Understanding Angular CLI Command for Bundle Size Analysis

The accurate answer to the Angular CLI command used to analyze the size of the application bundles is indeed, "ng build --prod --stats-json". This command, when executed, helps to analyze and understand the bundle size of your Angular application and thereby allows you to optimize your application further.

The Angular CLI, or Command Line Interface, is a powerful tool that streamlines your Angular development process. It provides commands for building, serving, testing, and even deploying your Angular applications.

Now, let's unwrap the 'ng build --prod --stats-json' command:

• ng build: This command is used to compile an Angular application into an output directory.

• --prod: A flag that builds your application for production. It applies several build optimization techniques like AOT (Ahead Of Time) Compilation, smaller bundle sizes, and more.

• --stats-json: The flag 'stats-json' generates a 'stats.json' file in your output directory once the build completes. This file contains detailed insights about the size of each part of your bundled application. It can be used with several bundle analysis tools like webpack-bundle-analyzer, which provides a graphic visualization of your bundle.

With this command, an Angular application can significantly enhance its performance by identifying parts of the application that contribute most to the bundle size, revealing potential areas for optimization.

However, remember that while bundle analysis is crucial for maintaining optimal performance, rigorous code quality practices should also be in place in your development process. Proper code splitting, lazy-loading of modules, and keeping third-party library usage in check are a few ways to keep the bundle size in control aside from using the Angular CLI command effectively.

So, the next time you're nearing the deployment of your Angular application, remember to use the 'ng build --prod --stats-json' command to analyze your bundle size and make the appropriate optimizations for a high-performance application.