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  • Learn Python, Break Python: A Beginner's Guide to Programming

    This book is a hands-on introduction to the Python programming language, written for people who have no experience with programming whatsoever. You don't need to worry. Learning how to program a computer is far from impossible.

  • Python for Everybody: Exploring Data in Python 3

    This book is designed to introduce students to programming and software development through the lens of exploring data. You can think of the Python programming language as your tool to solve data problems that are beyond the capability of a spreadsheet.

  • Automate the Boring Stuff with Python (Albert Sweigart)

    Learn how to use Python to write programs that do in minutes what would take you hours to do by hand - no prior programming experience required. You'll create Python programs that effortlessly perform useful and impressive feats of automation.

  • O'Reilly® Test-Driven Development with Python (Harry Percival)

    By taking you through the development of a real web application from beginning to end, this hands-on guide demonstrates the practical advantages of test-driven development (TDD) with Python. You'll learn how to write and run tests BEFORE building your apps.

  • The Coder's Apprentice: Learning Programming with Python 3

    This book is aimed at teaching Python 3 to students and teenagers who are completely new to programming, assumes no previous knowledge of programming on the part of the students, and contains numerous exercises to train their programming skills.

  • Non-Programmer's Tutorial for Python 3 (Josh Cogliati, et al)

    This book is a tutorial designed to be a introduction to the Python programming language. This guide is for someone with no programming experience. There are a lots of code inside this guide. You should type in code that to see what happens.

  • A Whirlwind Tour of Python (Charles Severance)

    This book a fast-paced introduction to essential features of the Python language, aimed at researchers and developers who are already familiar with programming in another language, particularly for using Python for data science and/or scientific programming.

  • O'Reilly® 20 Python Libraries You Aren't Using (But Should)

    This book helps you explore some of the lesser known Python libraries and tools, including third-party modules and several extremely useful tools in the standard library that deserve more attention.

  • The Hitchhiker's Guide to Python: Best Practices for Development

    This guide describes best practices currently used by package and application developers. Unlike other books for this audience, It is light on reusable code and heavier on design philosophy, directing the reader to excellent sources that already exist.

  • O'Reilly® Think Python, 2nd Edition (Allen B. Downey)

    This hands-on guide takes you through the Python programming language a step at a time, beginning with basic programming concepts before moving on to functions, recursion, data structures, and object-oriented design. 2nd edition updated for Python 3.

  • O'Reilly® Python Data Science Handbook: Essential Tools

    Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all - IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.

  • Cracking Codes with Python: Building and Breaking Ciphers

    Learn how to program in Python while making and breaking ciphers - algorithms used to create and send secret messages! You'll begin with simple programs for the reverse and Caesar ciphers and then work your way up to public key cryptography, etc.

  • Python and Coding Theory (David Joyner)

    This is the lecture notes for a course on Python and coding theory designed for students who have little or no programmig experience. You will learn some of the Python computer programming language and selected topics in coding theory.

  • Learning IPython for Interactive Computing and Data Visualization

    This book is a beginner-friendly guide to the Python data analysis platform. With data analysis and numerical computing tutorials at your disposal it offers you the chance to discover how to make the most of IPython right now. Discover why Python is so loved in the data world and revolutionize your work today!

  • Hands-on Python Tutorial (Dr. Andrew N. Harrington)

    This book provides a concise, step-by-step guide to Python programming for beginners. A lot of examples, illustrations, end of chapter summary and practice exercises (with solutions) are provided to help the reader learn faster, remember longer, etc.

  • O'Reilly® Python Web Frameworks (Carlos De La Guardia)

    This book describes Python web frameworks ranging from full-stack options that offer a lot of functionality to micro frameworks that focus on simplicity with fewer features. Learn how to choose a framework that best fits your development needs.

  • Hadoop with Python (Zachary Radtka, et al)

    This book takes you through the basic concepts behind Hadoop, MapReduce, Pig, and Spark. Then, through multiple examples and use cases, you'll learn how to work with these technologies by applying various Python tools.

  • Python Notes for Professionals (Stack Overflow Contributors)

    This book is compiled from Stack Overflow Documentation, the content is written by the beautiful people at Stack Overflow. Text content is released under Creative Commons BY-SA. See credits at the end of this book whom contributed to the various chapters.

  • Learning Python (Fabrizio Romano)

    The book begins by exploring the essentials of programming, data structures and teaches you how to manipulate them. It then moves on to controlling the flow of a program and writing reusable and error proof code.

