50 Free eBooks On Python!

Forget 5, 10, 20, EFYTimes brings to you 50 ebooks to learn and understand Python programming. Python is one of the most popular languages today amongst programmers. This is especially because Python is free to use, even for commercial products, thanks to its OSI-approved open source license. So when the language is open sources it will be highly unjustified to share paid books for Python. So here we bring to you 50 Free ebooks to help you understand, interpret and work with Python more smoothly and efficiently. This is absolutely in the spirit of open source! 1. Python Cookbook by David Beazley, Brian K. Jones - O'Reilly Media, 2013 This cookbook is for experienced Python programmers who want to focus on modern tools and idioms. You'll find complete recipes for more than a dozen topics, covering the core Python language as well as tasks common to a wide variety of applications. 2. Python for Education by Ajith Kumar - Inter University Accelerator Centre, 2010 Primary objective of this book is to explore the possibilities of using Python language as a tool for learning mathematics and science. The reader is not assumed to be familiar with computer programming. Ability to think logically is enough. 3. Hacking Secret Ciphers with Python by Al Sweigart, 2013 The book teaches complete beginners how to program in the Python programming language. The book features the source code to several ciphers and hacking programs for these ciphers. The programs include the Caesar cipher, transposition cipher, etc. 4. Effective Django by Nathan Yergler - PyCon, 2013 Effective Django development means building applications that are testable, maintainable, and scalable. After reading this book you should have an understanding of how Django's pieces fit together and how to use them to engineer web applications. 5. The Python Game Book by Horst Jens et al. - thepythongamebook.com, 2012 The Python Game Book written by Horst Jens and friends aims to provide interested students and teachers a broad range of material to teach themselves how to write computer games using the language Python and other free Open Source tools. 6. Test-Driven Development with Python by Harry Percival - O'Reilly Media, 2013 Test-Driven Development with Python focuses on web development, with some coverage of JavaScript. This book uses a concrete example -- the development of a website, from scratch -- to teach the TDD methodology and how it applies to web programming. 7. PyQt4 Tutorial by Jan Bodnar - ZetCode, 2013 PyQt4 is a toolkit for creating GUI applications. It is a blending of Python language and the successful Qt library. This tutorial is suited for beginners and intermediate programmers. You will learn to program non trivial PyQt4 applications. 8. Python Programming by Hannes Röst, et al. - Wikibooks, 2013 This book describes Python, an open-source general-purpose interpreted programming language, available for all Platforms. Python is a high-level, structured programming language that can be used for a wide variety of programming tasks. 9. Python Scientific Lecture Notes by EuroScipy tutorial team, 2012 Teaching material on the scientific Python ecosystem, a quick introduction to central tools and techniques. The different chapters each correspond to a 1 to 2 hours course with increasing level of expertise, from beginner to expert. 10. The Art and Craft of Programming: Python Edition by John C. Lusth - The University of Alabama, 2012 Contents: Starting Out; Literals; Combining Literals; Precedence and Associativity; Variables; Assignment; Conditionals; Functions; Python Programs and Using Files; Input and Output; More about Functions; Scope; Loops; Lists; Recursion; etc. 11. Porting to Python 3: An in-depth guide by Lennart Regebro, 2011 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. Using plenty of code examples is takes you cross the hurdles and shows you the new Python features. 12. Introduction to Python for Econometrics, Statistics and Numerical Analysis by Kevin Sheppard, 2012 Python is a widely used general purpose programming language, which happens to be well suited to Econometrics and other more general purpose data analysis tasks. These notes provide an introduction to Python for a beginning programmer. 13. Python Scripting for Computational Science by Hans Petter Langtangen - Springer, 2009 With a primary focus on examples and applications of relevance to computational scientists, this useful book shows computational scientists how to develop tailored, flexible, and human-efficient working environments built from small scripts. 14. The Programming Historian by W.J. Turkel, A. Crymble, A. MacEachern - NiCHE, 2010 This book is a tutorial-style introduction to programming in Python for practicing historians (and other humanists). We assume that you're starting out with no prior programming experience and only a basic understanding of computers. 15. Programming Computer Vision with Python by Jan Erik Solem - O'Reilly Media, 2012 The idea behind this book is to give 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 and enthusiasts. 