$npx skillfedfor your agent

gravis

Interactive graph visualizations with Python and HTML/CSS/JS.

With conditionsPyPI Scientific/EngineeringReleased Dec 202182.7K downloads / moApache License, Version 2.0Pure Python

Decision gist · record as of 2026-08-14

pure-Python wheel — gravis-0.1.0-py3-none-any.whl
v0.1.0 · released 2021-12-08 · Python >=3.5 · 1 runtime deps: setuptools

Yes, but with caution. Gravis is worth installing if you need a lightweight way to turn Python graph data into interactive HTML visualizations and you don't require ongoing maintenance or support. The permissive Apache License, Version 2.0 and low install friction make it accessible. However, its abandoned status since 2021-12-08 means no updates for Python version compatibility, browser standards, or bug fixes—use it only for one-off visualizations or internal tools where stagnation is acceptable.AI-flagged interpretation of the facts on this page — verify before relying

Before you install

  • Requires Python 3.5 or later; output is HTML/CSS/JS intended for viewing in a web browser.
  • Installation is straightforward with low friction—a pure Python wheel with only setuptools as a runtime dependency.
  • However, the package has been abandoned since its single release on 2021-12-08, with no maintenance activity in years, so expect no bug fixes or updates.

License · maintenance · safety

Apache License, Version 2.0 (permissive) — Apache License 2.0 is permissive, allowing commercial and private use with minimal restrictions. You may use, modify, and distribute gravis freely as long as you include a copy of the license and state any changes.

last release 2021-12-08 (1710 days)

0 known vulnerabilities (OSV.dev, 2026-08-14) · 82,650 downloads/mo, #14,147 on PyPI

Verify before relying

pip install gravis

import gravis

# Create and visualize a simple graph
graph = gravis.Graph()
graph.add_node('A')
graph.add_node('B')
graph.add_edge('A', 'B')
gravis.render(graph, output_file='graph.html')
  • Whether the package handles large graphs efficiently or has known performance limits.
  • What graph layout algorithms are available and how customizable the visualization styling is.
  • Whether the HTML output works with modern browser versions and what dependencies it expects client-side.
  • What specific graph data structures and methods the API provides beyond basic node/edge operations.
Same gist for agents: .md · .json

What it is and what it does

Gravis is a Python library for creating interactive graph visualizations that render as standalone HTML files. It takes graph data (nodes and edges) and generates a web-based visualization you can open in any browser to explore the structure interactively. The library is designed for developers and researchers who need to visualize networks, hierarchies, or relationship diagrams without building a full web application.

The package depends only on setuptools and produces pure HTML/CSS/JavaScript output, making it portable and easy to share. However, it has been abandoned since its initial 0.1.0 release in December 2021 and receives no maintenance, so there will be no bug fixes, feature additions, or compatibility updates for newer Python versions or browser standards.

Use it for

  • Visualize knowledge graphs or semantic networks for research and documentation.
  • Explore social network structures or organizational hierarchies interactively in a browser.
  • Generate interactive diagrams of software dependencies or system architectures.
  • Create educational visualizations of algorithms or data structures for teaching.
  • Export graph data from Python analysis pipelines as shareable HTML reports.

Worth the install?

AI-flagged interpretation of the facts on this page. Verify before relying on it.

With conditions

Yes, but with caution.

Gravis is worth installing if you need a lightweight way to turn Python graph data into interactive HTML visualizations and you don't require ongoing maintenance or support. The permissive Apache License, Version 2.0 and low install friction make it accessible. However, its abandoned status since 2021-12-08 means no updates for Python version compatibility, browser standards, or bug fixes—use it only for one-off visualizations or internal tools where stagnation is acceptable.

Install

gravis on PyPI

Before you install

Installation is straightforward with low friction—a pure Python wheel with only setuptools as a runtime dependency. However, the package has been abandoned since its single release on 2021-12-08, with no maintenance activity in years, so expect no bug fixes or updates.

Requires Python 3.5 or later; output is HTML/CSS/JS intended for viewing in a web browser.

License in practice

Apache License 2.0 is permissive, allowing commercial and private use with minimal restrictions. You may use, modify, and distribute gravis freely as long as you include a copy of the license and state any changes.

