CS 426 Senior Project in Computer Science, Spring 2025
University of Nevada, Reno, Department of Computer Science & Engineering
Team 40
Lucas Black, Chantelle Cabanilla, Jax Hendrickson, Matthew Stenvold
Instructors: David Feil-Seifer, Sara Davis, Vinh Le, Levi Scully
Advisor: Josh Watson, CSE Instructor
Pass the Aux is an online platform to find, search, rate music as well as interact with other users on a social forum. It is built in Python, Flask, Vue.js, and PostgreSQL with ongoing full-stack development from our team. The website allows users to search and browse information related to songs, albums, and artists. If they decide to sign up to create an account and log in, then they are currently able to rate songs. Any visitor to an artist's page, or song/album, will see the average rating from all users. We want to allow users to be able to generate playlists that can be shared and collaborated between multiple users, with the Spotify API integrated to load playlists if they so desire. We are planning to add a page dedicated to upcoming album releases with their corresponding release times. We are also planning to add a dedicated forum that will allow users to discuss any artist, album, song, or arbitrary topic that will engage user interaction. Pass the Aux will become a cohesive platform for someone to keep track of their playlists, look up information on artists and songs, keep them up-to-date with their favorite artist(s), and log in to discuss music topics. This project aims to satisfy the curiosity of music nerds by providing a set of social media features and integrate data from popular streaming platforms, such as Spotify's API.
Right now, the project is developed using the Python3 language, Flask micro web framework, Vue.js front-end framework, and PostgreSQL for database management.
Your password is encrypted when creating and signing into an account on Pass the Aux. Your email is will be verified as well when you create an account.
Keep track of artists, discuss thoughts or ideas, and build your personal record of your favorite music.
The project is currently a web application that is designed for desktop computers. We would like to extend functionality of the website to be functional enough for tablets or ideally mobile.
Here are the recent updates based on our GitHub activity since the mid-point demo:
Development is currently focused on polishing existing features and adding planned functionality, like admin reporting and improved user features.
The following is a list of resources relevant to the project.
Music Data Mining, 1st Edition, Tao Li, et. al.: https://www.amazon.com/Music-Mining-Chapman-Knowledge-Discovery/dp/1439835527
Discogs Monthly Data Dump: https://discogs-data-dumps.s3.us-west-2.amazonaws.com/index.html
Discogs OAuth Example: https://github.com/jesseward/discogs-oauth-example
Spotify API: https://developer.spotify.com/documentation/web-api
List of Publicly Available Music APIs: https://publicapis.dev/category/music
Music Information Retrieval: https://www.sciencedirect.com/topics/computer-science/music-information-retrieval
Academic Press Library in Signal Processing: Volume 1: Signal Processing Theory and Machine Learning, Chapter 26 - Music Mining: https://www.sciencedirect.com/science/article/abs/pii/B9780123965028000267
Upcoming Album Releases (Metacritic): https://www.metacritic.com/browse/albums/release-date/coming-soon/date
Apple News Dedidicated Music Page: https://www.apple.com/newsroom/topics/music/