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Why are you using an asynchronous IO framework on a reactive application? This is a question I am often asked when presenting a design I use a lot in RxPy based applications. This a very interesting question because the answer is not obvious: Asynchronous and Reactive programming are both event-driven programming tools. So at first, they look more like competitors than allies.

This article clarifies what each technology is exactly, and shows why they shine when being combined. I make some focus on Python AsyncIO and RxPY, but most of the following explanations apply to any programming language and framework.

Asynchronous IO Programming

Let’s start with asynchronous IO programming. For a long time, it has been neglected by programmers. Probably the main reason was that it was hard to use correctly due to callback-based code. This started to change with the support of futures, and then with the availability of the async/await syntax in several programming languages. Still, asynchronous IO programming with async/await is far from being natural for many programmers. So what problem does it solve that is worth the effort? …

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ReactiveX is a wonderful framework that allows to write event based code in a very elegant and readable way. Still, getting started in it can be challenging, and intimidating. In practice once you understand few key principles of ReactiveX, you can start writing reactive code easily.

The aim of this article is to explain these keys principles, and show how they apply though a simple example. By the way, the first half of this article is language agnostic. So feel free to read it even if you use another programming languages than Python.

Before reading on, be aware of one important thing: Reactive Programming is addictive ! Once you start thinking as a data flows instead of control flows, you trend to consider that it solves problems better than other programming approaches, and you use reactive programming more and more. …

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Reactive Programming is really great to write event driven applications, data driven applications, and asynchronous applications. However, it can be difficult to find a good way to structure the code. Fortunately for JavaScript developers, there is CycleJs. So I developed a similar framework for Python and RxPY: Cyclotron.

edit 2020/10: Updated examples to RxPY v3, and cyclotron drivers list.

Cyclotron is a functional and reactive framework. It allows structuring reactive code in a functional way. More specifically, functional means the following:

  • Pure code and side effects are clearly separated
  • All the code is implemented via functions (no class)

Moreover, it is specifically designed to write reactive…

About

Romain Picard

Data Scientist, former software architect, author, core developer of RxPY.

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