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sPyTial: Spatial Python visualization with declarative constraints

Project description

sPyTial: Lightweight Diagrams for Structured Python Data

pip install spytial-diagramming

Sometimes you just want to see your data.

You’re working with a tree, a graph, a recursive object -- maybe an AST, a neural network, or a symbolic term. You don’t need an interactive dashboard or a production-grade visualization system. You just need a diagram, something that lays it out clearly so you can understand what’s going on.

That’s what sPyTial is for. It’s designed for developers, educators, and researchers who work with structured data and need to make that structure visible — to themselves or to others — with minimal effort.

Why Spatial Representation Matters

There’s strong evidence — from cognitive science, human-computer interaction, and decades of programming tool design — that spatial representations help people understand structure. When elements are placed meaningfully in space — grouped, aligned, oriented — we can spot patterns, detect errors, and reason more effectively. This idea shows up in research from Barbara Tversky, Larkin & Simon, and in the design of tools like Alloy and Scratch.

sPyTial gives you that kind of spatial layout by default. When you visualize a Python object, the diagram reflects how the parts are connected, not just how they're stored. You get:

  • A box-and-arrow diagram that shows the shape of your data
  • A layout that follows cognitive and structural conventions
  • A tool that knows when something doesn't make sense

Quick Start

import spytial

# Visualize any Python object
data = {
    'name': 'root',
    'children': [
        {'value': 1},
        {'value': 2},
        {'value': 3}
    ]
}

# Opens in browser or inline if in a jupyter notebook.
spytial.diagram(data)

# Or save to file
spytial.diagram(data, method='file')

License

This project is licensed under the MIT License. See the LICENSE file for details.

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