Update:
Since we currently don't have the time to edit/author more content we have opened up the entire archive (no login/password required) for everyone to read. We would like to thank all the wonderful authors and editors who have helped us over the years.

Do you have Python related announcements to make? Try opensourcexperts.com's new (and free) Open Source PR System. Please don't email our editors if you have a new Open Source related service, product or case study to announce we will be monitoring this system instead.

Do you provide support for Python? Then list yourself in the Index of Python Solution Providers. (It's free).

Articles:   Snakes and Molecules by: Vineeth Surendra Python finds direct relevance to the domain of molecular biology and genetics since the framework needed here is one in which ideas can be expressed synonymously without having to coerce the ideas into different forms to satiate the semantics of a language or limited by the constructs it offers. Python's collection of rich data structures which work out of the box are a boon for bioinformaticians ranging from sequence analysis to image analysis, not excluding creation of databases and data storage constructs as well as rapid construction of probability models which play a very important role in data analysis in various biological contexts. This article will categorize the programming needs of a bioinformatician or a molecular biologist in theri everyday research work drawing from experiences at The Genomic Research Trust in collaboration with the JHMI's Institute of Genetic Medicine, and at the MPI-Molecular Cell Biology and Genetics, Dresden. It will then look at these needs from a Python perspective, working from scratch, and illustrating actual code used in implementations. The article then proceeds to illustrate the ease of use and the rapid development possible with Python, stressing on how the idea to program translation minimizes the focus shifting from the problem at hand to the problem of programming.   Extending Popular Software Applications with Python by: Chris Downey The power and versatility of Python can be used to make popular shrink-wrapped applications work together in new and exciting ways. For example, I've been using Intuit's Quicken and Microsoft's Excel for more than 10 years. But they've never worked together the way I'd like. Quicken has good canned reports, but I often need the data rearranged and analyzed in different ways that are easily handled in a spreadsheet but impossible in Quicken. This article will illustrate the use of Python and XML to map Quicken report data to Excel spreadsheet named cells, Python to parse the data from Quicken reports, Python/COM to send the data to Excel, and the logic involved in providing a useful summary of actions for the user. By the end of the article, you should have a better understanding of how Python can be used to extend the inherent abilities of popular software applications with a surprisingly small amount of code.   CGI Web Applications with Python - (Part II of III of a Series) by: Michael Foord In the first part of 'Python at Both Ends of the Web' we looked at fetching resources across the internet, using http. This time we're at the other end of the web. One of today's hottest buzzwords is 'web application'. These are programs delivered across the internet, rather than run on the client machine. Because the user connects to the application via the Internet and HTTP, the application can be accessed remotely - freeing users from restrictions of location. A single application can serve many people. You'll be pleased to know that Python is right up with the action. Python is perfectly suited to delivering dynamic information across the internet, and the simplest way of doing this is writing our applications as CGIs.   Doctests by: Brian Sutherland For good code to be useful, it requires two additional things: good documentation and good unit testing. Doctests allow the programmer to do both at the same time with the additional benefits that the documentation is tested and the prose between the tests documents the tests themselves. There are few things worse than undocumented unit tests which over time grow contorted by special cases until they are as understandable as black magic. Forming a link between code, documentation and testing is the greatest advantage of doctests.

More Articles: Pythoneering Eclipse by: Fabio Zadrozny Eclipse? Python? How do they mix? Eclipse is an IDE that IBM is giving away for free to JAVA programmers - right? That's only part of the story. Eclipse itself is designed as a plugin platform and supports many languages. In this article, we disect "PyDev", an open source plugin for using Python within Eclipse, as well as other things one has to know to use Eclipse to program in Python. In this article, we present concepts, techniques and examples on how to make unittests for GUIs. A framework implemented on top of the standard unittest module that comes along with the official python distribution is also supplied, which can be used to test PyQt applications. It can also be easily extended to work with other GUI toolkits as well. A Crash Course in Character Encoding by: Michael Foord Character encodings and Unicode can seem like a black art, fraught with complexity and voodoo-like machinations. To anyone who has only ever used ordinary strings, the mere mention of the word "Unicode" can provoke a mind numbing headache. Unfortunately, it's no longer possible to bury your head in the sand. Computer users span the globe, with participants from every culture, speaking many different languages. If your program can only cope with ASCII, or more likely has no concept of different character sets, you automatically exclude many people from using your programs. Worse, Unicode issues can cause inexplicable problems even for those who try never to think about them Book Review: Python Network Programming by: Samuel Sotillo A Book of Apress' Python Network Programming Book.