  • Functional Programming in Python (David Mertz)

    It describes ways to avoid Python’s imperative-style flow control, the nuances of callable functions, how to work lazily with iterators, and the use of higher-order functions. He also lists several third-party Python libraries useful for functional programming.

  • Building Machine Learning Systems with Python (Willi Richert)

    Featuring a wealth of real-world examples, this book provides gives you with an accessible route into Python machine learning. You'll learn everything you need to tackle the modern data deluge - by harnessing the unique capabilities of Python.

  • How to Make Mistakes in Python? (Mike Pirnat)

    Even the best programmers make mistakes. Some have been simple and silly; others were embarrassing and downright costly. The author dissects some of his most memorable blunders, peeling them back layer-by-layer to reveal just what went wrong.

  • Fast Lane to Python (Norm Matloff)

    This book aims to enable the reader to quickly acquire a Python foundation. The material particularly feel quite comfortable to anyone with background in an object-oriented programming (OOP) language such as C++ or Java.

  • A Beginner's Python Tutorial (Wikibooks)

    If you are new to programming with Python and are looking for a solid introduction, this is the book for you - a comprehensive and easy-to-read introduction to Python programming includes a wealth of programming tutorials for writing your first lines of code.

  • Programming for Computations - Python (Svein Linge, et al)

    This book presents computer programming as a key method for solving mathematical problems using Python. Each treated concept is illustrated and explained in detail by means of working examples. It is intended for novice programmers and engineers.

  • Solving PDEs in Python: The FEniCS Tutorial I (H. Langtangen)

    This book offers a concise and gentle introduction to finite element programming in Python based on the popular FEniCS software library. Using a series of examples, it guides readers through the essential steps to quickly solving a PDE in FEniCS.

  • Guide to NumPy (Travis E. Oliphant)

    This book is for programmers, scientists, or engineers, who have basic Python knowledge and would like to be able to do numerical computations with Python. It will give you a solid foundation in NumPy arrays and universal functions.

  • Scipy Lecture Notes (Emmanuelle Gouillart, et al)

    This book is the teaching material on the scientific Python ecosystem, a quick introduction to central tools and techniques. It is for programmers from beginner to expert. Work on real-world problems with SciPy, NumPy, Pandas, scikit-image, and other Python libraries.

  • Bayesian Methods for Hackers: Using Python and PyMC

    This book illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, Matplotlib, through practical examples and computation - no advanced mathematics required.

  • O'Reilly® Picking a Python Version: A Manifesto (David Mertz)

    This report guides you through the implicit decision tree of choosing what Python version, implementation, and distribution is best suited for you. There are two major versions: the Python 2.x series, and the newer Python 3.x series.

  • Dive Into Python 3 (Mark Pilgrim)

    This book is a hands-on guide to Python 3 (the latest version of the Python language) and its differences from Python 2. Each chapter starts with a real, complete code sample, proceeds to pick it apart and explain the pieces, and then puts it all back together in a summary at the end.

  • Porting to Python 3: An In-depth Guide (Lennart Regebro)

    Porting to Python 3 doesn't have to be daunting. This book guides you through the process of porting your Python 2 code to Python 3, from choosing a porting strategy to solving your distribution issues.

  • Python Scripting for Spatial Data Processing (Pete Bunting, et al)

    This book is a Python tutorial for beginners aiming at teaching spatial data processing. It is used as part of the courses taught in Remote Sensing and GIS, using psycopg2, and ogr2ogr, etc., at Aberystwyth University, UK.

  • Python 3 Basics Tutorial (Kristian Rother)

    Written specifically for beginners, it takes you step-by-step through writing your very first program, explaining each portion of code as we go along, guides you through setting up Python, choosing an IDE, as well as the various elements of coding in Python.

  • Modeling Creativity - Case Studies in Python (Tom De Smedt)

    This book is to model creativity using computational approaches in Python. The aim is to construct computer models that exhibit creativity in an artistic context, that is, that are capable of generating or evaluating an artwork (visual or linguistic), etc.

  • Python 201: (Slightly) Advanced Python Topics (Dave Kuhlman)

    This course contains discussions of several advanced topics that are of interest to Python programmers: regular expressions, unit tests, extending and embedding Python, parsing, GUI applications, guidance on packages and modules.

  • Raspberry Pi Cookbook for Python Programmers (Tim Cox)

    Stuffed with more than 50 hands-on recipes, this FREE eBook shows you how to get the most out of your Raspberry Pi. Discover what the Raspberry Pi has to offer using detailed Python code examples that you can adapt and extend.

