: associated metric that is to be evaluated
:param resource: resource that produced the associated metric
(may optionally be consulted)
:returns: :class:`~.result.Result` object
"""
return self.result_cls(Ok, metric=metric)
def performance(self, metric, resource):
"""Derives performance data from a given metric.
This base implementation just returns none. Plugin authors may
override this method in subclass to specialize behaviour.
:param metric: associated metric from which performance data are
derived
:param resource: resource that produced the associated metric
(may optionally be consulted)
:returns: :class:`Perfdata` object or `None`
"""
return None
def describe(self, metric):
"""Provides human-readable metric description.
Formats the metric according to the :attr:`fmt_metric`
attribute. If :attr:`fmt_metric` is a string, it is evaluated as
format string with all metric attributes in the root namespace.
If :attr:`fmt_metric` is callable, it is called with the metric
and this context as arguments. If :attr:`fmt_metric` is not set,
this default implementation does not return a description.
Plugin authors may override this method in subclasses to control
text output more tightly.
:param metric: associated metric
:returns: description string or None
"""
if not self.fmt_metric:
return
try:
return self.fmt_metric(metric, self)
except TypeError:
return self.fmt_metric.format(
name=metric.name, value=metric.value, uom=metric.uom,
valueunit=metric.valueunit, min=metric.min, max=metric.max)
class ScalarContext(Context):
def __init__(self, name, warning=None, critical=None,
fmt_metric='{name} is {valueunit}', result_cls=Result):
"""Ready-to-use :class:`Context` subclass for scalar values.
ScalarContext models the common case where a single scalar is to
be evaluated against a pair of warning and critical thresholds.
:attr:`name`, :attr:`fmt_metric`, and :attr:`result_cls`,
are described in the :class:`Context` base class.
:param warning: Warning threshold as
:class:`~nagiosplugin.range.Range` object or range string.
:param critical: Critical threshold as
:class:`~nagiosplugin.range.Range` object or range string.
"""
super(ScalarContext, self).__init__(name, fmt_metric, result_cls)
self.warning = Range(warning)
self.critical = Range(critical)
def evaluate(self, metric, resource):
"""Compares metric with ranges and determines result state.
The metric's value is compared to the instance's :attr:`warning`
and :attr:`critical` ranges, yielding an appropropiate state
depending on how the metric fits in the ranges. Plugin authors
may override this method in subclasses to provide custom
evaluation logic.
:param metric: metric that is to be evaluated
:param resource: not used
:returns: :class:`~nagiosplugin.result.Result` object
"""
if not self.critical.match(metric.value):
return self.result_cls(Critical, self.critical.violation, metric)
elif not self.warning.match(metric.value):
return self.result_cls(Warn, self.warning.violation, metric)
else:
return self.result_cls(Ok, None, metric)
def performance(self, metric, resource):
"""Derives performance data.
The metric's attributes are combined with the local
:attr:`warning` and :attr:`critical` ranges to get a
fully populated :class:`~nagiosplugin.performance.Performance`
object.
:param metric: metric from which performance data are derived
:param resource: not used
:returns: :class:`~nagiosplugin.performance.Performance` object
"""
return Performance(metric.name, metric.value, metric.uom,
self.warning, self.critical,
metric.min, metric.max)
class Contexts:
"""Container for collecting all generated contexts."""
def __init__(self):
self.by_name = dict(
default=ScalarContext('default', '', ''),
null=Context('null'))
def add(self, context):
self.by_name[context.name] = context
def __getitem__(self, context_name):
try:
return self.by_name[context_name]
except KeyError:
raise KeyError('cannot find context', context_name,
'known contexts: {0}'.format(
', '.join(self.by_name.keys())))
def __contains__(self, context_name):
return context_name in self.by_name
def __iter__(self):
return iter(self.by_name)
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