Package: netaccess_perfmetrics
IntroductionThe perfmetrics package provides a simple way to add software performance
metrics to Python libraries and applications.  Use perfmetrics to find the
true bottlenecks in a production application.The perfmetrics package is a client of the Statsd daemon by Etsy, which
is in turn a client of Graphite (specifically, the Carbon daemon).  Because
the perfmetrics package sends UDP packets to Statsd, perfmetrics adds
no I/O delays to applications and little CPU overhead.  It can work
equally well in threaded (synchronous) or event-driven (asynchronous)
software.UsageUse the@metricand@metricmethoddecorators to wrap functions
and methods that should send timing and call statistics to Statsd.
Add the decorators to any function or method that could be a bottleneck,
including library functions.Sample:from perfmetrics import metric
from perfmetrics import metricmethod

@metric
def myfunction():
    """Do something that might be expensive"""

class MyClass(object):
    @metricmethod
    def mymethod(self):
        """Do some other possibly expensive thing"""Next, tell perfmetrics how to connect to Statsd.  (Until you do, the
decorators have no effect.)  Ideally, either your application should read the
Statsd URI from a configuration file at startup time, or you should set
the STATSD_URI environment variable.  The example below uses a
hard-coded URI:from perfmetrics import set_statsd_client
set_statsd_client('statsd://localhost:8125')

for i in xrange(1000):
    myfunction()
    MyClass().mymethod()If you run that code, it will fire 2000 UDP packets at port
8125.  However, unless you have already installed Graphite and Statsd,
all of those packets will be ignored and dropped.  Dropping is a good thing:
you don’t want your production application to fail or slow down just
because your performance monitoring system is stopped or not working.Install Graphite and Statsd to receive and graph the metrics.  One good way
to install them is thegraphite_buildout exampleat github, which
installs Graphite and Statsd in a custom location without root access.Pyramid and WSGIIf you have a Pyramid app, you can set thestatsd_urifor each
request by including perfmetrics in your configuration:config = Configuration(...)
config.include('perfmetrics')Also add astatsd_urisetting such asstatsd://localhost:8125.
Once configured, the perfmetrics tween will set up a Statsd client for
the duration of each request.  This is especially useful if you run
multiple apps in one Python interpreter and you want a differentstatsd_urifor each app.Similar functionality exists for WSGI apps.  Add the app to your Paste Deploy
pipeline:[statsd]
use = egg:perfmetrics#statsd
statsd_uri = statsd://localhost:8125

