semvec/pypi-packages huggingface dataset:
word2vec-wikification-py 0.17
A package to run wikification
License: MIT

wiki\_node\_disambiguation - - -

What's this ?
=============

-  You can run "Wikification" as easy as possible.

   -  According to wikipedia,
      `Wikification <https://en.wikipedia.org/wiki/Wikification>`__ is
      ``in computer science, entity linking with Wikipedia as the target knowledge base``

-  You can get disambiguated result with its score.

Please visit `Github
page <https://github.com/Kensuke-Mitsuzawa/word2vec_wikification_py>`__
also. If you find any bugs and you report it to github issue, I'm glad.
Any pull-requests are welcomed.

Requirement
===========

-  Python3.x (checked under )

   -  I recommend to use "Anaconda" distribution.

Setup
=====

``python setup.py install``

Get wikipedia entity vector model
---------------------------------

Go to `this
page <http://www.cl.ecei.tohoku.ac.jp/~m-suzuki/jawiki_vector/>`__ and
download model file from
`here <http://www.cl.ecei.tohoku.ac.jp/~m-suzuki/jawiki_vector/entity_vector.tar.bz2>`__.
Or run ``download_model.sh``

To those who uses interface.predict\_japanese\_wiki\_names()
------------------------------------------------------------

You're supposed to have mysql somewhere.

The step until using it.

1. start mysql server somewhere
2. download latest mysql dump files
3. initialize wikipedia database with mysql

To download wikipedia dump files, execute following commands

::

    wget https://dumps.wikimedia.org/jawiki/latest/jawiki-latest-redirect.sql.gz
    wget https://dumps.wikimedia.org/jawiki/latest/jawiki-latest-page.sql.gz
    gunzip jawiki-latest-redirect.sql.gz
    gunzip jawiki-latest-page.sql.gz

To initialize wikipedia database with mysql,

::

    % CREATE DATABASE wikipedia;
    % mysql -u [user_name] -p[password] wikipedia < jawiki-latest-redirect.sql
    % mysql -u [user_name] -p[password] wikipedia < jawiki-latest-page.sql

Change logs
===========

-  version0.1

   -  released
   -  It supports only Japanese wikipedia
marbaloo_mako 0.1.1
Mako template support for cherrypy.
License: MIT
Keywords: mako cherrypy marbaloo marbaloo_mako

Marbaloo Mako
=============

`Mako <http://www.makotemplates.org/>`_ template support for cherrypy.

Installation
------------
::

    pip install marbaloo_mako

Usage
-----

::

    # templates/dir1/index.mak
    <h1>Today: ${today}</h1>


::

    # app.py
    import os
    import marbaloo_mako
    import cherrypy
    from datetime import date
    cherrypy.tools.mako = marbaloo_mako.Tool()

    class Root(object):
        @cherrypy.expose
        @cherrypy.tools.mako(filename='/index.mak')
        def simple(self):
            return  {'today': date.today()}

    root_path = os.path.dirname(__file__)
    cherrypy.quickstart(Root(), '/', {
                                '/': {
                                    'tools.mako.on': True,
                                    'tools.mako.directories': [os.path.join(root_path, 'templates/dir1')]
                                }
                            })
dataIO 0.0.5
Data IO tool set.
License: MIT

.. image:: https://travis-ci.org/MacHu-GWU/dataIO-project.svg?branch=master

.. image:: https://img.shields.io/pypi/v/dataIO.svg

.. image:: https://img.shields.io/pypi/l/dataIO.svg

.. image:: https://img.shields.io/pypi/pyversions/dataIO.svg


Welcome to the dataIO Documentation
===================================

``dataIO`` provides lots of utility method working on IO in between ``string``, ``bytes``, ``file``, ``json``, ``pickle``, ``compress and decompress``. Most of the cases you can do your work **in single line of code**. ``dataIO`` **written in pure python, no other dependency required**.

Now it support:

- gzip
- json
- pickle
- text file


**Quick links**:

- `GitHub Homepage <https://github.com/MacHu-GWU/dataIO-project>`_
- `Online Documentation <http://pythonhosted.org/dataIO>`_
- `PyPI download <https://pypi.python.org/pypi/dataIO>`_
- `Install <install_>`_
- `Issue submit and feature request <https://github.com/MacHu-GWU/dataIO-project/issues>`_
- `API reference and source code <http://pythonhosted.org/dataIO/py-modindex.html>`_


.. _install:

Install
-------
``dataIO`` is released on PyPI, so all you need is:

.. code-block:: console

	$ pip install dataIO

To upgrade to latest version:

.. code-block:: console
	
	$ pip install --upgrade dataIO