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Minimalist library to generate SVG views of scientific data

Just 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. :-)

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Mar 23, 2026Visit website

✨ AI Summary

A minimalist, open-source Python library for generating SVG visualizations of scientific data. It produces smaller SVG files than standard libraries and allows CSS-based styling for features like dark/light mode support.

Best For

Python developers working with scientific data, Users needing lightweight SVG charts, Individuals who want CSS-customizable visualizations

Why It Matters

Generates compact, CSS-stylable SVG charts from JSON data using Python.

Key Features

  • Generates minimalist SVG files for scientific data visualization.
  • Supports scatterplots, line plots, histograms, and box plots.
  • Configurable visuals via CSS for dark/light mode support.
  • Graphs are specified using JSON files.

Use Cases

  • A data scientist developing a research paper can use this library to quickly generate clean, compact SVG visualizations of experimental results, which can then be easily embedded into their publications or online articles, ensuring compatibility across different platforms and browsers.
  • A web developer building an interactive dashboard for scientific data can leverage this Python library to create dynamic charts and graphs specified in JSON. The CSS configurability allows them to seamlessly integrate these visualizations into their web application, supporting features like dark mode.
  • An educator teaching data visualization principles can use this tool to demonstrate how to represent various data types (scatterplots, line plots, histograms, box plots) in a minimalist SVG format, highlighting the benefits of smaller file sizes and CSS-driven styling for educational materials.

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