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Spotify Track Features Analysis and Mood-Based Playlist Application

Try it: betterspotify.streamlit.app

This is a web application built using Streamlit and the Spotify API. The application allows users to explore track features, generate mood-based playlists, and visualize audio features with interactive charts.

Features

  • Spotify Authentication: Log in with your Spotify account to access your personal data.
  • Track Feature Analysis: Get detailed insights into audio features like danceability, energy, valence, and more.
  • Mood-Based Playlist Generator: Create playlists tailored to your current mood (e.g., Happy, Sad, Relaxed, Energetic).
  • Playlist Creation: Generate new playlists directly within the app and add your favorite tracks.
  • Audio Feature Visualizations: Choose between bar charts, radar charts, and pie charts to visualize track data.
  • Add to Liked Songs: Easily add recommended tracks to your liked songs.

Tech Stack

  • Frontend: Streamlit
  • Backend: Spotify API
  • Visualizations: Plotly, Pandas, Matplotlib

Setup Instructions

Prerequisites (until extension request is approved by Spotify)

  • Python 3.8 - 3.11: Ensure that you have a compatible version of Python installed.
  • Spotify Developer Account: Create a Spotify Developer account and set up a new application to get your CLIENT_ID and CLIENT_SECRET.

Installation

  1. Clone the repository: 
    git clone https://github.com/ishan-rawat1/SpotifyApp.git
cd SpotifyApp
  2. Install the required dependencies: 
    pip install -r requirements.txt
  3. Create a .env file in the root directory and add your Spotify credentials: 
    CLIENT_ID='your_spotify_client_id'
CLIENT_SECRET='your_spotify_client_secret'
REDIRECT_URI='your_redirect_uri'
  4. Running the application 
    streamlit run Home.py

This will launch the app in your browser. Follow the authentication flow to log in to your Spotify account

Contribution

Feel free to open issues or submit pull requests for improvements and new features. Contributions are welcome!