SciPy can calculate spherical Voronoi diagrams, and MatPlotLib can display them with map projections. I haven't tried to display them as a rotatable globe, but years ago I did it in 2D for volcanos: https://news.ycombinator.com/item?id=21301942, https://imgur.com/closest-volcano-lsxjRXP (argh, Imgur has gotten really aggressive with autoplaying unrelated videos - at least they're silent).
It would be fun to do Turtle graphics with geodesic motions on the sphere. If one adds Loxodromic motions, even better.
The geodesic turtle on the globe would be a good way to play with other platonic solids.
The idea that springs to my mind is to do Delaunay and Voronoi using spherical geometry. I think the article uses flat Euclidean geometry but if we tweak the fifth axiom we could do spherical or hyperbolic?
edit: Found the code. Looks like I instead ended up simply building a convex hull (which is the Delaunay triangulation) and deriving the Voronoi diagram from it.
Compute the Voronoi tessellation as usual and then project the linear separators back to the sphere (by connecting points on it to centre and extending the ray to the spherical surface).
I think it was this one: https://www.math.kent.edu/~zheng/papers/voronoi_paper_update... or this one http://nautilus.fc.ul.pt/jd/jd10sphere.pdf
From the looks of it the separators seem to be segments of great circles. That is what you would get as loci of angular bisectors.
Angular bisectors is what you would get when you use spherical geometry / arc length metric / Haversine metric.
You could still be right though. Euclidean would get you straight line bisectors, but when you project them back to the surface of the sphere, you get great circles again.
This connects with an important point (no pun intended):
People often use Haversine distance to find nearest neighbours on the globe. As long as you want to compute them modulo a hemisphere, this is unnecessary. Haversine distance and Euclidean restricted to the sphere are monotonic transforms of each other. Therefore the nearest point will be the same regardless of which one you used.
This makes me think he uses the Euclidean geometry of the surrounding three-dimensional space. But of course spherical geometry is induced by the surrounding Euclidean geometry, so the results are the same as using spherical geometry directly.