reactive-programming

name	reactive-programming
description	Implement reactive programming patterns using RxJS, streams, observables, and backpressure handling. Use when building event-driven UIs, handling async data streams, or managing complex data flows.

Reactive Programming

Table of Contents

• Overview
• When to Use
• Quick Start
• Reference Guides
• Best Practices

Overview

Build responsive applications using reactive streams and observables for handling asynchronous data flows.

When to Use

• Complex async data flows
• Real-time data updates
• Event-driven architectures
• UI state management
• WebSocket/SSE handling
• Combining multiple data sources

Quick Start

Minimal working example:

import {
  Observable,
  Subject,
  BehaviorSubject,
  fromEvent,
  interval,
} from "rxjs";
import {
  map,
  filter,
  debounceTime,
  distinctUntilChanged,
  switchMap,
} from "rxjs/operators";

// Create observable from array
const numbers$ = new Observable<number>((subscriber) => {
  subscriber.next(1);
  subscriber.next(2);
  subscriber.next(3);
  subscriber.complete();
});

numbers$.subscribe({
  next: (value) => console.log(value),
// ... (see reference guides for full implementation)

Reference Guides

Detailed implementations in the references/ directory:

Guide	Contents
RxJS Basics	RxJS Basics
Search with Debounce	Search with Debounce
State Management	State Management
WebSocket with Reconnection	WebSocket with Reconnection
Combining Multiple Streams	Combining Multiple Streams
Backpressure Handling	Backpressure Handling
Custom Operators	Custom Operators

Best Practices

✅ DO

• Unsubscribe to prevent memory leaks
• Use operators to transform data
• Handle errors properly
• Use shareReplay for expensive operations
• Combine streams when needed
• Test reactive code

❌ DON'T

• Subscribe multiple times to same observable
• Forget to unsubscribe
• Use nested subscriptions
• Ignore error handling
• Make observables stateful