What first attracted me to this book is its coverage of several languages that I know little or nothing about. For reasons mostly due to chance, I’ve been exposed to only a handful of well-known programming languages during my professional career. Recently, I’ve been quite intrigued by Erlang’s concurrency model and robustness even though there is no place for it in my day-day tasks. Having the opportunity to read about Erlang being evaluated against other languages was just what I wanted. So, I took the red pill and found out just how deep the rabbit hole goes.

Django 1.1 Testing and Debugging covers all the essential tools for testing web applications, specifically Django apps. The topics covered are sometimes specific to Django but many are applicable to other web frameworks or straight Python code. Weighing in at about 400 pages, the book includes a balanced mix of discussion, code examples screenshots and stack traces. The book is targeted at web developers familiar with Python, Django and relational databases who are eager to learn more about testing and debugging. The author's writing style is relaxed yet not full of the smarmy jokes found in some technical books. She does a find job of explaining the concepts covered in the book. It should be considered required reading for perfectionists with deadlines.

The authors of this book are also the creators of the Processing language and environment. Processing is “an open source programming environment for teaching computational design and sketching interactive media”.

Vernon Cedar, the author of The Quick Python Book, First Edition, has written a well rounded introduction and reference manual to the Python scripting language. My previous experience with coding was writing C at Nortel in the 90's. I hadn't done much coding since, but I always had the bug to get back into it. My friend suggested that I read and review this book as my introduction to Python.

The Quick Python Book is a good and short introduction/overview of Python 3. The book covers a lot of ground, but because it is relatively slim (about 300 pages or so) it is no wonder that in many places the author instructs the reader to look for more information from online sources. Additionally some more challenging topics (like decorators) are not explained in enough detail, which leaves the reader wondering if those part should have been left out of the book completely (or explained better).

This book is a very good introduction to the R programming language. R is a free, general purpose programming language(with a strong support for doing statistics). The language has its idiosyncrasies. For example, the assignment operator is denoted by a reverse arrow (x<-2); this book does a pretty good job of explaining all these in detail. Once you get past these details, you will find that R is a pretty versatile language.

This book is for people who have a Mac and are willing to invest in a text editor called TextMate.

If you're like me, when Google announced free hosting on their App Engine platform, you couldn't wait to start tinkering with the new bit of goodness that Google was giving to the world...

As a biologist preparing to teach my first course (on Python programming for biologists), I was excited to hear about Mitchell L. Model's Bioinformatics Programming Using Python. A quick look through the table of contents indicated a thorough coverage of the language and useful libraries, and the introduction indicated that it would be appropriate for students in the life sciences with no prior programming experience...

This book is a near-perfect blend of Natural Language Processing done Python usage to its fullest. Not only did the authors describe NLP extremely well and provided great explanation to many different conditions but they also showed an effective use of Python to substantiate the technical content.