  • Python for Informatics: Exploring Information (Charles Severance)

    This book provides an Informatics-oriented introduction to programming. The primary difference between a computer science approach and the Informatics approach taken in this book is a greater focus on using Python to solve problems.

  • Algorithmic Problem Solving with Python (John B. Schneider)

    This book uses Python to introduce folks to programming and algorithmic thinking. It is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving techniques.

  • Python for Econometrics, Statistics and Data Analysis

    This book provides an introduction to Python for a beginning programmer. They may also be useful for an experienced Python programmer interested in using NumPy, SciPy, and matplotlib for numerical and statistical analaysis.

  • The Full Stack Python (Matt Makai)

    This book explains each Python web application stack layer and provides the best web resources for those topics. Throughout the book it takes an example open source Python web application through a complete deployment on a virtual private server.

  • O'Reilly® Natural Language Processing with Python

    This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation.

  • O'Reilly® Think DSP: Digital Signal Processing in Python

    This book is an introduction to signal processing and system analysis using a computational approach with Python as the programming language. It develops the important ideas incrementally, with a focus on applications.

  • Think Stats, 2nd Edition: Exploratory Data Analysis in Python

    This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.

  • Gui Programming With Python: Using the Qt Toolkit (B. Rempt)

    The main topic of this book is application development using PyQt. Whether you're building GUI prototypes or full-fledged cross-platform GUI applications with native look-and-feel, PyQt is your fastest, easiest, most powerful solution.

  • Deep Learning Tutorials using Python (LISA Lab)

    The tutorials presented here will introduce you to some of the most important deep learning algorithms and will also show you how to run them using Theano. Theano is a python library that makes writing deep learning models easy, and gives the option of training them on a GPU.

  • Python for Kids: A Playful Introduction to Programming

    This book brings Python to life and brings you (and your parents) into the world of programming. It will guide you through the basics as you experiment with unique example programs that feature ravenous monsters, secret agents, thieving ravens, and more.

  • Hacking Secret Ciphers with Python (Albert Sweigart)

    This book teaches you how to write your own cipher programs and also the hacking programs that can break the encrypted messages from these ciphers.

  • O'Reilly® Think Python - How to Think Like a Computer Scientist

    This free book is an introduction to Python programming for students with no programming experience.

  • Problem Solving with Algorithms and Data Structures Using Python

    This is a textbook about computer science. It is also about Python. However, there is much more. The tools and techniques that you learn here will be applied over and over as you continue your study of computer science.

  • O'Reilly® Think Bayes: Bayesian Statistics in Python

    With this book, you'll learn how to solve statistical problems with Python code instead of mathematical notation, and use discrete probability distributions instead of continuous mathematics.

  • Programming Computer Vision with Python: Tools and Algorithms

    This book is a hands-on introduction to computer vision using Python. It gives an easily accessible entry point to hands-on computer vision with enough understanding of the underlying theory and algorithms to be a foundation for students, researchers.

  • Learning OpenCV 3 Computer Vision with Python (Joe Minichino)

    Intended for novices to the world of OpenCV and computer vision, as well as OpenCV veterans that want to learn about what's new in OpenCV 3, this book is useful as a reference for experts and a training manual for beginners.

  • Invent Your Own Computer Games with Python, 3rd Edition

    It teaches you how to program computer games in the Python programming language. Each chapter gives you the complete source code for a new game. It was written to be understandable by anyone of any age who has never programmed before.

  • Learn to Program Using Python: A Tutorial for Hobbyists, Starters

    This book is based on a popular on-line tutorial that has been expanded and enhanced for this book. It takes you step-by-step through all the essential programming topics.

  • Python Scripting for Computational Science (Hans Langtangen)

    With a primary focus on examples and applications of relevance to computational scientists, this brilliantly useful book shows computational scientists how to develop tailored, flexible, and human-efficient working environments built from small scripts written in the easy-to-learn, high-level Python language.

  • Python Succinctly (Jason Cannon)

    Learn to use the Python language to create programs of all kinds. It will guide you from complete unfamiliarity with Python to creating practical applications. With Python Succinctly, lack of experience isn't an obstacle to programming language mastery.

  • The Python Language Reference Manual (Guido van Rossum, et al)

    This manual is intended for advanced users who need a complete description of the Python 3.x language syntax and object system.

