Book Image

Expert Python Programming - Second Edition

By : Michał Jaworski
Book Image

Expert Python Programming - Second Edition

By: Michał Jaworski

Overview of this book

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.
Table of Contents (21 chapters)
Expert Python Programming Second Edition
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Preface
Index

Why you might want to use extensions


It's not easy to say when it is a reasonable decision to write extensions in C/C++. The general rule of thumb could be, never, unless you have no other choice. But this is a very subjective statement that leaves a lot of room for interpretation of what is not doable in Python. In fact, it is hard to find a thing that cannot be done using pure Python code, but there are some problems where extensions may be especially useful:

  • Bypassing GIL (Global Interpreter Lock) in the Python threading model

  • Improving performance in critical code sections

  • Integrating third-party dynamic libraries

  • Integrating source code written in different languages

  • Creating custom datatypes

For example, the core language constraints such as GIL can easily be overcome with a different approach to concurrency, such as green threads or multiprocessing instead of a threading model.

Improving performance in critical code sections

Let's be honest. Python is not chosen by developers because of performance...