image resizer - a utility web app

Project Overview

This project delivers a robust image processing API built with Node.js, TypeScript, and Express that allows users to upload and transform images through a clean, intuitive interface. At its core, the application leverages Sharp—a high-performance image processing library—to handle various transformation operations including resizing dimensions and converting between different image formats (JPG, PNG, WebP, AVIF, and GIF).

The application features a responsive front-end with drag-and-drop functionality that provides immediate visual feedback. On the back-end, it implements intelligent caching mechanisms using node-cache to store processed images, significantly improving performance for repeated requests while reducing server load. Error handling is comprehensive throughout the application, with user-friendly messages that guide users when issues arise.

The codebase demonstrates modern TypeScript practices with strong typing and interfaces, maintaining separation of concerns through a modular architecture. Routes are clearly organized, with middleware handling authentication, logging, and file validation. The project includes thorough test coverage using Jasmine and Supertest, ensuring reliability across unit tests for the image processor service and integration tests for the API endpoints.

Deployment is streamlined through configuration for Vercel, making the application production-ready with minimal setup. Security considerations are addressed by implementing file size limitations, type validation, and proper error handling to prevent common vulnerabilities. Overall, this project showcases professional-grade development practices while solving the practical need for on-demand image transformation services.