Sharing my odd collection of custom-built, self-quantification software

For the past three or four months, I have been working earnestly to build data processing and visualization tools. For uses cases ranging from OSINT to audio analysis. And beyond.

With this thread, I would like to occasionally post an update that explains a new free and open source self-quantification tool that I have developed. This approach is in contrast to sharing each application individually. Which I had done previously with my Pi-hole data thread.

To help get this conversation started, I would like to offer an excellent example of quantifying common everyday experiences. In this case it is listening to audio on your computer. The difference here, is that there are nine metrics that have been visualized as line graphs, along with an interactive audio playback feature.

The nine metrics that are being displayed for any given audio file include onsets, timbre, loudness, chroma, tempo, spectral centroid, spectral bandwidth, zero crossing and spectral contrast.

If you would like to view the source code for a previous release of the software explored in the above YouTube video, here is a link to the related GitHub repo. The version that is shown in the video, is still unreleased.


I have significantly expanded the audio analysis and visualization software mentioned in my previous post. To help explain, I would like to share a screenshot from after having processed and displayed four Drum And Bass tracks on my own computer.

Here is that screenshot:

I personally think the visualization aspect of this program is rather beautiful. And capable of showing how each and every audio file has its own fingerprint, albeit through the lens of data.

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What are the items in the legend? I zoomed in but the photo is a little bit too low of a resolution for me to make out what it says.

What led you to want to create this type of analysis? It seems pretty cool but as a non-audiophile I can’t really imagine what to use this for.

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Here is a closer look at those colorful squares, which are actually buttons that toggle each measurement on and off.

The primary (and original) intended use case for this software was to visualize electronic dance music (EDM). Drum And Bass in particular.


That’s really interesting! Thank you for posting about it.


Another related software project I have been working on is the “YouTube Playlists Tracker App”. It works by entering a game title, video number, YouTuber name and playlist link. Which are then organized and printed alphabetically, by game title. The number next to each YouTuber’s name represents the last video watched in that playlist. Ultimately this is how I track my viewing progress for different video game playthroughs.

Future versions of this program will include data “widgets”, to help users understand how the application has performed. Please visit the GitHub repo if you would like review the code and/or use the tool yourself.

Here is a screenshot of the application’s frontend user interface as it stands right now:

With the intended use case aside, this application could be used to collect and quantify any variety of hyperlinks.