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    "info": {
        "author": "Shane Hathaway",
        "author_email": "shane@hathawaymix.org",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 5 - Production/Stable",
            "Intended Audience :: Developers",
            "License :: Repoze Public License",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Programming Language :: Python :: Implementation :: CPython",
            "Programming Language :: Python :: Implementation :: PyPy",
            "Topic :: System :: Monitoring"
        ],
        "description": "=============\n perfmetrics\n=============\n\nThe perfmetrics package provides a simple way to add software performance\nmetrics to Python libraries and applications.  Use perfmetrics to find the\ntrue bottlenecks in a production application.\n\nThe perfmetrics package is a client of the Statsd daemon by Etsy, which\nis in turn a client of Graphite (specifically, the Carbon daemon).  Because\nthe perfmetrics package sends UDP packets to Statsd, perfmetrics adds\nno I/O delays to applications and little CPU overhead.  It can work\nequally well in threaded (synchronous) or event-driven (asynchronous)\nsoftware.\n\nComplete documentation is hosted at https://perfmetrics.readthedocs.io\n\n.. image:: https://img.shields.io/pypi/v/perfmetrics.svg\n   :target: https://pypi.org/project/perfmetrics/\n   :alt: Latest release\n\n.. image:: https://img.shields.io/pypi/pyversions/perfmetrics.svg\n   :target: https://pypi.org/project/perfmetrics/\n   :alt: Supported Python versions\n\n.. image:: https://travis-ci.org/zodb/perfmetrics.svg?branch=master\n   :target: https://travis-ci.org/zodb/perfmetrics\n   :alt: Travis CI Build Status\n\n.. image:: https://coveralls.io/repos/github/zodb/perfmetrics/badge.svg\n   :target: https://coveralls.io/github/zodb/perfmetrics\n   :alt: Code Coverage\n\n.. image:: https://readthedocs.org/projects/perfmetrics/badge/?version=latest\n   :target: https://perfmetrics.readthedocs.io/en/latest/?badge=latest\n   :alt: Documentation Status\n\nUsage\n=====\n\nUse the ``@metric`` and ``@metricmethod`` decorators to wrap functions\nand methods that should send timing and call statistics to Statsd.\nAdd the decorators to any function or method that could be a bottleneck,\nincluding library functions.\n\n.. caution::\n\n   These decorators are generic and cause the actual function\n   signature to be lost, replaced with ``*args, **kwargs``. This can\n   break certain types of introspection, including `zope.interface\n   validation <https://github.com/zodb/perfmetrics/issues/15>`_. As a\n   workaround, setting the environment variable\n   ``PERFMETRICS_DISABLE_DECORATOR`` *before* importing perfmetrics or\n   code that uses it will cause ``@perfmetrics.metric``, ``@perfmetrics.metricmethod``,\n   ``@perfmetrics.Metric(...)`` and ``@perfmetrics.MetricMod(...)`` to\n   return the original function unchanged.\n\nSample::\n\n    from perfmetrics import metric\n    from perfmetrics import metricmethod\n\n    @metric\n    def myfunction():\n        \"\"\"Do something that might be expensive\"\"\"\n\n    class MyClass(object):\n    \t@metricmethod\n    \tdef mymethod(self):\n    \t    \"\"\"Do some other possibly expensive thing\"\"\"\n\nNext, tell perfmetrics how to connect to Statsd.  (Until you do, the\ndecorators have no effect.)  Ideally, either your application should read the\nStatsd URI from a configuration file at startup time, or you should set\nthe STATSD_URI environment variable.  The example below uses a\nhard-coded URI::\n\n    from perfmetrics import set_statsd_client\n    set_statsd_client('statsd://localhost:8125')\n\n    for i in xrange(1000):\n        myfunction()\n        MyClass().mymethod()\n\nIf you run that code, it will fire 2000 UDP packets at port\n8125.  However, unless you have already installed Graphite and Statsd,\nall of those packets will be ignored and dropped.  Dropping is a good thing:\nyou don't want your production application to fail or slow down just\nbecause your performance monitoring system is stopped or not working.\n\nInstall Graphite and Statsd to receive and graph the metrics.  One good way\nto install them is the `graphite_buildout example`_ at github, which\ninstalls Graphite and Statsd in a custom location without root access.\n\n.. _`graphite_buildout example`: https://github.com/hathawsh/graphite_buildout\n\nPyramid and WSGI\n================\n\nIf you have a Pyramid app, you can set the ``statsd_uri`` for each\nrequest by including perfmetrics in your configuration::\n\n    config = Configuration(...)\n    config.include('perfmetrics')\n\nAlso add a ``statsd_uri`` setting such as ``statsd://localhost:8125``.\nOnce configured, the perfmetrics tween will set up a Statsd client for\nthe duration of each request.  