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An archive dedicated to preserving and extending the original work of Glenn McDonald, the former Data Alchemist at Spotify, known for his project Every Noise at Once

License: MIT License

archive data data-science database datascience everynoise good-first-contribution good-first-example good-first-issue good-first-issues

musicgenredb's Introduction

MusicGenreDB

Welcome to MusicGenreDB, an archive dedicated to preserving and extending the original work of Glenn McDonald, the former Data Alchemist at Spotify, known for his project Every Noise at Once. This repository aims to maintain and potentially expand on the intricate genre classifications that McDonald created, ensuring the longevity and accessibility of this valuable data.

Project Overview

MusicGenreDB is an extensive collection of 6,291 genre-shaped distinctions as categorized by Spotify. Each song in this repository is associated with a unique ID that links it to detailed metadata. This project serves as an archive and aims to possibly introduce new features in the future to enhance the original concept.

Data Structure

The repository contains two main components:

  1. songs/: A folder with 6,291 audio files. Each file is named with a number corresponding to its ID.
  2. songs_data.json: A JSON file containing metadata for each song. The structure of the JSON file is as follows:
[
    {
        "id": "SONG ID",
        "genre": "SONG GENRE",
        "url": "SONG URL",
        "title": "ARTIST - SONG NAME",
        "color": "CHOSEN COLOR"
    }
]

How to Use

  1. Clone the repository:

    git clone https://github.com/yourusername/MusicGenreDB.git
    cd MusicGenreDB
  2. Explore the data: You can browse the songs/ folder to access the audio files directly or use the songs_data.json file to retrieve detailed information about each song.

  3. Listen to the samples: Each song entry in songs_data.json includes a URL to a Spotify MP3 preview.

Contributing

We welcome contributions to MusicGenreDB! If you have ideas for new features, improvements, or just want to fix a bug, feel free to submit a pull request or open an issue.

Credits

All credit for the data itself goes to Glenn McDonald and the artists and bands who created the music. This project is a tribute to their work and aims to preserve and expand upon it.

License

This project is licensed under the MIT License.

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