Metadata-Version: 1.1
Name: statsdmetrics
Version: 1.0.0
Summary: Statsd metrics classes and clients
Home-page: https://github.com/farzadghanei/statsd-metrics
Author: Farzad Ghanei
Author-email: farzad.ghanei@gmail.com
License: MIT
Description: **************
        Statsd Metrics
        **************
        
        .. image:: https://travis-ci.org/farzadghanei/statsd-metrics.svg?branch=master
            :target: https://travis-ci.org/farzadghanei/statsd-metrics
        
        .. image:: https://codecov.io/gh/farzadghanei/statsd-metrics/branch/master/graph/badge.svg
            :target: https://codecov.io/gh/farzadghanei/statsd-metrics
        
        .. image:: https://ci.appveyor.com/api/projects/status/bekwcg8n1xe0w0n9/branch/master?svg=true
            :target: https://ci.appveyor.com/project/farzadghanei/statsd-metrics?branch=master
        
        Metric classes for Statsd, and Statsd clients (each metric in a single request, or send batch requests).
        
        Metric classes represent the data used in Statsd protocol excluding the IO, to create,
        represent and parse Statsd requests. So any Statsd server and client regardless of the
        IO implementation can use them to send/receive Statsd requests.
        
        The library also comes with a rich set of Statsd clients using the same metric classes, and
        Python standard library socket module.
        
        
        Metric Classes
        --------------
        
        * Counter
        * Timer
        * Gauge
        * Set
        * GaugeDelta
        
        .. code-block:: python
        
            from statsdmetrics import Counter, Timer
        
            counter = Counter('event.login', 1, 0.2)
            counter.to_request() # returns event.login:1|c|@0.2
        
            timer = Timer('db.search.username', 27.4)
            timer.to_request() # returns db.search.username:27.4|ms
        
        Parse metrics from a Statsd request
        
        .. code-block:: python
        
            from statsdmetrics import parse_metric_from_request
        
            event_login = parse_metric_from_request('event.login:1|c|@.2')
            # event_login is a Counter object with count = 1 and sample_rate = 0.2
        
            mem_usage = parse_metric_from_request('resource.memory:2048|g')
            # mem_usage is a Gauge object with value = 2028
        
        Statsd Clients
        --------------
        * ``client.Client``: Default client, sends request on each call using UDP
        * ``client.BatchClient``: Buffers metrics and flushes them in batch requests using UDP
        * ``client.tcp.TCPClient``: Sends request on each call using TCP
        * ``client.tcp.TCPBatchClient``: Buffers metrics and flushes them in batch requests using TCP
        
        Send Statsd requests
        
        .. code-block:: python
        
            from statsdmetrics.client import Client
        
            # default client, send metrics over UDP
            client = Client("stats.example.org")
            client.increment("login")
            client.decrement("connections", 2)
            client.timing("db.search.username", 3500)
            client.gauge("memory", 20480)
            client.gauge_delta("memory", -256)
            client.set("unique.ip_address", "10.10.10.1")
        
            # helpers for timing operations
            chronometer = client.chronometer()
            chronometer.time_callable("func1_duration", func1)
        
            # decorate functions to send timing metrics for the duration of their running time
            @chronometer.wrap("func2_duration")
            def func2():
                pass
        
            # send timing for duration of a with block
            with client.stopwatch("with_block_duration"):
                pass
        
        
        
        Sending multiple metrics in batch requests by ``BatchClient``, either
        by using an available client as the context manager:
        
        
        .. code-block:: python
        
            from statsdmetrics.client import Client
        
            client = Client("stats.example.org")
            with client.batch_client() as batch_client:
                batch_client.increment("login")
                batch_client.decrement("connections", 2)
                batch_client.timing("db.search.username", 3500)
            # now all metrics are flushed automatically in batch requests
        
        
        or by creating a ``BatchClient`` object explicitly:
        
        
        .. code-block:: python
        
            from statsdmetrics.client import BatchClient
        
            client = BatchClient("stats.example.org")
            client.set("unique.ip_address", "10.10.10.1")
            client.gauge("memory", 20480)
            client.flush() # sends one UDP packet to remote server, carrying both metrics
        
            # timing helpers are available on all clients
            chronometer = client.chronometer()
            chronometer.time_callable("func1_duration", func1)
        
            @chronometer.wrap("func2_duration")
            def func2():
                pass
        
            with client.stopwatch("with_block_duration"):
                pass
        
            client.flush()
        
        
        Installation
        ------------
        
        .. code-block:: bash
        
            pip install statsdmetrics
        
        
        The only dependencies are Python 2.7+ and setuptools.
        CPython 2.7, 3.2, 3.3, 3.4, 3.5, 3.6-dev, PyPy 2.6 and PyPy3 2.4, and Jython 2.7 are tested)
        
        However on development (and test) environment
        `mock <https://pypi.python.org/pypi/mock>`_ is required,
        `typing <https://pypi.python.org/pypi/typing>`_ and
        `distutilazy <https://pypi.python.org/pypi/distutilazy>`_ are recommended.
        
        .. code-block:: bash
        
            # on dev/test env
            pip install -r requirements-dev.txt
        
        
        Development
        -----------
        
        * Code is on `GitHub <https://github.com/farzadghanei/statsd-metrics>`_
        * Documentations are on `Read The Docs <https://statsd-metrics.readthedocs.org>`_
        
        Tests
        ^^^^^
        
        If you have make available
        
        .. code-block:: bash
        
            make test
        
        You can always use the setup.py file
        
        .. code-block:: bash
        
            python setup.py test
        
        Integration tests are available, bringing up dummy servers (but actually listening on
        network socket) to capture requests instead of processing them. Then send some metrics and
        assert if the captured requests match the expected.
        
        .. code-block:: bash
        
            python tests/integration_test_udp.py
            python tests/integration_test_tcp.py
        
        
        License
        -------
        
        Statsd metrics is released under the terms of the
        `MIT license <http://opensource.org/licenses/MIT>`_.
        
Keywords: statsd metrics client
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.2
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
Classifier: Programming Language :: Python :: Implementation :: Jython
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: System :: Networking :: Monitoring
