GitProbe

Turn any GitHub repository into comprehensive code analysis with interactive call graphs and multi-language support.

🚀 Features

• Multi-language Analysis: Support for Python, JavaScript, TypeScript, Rust, Go, C, and C++
• Tree-sitter Powered: Advanced syntax parsing with tree-sitter for accurate code analysis
• Call Graph Generation: Interactive visualizations showing function relationships
• Web API: RESTful API for integration with other tools and frontends
• Real-time Analysis: Live progress tracking and results
• Repository Insights: File structure, function counts, and relationship mapping
• LLM-Ready Output: Structured JSON optimized for AI analysis

📸 Preview

GitProbe's interactive call graph visualization showing function relationships and code structure analysis

📚 Requirements

• Python 3.8+
• Git (for repository cloning)
• Internet access for GitHub repository analysis

📦 Installation

# Clone the repository
git clone https://github.com/your-org/gitprobe.git
cd gitprobe

# Create virtual environment
python -m venv env
source env/bin/activate  # On Windows: env\Scripts\activate

# Install dependencies
pip install -r requirements.txt

💡 Command line usage

Start the Web Server

# Start GitProbe server
./gitprobe server

# Server will be available at http://localhost:8000
# API documentation at http://localhost:8000/docs

CLI Analysis (Legacy)

# Analyze a GitHub repository
python -m gitprobe https://github.com/user/repository

# With custom output directory
python -m gitprobe https://github.com/user/repository --output ./analysis/

🌐 Web API Usage

Analyze Repository

# Start analysis
curl -X POST "http://localhost:8000/analyze" \
  -H "Content-Type: application/json" \
  -d '{"github_url": "https://github.com/psf/requests"}'

Python API Client

import requests

# Analyze repository
response = requests.post("http://localhost:8000/analyze", json={
    "github_url": "https://github.com/psf/requests",
    "include_patterns": ["*.py"],
    "exclude_patterns": ["*test*", "docs/"]
})

result = response.json()
print(f"Found {result['data']['summary']['total_functions']} functions")
print(f"Languages: {result['data']['summary']['languages_analyzed']}")

Example Response

{
  "status": "success",
  "data": {
    "summary": {
      "total_functions": 235,
      "total_calls": 657,
      "languages_analyzed": ["python"],
      "files_analyzed": 45
    },
    "functions": [...],
    "relationships": [...],
    "visualization": {
      "cytoscape": {...}
    }
  }
}

🧪 Testing

GitProbe includes a comprehensive integration test suite that validates all language analyzers:

# Install test dependencies
pip install rich

# Run quick tests (1 repo per language)
python tests/test_integration.py --quick

# Test all languages comprehensive
python tests/test_integration.py

# Test specific language
python tests/test_integration.py --language python

# Verbose output with detailed progress
python tests/test_integration.py --verbose

# JSON output for CI/CD
python tests/test_integration.py --json > results.json

Test Coverage

• Python: rich, requests, flask, cpython
• JavaScript: lodash, axios, express, node.js
• TypeScript: vscode, typescript, angular
• Rust: clap, ripgrep, rust compiler
• Go: cobra, hugo, kubernetes
• C: cJSON, libuv, curl
• C++: fmt, catch2, protobuf

🏗️ Architecture

gitprobe/
├── src/gitprobe/
│   ├── analysis/           # Core analysis engine
│   │   ├── analysis_service.py
│   │   ├── call_graph_analyzer.py
│   │   └── repo_analyzer.py
│   ├── analyzers/          # Language-specific parsers
│   │   ├── python.py       # Python tree-sitter analyzer
│   │   ├── javascript.py   # JavaScript/TypeScript analyzer
│   │   ├── rust.py         # Rust analyzer
│   │   ├── go.py           # Go analyzer
│   │   ├── c_cpp.py        # C/C++ analyzer
│   │   └── ...
│   ├── web/               # FastAPI web server
│   │   └── server.py
│   └── models/            # Data models
│       └── ...
├── tests/                 # Integration test suite
│   ├── test_integration.py
│   └── README.md
└── requirements.txt

🎯 Language Support

Language	Functions	Calls	Classes	Imports	Status
Python	✅	✅	✅	✅	Stable
JavaScript	✅	✅	✅	✅	Stable
TypeScript	✅	✅	✅	✅	Stable
Rust	✅	✅	✅	✅	Stable
Go	✅	✅	✅	✅	Stable
C	✅	✅	❌	✅	Stable
C++	✅	✅	✅	✅	Stable

🔧 Configuration

Environment Variables

# Optional: Custom server configuration
export GITPROBE_HOST=0.0.0.0
export GITPROBE_PORT=8000

Analysis Options

# Include/exclude patterns
{
  "github_url": "https://github.com/user/repo",
  "include_patterns": ["*.py", "*.js"],
  "exclude_patterns": ["*test*", "node_modules/", "__pycache__/"]
}

🤝 Contributing

Running Tests

# Start GitProbe server (in one terminal)
./gitprobe server

# Run integration tests (in another terminal)
python tests/test_integration.py --quick

Adding New Languages

1. Create analyzer in src/gitprobe/analyzers/
2. Add tree-sitter language dependency to requirements.txt
3. Register analyzer in analysis service
4. Add test repositories to tests/test_integration.py

Development Setup

# Install in development mode
pip install -e .

# Install development dependencies
pip install pytest black isort mypy

# Run code formatting
black .
isort .

🛠️ Stack

• Tree-sitter - Syntax parsing and analysis
• FastAPI - Web API framework
• Pydantic - Data validation and modeling
• Rich - Beautiful terminal output
• Cytoscape.js - Graph visualization (frontend)

🐛 Known Issues

• Large repositories (>1000 functions) are limited to 900 functions for performance
• Some complex C++ template syntax may not parse correctly
• Private repositories require local cloning

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

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GitProbe - Comprehensive multi-language code analysis with interactive call graphs.