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)

Summary

This chapter set out to demonstrate that observables can be shared between services and applications, and do not have to be restricted inside an application.

Almost all communication protocols rely on three base patterns: publish/subscribe, channel, and request/response. Since all these protocols can be implemented on top of push-based communication, it means that observables can be used to implement all these protocols.

The three layers of the multiplexing stack are mandatory steps, each one serving a specific purpose. None can be omitted without breaking the functioning of a remote communication. These three layers are steps that must be taken when receiving and sending some messages.

The publish/subscribe implementation was relatively simple, thanks once again to AsyncIO and RxPY. This implementation requires additional features to be usable in production: more error...