Dilshan-H / spotify-song-recommender

Recommend songs based on your preferred tracks, artists using Spotify API

Home Page:https://spotify-song-recommender.up.railway.app/

Geek Repo:Geek Repo

Github PK Tool:Github PK Tool

Spotify Song Recommender

Recommend songs based on your preferred tracks, artists using Spotify API

📚 API 103: A boon for developers building applications Video Link - https://youtu.be/YRVmXdWZbJM

🚀 See the live demo here: https://spotify-song-recommender.up.railway.app/

About

This project is a song recommender system that recommends songs based on your preferred tracks and artists using Spotify API. It is a web application built using Node.js, Express.js, HTML, CSS, and JavaScript. The application is hosted on Railway Platform.

Screenshots

Spotify Song Recommender Spotify Song Recommender

How to use

  1. Go to Spotify for Developers and create a new app.
  2. Copy the Client ID and Client Secret.
  3. Create a new file named .env in the root directory of the project.
  4. Add the following lines to the .env file:
    PORT=5500
    SPOTIFY_CLIENT_ID=<your_client_id>
    SPOTIFY_CLIENT_SECRET=<your_client_secret>
    
  5. Run the following commands in the terminal:
    npm install
    npm start
    
  6. Open the browser and go to the URL: http://localhost:5500

Deploying on Railway

  1. Create an account on Railway Platform.
  2. Create a new project and connect it to your GitHub repository.
  3. Add the following environment variables in the .env file on Railway:
PORT=3000
SPOTIFY_CLIENT_ID=<your_client_id>
SPOTIFY_CLIENT_SECRET=<your_client_secret>
  1. Deploy the project on Railway.
  2. Open the browser and go to the URL: https://your-project-name.up.railway.app

References

License & Copyrights

The MIT License

This program is free software: you can redistribute it and/or modify it under the terms of the MIT License

Authors

About

Recommend songs based on your preferred tracks, artists using Spotify API

https://spotify-song-recommender.up.railway.app/


Languages

Language:JavaScript 70.3%Language:HTML 29.7%