[pipeline:main]
pipeline =
    statsd
    egg:myapp#myentrypointThreadingWhile most programs send metrics from any thread to a single global
Statsd server, some programs need to use a different Statsd server
for each thread.  If you only need a global Statsd server, use theset_statsd_clientfunction at application startup.  If you need
to use a different Statsd server for each thread, use thestatsd_client_stackobject in each thread.  Use thepush,pop, andclearmethods.Graphite TipsGraphite stores each metric as a time series with multiple
resolutions.  The sample graphite_buildout stores 10 second resolution
for 48 hours, 1 hour resolution for 31 days, and 1 day resolution for 5 years.
To produce a coarse grained value from a fine grained value, Graphite computes
the mean value (average) for each time span.Because Graphite computes mean values implicitly, the most sensible way to
treat counters in Graphite is as a “hits per second” value.  That way,
a graph can produce correct results no matter which resolution level
it uses.Treating counters as hits per second has unfortunate consequences, however.
If some metric sees a 1000 hit spike in one second, then falls to zero for
at least 9 seconds, the Graphite chart for that metric will show a spike
of 100, not 1000, since Graphite receives metrics every 10 seconds and the
spike looks to Graphite like 100 hits per second over a 10 second period.If you want your graph to show 1000 hits rather than 100 hits per second,
apply the Graphitehitcount()function, using a resolution of
10 seconds or more.  The hitcount function converts per-second
values to approximate raw hit counts.  Be sure
to provide a resolution value large enough to be represented by at least
one pixel width on the resulting graph, otherwise Graphite will compute
averages of hit counts and produce a confusing graph.It usually makes sense to treat null values in Graphite as zero, though
that is not the default; by default, Graphite draws nothing for null values.
You can turn on that option for each graph.Reference DocumentationDecorators@metricNotifies Statsd using UDP every time the function is called.
Sends both call counts and timing information.  The name of the metric
sent to Statsd is<module>.<functionname>.@metricmethodLike@metric, but the name of the Statsd metric is<classmodule>.<classname>.<methodname>.Metric(stat=None, rate=1, method=False, count=True, timing=True)A decorator or context manager with options.statis the name of the metric to send; set it to None to use
the name of the function or method.ratelets you reduce the number of packets sent to Statsd
by selecting a random sample; for example, set it to 0.1 to send
one tenth of the packets.
If themethodparameter is true, the default metric name is based on
the method’s class name rather than the module name.
Settingcountto False disables the counter statistics sent to Statsd.
Settingtimingto False disables the timing statistics sent to Statsd.Sample use as a decorator:@Metric('frequent_func', rate=0.1, timing=False)
def frequent_func():
    """Do something fast and frequently"""Sample use as a context manager:def do_something():
    with Metric('doing_something'):
        passIf perfmetrics sends packets too frequently, UDP packets may be lost
and the application performance may be affected.  You can reduce
the number of packets and the CPU overhead using theMetricdecorator with options instead ofmetricormetricmethod.
The decorator example above uses a sample rate and a static metric name.
It also disables the collection of timing information.When using Metric as a context manager, you must provide thestatparameter or nothing will be recorded.Functionsstatsd_client()Return the currently configuredStatsdClient.
Returns the thread-local client if there is one, or the global client
if there is one, or None.set_statsd_client(client_or_uri)Set the globalStatsdClient.  Theclient_or_urican be a StatsdClient, astatsd://URI, or None.
Note that when the perfmetrics module is imported, it looks for theSTATSD_URIenvironment variable and calls set_statsd_client()
if that variable is found.statsd_client_from_uri(uri)Create aStatsdClientfrom a URI, but do not install it as the
global StatsdClient.
A typical URI isstatsd://localhost:8125.  Supported optional
query parameters areprefixandgauge_suffix.  The default
prefix is empty and the default gauge_suffix
is.<host_name>.  See theStatsdClientdocumentation for
more information aboutgauge_suffix.StatsdClient MethodsPython code can send custom metrics by first getting the currentStatsdClientusing thestatsd_client()function.  Note thatstatsd_client()returns None if no client has been configured.Most of the methods below have optionalrate,rate_applied,
andbufparameters.  Therateparameter, when set to a value
less than 1, causes StatsdClient to send a random sample of packets rather
than every packet.  Therate_appliedparameter, if true, informsStatsdClientthat the sample rate has already been applied and the
packet should be sent regardless of the specified sample rate.If thebufparameter is a list, StatsdClient
appends the packet contents to thebuflist rather than send the
packet, making it possible to send multiple updates in a single packet.
Keep in mind that the size of UDP packets is limited (the limit varies
by the network, but 1000 bytes is usually a good guess) and any extra
bytes will be ignored silently.timing(stat, value, rate=1, buf=None, rate_applied=False)Record timing information.statis the name of the metric to record andvalueis the
timing measurement in milliseconds.  Note that
Statsd maintains several data points for each timing metric, so timing
metrics can take more disk space than counters or gauges.gauge(stat, value, suffix=None, rate=1, buf=None, rate_applied=False)Update a gauge value.statis the name of the metric to record andvalueis the new
gauge value.  A gauge represents a persistent value such as a pool size.
Because gauges from different machines often conflict, a
suffix is usually applied to gauge names.  If thesuffixparameter is a string (including an empty string), it overrides the
default gauge suffix.incr(stat, count=1, rate=1, buf=None, rate_applied=False)Increment a counter bycount.  Note that Statsd clears all counter
values every time it sends the metrics to Graphite, which usually
happens every 10 seconds.  If you need a persistent value, it may
be more appropriate to use a gauge instead of a counter.decr(stat, count=1, rate=1, buf=None, rate_applied=False)Decrement a counter bycount.sendbuf(buf)Send the contents of thebuflist to Statsd.CHANGES2.3 (2015-10-22)Add MANIFEST file2.2 (2015-10-22)Update CHANGES2.1 (2015-10-22)Detect if decorated method is class method or object method and behave
accordingly.2.0 (2013-12-10)Added the @MetricMod decorator, which changes the name of metrics in
a given context. For example, “@MetricMod(‘xyz.%s’)” adds a prefix.Removed the “gauge suffix” feature. It was unnecessarily confusing.Timing metrics produced by “@metric”, “@metricmethod”, and “@Metric”
now have a “.t” suffix by default to avoid naming conflicts.1.0 (2012-10-09)Added ‘perfmetrics.tween’ and ‘perfmetrics.wsgi’ stats for measuring
request timing and counts.0.9.5 (2012-09-22)Added an optional Pyramid tween and a similar WSGI filter app
that sets up the Statsd client for each request.0.9.4 (2012-09-08)Optimized the use of reduced sample rates.0.9.3 (2012-09-08)Support the STATSD_URI environment variable.0.9.2 (2012-09-01)Metric can now be used as either a decorator or a context manager.Made the signature of StatsdClient more like James Socol’s StatsClient.0.9.1 (2012-09-01)Fixed package metadata.0.9 (2012-08-31)Initial release.