Show HN: Minimalist library to generate SVG views of scientific data
github.comJust wanted to share with HN a simple/minimal open source Python library that generates SVG files visualizing two dimensional data and distributions, in case others find it useful or interesting.
I wrote it as a fun project, mostly because I found that the standard libraries in Python generated unnecessarily large SVG files. One nice property is that I can configure the visuals through CSS, which allows me to support dark/light mode browser settings. The graphs are specified as JSON files (the repository includes a few examples).
It supports scatterplots, line plots, histograms, and box plots, and I collected examples here: https://github.com/alefore/mini_svg/blob/main/examples/READM...
I did this mostly for the graphs in an article in my blog (https://alejo.ch/3jj).
Would love to hear opinions. :-)
Other than that the graphs look good, I don't have much to say about the code (not a Python person), but I think the approach is great, mostly because I like using custom-generated SVGs for visualizations myself as well.
The only downside I've experienced is that it's pretty much impossible to get data-dependent interactions (tooltips and clickable links that vary based on section) to work reliably: additional Javascript has gotten me to like 80% on desktop, but not on mobile.
Looks neat! As someone who also did a barplot library with SVG output, I can tell you that this sort of program is really fun to write.
I like how the plots look!
In recent months, I’ve been making charts for the benchmarks just by talking to Claude Code or Codex: “Generate the charts for this and that.”
I could try pointing it to your project next time. It would be easier to do with some kind of easy-to-install skills for AI agents.
I think it’s an inevitable trend this year, something people call "building for agents." (I saw someone phrase it that way on X.)
How does it compare to gnuplot svg output?