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Issue 6 - Revision 7  /   October 18, 2004 


 
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  Articles:
Throughout the quarter we cover topics of interest to Python developers.

  Python MIDI

  Python in Bioinformatics

  Getting Twisted

  optparse

  jEdit

  Python RFID

  3d Graphics in Python

 
 
 
     

Cover by Lia Avant        

Issue 4

Latest News:
All articles for Issue 6 have been published. The Issue 7 table of contents plues the first batch of articles should be up by Thursday.

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In this Issue 6 - Revision 7  /   October 18, 2004 
Articles:
  Python and Midi
by: Peter Parente

The Musical Instrument Digital Interface (MIDI) is a standard in the music industry for controlling audio devices such as keyboard synthesizers and computer sound cards. A client to a MIDI device can format, sequence, and stream MIDI commands in order to generate synthesized music and sound effects. Dealing with the low-level details of command structure, ordering, and timing can be difficult, which makes a layer of abstraction essential to ease the burden of controlling MIDI devices from software.
The PMIDI library for Python and Windows hides many of the details of controlling MIDI devices. In this article, we first present a programmer's view of MIDI. We next introduce PMIDI by explaining its purpose and its design. We then provide three examples of increasing complexity to demonstrate the features and use of PMIDI. Finally, we conclude with a discussion of the current limitations of the library, as well as possible improvements.
  Python in Bioinformatics
by: Titus Brown

Python is a language that is widely used in scientific research. Not only is it easy to learn and simple to use, it is particularly well suited to rapid development and can be used as a "glue" language to integrate a variety of different service. Our lab has been developing in Python since 2000, and we have used Python in a variety of ways, from simple data management and Web site development to the creation of user applications and frameworks supporting our research. In this article, I explore the uses to which we have put Python, and describe some of the more idiosyncratic problems we have solved, which include: distributing jobs automatically across a Beowulf with a Linda tuple space; providing a Web-based front-end to several command-line tools; and encapsulating closed-source binary packages with an API.
  Getting Twisted
by: Christopher Armstrong

Twisted is a framework for writing asynchronously networked applications. One of the greatest advantages of Twisted is that it allows developers to integrate many protocols in their application; it does this by offering consistent APIs to these many protocols. An overview of several of Twisted's parts, along with design ideals and code samples, is provided.
  RFID Product Development With Python
by: Jeff Gray

Py covers the use of Python to develop RFID applications. As Jeff Gray writes: "We originally intended to develop the core of the RFID application in C++ and just use Python for the client API related sections. But terrifying deadlines and limited resources forced us to consider the use of Python for the main application."
More Articles:
jEdit
by: Ollie Rutherfurd

jEdit is a powerful, flexible, and customizable programmer's text editor. There are many good text editors available, and programmers tend to be attached to their editor of choice, but what makes jEdit interesting from the perspective a Python programmer is that jEdit may be customized using Python. One of the many plugins available for jEdit embeds Jython into jEdit allowing one to write macros and plugins for jEdit using Python. This article will provide an overview of what level and types of customization are available and how to enhance jEdit with Python.
The optparse Module
by: Michele Simionato

Taking as an example a real life application - a search and replace tool - I will guide the reader through (some of) the wonders of optparse, showing how easy is to use it and how convenient it really is.
3d graphics in Python
by: Tamer Fahmy

A broad range of 3D modelling tools and 3D graphics libraries exist that take advantage of the power of Python. However, the sheer number of them available makes it hard to choose the appropriate tool for a given task. This article presents a taxonomy based on the types of application, strengths, weaknesses and different programming paradigms.




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