oldman-gg/RekordboxCollection-To-SpotifyPlaylist

This script searches for Spotify URIs corresponding to the songs listed in a exported Rekordbox collection CSV file. The Spotify URIs are then added to the .csv and into a specified Spotify playlist.

Rekordbox Collection -> Spotify Playlist

This script allows you to match tracks from a Rekordbox CSV file with their corresponding tracks on Spotify, exports the Spotify URI to the corresponding row in .csv, and adds tracks to a Spotify playlist. It utilizes the Spotipy library, a Python wrapper for the Spotify Web API, and the fuzzywuzzy library for fuzzy string matching.

Curious about what I'm listening to? Check out Old Man G.G's Rekordbox Collection Spotify Playlist

Features

• Matches tracks from a Rekordbox CSV file with their corresponding tracks on Spotify.
• Uses fuzzy string matching to handle slight variations in song and artist names.
• Updates the CSV file with the Spotify URIs of the matching tracks.
• Adds the matching tracks to a specified Spotify playlist.

Prerequisites

Before using this script, make sure you have the following:

• Python 3.x installed on your system.
• The necessary dependencies: pandas, spotipy, fuzzywuzzy.
• Rekordbox collection .csv file
• Create a Spotify app by navigating to https://developer.spotify.com/dashboard and add http://localhost:8080/callback as your redirect uri

To create the Rekordbox file, add the songs you want to a given Rekordbox playlist, Playlist > Export playlist to a file > Export playlist to a file (*.txt). Import the .txt file into a spreadsheet, I recommend Google Sheets as it auto detects the data schema, File > Export > .csv.

Note: This script relies on accurate artist and titles of your Rekordbox collection. To efficiently tag your songs, I recommend MP3Tag.

Installation

1. Clone the repository:

git clone https://github.com/your-username/RekordboxCollection-To-SpotifyPlaylist.git

2. Set up the environment variables by creating a file named environment_variables.pyin the project root directory. Open the file and define the following variables:

spotify_client_id = 'your-client-id' #found on https://developer.spotify.com/
spotify_client_secret = 'your-client-secret' #found on https://developer.spotify.com/
username = 'your-spotify-username' #found in account overview within Spotify profile
playlist_id = 'your-spotify-playlist-id' #found within playlist URL
rekordbox_csv_input = 'path-to-rekordbox-csv-file.csv' #Rekordbox .csv
output = 'path-to-output-csv-file.csv' #desired output file
redirect_uri = 'your-redirect-uri' #try http://localhost:8080/callback

Note: In the project, you will see an example environment_variables.py titled environment_variables_git.py

Note: Make sure that you add http://localhost:8080/callback to your redirect uri within your Spotify App settings.

Usage

To use the script, simply run the following command:

python Main.py

The script will start processing the Rekordbox CSV file and matching the tracks with their corresponding tracks on Spotify. The progress and any errors encountered will be displayed in the console. Once the matching process is complete, the updated CSV file will be saved to the specified output file and the tracks will be added to the specific playlist.

Contributing

Contributions are welcome! If you have any suggestions, bug reports, or feature requests, please open an issue on the GitHub repository. If you'd like to contribute code, please fork the repository, create a new branch, make your changes, and submit a pull request.

Acknowledgements

• The Spotipy library: https://spotipy.readthedocs.io
• The fuzzywuzzy library: https://github.com/seatgeek/fuzzywuzzy

To Dos

• Modify the function to not add songs that are already present therefore mitigating track duplicates in Spotify playlist