6. Supporting Python 3 by Lennart Regebro
Supporting Python 3 is an expertly written in-depth book which guides the reader through the process of adding Python 3 support, from choosing a strategy to solving distribution issues.
The process of switching to Python 3 is most often called “porting”. The first two editions of this book were also called “Porting to Python 3”. However, this gave the false impression that this was a lot of work, and that Python 3 was “a different language” than Python 2. Although moving to Python 3 can be hard work, for the most time it is not, and as Python 2.5 and Python 3.2 are rapidly falling out of use, it gets even easier.
If you want to ‘port’ Python 2 code to Python 3, read this book.
The author has been using Python since 2008.
This book is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.
7. Building Skills in Python by Steven F. Lott
Building Skills in Python is a 42 chapter book which helps build Python programming skills through a series of exercises. It includes useful projects from straightforward to sophisticated that will help solidify your Python skills.
This book is a close-to-complete presentation of the Python language, updated to cover Python 2.6 and some elements of Python 3.1. It’s oriented toward learning, which involves accumulating many closely intertwined concepts. This book is primarily targeted at professional programmers.
The first three parts are organized in a way that builds up the language in layers from central concepts to more advanced features. Programming exercises are provided to encourage further exploration of each layer. The last two parts cover the extension modules and provide specifications for some complex exercises that will help solidify programming skills.
The book explores a wide range of topics including:
- Numeric Expressions and Output.
- Advanced Expressions.
- Variables, Assignment and Input.
- Truth, Comparison and Conditional Processing.
- Loops and Iterative Processing.
This book is made available under a Creative Commons Attribution-Noncommercial-No Derivative Works License.
8. Think Complexity by Allen B. Downey
Think Complexity is about data structures and algorithms, intermediate programming in Python, computational modeling and the philosophy of science.
After reading the material, you’ll use graphs, cellular automata, and agent-based models to study topics in physics, biology, and economics.
Whether you’re an intermediate-level Python programmer or a student of computational modeling, you’ll delve into examples of complex systems through a series of worked examples, exercises, case studies, and easy-to-understand explanations.
Topics covered include:
- Graphs including random and connected graphs.
- Analysis of algorithms – the branch of computer science that considers the performance of algorithms.
- Small world graphs.
- Scale-free networks: Zipf’s law, cumulative, continuous and Pareto distributions.
- Cellular automata.
- Game of Life.
- Self-organized criticality.
- Case studies.
Permission is granted to copy, distribute, transmit and adapt this work under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
9. Programming Computer Vision with Python by Jan Erik Solem
Programming Computer Vision with Python gives a hands-on introduction to the underlying theory and algorithms of computer vision (images, videos, etc).
It seeks to explain computer vision in simple terms, without becoming too embroiled in theory. You learn techniques for object recognition, 3D reconstruction, stereo imaging, augmented reality, and other computer vision applications as you follow clear examples written in Python.
There are complete code samples with accompanying explanations.
The Python language comes with many powerful modules for handling images, mathematical computing and data mining.
Topics covered include:
- Learn techniques used in robot navigation, medical image analysis, and other computer vision applications.
- Work with image mappings and transforms, such as texture warping and panorama creation.
- Compute 3D reconstructions from several images of the same scene.
- Organize images based on similarity or content, using clustering methods.
- Build efficient image retrieval techniques to search for images based on visual content.
- Use algorithms to classify image content and recognize objects.
- Access the popular OpenCV library through a Python interface.
The final draft of the book is released under a Creative Commons license.
10. Annotated Algorithms in Python by Massimo Di Pierro
Annotated Algorithms in Python with Applications in Physics, Biology, and Finance is compiled from lectures given by the author over a period of 10 years at the School of Computing of DePaul University.
The lectures cover multiple classes, including Analysis and Design of Algorithms, Scientific Computing, Monte Carlo Simulations, and Parallel Algorithms. These lectures teach the core knowledge required by any scientist interested in numerical algorithms and by students interested in computational finance.
The book is published under the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.
