semvec/pypi-packages huggingface dataset:
plank 0.0.4
A simple task and build runner that doesn't get in the way.
License: MIT

Plank
=====

Plank is a simple and unopinionated python task runner. Plank doesn't manipulate Python or your environment to run the tasks. Plank doesn't provide any default or template tasks.

.. image:: https://travis-ci.org/atbentley/plank.svg?branch=master
  :target:  https://travis-ci.org/atbentley/plank

.. image:: https://coveralls.io/repos/github/atbentley/plank/badge.svg?branch=master
  :target: https://coveralls.io/github/atbentley/plank?branch=master


Usage
-----

Create a ``planks.py`` file in the project directory containing ``@task`` decorated methods, call them using ``plank task_name``.


Examples
--------

.. code-block:: python

  from plank import task

  @task
  def unit_tests():
      import pytest

      assert pytest.main(['tests/unit']) == 0


Tests
-----

Tests are written using pytest and can be run using plank, ``plank tests``.


License
-------

MIT
collectd-haproxy 1.2.1
HAProxy stats plugin for collectd.
License: MIT

HAProxy stats for Collectd
==========================

.. image::
    https://img.shields.io/pypi/v/collectd-haproxy.svg
    :target: PyPI_
    :alt: Python Package Version
.. image::
    https://readthedocs.org/projects/collectd-haproxy/badge/?version=latest
    :target: https://collectd-haproxy.readthedocs.org/en/latest
    :alt: Documentation Status
.. image::
    https://travis-ci.org/wglass/collectd-haproxy.svg?branch=master
    :alt: Build Status
    :target: https://travis-ci.org/wglass/collectd-haproxy
.. image:: https://codeclimate.com/github/wglass/collectd-haproxy/badges/gpa.svg
   :alt: Code Climate
   :target: https://codeclimate.com/github/wglass/collectd-haproxy
.. image:: https://codeclimate.com/github/wglass/collectd-haproxy/badges/coverage.svg
   :alt: Test Coverage
   :target: https://codeclimate.com/github/wglass/collectd-haproxy/coverage

A plugin for collectd_ to gather metrics for a local HAProxy_ instance, with a
focus on easy installation and configuration.

.. image:: http://collectd-haproxy.readthedocs.org/en/latest/_images/graphs.png
   :alt: Graphs made with HAProxy stats
   :align: center

(graphs made with Grafana_)


Installation
------------

The project is on PyPI_ so installation is a simple `pip` command::

    pip install collectd-haproxy

.. note::

   If collectd is running with a virtualenv activated (under an isolated
   supervisord_ setup, for instance) make sure the `collectd-haproxy` package
   is installed and available in the virtualenv's module path or collectd will
   run into an `ImportError`.


In order to function properly, the local HAProxy instance will need to have
the "stats socket" enabled, details about how to do that can be found
`here`_.

Configuration
-------------

The most basic configuration is to specify where the HAProxy socket file is
located::

    LoadPlugin "python"

    <Plugin python>
        Import "collectd_haproxy"

        <Module haproxy>
          Socket "/var/run/haproxy.sock"
        </Module>
    </Plugin>

For details on all of the options available, `read the docs`_!


Development
~~~~~~~~~~~

The code is hosted on GitHub_

To file a bug or possible enhancement see the `Issue Tracker`_, also found
on GitHub.


License
~~~~~~~
\(c\) 2015-2016 William Glass

collectd-haproxy is licensed under the terms of the MIT license.  See the
LICENSE_ file for more details.


.. _collectd: https://collectd.org
.. _HAProxy: http://www.haproxy.org
.. _Grafana: http://grafana.org
.. _PyPI: http://pypi.python.org/pypi/collectd-haproxy
.. _here: https://cbonte.github.io/haproxy-dconv/configuration-1.5.html#9.2
.. _supervisord: http://supervisord.org
.. _`read the docs`: http://collectd-haproxy.readthedocs.org/
.. _GitHub: https://github.com/wglass/collectd-haproxy
.. _`Issue Tracker`: https://github.com/wglass/collectd-haproxy/issues
.. _LICENSE: https://github.com/wglass/collectd-haproxy/blob/master/LICENSE
highfive 0.2
Framework for fault-tolerant cooperative distributed processing.
License: MIT
Keywords: distributed,queue,task queue,job queue,collaborative

HighFive is a simple distributed processing framework designed so you and your friends can donate CPU time to each other to run large, interesting computations. It's easy to spin up a HighFive master and connect as many remote workers as you want to it!

Don't want to lock down all your computers for hours while you wait for results? Since HighFive was designed for cooperative work, the workers can
disconnect at any time without harming the main process! Then, they can reconnect to the same process later and get back to work!

HighFive is written in Python 3, and uses asyncio for managing connections. Because it uses async/await syntax, it is currently only supported by Python 3.5 and up.