Book Review: IPython Notebook Essentials, Ch. 1

On a Google+ statistics group, sometime around the new year, I saw an offer for a free book on IPython Notebooks in exchange for a review of the book. I wanted to learn about IPython Notebooks, so I offered to write a review. The spring semester had started before I got my copy of the book, and what I should have foreseen happened: I got too busy to read the book and write the review. Well, I’m making a good faith effort to fulfill my side of the deal now. Better late than never, right?

The book is IPython Notebook Essentials, written by L. Felipe Martins, and published by Packt Publishing. I’ve read Chapters 1 and 2 so far. Both are clear and well-written, with only a few minor problems, and those possibly as much due to my own proclivities as anything else.

Chapter 1 covers the basics of installing a suitable scientific python package (e.g., Anaconda, which I’m a big, big fan of), creating a notebook, and executing some basic code in that notebook. The code given is a bit goofy, implementing a model of change in coffee temperature as a function of time and initial temperature, but introductory code in this kind of book is often fairly ridiculous.

I was already reasonably familiar with Python before getting this book, so it’s a bit difficult for me to judge the pedagogical effectiveness of the code in Chapter 1 for someone with little to no programming experience. Of course, it’s not meant to be a comprehensive introduction to Python, so this kind of intro has to fit into kind of an awkward space. It can’t be too boring to someone with some (or a lot of) experience, but it can’t be too confusing or complicated for less experienced programmers. This book does a pretty good job balancing the needs of a potentially wide variety of reader experience levels, I think.

One small issue I have with the code is that the convention for variable naming uses a lot of full words and underscores. The benefit of this is, of course, that the names are unambiguous and you mostly know what variables are just by looking at their names. The downside is that the code often spans multiple lines in the book, which can make it slightly more difficult to read. I tend to err very much in the other direction in my own code, giving variables short, but sometimes confusing, names. So, my taste runs a bit against the convention in this book. I don’t think the author should have gone as far as I often do, but I think some of the code snippets in the book would look nicer and be a bit easier to read if the variable names had been a bit shorter.

Okay, so Chapter 1 is fine. It’s not spectacular, but it does its job okay. I’ll give it B.

This entry was posted in Python. Bookmark the permalink.

Comments are closed.