Stop Using Inefficient Angular Practices

Inefficient Angular Practices

Angular is one of the most popular frameworks for building modern web applications, offering developers powerful tools to create scalable and maintainable applications. However, when using Angular, developers can sometimes fall into inefficient practices that degrade performance, maintainability, and scalability. These bad practices often arise from not fully understanding Angular’s architecture, APIs, or best practices. To ensure that your Angular apps remain fast, efficient, and easy to maintain, it’s crucial to recognize and avoid these inefficiencies.

In this article, we’ll explore common inefficient Angular practices and offer solutions for improving your development workflow.

1. Using Too Many ngOnChanges Lifecycle Hooks

The ngOnChanges lifecycle hook is called whenever an input property of a component changes. While it's useful for reacting to input changes, it can become inefficient if overused or misused. Calling heavy computations or HTTP requests in ngOnChanges for every input change can lead to unnecessary recalculations, negatively impacting performance.

Best Practice:

Instead of placing heavy logic inside ngOnChanges, you can use ngOnInit for initialization or use Angular’s ChangeDetectionStrategy.OnPush to optimize change detection. OnPush reduces the number of checks Angular needs to perform, as it only triggers change detection when specific inputs change.

@Component({
  selector: 'app-my-component',
  changeDetection: ChangeDetectionStrategy.OnPush,
  templateUrl: './my-component.component.html',
})
export class MyComponent implements OnChanges {
  @Input() data: any;

  ngOnChanges() {
    // Move heavy logic here only when truly necessary
  }
}

2. Ignoring Lazy Loading for Modules

Lazy loading is a powerful feature in Angular that allows you to load modules only when needed, improving the initial loading time of the application. Many developers neglect to implement lazy loading and instead bundle all components and services into a single large module, causing longer load times and unnecessary data transfer.