Map Python Codebases to Knowledge Graphs with Graphify and NetworkX
Decision Brief
What changedA tutorial on building a fully offline pipeline to convert multi-module Python apps into knowledge graphs.
Why it mattersAI builders can analyze code structure without relying on external APIs or LLMs.
Who should careAI coding tool users
Affected stackNo specific stack identified
Builder actionMonitor
Source confidenceMedium · Reliable media or first-hand reporting
This tutorial uses Graphify with tree-sitter to extract code graphs locally, running fully offline with no API keys or LLM backend. It then loads graph.json into NetworkX for analysis, including file types, relationship types, centrality scores, community detection, and shortest paths. Finally, it generates static and interactive visualizations showing connections between modules, classes, functions, and database objects.
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Sources
- MarkTechPost
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