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Hands-On Reactive Programming with Python

Hands-On Reactive Programming with Python

By : Picard
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Hands-On Reactive Programming with Python

Hands-On Reactive Programming with Python

By: 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)
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Available schedulers

The subscribe_on, observe_on, and factory operators take the scheduler object as a parameter. As its name implies, a scheduler is an object that is responsible for scheduling the emission of the items of an observable. Scheduling the emission means that, instead of calling the observer callbacks directly in the context of the observable, the emission of the items is transferred to another context. RxPY implement two kinds of scheduler: thread schedulers and event loop schedulers. However, the scheduler principle is very generic and it could be possible to implement much more specific schedulers, such as transferring execution to another IP of a chipset or even another device (even though these use cases should rather be implemented as drivers if the code is designed as functional and reactive).

Three schedulers are of interest when developing an AsyncIO application...

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