MUSIC-RECOMMENDATION 0.1.0

A music recommendation system

MUSIC_RECOMMENDATION

A music recommendation system using Spotify's API and cosine similarity to suggest songs based on a user's chosen track.

Features

• Fetches top 50 tracks from Spotify Japan Weekly Ranking
• Analyzes track features such as danceability, energy, loudness, etc.
• Recommends similar tracks based on cosine similarity

Installation

1. Clone the repository:

   git clone https://github.com/sayamiyaji/MUSIC_RECOMMENDATION.git
   cd MUSIC_RECOMMENDATION
   

2. Create a virtual environment and activate it:

   python -m venv music
   source music/bin/activate
   

3. Install the required packages:

   pip install -r requirements.txt
   

Usage

1. Set up your Spotify API credentials:

   • Create an application on the Spotify Developer Dashboard
   • Obtain your client_id and client_secret

2. Export your Spotify API credentials:

   export SPOTIPY_CLIENT_ID='your_client_id'
   export SPOTIPY_CLIENT_SECRET='your_client_secret'
   export SPOTIPY_REDIRECT_URI='http://localhost:8080'
   

3. Run the web application:

   python -m your_project.app
   

4. Open your web browser and go to http://localhost:5000

Project Structure

music-recommendation/ ├── data/ # データ保存用 ├── notebooks/ # Jupyter Notebooks用 ├── src/ # ソースコード │ ├── init.py │ └── recommender.py ├── requirements.txt # 必要なパッケージリスト └── README.md # プロジェクト説明

Contributing

1. Fork the repository
2. Create a new branch (git checkout -b feature-foo)
3. Commit your changes (git commit -am 'Add some foo')
4. Push to the branch (git push origin feature-foo)
5. Create a new Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgements

• Spotipy - A lightweight Python library for the Spotify Web API
• Flask - A micro web framework written in Python