Python has become the lingua franca of modern computing. The thesis of this book is that Python is the most important programming language in the world today…with outsized rewards for those who master it. This book is designed to teach you techniques, patterns, and tools to permanently catapult your skill with everything Python has to offer.
If you write Python code at least part of the time, this book will vastly amplify what you can accomplish and increase the speed at which you do it. And slash the amount of time you spend debugging, too.
This book is for you if you know the basics of Python and have mastered just about everything the beginner tutorials can teach you. It is also for those who want to learn more advanced techniques and strategies, so you can do more with Python, and more with coding, than you could before.
This book is not for people who want just enough Python to get by. Like I said, Python is important, and rewards those who master it.
And this book is not for the unambitious. In writing, I assume you want to build a career you are proud of, doing work with a high positive impact.
Further, this book is not for the mentally rigid. The difference between elite engineers and “normal” coders lies in the distinctions they make, the mental models they leverage, and their ability to perceive what others cannot.
It is not enough to gather knowledge. What you really want is to develop new capabilities. Hence, this book recognizes two levels of learning.
The first is the information level. This is the level of learning where you read something, or I tell you something, and you memorize it. This puts facts, opinions, and other information in your mind that you can recall later; parrot back to me; and use in logical reasoning.
Which is great. We certainly need this, as a foundation.
But there is a deeper level of learning, called the ability level. The ability to do things you could not do before, when you are writing code.
Both are important. But the ability level is what truly matters.
You see, the information level can be deceptive. It makes you feel like you understand something. But then you go to write code using it, staring at a blank editor…and you find yourself stuck. “Wait a second. How do I actually use this?”
Know that feeling? Of course you do. Every coder does.
That feeling means you have learned at the information level, but not yet at the ability level. Because when you do, what you need just comes out of you, as naturally as thought itself.
For the most part, reading a book or watching a video can only teach you at the information level. But this book aims to break that trend in several ways.
Modern Problem #1: You have too much to learn.
Modern Problem #2: Society has evolved to reduce your time and energy for deep focused learning, due to changes in technology and culture.
This seems like a recipe for misery. But there is a way out: what are called first principles.
In any field of human activity—including Python coding—there are foundational concepts which everything builds on. These include powerful distinctions, abstractions, and mental models. When you learn what these first principles are and how to work with them, you find yourself cutting through the noise and getting ahead much more easily.
These first principles are accelerators, in that they give you the tools, inner resources, and capabilities to solve many problems. It effectively creates a “95/5” rule: there is a 5% you can focus on learning, which makes the remaining 95% fall like dominos.
That 5% is what we mean by the first principles of Python. Which is what this book is really about.
Hence, this book is selective in what it covers. It is not a comprehensive “one stop shop” for everything Python. Further, this book contains practical guidance based on lessons learned when writing real-world software—often as part of a team of engineers.
So factors like maintainability, robustness, and readability are considered more important than anything else. There is a balance between leveraging powerful abstractions, and writing code that is easy to work with by everyone on your team. This book aims to walk that line.
Throughout, I give much attention to cognitive aspects of software development. How do you write code that you and others can reason about easily, quickly, and accurately? This is one reason variable and function naming is important. But it goes far beyond that syntax level…to intelligently choosing which language features and library resources to use, and which to avoid.
This book is not large, as measured by number of pages. That’s a feature, not a bug: you already have too much to read. The focus is on what’s most valuable, so that—as much as possible—everything you learn will serve you for years.
Here are some topics I have chosen to omit:
I barely mention anything outside the standard library. We have plenty to cover just for Python and its included batteries.
Type annotations. As we go to press, the dust is still settling on this rich feature. And as dear as it is to some, it is far from universally used.
Dataclasses. There are endless tutorials on this tool, and Chapter 6, “Classes and Objects: Beyond the Basics” is already the largest in the book.
Concurrency. The fact is, most Python is written as single-threaded programs. And doing justice to threading, multiprocessing, and asyncio could double the page count.
Anything depending on specific Python versions. Fortunately, the Python patterns and strategies that work best are surprisingly independent of version. It is these slow changing yet powerful principles we focus on.
Less commonly used features such as keyword-only and positional-only arguments, conditional (ternary) expressions, pattern matching, and so on. Not to say they are not useful; but better for them to be covered elsewhere.
And other topics people like, I am sure.
What is present covers the important keys of Python, many of which are not new, but are criminally underused and misunderstood, and will be highly valuable for all Pythonistas.
If you simply cannot bear the injustice of this book not covering your favorite Python topic, I can only refer you to what the French poet Paul Valéry said. Which—translated, paraphrased, and shortened—boils down to: “A work of art is never completed, only abandoned.”
Such is this book, which I have invested nearly a full decade of my life producing for you. At some point, if it is to be of value to anyone at all, I must ship this thing.
It is ultimately up to you to transform the information in this book into ability-level learning. And you do that by putting what you read into practice.
To help, I have created coding exercises for every chapter, plus other fun resources—exclusively for readers of this book. To get these along with email notifications of future book releases, go to https://powerfulpython.com/register and follow the instructions.
For professional training options, go to https://powerfulpython.com and browse the resources there. If you have feedback on this book; corrections; or suggestions for the future, send them to aaron@powerfulpython.com.
The following typographical conventions are used in this book:
Indicates new terms, URLs, email addresses, filenames, and file extensions.
Constant widthUsed for program listings, as well as within paragraphs to refer to program elements such as variable or function names, databases, data types, environment variables, statements, and keywords.
Constant width boldShows commands or other text that should be typed literally by the user.
Constant width italicShows text that should be replaced with user-supplied values or by values determined by context.
This element signifies a tip or suggestion.
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This book was nearly a decade in the making. And I have many to thank.
First, I want to thank the thousands of readers of the earlier, self-published editions of this book—including the hundreds of professional students in Powerful Python Bootcamp. Your many excellent questions and comments—and pointing out bugs!—helped me continually improve the book from day one.
Speaking of which, the O’Reilly team is stellar. If you are an author considering publishing with this amazing group of people, I cannot recommend them enough. I specifically want to thank my development editor, Virginia Wilson; my production editor, Aleeya Rahman; Sarah Grey and Helena Stirling, who together caught more errors than I thought possible; Brian Guerin, for ensuring the project got started in the first place; Yasmina Greco, for wrangling the live O’Reilly training sessions that formed fertile ground for researching this book; and others I am unfairly not mentioning, or who worked behind the scenes.
But the greatest heroes are the technical reviewers. I want to thank Peter Norvig, whose deep feedback on the final self-published version stratospherically elevated this O’Reilly edition; Rodrigo Girão Serrão, whose exceptional expertise in the Python language prevented what would have been many terrible errors; Jess Males, who saved you all from a number of confusingly worded passages and pointed out how to make them comprehensible; and Han Qi, whose formidably sharp mind made it nearly impossible for any bug to escape detection. To all of you, I cannot express enough my gratitude for your help in creating this wonderful book, and making it the best it can be.