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Reactive Programming in Python [Video]

More Information
  • Use reactive programming to build distributed systems running on multiple nodes
  • What is Reactive programming and when should you use it?
  • Handle UI interactions/events very easily
  • Handle errors with Reactive programming
  • Create a distributed application using Tornado that uses Reactive programming
  • Test a cluster of reactive, distributed web servers and clients to make sure your app can scale
  • Unit-test reactive programs whether they’re GUIs or web servers
  • Build a reactive real-time stock exchange with Python, Qt, Tornado, and RxPy

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 https://github.com/PacktPublishing/Reactive-Programming-in-Python.

Style and Approach

In this video, you'll learn how to build reactive applications in a step-by-step manner. You'll build applications that use reactive programming principles, the Qt GUI framework, and the Tornado web framework. you'll test these parts and then put them together to build a real-time stock exchange.

  • 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
Course Length 3 hours 22 minutes
Date Of Publication 7 Oct 2018
Reactive Operators and Observables – From, Interval, and Buffer
More Reactive Operators and Observables – Group By, Sample, and Max
Loading CSV Data Reactively with RxPy
Even More Reactive Operators – Map, FlatMap, Window, CombineLatest, and Zip
Real-Time Async Client – Part 1
Queues in Tornado
Real-Time Async Client - Part 2


Rudolf Olah

Rudolf Olah is a software development expert who has presented at PyCon Canada 2017 on Python as a Programming Philosophy (Jupyter Notebooks, Sphinx and Python), and the Toronto Node.js meetup in 2015 on Node.js as an API Shim. In between, he has presented on Freedombox on Raspberry Pi. He has trained developers in how to use Elm, TypeScript, and AngularJS. For Packt Publishing, he is the author of the Testing AngularJS video course, and keeps Angular developers up-to-date with the Learning AngularJS newsletter.

Rudolf blogs about free/open source software at SourceContribute.com and about Python, web development, and tech leadership at NeverFriday.com