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Hands-On Reactive Programming with Python

More Information
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
About

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.

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
Page Count 420
Course Length 12 hours 36 minutes
ISBN9781789138726
Date Of Publication 23 Oct 2018

Authors

Romain Picard

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.