This is the code repository for Reactive Programming in Python [Video], published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.
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
- 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
To fully benefit from the coverage included in this course, you will need:
This video course is for Python developers who would like to build fault-tolerant, scalable, and distributed systems. No knowledge of Reactive programming is required.
This course has the following software requirements:
RxPy Reactive Extension
Qt5
PyQt5
Tornado Web Framework