Metadata-Version: 1.1
Name: statsdmetrics
Version: 2.0.2
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-Content-Type: UNKNOWN
Description: **************
        Statsd Metrics
        **************
        
        .. image:: https://travis-ci.org/farzadghanei/statsd-metrics.svg?branch=master
            :target: https://travis-ci.org/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, 3.4+, 3.7-dev, PyPy, and Jython 2.7 are tested)
        
        However on development (and test) environment
        `pytest <https://pypi.org/project/pytest/>`_, `mock <https://pypi.org/project/mock>`_ is required (for Python 2),
        `typing <https://pypi.org/project/typing>`_ is 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
        ^^^^^
        
        `Tox <https://pypi.org/project/tox/>`_ is most convenient to run tests with since it handles creation of virtualenvs
        
        .. code-block:: bash
        
            $ tox
        
        When development dependencies are installed (preferably with a virtual environment),
        tests can be run by calling `pytest`.
        
        .. code-block:: bash
        
            $ pytest
        
        Integration tests are available as part of the test suite, 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.
        
        License
        -------
        
        Statsd metrics is released under the terms of the
        `MIT license <http://opensource.org/licenses/MIT>`_.
        
        The MIT License (MIT)
        
        Copyright (c) 2015-2018 Farzad Ghanei
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.
        
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 :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
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
