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NetworkX is a Python library for studying graphs and networks. NetworkX is free software released under the BSD-new license.
History & Applications
Explore the main themes, entities and connections around NetworkX. Start with the topic map, then use the sections below for research and deeper semantic analysis.
Start with a few of the strongest sections from the source topic. These are research directions, not a list of keywords you must use.
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Browse the full topic structure. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
See the strongest relationship patterns around the current topic before diving into the raw triples.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
graph nodes layout graphs edges matlab networks data used python algorithms it's structure large node many analysis also provides useful
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| NetworkX | Developer | Many others | 1.00 | infobox |
| NetworkX | License | BSD-new license | 1.00 | infobox |
| NetworkX | Operating system | Cross-platform | 1.00 | infobox |
| NetworkX | Original authors | Aric Hagberg Pieter Swart Dan Schult | 1.00 | infobox |
| NetworkX | Release | 11 April 2005; 21 years ago (2005-04-11) | 1.00 | infobox |
| NetworkX | Repository | github.com/NetworkX/NetworkX | 1.00 | infobox |
| NetworkX | Stable release | 3.6.1 / 8 December 2025; 8 months ago (8 December 2025) | 1.00 | infobox |
| NetworkX | Type | Software library | 1.00 | infobox |
| NetworkX | Website | networkx.github.io | 1.00 | infobox |
| NetworkX | Written in | Python | 1.00 | infobox |
| NetworkX | is a | Python library for studying graphs and networks | 0.90 | text |
| NetworkX | is a | popular way to visualize graphs using a force-directed algorithm | 0.90 | text |
| NetworkX | is a | reasonably efficient | 0.90 | text |
These clusters group vocabulary that occurs around closely connected concepts in the source material.
Bridges can reveal useful research angles that are easy to miss in a flat list of related terms.