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Spotify Dashboard

A personal Spotify analytics dashboard that visualizes listening habits, top artists, favorite tracks, and audio insights using the Spotify Web API.

This project allows users to log in with their Spotify account and explore detailed statistics about their music preferences.


Node License Spotify API Status GitHub stars GitHub forks GitHub issues

Demo

tildeath.site

Features

  • Spotify OAuth authentication
  • View Top Artists
  • View Top Tracks
  • Listening insights and trends
  • Audio feature visualizations
  • Interactive dashboard UI
  • Personal listening analytics

Tech Stack

  • Node.js
  • Express.js
  • Spotify Web API
  • HTML / CSS / JavaScript
  • Chart.js (data visualizations)

Getting Started

1. Clone the repository

git clone https://github.com/sudo13samurai/spotify-dashboard.git
cd spotify-dashboard

2. Install dependencies

npm install

3. Create a Spotify Developer App

Visit:

https://developer.spotify.com/dashboard

Create an application and copy your:

  • Client ID
  • Client Secret
  • Redirect URI

4. Create .env

Create a .env file in the project root:

SPOTIFY_CLIENT_ID=your_client_id
SPOTIFY_CLIENT_SECRET=your_client_secret
SPOTIFY_REDIRECT_URI=http://localhost:3000/callback
PORT=3000

5. Run the application

npm start

Then open:

http://localhost:3000

Project Structure

spotify-dashboard/
│
├── public/        # static assets
├── views/         # dashboard templates
├── routes/        # API and auth routes
├── server.js      # main server file
├── package.json
└── .env

Spotify API Permissions

This app may request scopes such as:

  • user-top-read
  • user-read-recently-played
  • user-library-read

These allow the dashboard to access listening statistics and track data.


Future Improvements

  • Dark mode dashboard
  • Playlist analytics
  • Listening history graphs
  • Export statistics
  • Mobile responsive layout

License

MIT License


Author

Krystian J GitHub: https://github.com/sudo13samurai

About

Personal Spotify analytics dashboard with listening archetypes, audio feature insights, and terminal reporting.

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