What is (functional) reactive programming?

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Functional Reactive Programming (FRP) is a programming paradigm that combines the principles of functional programming and reactive programming to manage and propagate changes in data and user interfaces in a more declarative and reactive way. FRP provides a way to express the dynamic behavior of a system as a stream of events and transformations on those events.

Key concepts in FRP include:

  1. Streams and Observables: Streams or observables are sequences of values over time. They can represent user input, data changes, or any other kind of events. FRP libraries provide abstractions for working with these streams.

  2. Transformation and Composition: FRP allows you to apply various transformations and composition operations on streams to create new streams. This makes it easy to model complex behaviors by composing simpler ones.

  3. Declarative Approach: FRP encourages a declarative approach to programming, where you specify what should happen in response to events rather than explicitly defining how it should happen.

  4. Reactivity: FRP systems automatically update and propagate changes in response to events or changes in the data. This makes it suitable for building real-time and interactive applications.

Here's a simple example of FRP in JavaScript using the RxJS library:

javascript
import { fromEvent } from 'rxjs';
import { map, filter } from 'rxjs/operators';

// Create an observable from a button click event
const button = document.getElementById('myButton');
const clickStream = fromEvent(button, 'click');

// Transform the click stream to get only even-click counts
const evenClickStream = clickStream.pipe(
  scan(count => count + 1, 0), // Accumulate click count
  filter(count => count % 2 === 0) // Filter even counts
);

// Subscribe to the evenClickStream to perform an action
evenClickStream.subscribe(count => {
  console.log(`Even click count: ${count}`);
});

In this example, we:

  1. Create an observable clickStream from the click events of an HTML button.
  2. Transform the clickStream using pipe to accumulate the click count and then filter for even counts.
  3. Subscribe to the evenClickStream and log the even click count.

With FRP and RxJS, we've created a declarative and reactive system for handling button clicks and processing them. As you click the button, the system automatically keeps track of even click counts and logs them. This is just a simple example, but FRP becomes especially powerful in complex applications with many asynchronous events and data flows, where it helps manage state and interactions in a more elegant and maintainable way.

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