Metadata-Version: 2.0
Name: pyth
Version: 0.6.0
Summary: Python text markup and conversion
Home-page: http://wiki.github.com/brendonh/pyth
Author: Brendon Hogger
Author-email: brendonh@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 2.5
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Topic :: Office/Business
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Text Editors :: Word Processors
Classifier: Topic :: Text Processing
Classifier: Topic :: Text Processing :: Markup
Classifier: Topic :: Text Processing :: Filters

========================================
pyth - Python text markup and conversion
========================================

Pyth is intended to make it easy to convert marked-up text between different common formats.

*Marked-up text* means text which has:

* Paragraphs
* Headings
* Bold, italic, and underlined text
* Hyperlinks
* Bullet lists
* Simple tables
* Very little else


Formats I initially want to support are:

* xhtml
* rtf
* pdf (output)


These three formats cover web, Word / OpenOffice, and print. 


Design principles
=================

* Ignore unsupported information in input formats (e.g. page layout)
* Ignore font issues -- output in a single font.
* Ignore specific text sizes -- support relative sizes (bigger, littler) only. Output in a single base size.
* Have no dependencies unless they are written in Python, and work
* Make it easy to add support for new formats, by using an architecture based on *plugins* and *adapters*.



Examples
========

See http://github.com/brendonh/pyth/tree/master/examples/


Unit tests
==========

The sources contains some unit tests (written using python unittest
module) in the 'tests' directory.

To run the tests we can either run them individually as python script,
either use `python nose`_.  If using nose then we just need to go into
the tests directory and invoke nosetest from there (make sure that
pyth module is in PYTHONPATH).

.. _python nose: http://code.google.com/p/python-nose/


