Reactive Programming — Explained with Examples

Reactive programming is a declarative programming paradigm focused on working with asynchronous data streams and the automatic propagation of change. Instead of writing imperative code that pulls values on demand (e.g., myVar = getValue()), you define relationships between streams — when a source stream emits a new value, all dependent streams automatically update.

Reactive programming is popularized by libraries like RxJS (JavaScript), Project Reactor (Java), and ReactiveX (multiple languages). It combines the observer pattern, the iterator pattern, and functional programming. Key abstractions are Observable (a stream of data over time), Observer (consumer of the stream), and operators (transformations like map, filter, debounce, merge).

Real-world analogy. Reactive programming is like a spreadsheet. If cell A1 contains =B1 + C1, and you change B1, A1 recalculates automatically. You never manually update A1 — the relationship is declared once, and the system propagates changes.

Example (RxJS — autocomplete search):

fromEvent(input, 'keyup')
  .pipe(
    debounceTime(300),
    map(e => e.target.value),
    filter(text => text.length >= 3),
    distinctUntilChanged(),
    switchMap(search => ajax(`/api/search?q=${search}`))
  )
  .subscribe(results => render(results));

Related terms: Functional Programming, Event-Driven Programming, Observability, Declarative vs Imperative, OOP

Related tutorial: Reactive Programming Guide