A tool to generate comprehensive Markdown artifacts of directory structures and file contents
Project description
CodeMapper
Overview
[!IMPORTANT] CodeMapper: Bridging Code Understanding for AI and Human Analysis Install:
pip install codemapper
CodeMapper is a powerful Python tool that transforms complex codebases into navigable, single-file Markdown artifacts, with a unique ability to bootstrap AI chat prompts for code analysis. Designed with both AI engineers and hobbyist developers in mind, it serves as a bridge between traditional code exploration and modern AI-assisted development workflows. Whether you're training large language models, conducting interactive AI-assisted code reviews, or simply trying to understand a new project, CodeMapper provides a unified, accessible view of your codebase that's optimized for both human readability and AI consumption.
Key Features
-
Unified Code Visualization: Automatically generates a comprehensive Markdown representation of your entire codebase, including:
- Complete directory structure visualization
- Syntax-highlighted code content
- Intelligent file categorization
- Documentation aggregation
-
AI Integration Optimizations:
- Structured output format ideal for LLM training and analysis
- Consistent formatting for improved token efficiency
- Built-in support for common documentation patterns
- Metadata preservation for enhanced context
-
Git-Aware Processing:
- Respects
.gitignorerules by default - Direct GitHub repository URL support
- Handles large repositories efficiently
- Smart binary file detection
- Respects
-
Documentation Focus:
- Dedicated DocMap generation for documentation-heavy projects
- README file prioritization
- Support for multiple documentation directory conventions
- Markdown-native output for universal compatibility
AI Chat Integration
CodeMapper excels at bootstrapping AI chat interactions for code analysis. When you need to understand, debug, or enhance your code with AI assistance:
- Generate a codemap of your project
- Copy the generated markdown into your AI chat
- Start asking detailed questions about your codebase
The AI assistant receives:
- Complete project structure
- All file contents with proper syntax highlighting
- Documentation in context
- Clear navigation structure
This enables the AI to provide more accurate, contextual responses about your code without manual file copying or context limitations.
Use Cases
For AI Engineers
- AI Chat Prompt Bootstrapping: Instantly generate context-rich prompts for AI chat interactions about your code
- Interactive Code Analysis: Seamlessly feed comprehensive codebase context to AI assistants
- Training Data Preparation: Generate consistently formatted codebase representations for model training
- Documentation Generation: Train models on well-structured documentation patterns
- Code Understanding: Feed entire codebases to LLMs for comprehensive analysis
Example AI Chat Workflow:
# Generate a codemap for your project
codemapper /path/to/project
# The generated codemap can be directly used in AI chat prompts:
"Here's my project structure and code, help me understand the dependency flow:
[paste _codemap.md content]"
For Hobbyists
- Project Exploration: Quickly understand new codebases without complex IDE setup
- Documentation Creation: Generate comprehensive project documentation automatically
- Code Reviews: Facilitate easier code reviews with a unified view
- Learning Tool: Study and understand how different projects are structured
Getting Started
# Install from PyPI
pip install codemapper
# Basic usage
codemapper /path/to/project
# Generate documentation map
codemapper --docs /path/to/project
# Process GitHub repository
codemapper https://github.com/username/repo
Example Output
CodeMapper generates two main types of outputs:
-
CodeMap (
project_codemap.md):- Complete directory tree
- File contents with syntax highlighting
- Smart handling of binary and large files
- Navigation-optimized structure
-
DocMap (
project_docmap.md):- Documentation-focused view
- README files
- Documentation directory contents
- Structured for easy consumption
Future Development
CodeMapper is actively developing focused on:
- Expanded format support (JSON, YAML, reStructuredText)
- Enhanced AI integration capabilities
- Real-time code change tracking
- Collaborative annotation features
- Intelligent code pattern recognition
- API access for programmatic integration
Target Audiences
AI Engineers Will Appreciate
- Consistent, clean output format for training data
- Efficient handling of large repositories
- Structured metadata preservation
- Integration-ready design
Hobbyists Will Value
- Simple, straightforward installation
- Clear, readable output
- No complex configuration required
- Immediate utility for project understanding
Installation Options
# For basic installation
pip install codemapper
# For development installation
git clone https://github.com/shaneholloman/codemapper
cd codemapper
pip install -e .
Contributing
CodeMapper welcomes contributions from both AI engineers and hobbyist developers. The project maintains a balance between sophisticated features for AI integration and accessibility for general use.
Visit the GitHub repository to:
- Report issues
- Submit feature requests
- Contribute code
- Join the discussion
Resources
CodeMapper represents a bridge between traditional code exploration and modern AI-assisted development, making codebases more accessible and understandable for everyone from AI researchers to hobbyist developers.
License
This project is licensed under the MIT License - see the LICENSE file for details.
Acknowledgments
- Thanks to the
pathspecandchardetlibraries for enhancing CodeMapper's functionality.
Version History
For a detailed version history, please refer to the changelog.md.
If you find CodeMapper useful, don't forget to star this repository!
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