Hands-On Reactive Programming with Python

Event-driven development unraveled with RxPY

A comprehensive guide to help you understand the principles of Reactive and asynchronous programming and its benefits

Key Features

Explore the advantages of Reactive programming
Use concurrency and parallelism in RxPY to build powerful reactive applications
Deploy and scale your reactive applications using Docker

Book DescriptionReactive 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. Les mer
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Paperback
Legg i
Paperback
Legg i
Vår pris: 543,-

(Paperback) Fri frakt!
Leveringstid: Sendes innen 21 dager
På grunn av Brexit-tilpasninger og tiltak for å begrense covid-19 kan det dessverre oppstå forsinket levering.

Om boka

A comprehensive guide to help you understand the principles of Reactive and asynchronous programming and its benefits

Key Features

Explore the advantages of Reactive programming
Use concurrency and parallelism in RxPY to build powerful reactive applications
Deploy and scale your reactive applications using Docker

Book DescriptionReactive 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.

What you will learn

Structure Python code for better readability, testing, and performance
Explore the world of event-based programming
Grasp the use of the most common operators in Rx
Understand reactive extensions beyond simple examples
Master the art of writing reusable components
Deploy an application on a cloud platform with Docker and Traefik

Who this book is forIf you are a Python developer who wants to learn Reactive programming to build powerful concurrent and asynchronous applications, this book is for you. Basic understanding of the Python language is all you need to understand the concepts covered in this book.

Fakta

Innholdsfortegnelse

Table of Contents

An introduction to Reactive Programming
Asynchronous Programming in Python
Functional Reactive Programming
Exploring Observables and Observers
Concurrency and Paralellism in RxPY
Implementation of an Audio Transcoding Server
Using third-party services
Dynamic reconfiguration
Other operators in RxPY
Testing and Debugging
Deploying and Scaling your Application
Reactive Streams for Remote Communication
A checklist on best practices

Om forfatteren

Romain Picard is currently a data science engineer. He has been working in the digital TV and telecommunications industry for 20 years. His daily work consists of data manipulation, machine learning model training, and model deployment. Almost all of these tasks are based on Python code, and he uses reactive programming whenever it's applicable. He was previously a media software architect and a software developer. In these previous positions, he designed and developed TV and OTT players that have been used in tens of millions of set top boxes. Romain is especially interested in algorithms, looking for the most suitable algorithm for each use case.