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)

Mathematical operators

The operators listed here implement some basic mathematical operations, as well as being building blocks to implement any kind of computation on items.

The average operator

The average operator computes the average value of all items emitted on the source observable. The following figure shows the marble diagram of this operator:

Figure 9.35: The average operator

Its prototype is the following:

Observable.average(self, key_selector=None)

Here, the key_selector argument is a transform function that returns the value to average from an item. If no key_selector is provided, then the item itself is used.

Here is an example of the average operator:

numbers = Observable.from_([1, 2, 3, 4])

numbers1.average...