kirito-chen

kirito-chen / CodeMap

Public

Visualize your Python project

21
11
89% credibility
Found May 22, 2026 at 21 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

CodeMap is a developer tool that takes any Python project and creates visual diagrams to help you understand how the code is organized. You can see which files connect to which, follow the path of function calls through your program, find areas of high complexity, and trace how objects interact with each other. The tool works entirely in your browser with interactive visualizations - no configuration needed, just point it at a folder and explore.

How It Works

1
📁 You have a Python project

You've been working on some Python code and want to understand how all the pieces fit together.

2
🔧 You install CodeMap

You download and install the tool with a simple one-line command, and everything sets itself up automatically.

3
You choose what to explore
🕸️
See how modules connect

A web of lines showing which files import which other files.

🌳
Follow function calls

A tree showing what happens when a function runs, and what it calls next.

🔥
Find complex spots

A heat map revealing which parts of your code are most complicated.

🔗
Trace method calls

A sequence diagram showing how objects talk to each other.

4
👆 You point it at your folder

You simply tell CodeMap which folder contains your project, and it immediately starts reading through all your files.

5
✨ Your code comes to life

An interactive visualization appears in your browser with colorful diagrams, clickable nodes, and tooltips showing details.

🎉 You understand your project

You can now see exactly how your code is structured, which pieces depend on which, and where the complexity lives.

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Star Growth

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AI-Generated Review

What is CodeMap?

CodeMap is a Python code visualization tool that generates interactive diagrams from your source code. Point it at any Python project and it produces dependency graphs showing which modules import which, call trees mapping nested function execution paths, and heatmaps highlighting complexity hotspots. It works entirely through static analysis using Python's AST module, so no runtime execution is needed. The tool exposes both a CLI for quick one-off analysis and a Python API for embedding visualization into your own scripts.

Why is it gaining traction?

The zero-configuration workflow is the main draw -- you run one command and get an interactive HTML visualization. The Mermaid output for call graphs is particularly useful for embedding execution flow diagrams directly into documentation or pull requests. Unlike heavy IDE plugins, this runs from the terminal and produces portable HTML files you can share with anyone. The heatmap feature using cyclomatic complexity gives you immediate insight into which files need attention without manually running separate linting tools.

Who should use this?

Technical leads reviewing unfamiliar codebases during due diligence or onboarding will find the dependency graph most useful. Developers maintaining legacy Python projects can use the complexity heatmap to prioritize refactoring efforts. Anyone writing technical documentation would benefit from generating Mermaid call graphs to illustrate how their code executes. Teams practicing code review can use the visualizations to communicate architecture changes without requiring reviewers to run the code themselves.

Verdict

CodeMap solves a real problem with a clean interface, but the 21 stars and version 0.1.0 indicate early-stage software. The documentation is functional and the CLI is straightforward, but test coverage and error handling reflect a project still finding its footing. The credibility score of approximately 0.9% is low, meaning you should expect rough edges. Worth trying for personal projects or low-stakes codebases, but hold off on production pipelines until the project matures -- or consider contributing to help it get there.

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