spotify_recommendation_system

Description

The Spotify Recommendation System is designed to recommend songs based on a given Spotify URL or an artist's profile link. Users can choose to use either the Spotify API or a machine learning model for generating recommendations.

Features

• Recommend songs based on a Spotify track URL.
• Recommend songs based on an artist's profile link.
• Option to use Spotify API or a machine learning model for recommendations.

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/spotify_recommendation_system.git
   cd spotify_recommendation_system

2. Install the required dependencies:

   pip install -r requirements.txt

Usage

1. Obtain Spotify API credentials by creating a developer account on the Spotify Developer Dashboard.
2. Set up your environment variables with your Spotify API credentials:

   export SPOTIFY_CLIENT_ID='your_client_id'
   export SPOTIFY_CLIENT_SECRET='your_client_secret'

3. Run the recommendation script:

   python recommend.py --url <spotify_url> --method <api_or_ml>

NOTE

set up a virtual environment to avoid version collision between packages like numpy,streamlit and protobouf... etc

API Reference

This project uses the Spotify Web API to fetch song and artist data.

Machine Learning Model

The machine learning model is trained on a dataset of songs and their features. It uses collaborative filtering and content-based filtering techniques to generate recommendations.

Contributing

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

License

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