  • A Practical Introduction to Python Programming (Brian Heinold)

    This book is for anyone who wants to understand Python programming. Both a tutorial and a reference, you'll code along with the book, writing programs to solve real-world problems as you learn the fundamentals of programming using Python 3.

  • An Introduction to Python (Guido van Rossum)

    This manual provides an introduction to Python, an easy to learn object-oriented programming language. Python combines power with clear syntax. It has modules, classes, exceptions, very high level data types, and dynamic typing.

  • Python for You and Me (Kushal Das)

    This is a simple book to learn Python programming language - it shall introduce you to an easy way to learn Python and be able to complete your own projects!

  • Make Games with Python on Raspberry Pi (Sean M. Tracey)

    You are going to learn how to make a game on our Raspberry Pi from the ground up. It is designed to help you learn many of the essential skills you'll need to make games with Python and Pygame on your Raspberry Pi.

  • O'Reilly® Mining the Social Web, 2nd Edition (Matthew A. Russell)

    This book shows you how to answer these questions like how can you tap into social data and discover who's connecting with whom, which insights are lurking just beneath the surface, and what people are talking about?

  • O'Reilly® Think Stats: Probability and Statistics using Python

    This book shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.

  • O'Reilly® The Python Standard Library (Fredrik Lundh)

    Ideal for any working Python developer, this book provides an excellent tour of some of the most important modules in today's Python standard.

  • Learning to Program Using Python (Cody Jackson)

    The core Python language (both versions 2.x and 3.x) is discussed, as well as an introduction to graphical user interface creation. The ideas covered in this book provide the reader with many major programming topics, applicable to a wide variety of programming languages.

  • Programming and Mathematical Thinking: Discrete Math & Python

    Starting at an elementary level, this book teaches about fundamental structures of discrete mathematics and many simple but powerful programming techniques using those structures.

  • How to Think Like a Computer Scientist: Learning with Python

    This book is an introduction to computer science using the Python programming language.

  • Keras Succinctly (James McCaffrey)

    The goal of this book is to introduce you Keras, the one of the most popular and powerful libraries for building neural networks in Python. You'll learn how to build a convolutional neural network in Python!

  • Dive Into Python: Python from Novice to Pro (Mark Pilgrim)

    This book is your 'desert island' Python book. If you've never programmed before, Python is an excellent language to learn modern programming techniques.

  • A Byte of Python (Swaroop C H)

    This book serves as a tutorial or guide to the Python language for a beginner audience. It is written for the latest Python 3, even though Python 2 is the commonly found version of Python today (read more about it in Python 2 versus 3 section).

  • Text Processing in Python (David Mertz)

    This book is an example-driven, hands-on tutorial that carefully teaches programmers how to accomplish numerous text processing tasks using the Python language.

  • Making Games with Python and Pygame (Albert Sweigart)

    This is a programming book that covers the Pygame game library for the Python programming language.

  • Effective Django (Nathan Yergler)

    With this book, you should have an understanding of how Django's pieces fit together, how to use them to engineer web applications, and where to look to dig deeper.

  • The Definitive Guide to Django: Web Development Done Right

    This book will show you how to assemble Django's features and take advantage of its power to design, develop, and deploy a fully-featured web site.

  • O'Reilly® Think Complexity: Science and Modeling (Allen Downey)

    This book is about complexity science, data structures and algorithms, intermediate programming in Python, and the philosophy of science.

  • Computational Physics with Python (Eric Ayars)

    This book provides an unusually broad survey of the topics of modern computational physics. Its philosophy is rooted in learning by doing, with new scientific materials as well as with the Python programming language.

  • Computational Physics with Python (Mark Newman)

    A complete introduction to the field of computational physics, with examples and exercises in the Python programming language. It explains the fundamentals of computational physics and describes in simple terms the techniques that every physicist should know,.

  • Python Scientific Lecture Notes (Scipy Lectures )

    This book is the teaching material on the scientific Python ecosystem, a quick introduction to central tools and techniques. It is for programmers from beginner to expert. Work on real-world problems with SciPy, NumPy, Pandas, scikit-image, and other Python libraries.

  • Modeling and Simulation in Python (Allen B. Downey)

    This book is an introduction to physical modeling using a computational approach with Python. You will learn how to use Python to accomplish many common scientific computing tasks: importing, exporting, and visualizing data; numerical analysis; etc.

  • Python in Hydrology (Sat Kumar Tomer)

    This book is written for learning Python using its applications in hydrology. The book covers the basic applications of hydrology, and also the advanced topic like use of copula.

