A Review of The Quick Python Book, Fourth Edition

I’ve been given a review copy of The Quick Python Book, Fourth Edition by Naomi Ceder, published by Manning. Since I often get asked for Python book recommendations, I thought it would be a good idea to share a review, in case you are looking for material to sharpen your Python skills.

Before I start I want to clarify that Manning shared a pre-release copy of this book with me and asked if I could give a recommendation to use in their promotion materials for the book. I’m not getting paid to write a review, aside from a coupon to get a free copy of the e-book once it is released. I do not make any income from traffic or sales I send to Manning from this page. While I know who Naomi (the author) is, I do not know her personally.

With that out of the way, here is my review of The Quick Python Book, Fourth Edition.

Intended Audience

This book does an excellent job covering modern Python. It starts from the basics, so beginners will get the most out of it. Readers will need to have at least a tiny bit of programming experience, because some of the most basic concepts such as what a variable is, or how conditionals and loops work are assumed to be known.

Structure

The book is divided into four parts: “Starting Out”, “The Essentials”, “Advanced Language Features” and “Working with Data”. There is also one appendix titled “A guide to Python’s documentation”.

Included in the book is a high-level table of contents, the “brief contents”, that I found extremely useful. While a complete beginner to Python may benefit from reading the book sequentially, a slightly more experienced reader may choose to use this concise table of contents to jump to specific topics of interest such as “Strings”, “Functions”, etc. The PDF edition that I’m reviewing includes hyperlinks, which makes navigation through the book very enjoyable.

Part 1: Starting Out

The first part of the book, divided in three chapters, provides an introduction and overview of the Python language.

Here the author discusses the different versions of Python, and how to choose one. I was surprised to see that the author recommends readers to not install Python on their computers, but instead work on the examples presented using Google Colaboratory, an implementation of Python that is hosted on the web. I would agree with this recommendation for users interested in data science applications, but as a general recommendation I would suggest beginners to use a standard Python interpreter installed on their computers, an option that is also discussed in the book.

The third and last chapter in this part is a short, yet fairly complete reference of the Python language. If you are attracted to this book because of the “quick” in the title, then you are going to love this chapter, because in just a few pages it manages to walk you through most of the features of the language with abundant examples.

Part 2: The Essentials

The meat of this book is in the second part, which contains eleven chapters, each covering one aspect of the language in detail. The early chapters in this section discuss how to work with lists, strings, dictionaries, control flow statements and functions. Then in the later chapters I was happy to see topics that are a bit beyond the basics that are often neglected in books and tutorials, such as organizing code in multiple modules, distributing your Python programs to others, working with files and handling errors.

Part 3: Advanced Language Features

The third part includes five chapters, dedicated to object-oriented programming, regular expressions, data types, packages and libraries.

I hope having “advanced” in the title of this section does not scare readers away, as some of these chapters are a must-read, even for beginners. For example, I can’t imagine any Python developer not knowing how to work with libraries, either those that come with Python or those released by third parties.

Part 4: Working with Data

The final part in this book is dedicated to data applications and is divided in five chapters, covering a variety of ways to obtain, process, store and analyze data. This part is for you if you are interested in working with CSV files, databases, APIs and charts.

Appendix: A guide to Python’s documentation

You would think from the title that the appendix at the end of the book is just a standard collection of links to the usual resources, but while the chapter starts that way it soon evolves into another quick guide, this time for writing idiomatic Python code using PEP8 style recommendations. So don’t let the title fool you; this is another great little chapter with a lot of content you would want to know.

Conclusion

What I really like about The Quick Python Book, Fourth Edition is that it is true to its title. Do you want a quick guide to the language? There’s a chapter for that. A quick reference on a specific Python feature? The most important ones have a chapter dedicated to them. Do you want to learn how to write modern, clear, idiomatic Python code? The appendix has you (quickly) covered as well.

To be fair, I should also mention things that I’ve found to be missing in this book. From the areas and topics I usually work on, I did not find anything on the asynchronous features of the language, and also nothing on building web applications. I don’t think this is a big issue though, since these are topics you will take on after you have learned the basics. If these are areas you have an interest in, then you can come back to this blog when you are done with the book and you will find plenty of content!

The final comment I have about this book is related to Generative AI. The book claims to include coverage of GenAI, which seemed strange for a book of this type. What this means is that the author has included tips and examples related to code generation with AI tools throughout the book. In a few places the author proposes an exercise and then goes on to compare her own solution against a solution she produced using an AI coding tool. I’m not sure there is a lot of use for this, but if you are interested in seeing GenAI examples you’ll find some in this book.

Overall I can say that really liked this book as a way to get up to speed with Python quickly.