16. An Introduction to Python by John C. Lusth - The University of Alabama, 2012 Contents: Starting Out; Literals; Combining Literals; Precedence and Associativity; Variables; Assignment; Conditionals; Functions; Python Programs and Using Files; Input and Output; Scope; Loops; Recursion; Arrays; Sorting; Footnotes; etc. 17. Design Patterns In Python by Rahul Verma, Chetan Giridhar - Testing Perspective, 2011 This book is about learning design patterns with Python language. If you are new to design patterns, this text provides the first building blocks. If you are interested in design of test automation frameworks, this book will be very useful. 18. Making Games with Python and Pygame by Al Sweigart, 2012 This is a programming book that covers the Pygame game library for the Python programming language. Each chapter gives you the complete source code for a new game and teaches the important programming concepts from these examples. 19. Learning to Program with Python by Richard L. Halterman - Southern Adventist University, 2011 The focus is on introducing programming techniques and developing good habits. Our approach avoids some more esoteric features of Python and concentrates on the programming basics that transfer directly to other imperative programming languages. 20. How to Think Like a Computer Scientist: Learning with Python by Jeffrey Elkner, Allen B. Downey, Chris Meyers - Green Tea Press, 2012 This book is an introduction to computer science using the Python programming language. It covers the basics of programming, including variables, functions, control flow, program debugging. Later chapters cover basic algorithms and data structures. 21. Natural Language Processing with Python by Steven Bird, Ewan Klein, Edward Loper - O'Reilly Media, 2009 This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies. With it, you'll learn how to write Python programs that work with large collections of unstructured text. 22. Learn Python The Hard Way by Zed A. Shaw, 2011 This is a very beginner book for people who want to learn to code. If you can already code then the book will probably drive you insane. It's intended for people who have no coding chops to build up their skills before starting a more detailed book. 23. Think Stats: Probability and Statistics for Programmers by Allen B. Downey - Green Tea Press, 2011 Think Stats is an introduction to Probability and Statistics for Python programmers. This new book emphasizes simple techniques you can use to explore real data sets and answer interesting statistical questions. Basic skills in Python are assumed. 24. Python for Informatics: Exploring Information by Charles Severance - PythonLearn, 2010 The goal of this book is to provide 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. 25. Start Here: Python Programming for Beginners by Jody Scott Ginther - toonzcat.com, 2010 This book is meant to help you begin learning the basics of Python programming version 3 or later. It is a brief introduction to Python. The author attempts to be as brief as possible to get the new programmer into programming as fast as possible. 26. Practical Programming in Python by Jeffrey Elkner, at al., 2010 The goal of this book is twofold: to teach you how to program in Python; and to teach you to think like a computer scientist. This way of thinking combines some of the best features of mathematics, engineering, and natural science. 27. Introduction to Media Computation: A Multimedia Cookbook in Python by Mark Guzdial - Georgia Institute of Technology, 2002 Guzdial introduces programming as a way of creating and manipulating media -- a context familiar to today's readers. Starts readers with actual programming early on. Puts programming in a relevant context (Computing for Communications). 28. Snake Wrangling for Kids by Jason R Briggs - Lulu.com, 2007 Snake Wrangling for Kids is a printable electronic book, for children 8 years and older, who would like to learn computer programming. It covers the very basics of programming, and uses the Python 3 programming language to teach the concepts. 29. The Definitive Guide to Django by A. Holovaty, J. Kaplan-Moss - Apress, 2007 Django is the Python–based equivalent to the Ruby on Rails web development framework. The authors show you how they use this framework to create award–winning web sites. This is the first edition of the Django Book which covers 0.96 version. 30. Python course in Bioinformatics by Katja Schuerer, Catherine Letondal - Pasteur Institute, 2008 This course is designed for biologists who already have some programming knowledge in other languages. The focus is on biological examples that are used throughout the course, as well as the suggested exercises drawn from the field of biology. 31. Python 201: (Slightly) Advanced Python Topics by Dave Kuhlman, 2003 This document 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. 32. Python 101: Introduction to Python by Dave Kuhlman, 2008 This document is a syllabus for a first course in Python programming. It contains an introduction to the Python language, instruction in the important features of the language, and practical exercises in the use of those features. 33. Python for Fun by Chris Meyers, 2004 This collection is a presentation of several small Python programs. They are aimed at intermediate programmers - people who have studied Python and are fairly comfortable with basic recursion and object oriented techniques. 