Modern Python Cookbook: 133 recipes to develop flawless and expressive programs in Python 3.8 , Second Edition

My son was very pleased with this for Christmas.

I do like code cookbooks, because they are packed with dense information. You can turn to any page and learn something new. And this book has some good recipes. The type of code you will find yourself writing over and over again. A few of the recipes I actually remembering searching for and ending up on Stack Overflow.The book has 15 chapters on topics ranging from the simple ones on basic string manipulation to more complex topics like linear regression.The format is easy to read and understand and doesn't come with the extra fluff and setup procedures that you find filling half of most coding books. It is a great book for Python beginners to browse and pickup new coding techniques and get familiar with Python idioms.

While I don't particularly like the code-as-cookbook structure, the key factor is: does the material provide useful functionality to the reader? In this book, the answer is yes.I've been programming in Python since 2005 or so. While some of the information I know from experience and having to learn it for inclusion in my own books, there is always something new to learn. In this case, there are some aspects of Python and programming that I didn't know before, and there are some things that I've been aware of but never had a need to use them.In some cases, there are recipes that do provide added-value to the reader in terms of shortcuts or best-practices that improved coding efficiency, reduce programming time, or simply expand the knowledge of the reader.Some of the most useful information, I think, for new Python programmers is type hints. While not necessary, they do provide some backup in terms of data type verification. Essentially, they allow programmers to utilize the dynamic capabilities of Python while incorporating some of the "type safety" of static-typed languages. You aren't forced to use them, and you can ignore the warnings, but from personal experience, they do help when troubleshooting.As an added note, if you learn Python type hints, then learning Rust is actually pretty easy. The syntax of Rust is very much like Python with type hints, so it's actually easier for a Python programmer to learn Rust than a C/C++ programmer, at least based on Internet comments.Some of the information in the book is pretty basic; things you would expect to see in any introductory book, such as working with lists and dictionaries. It doesn't mean it's bad, just that there are portions of the book that intermediate and advanced Python programmers can probably skip over.On the other hand, there are always those little nuggets of information that you either forgot about or didn't know about, so I would at least recommend skimming those sections to see if there is anything useful you can glean from them.Functional programming gets an entire chapter, which is good. Frequently, books will discuss functional programming when the examples demand it. This can result in hunting to find what you need, as functional programming isn't a common paradigm outside of certain languages. Having a whole chapter dedicated to it makes it easier to understand the how and why of functional programming.Finally, some commonly overlooked programming aspects are covered: testing, statistical programming, web development, and application integration. While some (very thick) books may incorporate these topics (and this is a thick book at 800+ pages), it's always good to see these mentioned.It's hard to program nowadays without having to deal with web services, so even the basics of web development are appreciated. Testing is also not commonly taught in CS curriculums or even in general purpose programming books, so proper unit testing is a valuable skill to have. And the push for data science means knowing just the basics of statistics with Python opens up new avenues for knowledge expansion.Overall, this book straddles the line of introduction to Python and "cheat sheet" for advanced programming. It's a very nice supplement to any number of basic Python books and can be used as a reference or template for development.

I like the examples and explanations. While no single book can overcome a student's complete ignorance, this is filling in gaps I didn't know existed.

This book, written and reviewed by the "dinosaurs" of the industry and the "founding fathers" of Python itself, covered such a wide range of topics, starting from the basics of the syntax of the language and ending with Statistical Programming and Application Development. Did not expect to see that much of the scope covered in a single book.One unique feature of the book I'd like to highlight is this presence of the bigger picture and "why" for every topic explained in the book - why this was done one way and not the other, what role does it play and why is smth important. These reflections really helped me always have the context of why I want (or don't want) to learn a particular subject.