Spotify Music Recommendation System

An interactive web application that leverages the Spotify API and machine learning algorithms to provide song recommendations based on mood.

🎵 Features

• Dataset Recommendation: Recommend songs from a provided dataset based on mood.
• API Recommendation: Use the Spotify API to fetch and recommend songs.
• Data Analysis: View data visualizations and analyses on various datasets related to Spotify songs.

🛠 Installation & Setup

1. Clone the Repository

git clone https://github.com/EJmpa/Spotify_Music_Recommendation-_System.git
cd spotify_music_recommendation_system

2. Set up a Virtual Environment

python -m venv venv
source venv/bin/activate
# On Windows use: venv\Scripts\activate

3. Install the Required Packages

pip install -r requirements.txt

4. Spotify API Setup

• Register your application on the Spotify Developer Dashboard.
• Retrieve your client_id and client_secret.

export SPOTIPY_CLIENT_ID='your_client_id'
export SPOTIPY_CLIENT_SECRET='your_client_secret'

5. Run the Streamlit App

streamlit run app2.py

📋 Usage

Dataset Recommendation:

1. Select a song from the dropdown.
2. Choose a mood.
3. Get a list of recommended songs based on your selection.

API Recommendation:

1. Input a song name.
2. Choose a mood.
3. Get a list of recommended songs fetched from the Spotify API based on your input.

Data Analysis:

1. Choose a dataset from the sidebar.
2. Load and view various analyses and visualizations based on the dataset.

📜 License

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