Quickstart

pip install gravis

import gravis

# Create and visualize a simple graph
graph = gravis.Graph()
graph.add_node('A')
graph.add_node('B')
graph.add_edge('A', 'B')
gravis.render(graph, output_file='graph.html')

Verify before relying

  • Whether the package handles large graphs efficiently or has known performance limits.
  • What graph layout algorithms are available and how customizable the visualization styling is.
  • Whether the HTML output works with modern browser versions and what dependencies it expects client-side.
  • What specific graph data structures and methods the API provides beyond basic node/edge operations.

Package facts

LicenseApache License, Version 2.0 permissive
Python supportSupports the current Python release >=3.5
Install frictionLow. Pure-Python wheel
Runtime dependencies
1 package
setuptools
MaintenanceAbandoned 1,710 days since the last release
First released
Downloads82,650 / month, #14,147 on PyPI 30-day window, as of 2026-08-14
Known vulnerabilitiesNone known OSV.dev, checked 2026-08-14
Classifiers
Development Status :: 4 - BetaIntended Audience :: DevelopersIntended Audience :: EducationIntended Audience :: Science/ResearchLicense :: OSI Approved :: Apache Software LicenseNatural Language :: EnglishOperating System :: OS IndependentProgramming Language :: Python :: 3Topic :: Multimedia :: GraphicsTopic :: Multimedia :: Graphics :: 3D RenderingTopic :: Scientific/EngineeringTopic :: Scientific/Engineering :: Visualization

Evidence: gravis-0.1.0-py3-none-any.whl

Tags

Capabilities
interactive graph visualizationnetwork diagram HTMLgraph rendering Pythonvisual graph explorernetwork structure displaygraph layout visualizationinteractive network browser
Topics
graph-visualizationinteractive-htmlabandoned

Let your AI agent find packages like this

Example. Real query, live index.

You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.

wish › “graph rendering Python”

  • gravisGravis generates interactive graph visualizations as…
  • pydotplusPyDotPlus provides a Python interface to Graphviz's Dot language,…
  • graphttyRenders directed graphs as colored ASCII art in the terminal using a…

Give your agent the search over MCP, or paste the wish link into any chat.

More Scientific/Engineering packages

numpy Worth it
PyPI · Software Development · released Aug 2026

NumPy provides an N-dimensional array object and a comprehensive suite of mathematical, linear algebra, Fourier transform, and random number functions for scientific computing in Python.

BSD-3-Clause AND 0BSD AND MIT AND Zlib AND CC0-1.0compiled wheel · 3.12+
1.1Bdownloads / mo
pandas Worth it
PyPI · Scientific/Engineering · released Jul 2026

pandas provides fast, flexible data structures (Series and DataFrame) for loading, cleaning, transforming, and analyzing labeled or relational data in Python.

BSD-3-Clausecompiled wheel · 3.11+
769.1Mdownloads / mo
scipy Worth it
PyPI · Libraries · released Jun 2026

scipy provides numerical algorithms for mathematics, science, and engineering—including optimization, integration, linear algebra, Fourier transforms, signal and image processing, and ODE solvers—built on numpy arrays.

BSD-3-Clausecompiled wheel · 3.12+
449.0Mdownloads / mo
scikit-learn Worth it
PyPI · Software Development · released Jun 2026

scikit-learn provides a comprehensive Python library for supervised and unsupervised machine learning, including classification, regression, clustering, dimensionality reduction, and model evaluation tools built on NumPy and SciPy.

Install it if you need to train, evaluate, or deploy supervised or unsupervised learning models.

BSD-3-Clausecompiled wheel · 3.11+
235.5Mdownloads / mo
dill Worth it
PyPI · Software Development · released Jan 2026

dill extends Python's pickle module to serialize and deserialize a much wider range of Python objects, including functions, lambdas, classes, and interpreter sessions, to byte streams for storage or network transmission.

BSD-3-Clausepure Python · 3.9+
208.1Mdownloads / mo
multiprocess Worth it
PyPI · Software Development · released Jan 2026

Multiprocess is an enhanced fork of Python's standard multiprocessing library that uses dill for better serialization, allowing you to spawn processes with a threading-like API and share complex objects between them.

Install it if you use multiprocessing and encounter pickle serialization limits with lambdas or complex objects.

BSD-3-Clausepure Python · 3.9+
202.7Mdownloads / mo

See also pyvis · trame · torchviz · pygraphviz · pygexf · missingno · dash-cytoscape · highcharts-core · branca · sphinxcontrib-jsmath