---
id: ipysigma
version: "0.24.6"
license: MIT
license_treatment: permissive
maintenance: aging
---

# ipysigma — A Jupyter widget using sigma.js to render interactive networks.

License: permissive · Maintenance: aging · Downloads: 107.6K/mo

## What it is and what it does

ipysigma is a Jupyter widget that embeds interactive network visualizations directly into notebook cells. It wraps sigma.js and graphology to display graphs with rich visual customization—you can map node and edge properties to color, size, shape, labels, and other visual attributes. The widget supports both static exploration and synchronized "small multiples" for comparing graph features side-by-side.

The package is designed for exploratory network analysis in notebooks. You pass a graph object and optionally specify which attributes or computed metrics should drive the visual encoding. It can compute metrics on the widget side without round-tripping to Python, and integrates with ipywidgets for interactivity.

Use it for:

- Explore community structure in a network by coloring nodes by computed partition.
- Compare two layouts or metrics of the same graph side-by-side using SigmaGrid's small multiples.
- Visualize a knowledge graph or ontology with custom node shapes, colors, and labels mapped to attributes.
- Interactively inspect node degree, centrality, or other metrics as node size or color.
- Render a directed graph with edge weights as visual size in an interactive notebook cell.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

A Jupyter widget that renders interactive network graphs directly in notebook cells using sigma.js, supporting graph objects with extensive visual customization of nodes and edges.

Yes, if you work with networks in Jupyter notebooks and want interactive visualization without leaving the cell. The low install friction, permissive license, and stable maintenance make it practical. The aging status (262 days since last release) is not a blocker for stable use, but verify compatibility with your Jupyter version before relying on it for production workflows.

## Install

pip install ipysigma
uv add ipysigma
poetry add ipysigma

## Installing ipysigma

Before you install: Low friction installation with a single runtime dependency (ipywidgets). The package is aging—last release was 262 days ago—but the repository remains active with 308 stars, suggesting stable maintenance rather than abandonment.

License in practice: MIT license is permissive; you can use, modify, and distribute ipysigma with minimal restrictions, making it suitable for both open and closed-source projects.

Quickstart:

pip install ipysigma

from ipysigma import Sigma

Sigma(g, node_size='degree', node_color='category')

Requires Jupyter Notebook or Lab with widget support enabled; on Google Colab, must call output.enable_custom_widget_manager() first.

Verify before relying:

- Compatibility with current Jupyter versions (classifiers list Python 3.4–3.7, which are EOL).
- Performance characteristics when rendering very large graphs (node/edge count thresholds).
- Whether widget-side metric computation (e.g., Louvain) works reliably in all Jupyter environments.

## Package facts

- License: MIT (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: aging
- Downloads: 107.6K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

jupyter network visualization, interactive graph widget, sigma.js jupyter, graph rendering notebook, network graph interactive, jupyter graph display, interactive network explorer, jupyter-widget, network-analysis, graph-visualization

[View on SkillFed](https://skillfed.io/packages/ipysigma) · [View on PyPI](https://pypi.org/project/ipysigma/)