Cython is a very powerful combination of Python and C. Using Cython, you can write Python code that calls back and forth from and to C or C++ code natively at any point. It is a language with extra syntax allowing for optional static type declarations. It is also a very popular language as it can be used for multicore programming.Learning Cython Programming will provide you with a detailed guide to extending your native applications in pure Python; imagine embedding a twisted web server into your native application with pure Python code. You will also learn how to get your new applications up and running by reusing Python's extensive libraries such as Logging and Config Parser to name a few.With Learning Cython Programming, you will learn that writing your own Python module in C from scratch is not only hard, but is also unsafe. Cython will automatically handle all type-conversion issues as well as garbage collection on your code. You can also still write all your code in Python but have it compiled and called directly in C as if it was just another function or data.This book also demonstrates how you can take the open source project Tmux and extend it to add new commands directly in pure Python. With this book, you will learn everything you need to know to get up and running with Cython and how you can reuse examples in a practical way.

Build software that combines Python’s expressivity with the performance and control of C (and C++). It’s possible with Cython, the compiler and hybrid programming language used by foundational packages such as NumPy, and prominent in projects including Pandas, h5py, and scikits-learn. In this practical guide, you’ll learn how to use Cython to improve Python’s performance—up to 3000x— and to wrap C and C++ libraries in Python with ease. Author Kurt Smith takes you through Cython’s capabilities, with sample code and in-depth practice exercises. If you’re just starting with Cython, or want to go deeper, you’ll learn how this language is an essential part of any performance-oriented Python programmer’s arsenal. Use Cython’s static typing to speed up Python code Gain hands-on experience using Cython features to boost your numeric-heavy Python Create new types with Cython—and see how fast object-oriented programming in Python can be Effectively organize Cython code into separate modules and packages without sacrificing performance Use Cython to give Pythonic interfaces to C and C++ libraries Optimize code with Cython’s runtime and compile-time profiling tools Use Cython’s prange function to parallelize loops transparently with OpenMP

Learn the fundamentals of Cython to extend the legacy of your applications About This Book Learn how to extend C applications with pure Python code Get more from Python – you'll not only learn Cython, you'll also unlock a greater understanding of how to harness Python Packed with tips and tricks that make Cython look easy, dive into this accessible programming guide and find out what happens when you bring C and Python together! Who This Book Is For This book is for developers who are familiar with the basics of C and Python programming and wish to learn Cython programming to extend their applications. What You Will Learn Reuse Python logging in C Make an IRC bot out of your C application Extend an application so you have a web server for rest calls Practice Cython against your C++ code Discover tricks to work with Python ConfigParser in C Create Python bindings for native libraries Find out about threading and concurrency related to GIL Expand Terminal Multiplexer Tmux with Cython In Detail Cython is a hybrid programming language used to write C extensions for Python language. Combining the practicality of Python and speed and ease of the C language it's an exciting language worth learning if you want to build fast applications with ease. This new edition of Learning Cython Programming shows you how to get started, taking you through the fundamentals so you can begin to experience its unique powers. You'll find out how to get set up, before exploring the relationship between Python and Cython. You'll also look at debugging Cython, before moving on to C++ constructs, Caveat on C++ usage, Python threading and GIL in Cython. Finally, you'll learn object initialization and compile time, and gain a deeper insight into Python 3, which will help you not only become a confident Cython developer, but a much more fluent Python developer too. Style and approach This practical and a fast-paced guide gives you all the information you need to start programming using Cython.

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Your Python code may run correctly, but you need it to run faster. Updated for Python 3, this expanded edition shows you how to locate performance bottlenecks and significantly speed up your code in high-data-volume programs. By exploring the fundamental theory behind design choices, High Performance Python helps you gain a deeper understanding of Python’s implementation. How do you take advantage of multicore architectures or clusters? Or build a system that scales up and down without losing reliability? Experienced Python programmers will learn concrete solutions to many issues, along with war stories from companies that use high-performance Python for social media analytics, productionized machine learning, and more. Get a better grasp of NumPy, Cython, and profilers Learn how Python abstracts the underlying computer architecture Use profiling to find bottlenecks in CPU time and memory usage Write efficient programs by choosing appropriate data structures Speed up matrix and vector computations Use tools to compile Python down to machine code Manage multiple I/O and computational operations concurrently Convert multiprocessing code to run on local or remote clusters Deploy code faster using tools like Docker

The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science. From the reviews: Langtangen ... does an excellent job of introducing programming as a set of skills in problem solving. He guides the reader into thinking properly about producing program logic and data structures for modeling real-world problems using objects and functions and embracing the object-oriented paradigm. ... Summing Up: Highly recommended. F. H. Wild III, Choice, Vol. 47 (8), April 2010 Those of us who have learned scientific programming in Python ‘on the streets’ could be a little jealous of students who have the opportunity to take a course out of Langtangen’s Primer.” John D. Cook, The Mathematical Association of America, September 2011 This book goes through Python in particular, and programming in general, via tasks that scientists will likely perform. It contains valuable information for students new to scientific computing and would be the perfect bridge between an introduction to programming and an advanced course on numerical methods or computational science. Alex Small, IEEE, CiSE Vol. 14 (2), March /April 2012 “This fourth edition is a wonderful, inclusive textbook that covers pretty much everything one needs to know to go from zero to fairly sophisticated scientific programming in Python...” Joan Horvath, Computing Reviews, March 2015

Become an ace Python programmer by learning best coding practices and advance-level concepts with Python 3.5 About This Book Based on the latest stable version of Python (version 3.5) Creating well manageable code that will run in various environments with different sets of dependencies Packed with advanced concepts and best practices to write efficient Python code Who This Book Is For The book would appeal to web developers and Python programmers who want to start using version 3.5 and write code efficiently. Basic knowledge of Python programming is expected. What You Will Learn Conventions and best practices that are widely adopted in the python community Package python code effectively for community and production use Easy and lightweight ways to automate code deployment on remote systems Improve your code's quality, reliability, and performance Write concurrent code in python Extend python with code written in different languages In Detail Python is a dynamic programming language, used in a wide range of domains by programmers who find it simple, yet powerful. Even if you find writing Python code easy, writing code that is efficient and easy to maintain and reuse is a challenge. The focus of the book is to familiarize you with common conventions, best practices, useful tools and standards used by python professionals on a daily basis when working with code. You will begin with knowing new features in Python 3.5 and quick tricks for improving productivity. Next, you will learn advanced and useful python syntax elements brought to this new version. Using advanced object-oriented concepts and mechanisms available in python, you will learn different approaches to implement metaprogramming. You will learn to choose good names, write packages, and create standalone executables easily. You will also be using some powerful tools such as buildout and vitualenv to release and deploy the code on remote servers for production use. Moving on, you will learn to effectively create Python extensions with C, C++, cython, and pyrex. The important factors while writing code such as code management tools, writing clear documentation, and test-driven development are also covered. You will now dive deeper to make your code efficient with general rules of optimization, strategies for finding bottlenecks, and selected tools for application optimization. By the end of the book, you will be an expert in writing efficient and maintainable code. Style and approach An easy-to-follow guide that covers industry followed best practices in Python programming