www.trudy.tube 🎧

I was frustrated that I couldn’t see every song I listened to on Spotify. So, as a personal project, I made a Spotify listening archiver to…

1. Collect every single song I listen to and

2. Generate interactive listening charts, plotted by time of day.

version 1.0

In 2020, I made a mood tracker for my Spotify listening behavior. I learned a lot of valuable skills about APIs, data organizing, and visualizations.

However, there were a few things I thought could be improved from the old site.

• The site was not reliable. I collected songs using a scheduled task on my physical MacBook. So, if I had my computer turned off or was not connected to the internet, the data wouldn't be collected. The data was also stored in CSV files in Github. This is a crafty, free solution. However, this isn't best practice for storing lots of large data.

• The site was made using plain HTML/JS/CSS. This implementation was fine for this specific project, but I wanted to practice making more modular sites for the next project (React)

• The mood graph was non-sensical. I thought the mood indices provided by the Spotify API would be more insightful. But, the graphs didn't make much sense.

version 2.0

This time, I wanted to make a listening tracker that was reliable, modular, and insightful.

So, this listening tracker is a React app with a Flask backend (hosted on Heroku). And the listening data is stored in an SQL database.

The data is also all plotted by time of day. Users can hover on a circle to play a song, click the circle to open it in Spotify, and scroll below to see all recorded songs.

⭐️ Check out www.trudy.tube 🐸

Below is a demo and diagram of the new site.