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 was the conclusion of our journey from an initial echo example up to a realistic application being deployed on a cloud environment, which was scalable and secured with TLS.

Reverse proxies are some of the basic tools needed to deploy applications, especially when they are composed of several services. Reverse proxies that operate on layer 7 also often implement load balancing features. Load balancing allows us to distribute the load between several instances of a service. Some of these tools, such as Traefik, leverage the Docker ecosystem to make their configuration very easy and dynamic.

Docker Compose allows us to manage containers much more easily than directly using Docker. Using it simplifies the deployment of applications that use multiple containers. Moreover, it allows us to easily scale a container up or down by starting or stopping some instances...