The Music Recommendation System is a modern web application designed to enhance your music discovery experience. This application allows users to search for songs by either song name or artist name using the Spotify API. It provides detailed information about the searched song, including the title, artist, album cover, and a direct link to listen on Spotify. Additionally, the system offers personalized music recommendations based on the searched song, displaying similar tracks along with their album art and Spotify links.
The project utilizes Flask, a lightweight and flexible Python web framework, to handle backend operations and API interactions. Flask ensures a robust and scalable server-side architecture, allowing smooth communication between the frontend and the Spotify API. The frontend is styled using Bootstrap and custom CSS to provide a visually appealing and responsive user interface, ensuring an optimal experience across all devices.
With a focus on both functionality and design, the Music Recommendation System delivers a user-friendly and engaging platform for discovering new music and exploring personalized recommendations.
Client: HTML, CSS, JS, Bootstrap
Server: FLask, Spotipy, dotenv(Additional Tools for managing environment variables likSpotify API credentials)