semvec/pypi-packages huggingface dataset:
urlmon 0.1.1
Python script to monitor a webpage for changes.
License: MIT
Keywords: urlmon

urlmon
======

**Work in progress.** Python script to monitor a webpage component for
changes.

-  Free software: MIT
-  Documentation: [STRIKEOUT:https://urlmon.readthedocs.org]

Features
--------

-  Checks for changes in a website (or list of websites) since last run
-  Sends a Pushover notification if there have been changes

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

-  Get a `Pushover API token <https://pushover.net/apps/build>`__ (and
   your ``user`` info) \`\`\`bash git clone
   https://github.com/n8henrie/urlmon.git cd urlmon python3 -m venv venv
   source venv/bin/activate pip install -r requirements.txt pip install
   -e .

Enter your Pushover API token:
==============================

keyring set pushover api\_token

Enter your Pushover user:
=========================

keyring set pushover user \`\`\`

Usage
-----

-  Take single URL from stdin:
   ``echo 'http://n8henrie.com' | python3 urlmon -``
-  Take multiple URLs from file: ``urlmon urls.txt``


History
=======

0.1.1 20151229
--------------

-  First release on PyPI.
scluster 0.0.2
an implementation of spectral clustering for text document collections
License: MIT

=====================
SCluster
=====================
--------------------------------------------------------
an implementation of spectral clustering for documents
--------------------------------------------------------

 :Homepage: http://github.com/whym/scluster
 :Contact:  http://whym.org

Overview
==============================
Spectral clustering a modern clustering technique considered to be effective for image clustering among others. [#]_ [#]_

This software find clusters among documents based on the bag-of-words representation [#]_ and TF-IDF weighting [#]_.

.. [#] Ulrike von Luxburg, A Tutorial on Spectral Clustering, 2006. http://arxiv.org/abs/0711.0189
.. [#] Chris H. Q. Ding, Spectral Clustering, 2004. http://ranger.uta.edu/~chqding/Spectral/
.. [#] http://en.wikipedia.org/wiki/Bag_of_words_model
.. [#] http://en.wikipedia.org/wiki/Tf%E2%80%93idf

Requirements
==============================
Following softwares are required.

- Python 2 or 3
- Numpy
- Scipy

How to use
==============================
1. Prepare documents as raw-text files, and put them in a directory, for example, 'reuters'.
2. Prepare a category file. For example, 'cats.txt' may contain: ::

     14833 palm-oil veg-oil
     14839 ship

   This means that the file '14833' has 'palm-oil' and 'veg-oil' as
   its categories, and '14839' has 'ship' as its category.

3. Run: ``python scluster/clusterer.py cats.txt reusters/ -m kmeans``,

Notes
==============================
- When you use the Reuters set, notice No 17980 might contain
  non-Unicode character at Line 10. It should probably read: "world
  economic growth-side measures ..."

.. [#] http://www.daviddlewis.com/resources/testcollections/reuters21578/
mdx 0.1
A simple package for generating mdx scripts
License: MIT
Keywords: MDX builder bi business intelligence

MDX
---

This is a simple library to help building .mdx scripts.
It is composed by:

* A simple syntax module to generate mdx
* Functions to generate mdx sets from lists, .json arrays or prefined .mdx sets
* A writer class and a writer context manager

Installation
============

``pip install mdx``

Usage
=====

.. code-block:: python

  # Usage
  from mdx import syntax as s
  from mdx import MDXSetConstructor, writerContext
  from mdx import loadJson, loadMDX

  toyCodeBuilder = MDXSetConstructor(memberPath="[Products].[ProductName]", comment="Product Codes")
  colorCodeBuilder = MDXSetConstructor(memberPath="[Colors]", comment="Color Codes")

  toys = {
    'dolls' : toyCodeBuilder(codeList=[1,2,3], listName="toy dolls")
  }

  colors = {
    'blue' : colorCodeBuilder(codeList=['blue', 'cyan'], listName="blues")
  }

  # Loads .mdx files in path
  # Each file becomes available as a tuple member with the file name as key
  toys = loadMDX(
    "path/to/toys",
    extraMembers = toys, # Add extra members defined by hand
    toyCodeBuilder
  )

  # Loads .json files in path
  # Each file becomes available as a member of a named tuple with the file name as field
  colors = loadJSON(
    "path/to/colors",
    extraMembers = colors,  # Add extra members defined by hand
    colorCodeBuilder
  )

  # The first two arguments are passed automatically by the context manager
  @measure
  def volume(writer, sets, name, *expressions, **kwargs):

    # Perform some common .mdx operations here...

    writer.write(
      s.createMeasure(s.measureMember(name),
        s.sumExisting('[Measures].[PurchaseCount]', s.intersect(*expressions)
        )
      )
    )

  writer = MDXWriter(name='writer', path='./interestingToys') # by default the path is set on config["OUTPUT_FOLDER"]

  # Putting it all together
  with writerContext((toys, colors), writer) as (measures, config):

    measures(volume)(
      # the writer and set variables are passed to the measure after the arguments
      'volume of interesting toy purchases',
      s.tuple(toys.dolls, colors.blue),
      s.exclude(
        s.tuple(toys.cars, colors.any),
        s.tuple(toys.cars, colors.red),
      )
    )

  # The output will be available at ./interestingToys.mdx

  # Configuration options
  from mdx import config
  config["OUTPUT_FOLDER"] = "./path/to/folder"
  config["LIST_BASE_PATH"] = "./path/to/folder"
  config["TAB_SIZE"] = 2