Book Image

Hands-On Reactive Programming with Python

By : Romain Picard
Book Image

Hands-On Reactive Programming with Python

By: Romain Picard

Overview of this book

Reactive programming is central to many concurrent systems, but it’s famous for its steep learning curve, which makes most developers feel like they're hitting a wall. With this book, you will get to grips with reactive programming by steadily exploring various concepts This hands-on guide gets you started with Reactive Programming (RP) in Python. You will learn abouta the principles and benefits of using RP, which can be leveraged to build powerful concurrent applications. As you progress through the chapters, you will be introduced to the paradigm of Functional and Reactive Programming (FaRP), observables and observers, and concurrency and parallelism. The book will then take you through the implementation of an audio transcoding server and introduce you to a library that helps in the writing of FaRP code. You will understand how to use third-party services and dynamically reconfigure an application. By the end of the book, you will also have learned how to deploy and scale your applications with Docker and Traefik and explore the significant potential behind the reactive streams concept, and you'll have got to grips with a comprehensive set of best practices.
Table of Contents (16 chapters)

What is asynchronous programming?

Chapter 1, An Introduction to Reactive Programming, discussed in detail the principles of event-driven programming and reactive programming. As explained in the previous chapter, event-driven programming can be implemented in many ways: with different programming paradigms such as imperative or object-oriented, but also with different concurrency mechanisms. Asynchronous programming is one way to manage concurrency.

Concurrency is several tasks competing for the same resource at the same time. The definition of "at the same time" can be different depending on the resource being used. There are two main resources that a task may require: a Central Processing Unit (CPU) and I/O. In most cases, a task is either CPU bound or I/O bound; that is, either a task makes a lot of computations and is constrained by the available CPU resources,...