  • How To Write Your Own Software Using Python (Steven F. Lott)

    This book will help you build basic programming skills, organized in a way that builds up the language in layers from simple, central concepts to more advanced features.

  • First Course in Programming with Karel the Robot and Python

    A gentle, efficient and comprehensive introduction to modern algorithmic design and computer programming with two programming languages: Karel the Robot and Python.

  • Practical Data Science Cookbook using Python and R

    Starting with the basics, this book covers how to set up your numerical programming environment, introduces you to the data science pipeline, and guides you through several data projects in a step-by-step format.

  • Basic Data Analysis and More - A Guided Tour Using Python

    In this book, a selection of frequently required statistical tools will be introduced and illustrated. From a point of view of data analysis, an exemplary implementation of the presented techniques using the Python programming language is provided.

  • A Python Book (Dave Kuhlman)

    This book is a self-learning document for a course in Python programming. It contains (1) a part for beginners, (2) a discussion of several advanced topics that are of interest to Python programmers, and (3) a Pythonworkbook with lots of exercises.

  • Become a Code Breaker with Python: a Beginner's Guide

    This book describes several encryption Python programs for various ciphers, along with how to write Python programs that can break these ciphers.

  • Python Tutorial (Guido van Rossum)

    This tutorial introduces the reader informally to the basic concepts and features of the Python language and system.

  • The Art and Craft of Programming, Python Edition (John C. Lusth)

    This book is designed to be used as the primary textbook in a college-level first course in computing. It takes a fairly traditional approach, emphasizing problem solving, design, and programming as the core skills of computer science.

  • Learning with Python: Interactive Edition

    This book provides a comprehensive, accessible introduction to Python fundamentals. An ideal first language for learners entering the rapidly expanding field of computer science, Python gives students a solid platform of key problem-solving skills that translate easily across programming languages.

  • Learning to Program with Python (Richard L. Halterman)

    This book does not attempt to cover all the facets of the Python programming language. The focus here is on introducing programming techniques and developing good habits. The code in this book is based on Python 3.

  • Python 3 Patterns, Recipes and Idioms (Bruce Eckel, et al)

    This book is aimed at more experienced Python programmers who are looking to deepen their understanding of the language and modern programming idioms. It focuses on some of the more advanced techniques used by libraries, frameworks, and applications.

  • Design Patterns in Python (Brandon Rhodes, et al)

    Understand the structural, creational, and behavioral Python design patterns - this book will help you learn the core concepts of design patterns and the way they can be used to resolve software design problems using Python.

  • O'Reilly® Python Cookbook, 3rd Ed: Recipes for Mastering Python 3

    This book is packed with practical recipes written and tested with Python 3.3, this unique cookbook is for experienced Python programmers who want to focus on modern tools and idioms.

  • Building Skills in Python: A Programmer's Introduction to Python

    It will lead you from a very tiny, easy to understand subset of statements to the entire Python language and all of the built-in data structures.

  • Fundamentals of Programming: With OOP, Python Edition

    This book presents a balanced and flexible approach to the incorporation of object-oriented principles in introductory courses using Python.

  • Artificial Intelligence with Python (Prateek Joshi)

    This book is for Python developers who want to build real-world Artificial Intelligence applications. It is friendly to Python beginners, will also be useful for experienced Python programmers who are looking to use AI techniques in their existing technology stacks.

  • Building Skills in Object-Oriented Design (in Java and Python)

    Helps you build OO design skills through the creation of a moderately complex family of application programs. This is a step-by-step guide to OO design and implementation.

  • The Definitive Guide to Pylons (James Gardner)

    A comprehensive introduction to Pylons, the web framework that uses the best of Ruby, Python, and Perl and the emerging WSGI standard to provide structure and flexibility.

  • Data Structures and Algorithms with OPP Design Patterns in Python

    It promotes object-oriented design using Python and illustrates the use of the latest object-oriented design patterns. Virtually all the data structures are discussed in the context of a single class hierarchy.

  • Start Here: Python Programming for Beginners (Jody S. Ginther)

    This is a book for the total beginner who is interested in programming. It teaches the new programmer from ground zero through hands-on exercises.

  • Python Deep Learning (Valentino Zocca, et al)

    Take your machine learning skills to the next level by mastering Deep Learning concepts and algorithms using Python. This book will give you all the practical information available on the subject, including the best practices, using real-world use cases.

  • Python Programming

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