semvec/pypi-packages huggingface dataset:
wechinelearn 0.0.1
Weather data based machine learning R&D framework
License: MIT

.. image:: https://travis-ci.org/MacHu-GWU/wechinelearn-project.svg?branch=master

.. image:: https://img.shields.io/pypi/v/wechinelearn.svg

.. image:: https://img.shields.io/pypi/l/wechinelearn.svg

.. image:: https://img.shields.io/pypi/pyversions/wechinelearn.svg


Welcome to wechinelearn Documentation
===============================================================================
``wechinelearn`` is a Weather data based machine learning R&D framework. Basically, if you want to use weather data to build a classification/prediction model, this framework could help.

The first major problem in model R&D is handling big dataset. ``wechinelearn`` can use any relational database as back-end, and easy to extend for adding more data or data point. Using database can greatly reduce the average time cost for trying your idea.

Your target object, could be a user, a region or anything associated with local weather by location. One major problem ``wechinelearn`` solved is finding best weather data for your target, and also takes `missing data points`, `unreliable data points`, `multiple data source choice` into account.


**Quick Links**
-------------------------------------------------------------------------------
- `GitHub Homepage <https://github.com/MacHu-GWU/wechinelearn-project>`_
- `Online Documentation <http://pythonhosted.org/wechinelearn>`_
- `PyPI download <https://pypi.python.org/pypi/wechinelearn>`_
- `Install <install_>`_
- `Issue submit and feature request <https://github.com/MacHu-GWU/wechinelearn-project/issues>`_
- `API reference and source code <http://pythonhosted.org/wechinelearn/py-modindex.html>`_


.. _install:

Install
-------------------------------------------------------------------------------

``wechinelearn`` is released on PyPI, so all you need is:

.. code-block:: console

	$ pip install wechinelearn

To upgrade to latest version:

.. code-block:: console

	$ pip install --upgrade wechinelearn

If you have problem with installing ``numpy`` in Windows, download the compiled wheel file `here <http://www.lfd.uci.edu/~gohlke/pythonlibs/#numpy>`_, and install it with pip.
goodlogging 1.0.1
Logging module for command line utilities
License: MIT

goodlogging
==================

This logging package provides some additional functionality
to command line utilities allowing for good-looking terminal
displays. These include:

* Easy indentation of displayed lines
* Configurable verbosity levels
* Optional identifying tags on every message
* Easily trigger ERROR or FATAL messages (where fatal exits the program)
* Input method for getting user response from the command line
* Add consistent seperators or newlines to the displayed output

Requirements
---------------
This is a python package and requires the following:

- Python 3.4+

Installation
---------------
Install using pip:

.. code-block:: bash

    $ pip install goodlogging

Requests, Issues, Bugs or Suggestions
---------------------------------------------
Add any feature requests, issues, bugs or suggestions here: https://github.com/davgeo/goodlogging/issues

Please give as much detail as possible.
ohmu 1.1.0
View space usage in your terminal.
License: MIT
Keywords: space usage

Ohmu
====

View space usage in your terminal.

.. image:: https://img.shields.io/travis/paul-nechifor/ohmu.svg?style=flat-square
    :target: https://travis-ci.org/paul-nechifor/ohmu

.. image:: https://img.shields.io/codecov/c/github/paul-nechifor/ohmu.svg?style=flat-square
    :target: https://codecov.io/github/paul-nechifor/ohmu

.. image:: https://img.shields.io/pypi/v/ohmu.svg?style=flat-square
    :target: https://pypi.python.org/pypi/ohmu

.. image:: https://img.shields.io/pypi/dm/ohmu.svg?style=flat-square
    :target: https://pypi.python.org/pypi/ohmu

.. image:: https://img.shields.io/pypi/l/ohmu.svg?style=flat-square
    :target: http://opensource.org/licenses/MIT

.. image:: animation.gif

Usage
-----

Install the Python headers (TODO: specify the commands on every major OS.)

Install (prefix with ``sudo`` if you need to)::

    pip install ohmu --user --upgrade

Scan the current directory::

    ohmu

Scan some random directory::

    ohmu some/random/dir

Development
-----------

Make sure you have Tox_ installed globally.

Run the tests with::

    tox

License
-------

MIT

.. _Tox: https://tox.readthedocs.io/en/latest/