Zientzilaria

Covering the bioinformatics niche and much more

Python Testing Beginner’s Guide, Review

| Comments

I posted about a week ago that Packt Publishing had invited me to review Python Testing Beginner’s Guide by Daniel Arbuckle. Having finished reading the book (I must admit that I haven’t tried all the code in it), I can say that I have an excellent initial impression of the book. PTBG is not a long book and the topic is divided in 10 chapters and one appendix. One of the first things that I liked about the book is that there’s no introduction (or something similar) to Python. It just goes straight to the point assuming that you have some good understanding of the language and everything that surrounds it. In the past I was frustrated with some “Introduction to X with Python” that wasted precious space talking over and over about a topic, learning Python, better covered in many other books. PTBG does not waste time and space introducing its main topic which is testing, and in my opinion that’s the best approach, even though it might look a little bit abrupt by some. The language and text in the book is clear and very pleasant. PTBG is a very well written book and I really enjoyed its style. The first chapters of the book cover Python testing using doctests. For someone like me that didn’t write so many tests in the normal software development workflow (I know I should write more tests), this section seems like a really nice introduction to the topic, with well thought real-life like examples and a good flow on the explanation of the different features. One small complain that I have is that for a beginner sometimes the code listed in the examples might seem a little bit confusing, and maybe the addition of line numbers might have helped a bit here. But at the same I understand that this is normal style of some Packt books. After the doctests section, PTBG gets into more advanced techniques, covering a little bit mock objects with Mocker, then moving into unittest and nose. The latter is a Python tool that allows for managing, running and automating tests. Also covered is Twill, another third-party library that allows for testing of web applications. One full chapter is devoted to test-driven development, with a complete walkthrough of this approach. This gives a wrap-up of most of the techniques and modules covered in the book, but there’s still space for another chapter that shows how beautifully doctests, unittest and nose can be fully integrated and help the development of applications using the test-driven approach. Overall, I really enjoyed PTBG. As I mentioned, test driven development was never a high priority in the application I usually developed with Python. But certainly this book can be a good starting point for some Python test beginners to incorporate these techniques in their usual development workflow. Scientific software is also a perfect niche for this type of approach and we should do what is possible in order to avoid the nightmares of the past.