From The Preface An experienced programmer may start writing useful Python code in a matter of hours. As the first productive hours become weeks and months, a lot of developers go on writing Python code with a very strong accent carried from languages learned before. Even if Python is your first language, often in academia and in introductory books it is presented while carefully avoiding language-specific features.
As a teacher introducing Python to programmers experienced in other languages, I see another problem that this book tries to address: we only miss stuff we know about. Coming from another language, anyone may guess that Python supports regular expressions, and look that up in the docs. But if you’ve never seen tuple unpacking or descriptors before, you will probably not search for them, and may end up not using those features just because they are specific to Python.
This book is not an A-to-Z exhaustive reference of Python. Its emphasis is on the language features that are either unique to Python or not found in many other popular languages. This is also mostly a book about the core language and some of its libraries. I will rarely talk about packages that are not in the standard library, even though the Python package index now lists more than 60,000 libraries and many of them are incredibly useful.
Who This Book Is For This book was written for practicing Python programmers who want to become proficient in Python 3. If you know Python 2 but are willing to migrate to Python 3.4 or later, you should be fine. At the time of this writing, the majority of professional Python programmers are using Python 2, so I took special care to highlight Python 3 features that may be new to that audience.
However, Fluent Python is about making the most of Python 3.4, and I do not spell out the fixes needed to make the code work in earlier versions. Most examples should run in Python 2.7 with little or no changes, but in some cases, backporting would require significant rewriting.
Having said that, I believe this book may be useful even if you must stick with Python 2.7, because the core concepts are still the same. Python 3 is not a new language, and most differences can be learned in an afternoon. What’s New in Python 3.0 is a good starting point. Of course, there have been changes since Python 3.0 was released in 2009, but none as important as those in 3.0.
If you are not sure whether you know enough Python to follow along, review the topics of the official Python Tutorial. Topics covered in the tutorial will not be explained here, except for some features that are new in Python 3.
Who This Book Is Not For If you are just learning Python, this book is going to be hard to follow. Not only that, if you read it too early in your Python journey, it may give you the impression that every Python script should leverage special methods and metaprogramming tricks. Premature abstraction is as bad as premature optimization.
Fluent Python: Clear, Concise, and Effective Programming — Python’s simplicity lets you become productive quickly, but this often means you aren’t using everything it has to offer. With this hands-on guide, you’ll learn how to write effective, idiomatic Python code by leveraging its best—and possibly most neglected—features. Author Luciano Ramalho takes you through Python’s core language features and libraries and shows you how to make your code shorter, faster, and more readable at the same time.
Many experienced programmers try to bend Python to fit patterns they learned from other languages, and never discover Python features outside of their experience. With this book, those Python programmers will thoroughly learn how to become proficient in Python 3.
This book covers:
Python data model: understand how special methods are the key to the consistent behavior of objects
Data structures: take full advantage of built-in types, and understand the text vs bytes duality in the Unicode age
Functions as objects: view Python functions as first-class objects, and understand how this affects popular design patterns
Object-oriented idioms: build classes by learning about references, mutability, interfaces, operator overloading, and multiple inheritances
Control flow: leverage context managers, generators, coroutines, and concurrency with the concurrent.futures and asyncio packages
Metaprogramming: understand how properties, attribute descriptors, class decorators, and metaclasses work