This is the official tutorial. It covers all the basics, and offers a tour of the language and the standard library. Recommended for those who need a quickstart guide to the language.
Learnpython.org is an easy non-intimidating way to get introduced to Python. The website takes the same approach used on the popular Try Ruby website, it has an interactive Python interpreter built into the site that allows you to go through the lessons without having to install Python locally.
If you want a more traditional book, Python For You and Me is an excellent resource for learning all aspects of the language.
This beginner’s book is for those with no programming experience at all. Each chapter has the source code to a small game, using these example programs to demonstrate programming concepts to give the reader an idea of what programs “look like”.
This book teaches Python programming and basic cryptography for absolute beginners. The chapters provide the source code for various ciphers, as well as programs that can break them.
This is an excellent beginner programmer’s guide to Python. It covers “hello world” from the console to the web.
Also known as Python for Programmers with 3 Hours, this guide gives experienced developers from other languages a crash course on Python.
Dive Into Python 3 is a good book for those ready to jump in to Python 3. It’s a good read if you are moving from Python 2 to 3 or if you already have some experience programming in another language.
Think Python attempts to give an introduction to basic concepts in computer science through the use of the Python language. The focus was to create a book with plenty of exercises, minimal jargon and a section in each chapter devoted to the subject of debugging.
While exploring the various features available in the Python language the author weaves in various design patterns and best practices.
The book also includes several case studies which have the reader explore the topics discussed in the book in greater detail by applying those topics to real-world examples. Case studies include assignments in GUI and Markov Analysis.
Python Koans is a port of Edgecase’s Ruby Koans. It uses a test-driven approach, q.v. TEST DRIVEN DESIGN SECTION to provide an interactive tutorial teaching basic Python concepts. By fixing assertion statements that fail in a test script, this provides sequential steps to learning Python.
For those used to languages and figuring out puzzles on their own, this can be a fun, attractive option. For those new to Python and programming, having an additional resource or reference will be helpful.
More information about test driven development can be found at these resources:
A free introductory book that teaches Python at the beginner level, it assumes no previous programming experience.
A Codeacademy course for the absolute Python beginner. This free and interactive course provides and teaches the basics (and beyond) of Python programming whilst testing the user’s knowledge in between progress.
This book is for intermediate to advanced Python programmers who are looking to understand how and why Python works the way it does and how they can take their code to the next level.
Expert Python Programming deals with best practices in programming Python and is focused on the more advanced crowd.
It starts with topics like decorators (with caching, proxy, and context manager case-studies), method resolution order, using super() and meta-programming, and general PEP 8 best practices.
It has a detailed, multi-chapter case study on writing and releasing a package and eventually an application, including a chapter on using zc.buildout. Later chapters detail best practices such as writing documentation, test-driven development, version control, optimization and profiling.
A Primer on Scientific Programming with Python, written by Hans Petter Langtangen, mainly covers Python’s usage in the scientific field. In the book, examples are chosen from mathematics and the natural sciences.
Problem Solving with Algorithms and Data Structures covers a range of data structures and algorithms. All concepts are illustrated with Python code along with interactive samples that can be run directly in the browser.
Programming Collective Intelligence introduces a wide array of basic machine learning and data mining methods. The exposition is not very mathematically formal, but rather focuses on explaining the underlying intuition and shows how to implement the algorithms in Python.
Python in a Nutshell, written by Alex Martelli, covers most cross-platform Python’s usage, from its syntax to built-in libraries to advanced topics such as writing C extensions.
This is Python’s reference manual, it covers the syntax and the core semantics of the language.
Python Pocket Reference, written by Mark Lutz, is an easy to use reference to the core language, with descriptions of commonly used modules and toolkits. It covers Python 3 and 2.6 versions.
Python Cookbook, written by David Beazley and Brian K. Jones, is packed with practical recipes. This book covers the core python language as well as tasks common to a wide variety of application domains.
“Writing Idiomatic Python”, written by Jeff Knupp, contains the most common and important Python idioms in a format that maximizes identification and understanding. Each idiom is presented as a recommendation of a way to write some commonly used piece of code, followed by an explanation of why the idiom is important. It also contains two code samples for each idiom: the “Harmful” way to write it and the “Idiomatic” way.