Book Image

Learning Concurrency in Python

By : Elliot Forbes
Book Image

Learning Concurrency in Python

By: Elliot Forbes

Overview of this book

Python is a very high level, general purpose language that is utilized heavily in fields such as data science and research, as well as being one of the top choices for general purpose programming for programmers around the world. It features a wide number of powerful, high and low-level libraries and frameworks that complement its delightful syntax and enable Python programmers to create. This book introduces some of the most popular libraries and frameworks and goes in-depth into how you can leverage these libraries for your own high-concurrent, highly-performant Python programs. We'll cover the fundamental concepts of concurrency needed to be able to write your own concurrent and parallel software systems in Python. The book will guide you down the path to mastering Python concurrency, giving you all the necessary hardware and theoretical knowledge. We'll cover concepts such as debugging and exception handling as well as some of the most popular libraries and frameworks that allow you to create event-driven and reactive systems. By the end of the book, you'll have learned the techniques to write incredibly efficient concurrent systems that follow best practices.
Table of Contents (20 chapters)
Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
Index

Shared resources and data races


One of the major things we need to guard against when implementing concurrency in your applications is race conditions. These race conditions can cripple our applications, and cause bugs that are hard to debug and even harder to fix. In order to prevent these issues, we need to both understand how these race conditions occur and how we can guard against them using the synchronization primitives we'll be covering in this chapter.

Understanding synchronization and the basic primitives that are available to you is vital if you are to create thread-safe, high-performance programs in Python. Thankfully, we have numerous different synchronization primitives available to us in the threading Python module that can help us in a number of different concurrent situations.

In this section, I'll be giving you a brief overview of all of the synchronization primitives available to you as well as a few simple examples of how you can use these within your programs. By the end...