Analysis updated 2026-05-18
Generate a dependency graph showing how files in a Python project import each other.
Explore an interactive call tree starting from any function in your codebase.
Export a function call chain as a Mermaid diagram for your documentation.
Spot the most complex or longest files in a project with a color-coded heatmap.
| kirito-chen/codemap | aevella/sky-pc-mcp-companion | alicankiraz1/gemma-4-31b-mtp-vllm-server | |
|---|---|---|---|
| Stars | 26 | 26 | 26 |
| Language | Python | Python | Python |
| Setup difficulty | easy | moderate | hard |
| Complexity | 2/5 | 3/5 | 4/5 |
| Audience | developer | vibe coder | ops devops |
Figures from each repo's GitHub metadata at analysis time.
CodeMap is a Python tool that generates visual diagrams from a Python codebase. You point it at a folder of Python files and it produces interactive charts you can open in a web browser, without needing to configure anything first. It creates four types of visuals. A dependency graph shows which files or modules in a project import from which other files, making it easier to see how the pieces connect. A call tree shows an interactive mind-map of how functions call other functions, starting from a function you name. A call graph traces a chain of function calls from one entry point and can export that chain in a format called Mermaid, which embeds directly into Markdown documents. A heatmap colors the codebase by complexity or line count, letting you see at a glance which files are the most tangled or the longest. The tool runs from a command line. You type a short command, point it at your project directory or a specific file, and it writes an HTML file you can open in any browser. There is also a Python API for developers who want to call these functions from inside their own scripts rather than from the terminal. The complexity measurement uses a standard metric called cyclomatic complexity, which counts the number of independent paths through a piece of code. Higher numbers generally mean harder-to-read code. The line-count metric ignores blank lines and comments. A third metric for commit history is listed in the project structure but noted as not yet implemented. Installation requires cloning the repository and running a standard Python package install command. The project is designed to be extended to other programming languages in the future, though only Python is supported in this version.
A command-line tool that turns a Python codebase into interactive dependency graphs, call trees, and complexity heatmaps.
Mainly Python. The stack also includes Python, Mermaid, HTML.
The README does not state a license.
Setup difficulty is rated easy, with roughly 5min to a first successful run.
Mainly developer.
This repo across BitVibe Labs
Verify against the repo before relying on details.