Pages in this article:
Page 1 – Think Python and more books
Page 2 – Supporting Python 3 and more books
Page 3 – Invent Your Own Computer Games with Python and more books
Page 4 – Making Games with Python & Pygame and more books
Page 5 – Hacking Secret Ciphers with Python and more books
Page 6 – How to Make Mistakes in Python and more books
Page 7 – Text Processing in Python and more books
Page 8 – The Coder’s Apprentice and more books
Page 9 – Building Skills in Object-Oriented Design and more books
All books in this series:
|Free Programming Books|
|Java||General-purpose, concurrent, class-based, object-oriented, high-level language|
|C||General-purpose, procedural, portable, high-level language|
|Python||General-purpose, structured, powerful language|
|C++||General-purpose, portable, free-form, multi-paradigm language|
|C#||Combines the power and flexibility of C++ with the simplicity of Visual Basic|
|PHP||PHP has been at the helm of the web for many years|
|HTML||HyperText Markup Language|
|SQL||Access and manipulate data held in a relational database management system|
|Ruby||General purpose, scripting, structured, flexible, fully object-oriented language|
|Assembly||As close to writing machine code without writing in pure hexadecimal|
|Swift||Powerful and intuitive general-purpose programming language|
|Groovy||Powerful, optionally typed and dynamic language|
|Go||Compiled, statically typed programming language|
|Pascal||Imperative and procedural language designed in the late 1960s|
|Perl||High-level, general-purpose, interpreted, scripting, dynamic language|
|R||De facto standard among statisticians and data analysts|
|COBOL||Common Business-Oriented Language|
|Scala||Modern, object-functional, multi-paradigm, Java-based language|
|Fortran||The first high-level language, using the first compiler|
|Scratch||Visual programming language designed for 8-16 year-old children|
|Lua||Designed as an embeddable scripting language|
|Logo||Dialect of Lisp that features interactivity, modularity, extensibility|
|Rust||Ideal for systems, embedded, and other performance critical code|
|Lisp||Unique features - excellent to study programming constructs|
|Ada||ALGOL-like programming language, extended from Pascal and other languages|
|Haskell||Standardized, general-purpose, polymorphically, statically typed language|
|Scheme||A general-purpose, functional language descended from Lisp and Algol|
|Prolog||A general purpose, declarative, logic programming language|
|Forth||Imperative stack-based programming language|
|Clojure||Dialect of the Lisp programming language|
|Julia||High-level, high-performance language for technical computing|
|Awk||Versatile language designed for pattern scanning and processing language|
|BASIC||Beginner’s All-purpose Symbolic Instruction Code|
|Erlang||General-purpose, concurrent, declarative, functional language|
|VimL||Powerful scripting language of the Vim editor|
|OCaml||The main implementation of the Caml language|
|ECMAScript||Best known as the language embedded in web browsers|
|Bash||Shell and command language; popular both as a shell and a scripting language|
|LaTeX||Professional document preparation system and document markup language|
|TeX||Markup and programming language - create professional quality typeset text|
|Arduino||Inexpensive, flexible, open source microcontroller platform|
|Elixir||Relatively new functional language running on the Erlang virtual machine|
|F#||Uses functional, imperative, and object-oriented programming methods|
|Tcl||Dynamic language based on concepts of Lisp, C, and Unix shells|
|Factor||Dynamic stack-based programming language|
|Eiffel||Object-oriented language designed by Bertrand Meyer|
|Agda||Dependently typed functional language based on intuitionistic Type Theory|
|Icon||Wide variety of features for processing and presenting symbolic data|
|XML||Rules for defining semantic tags describing structure ad meaning|
|Vala||Object-oriented language, syntactically similar to C#|
|Standard ML||General-purpose functional language characterized as "Lisp with types"|
|D||General-purpose systems programming language with a C-like syntax|
|Dart||Client-optimized language for fast apps on multiple platforms|
|Markdown||Plain text formatting syntax designed to be easy-to-read and easy-to-write|
|Kotlin||More modern version of Java|
|Objective-C||Object-oriented language that adds Smalltalk-style messaging to C|
|VHDL||Hardware description language used in electronic design automation|
|J||Array programming language based primarily on APL|
|LabVIEW||Designed to enable domain experts to build power systems quickly|