Day 3 of Building Secrin

Today’s focus was on extracting and counting structural elements from code repositories. We built a component that parses Python and JavaScript projects, identifies their key elements, and represents them as nodes and relationships in a graph structure.

The system now tracks:

print(f"Nodes extracted:")
print(f"  Files:       {files}")
print(f"  Classes:     {classes}")
print(f"  Functions:   {functions}")
print(f"  Variables:   {variables}")
print(f"  Packages:    {packages}")
print(f"  Docs:        {docs}")
print(f"  Total:       {len(graph_data.nodes)}")
print(f"\nRelationships: {len(graph_data.relationships)}")

This output summarizes the architecture that Secrin now understands. Every file, class, and function becomes a node. Dependencies and references between them become edges. The result is a knowledge graph that represents the structure and logic of a codebase in a connected form.

This graph-based view lays the foundation for everything that follows. With it, we can:

• Visualize how code components depend on each other.
• Query relationships between files and functions.
• Build higher-level understanding of repositories for documentation, onboarding, and AI-based code reasoning.

The Grand Line of Open Source continues. ⚓️

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Follow the project:

• GitHub: https://github.com/SecrinLabs/secrin
• Twitter (X): x.com/jenilsavani_