34. The Python Imaging Library by Fredrik Lundh, Matthew Ellis - PythonWare, 2002 The Python Imaging Library adds image processing capabilities to your Python interpreter. This library provides extensive file format support, an efficient internal representation, and fairly powerful image processing capabilities. 35. Python Tutorial by Guido van Rossum - Python Software Foundation, 2008 This tutorial introduces the reader informally to the basic concepts of the Python language and system. It introduces many of Python's most noteworthy features, and will give you a good idea of the language's flavor and style. 36. Python 2.5 Quick Reference by Richard Gruet, 2007 This reference covers invocation options, environment variables, lexical entities, basic types and their operations, advanced types, statements, iterators, generators, descriptors, decorators, built-in functions, built-in exceptions, and more. 37. How To Write Your Own Software Using Python by Steven F. Lott, 2008 The book will help you build basic programming skills. It is organized in a way that builds up the language in layers from simple concepts to more advanced features. Programming exercises are provided to encourage further exploration of each layer. 38. The Python Language Reference Manual by Guido Van Rossum - Network Theory Ltd., 2003 The definitive language reference for Python. It describes the syntax of Python and its built-in datatypes. It covers advanced topics, and is suitable for readers who are familiar with the details and rules of the Python and its object system. 39. Data Structures and Algorithms with Object-Oriented Design Patterns in Python by Bruno R. Preiss, 2004 The primary goal of this book is to promote object-oriented design using Python and to illustrate the use of the emerging object-oriented design patterns. The book shows how these patterns are used to create good software designs. 40. Think Python: An Introduction to Software Design by Allen Downey - Green Tea Press, 2008 A concise introduction to software design using Python. Intended for people with no programming experience, this book starts with the most basic concepts and gradually adds new material. The goal is to teach you to think like a computer scientist. 41. Learn to Program Using Python by Alan Gauld - Addison-Wesley Professional, 2000 Book for hobbyists, self-starters, and all who want to learn the art of computer programming in Python. Data types and variables, debugging, and namespaces are covered. Also includes sample applications that illustrate ideas and techniques in action. 42. Introduction to Programming using Python by K. Schuerer, et al. - Pasteur Institute, 2008 This text teaches programming concepts to biologists. It is aimed at people who are not professional computer scientists, but who need a better control of computers for their own research. This course is part of a course in informatics for biology. 43. Text Processing in Python by David Mertz - Addison-Wesley Professional, 2003 A hands-on tutorial that teaches how to accomplish numerous text processing tasks using Python. Filled with examples, the book provides efficient solutions to specific text processing problems and strategies for all text processing challenges. 44. A Byte of Python (for Python 3.0) by Swaroop C H, 2008 This is a tutorial and a guide on Python programming for absolute beginners. If all you know about computers is how to save text files, then this is the book for you. The book is updated for the upcoming Python 3.0 language. 45. Non-Programmers Tutorial For Python by Josh Cogliati - Wikibooks, 2005 This free tutorial is designed to be an introduction to the Python programming language. The guide is for someone with no programming experience. The author attempts to teach programming by reading code and writing code. 46. Building Skills in Python by Steven F. Lott, 2008 This book is a complete presentation of the Python for professional programmers who need to learn the language. The author leads you from a tiny, easy to understand subset of statements to the entire Python language and all built-in data structures. 47. Python Standard Library by Fredrik Lundh - O'Reilly, 2001 A large collection of useful Python scripts, the best parts of comp.lang.python newsgroup messages, plus hundreds of new scripts. The text covers the standard library, the examples should work on most platforms and Python versions. 48. GUI Programming with Python: QT Edition by Boudewijn Rempt - OpenDocs, LLC, 2002 This book covers application development using the library extension PyQt, which forms the basis for GUI programming. First part explains concepts using small examples, in the second part the author develops a complete, complex application. 49. Dive Into Python by Mark Pilgrim - Apress, 2004 This is a book for experienced programmers, a hands-on guide to the Python language. Each chapter starts with a complete code sample, picks it apart and explains the pieces, and then puts it all back together in a summary at the end. 50. An Introduction to Python by Guido van Rossum - Network Theory Ltd., 2006 This book is an introduction to Python, an easy to learn, powerful programming language. The tutorial explains the basics of the Python, it does not cover every single feature of the language, but introduces the most noteworthy features. Like Us on facebook Shivam Kotwalia, CodeKill