Reactive Programming in Python

Video description

Functional reactive data flows for GUIs and distributed network applications

About This Video

  • Explores Python’s inbuilt APIs to build reactive applications
  • Understand and use the concepts of reactive programming to build distributed systems running on multiple nodes
  • Master functional reactive programming and reactive microservices

In Detail

This video will be your guide to getting started with Reactive programming in Python. You will begin with the general concepts of Reactive programming and then gradually move on to work with asynchronous data streams.

You will then be introduced to functional reactive programming and will learn to apply FRP in practical use cases in Python. You will understand how ReactiveX works and how it efficiently supports sequences of data. You will then understand the role of asynchronous programming and event-based programming in detail to build reactive extensions.

You will learn to create dataflow-based systems, the building blocks of reactive programming. This course will take you through creating, merging, filtering, transforming, and error-handling observables to extend your asynchronous code.

You will then learn to scale applications using multi-node clusters and will learn to unit-test your clusters. This video also introduces you to Reactive microservices with Python.

All the code and supporting files for this course are available on GitHub at

Table of contents

  1. Chapter 1 : Installation and Setup
    1. The Course Overview 00:01:29
    2. Installing RxPy Reactive Extensions 00:02:24
    3. Installing Qt5 and PyQt5 00:02:43
    4. Installing the Tornado Web Framework 00:03:14
  2. Chapter 2 : Reactive Extensions for Python
    1. What Is Reactive Programming? 00:03:41
    2. Reactive Operators and Observables – From, Interval, and Buffer 00:21:59
    3. More Reactive Operators and Observables – Group By, Sample, and Max 00:08:55
    4. Loading CSV Data Reactively with RxPy 00:11:01
    5. Even More Reactive Operators – Map, FlatMap, Window, CombineLatest, and Zip 00:19:44
  3. Chapter 3 : Reactive GUIs and Data Flows with Qt and RxPy
    1. Hello World GUI with a Simple Reactive Button 00:05:41
    2. Displaying/Filtering Table Data from a Real-Time Source 00:08:56
    3. Real-Time Form Validation 00:12:59
  4. Chapter 4 : Reactive Web Servers/Clients with the Tornado Web Framework
    1. Async Real-Time Web Server 00:10:29
    2. Real-Time Async Client – Part 1 00:09:16
    3. Queues in Tornado 00:12:48
    4. Real-Time Async Client - Part 2 00:11:14
  5. Chapter 5 : Testing Reactive GUIs and a Cluster of Web Servers/Clients
    1. Unit Testing a Basic Reactive Data Flow 00:08:03
    2. Unit Testing a GUI Reactive Data Flow 00:05:54
    3. Unit Testing a Reactive Tornado Server 00:05:41
    4. Building and Testing a Web Server Cluster 00:13:53
  6. Chapter 6 : Build a Reactive Real-Time Stock Exchange
    1. Stock Exchange Web Server with WebSockets 00:05:17
    2. Stock Exchange GUI to Display Orders 00:11:52
    3. Connecting the Stock Exchange Reactive Client to the Server 00:05:29

Product information

  • Title: Reactive Programming in Python
  • Author(s): Rudolf Olah
  • Release date: October 2018
  • Publisher(s): Packt Publishing
  • ISBN: 9781786460332