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

Summary


In this chapter, we looked comprehensively at multiprocessing, and how it can be utilized within our systems. We followed the life of a process from its creation all the way through to its timely termination.

We looked at the various intricacies such as cross-process communication and synchronization, and we also looked at how your standard multiprocessing pools differ from the standard ProcessPoolExecutors that we explored in Chapter 7, Executors and Pools.

We then took a brief look at how we can implement things such as communication and synchronization between our various processes without incurring major performance penalties, or becoming the proud owners of systems plagued by race conditions.

In the next chapter, Event-driven programming, we'll be diving deep into the asyncio module, and understand how we can leverage this module in order to develop our own event-based Python programs.