This is especially useful if you run\nmultiple apps in one Python interpreter and you want a different\n``statsd_uri`` for each app.\n\nSimilar functionality exists for WSGI apps.  Add the app to your Paste Deploy\npipeline::\n\n    [statsd]\n    use = egg:perfmetrics#statsd\n    statsd_uri = statsd://localhost:8125\n\n    [pipeline:main]\n    pipeline =\n        statsd\n        egg:myapp#myentrypoint\n\nThreading\n=========\n\nWhile most programs send metrics from any thread to a single global\nStatsd server, some programs need to use a different Statsd server\nfor each thread.  If you only need a global Statsd server, use the\n``set_statsd_client`` function at application startup.  If you need\nto use a different Statsd server for each thread, use the\n``statsd_client_stack`` object in each thread.  Use the\n``push``, ``pop``, and ``clear`` methods.\n\n\nGraphite Tips\n=============\n\nGraphite stores each metric as a time series with multiple\nresolutions.  The sample graphite_buildout stores 10 second resolution\nfor 48 hours, 1 hour resolution for 31 days, and 1 day resolution for 5 years.\nTo produce a coarse grained value from a fine grained value, Graphite computes\nthe mean value (average) for each time span.\n\nBecause Graphite computes mean values implicitly, the most sensible way to\ntreat counters in Graphite is as a \"hits per second\" value.  That way,\na graph can produce correct results no matter which resolution level\nit uses.\n\nTreating counters as hits per second has unfortunate consequences, however.\nIf some metric sees a 1000 hit spike in one second, then falls to zero for\nat least 9 seconds, the Graphite chart for that metric will show a spike\nof 100, not 1000, since Graphite receives metrics every 10 seconds and the\nspike looks to Graphite like 100 hits per second over a 10 second period.\n\nIf you want your graph to show 1000 hits rather than 100 hits per second,\napply the Graphite ``hitcount()`` function, using a resolution of\n10 seconds or more.  The hitcount function converts per-second\nvalues to approximate raw hit counts.  Be sure\nto provide a resolution value large enough to be represented by at least\none pixel width on the resulting graph, otherwise Graphite will compute\naverages of hit counts and produce a confusing graph.\n\nIt usually makes sense to treat null values in Graphite as zero, though\nthat is not the default; by default, Graphite draws nothing for null values.\nYou can turn on that option for each graph.\n\n\n=========\n CHANGES\n=========\n\n3.0.0 (2019-09-03)\n==================\n\n- Drop support for EOL Python 2.6, 3.2, 3.3 and 3.4.\n\n- Add support for Python 3.5, 3.6, and 3.7.\n\n- Compile the performance-sensitive parts with Cython, leading to a\n  10-30% speed improvement. See\n  https://github.com/zodb/perfmetrics/issues/17.\n\n- Make decorated functions and methods configurable at runtime, not\n  just compile time. See\n  https://github.com/zodb/perfmetrics/issues/11.\n\n- Include support for testing applications instrumented with\n  perfmetrics in ``perfmetrics.testing``. This was previously release\n  externally as ``nti.fakestatsd``. See https://github.com/zodb/perfmetrics/issues/9.\n\n- Read the ``PERFMETRICS_DISABLE_DECORATOR`` environment variable when\n  ``perfmetrics`` is imported, and if it is set, make the decorators ``@metric``,\n  ``@metricmethod``, ``@Metric(...)`` and ``@MetricMod(...)`` return\n  the function unchanged. This can be helpful for certain kinds of\n  introspection tests. See https://github.com/zodb/perfmetrics/issues/15\n\n2.0 (2013-12-10)\n================\n\n- Added the ``@MetricMod`` decorator, which changes the name of\n  metrics in a given context. For example, ``@MetricMod('xyz.%s')``\n  adds a prefix.\n\n- Removed the \"gauge suffix\" feature. It was unnecessarily confusing.\n\n- Timing metrics produced by ``@metric``, ``@metricmethod``, and\n  ``@Metric`` now have a \".t\" suffix by default to avoid naming\n  conflicts.\n\n1.0 (2012-10-09)\n================\n\n- Added 'perfmetrics.tween' and 'perfmetrics.wsgi' stats for measuring\n  request timing and counts.\n\n0.9.5 (2012-09-22)\n==================\n\n- Added an optional Pyramid tween and a similar WSGI filter app\n  that sets up the Statsd client for each request.\n\n0.9.4 (2012-09-08)\n==================\n\n- Optimized the use of reduced sample rates.\n\n0.9.3 (2012-09-08)\n==================\n\n- Support the ``STATSD_URI`` environment variable.\n\n0.9.2 (2012-09-01)\n==================\n\n- ``Metric`` can now be used as either a decorator or a context\n  manager.\n\n- Made the signature of StatsdClient more like James Socol's\n  StatsClient.\n\n0.9.1 (2012-09-01)\n==================\n\n- Fixed package metadata.\n\n0.9 (2012-08-31)\n================\n\n- Initial release.\n\n\n",
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