Visualization

Hypergraph-DB provides built-in visualization capabilities through web-based interactive displays.

HypergraphViewer Class

hyperdb.draw.HypergraphViewer

HypergraphViewer(
    hypergraph_db: HypergraphDB, port: int = 8080
)

Hypergraph visualization tool

Source code in hyperdb/draw.py

def __init__(self, hypergraph_db: HypergraphDB, port: int = 8080):
    self.hypergraph_db = hypergraph_db
    self.port = port
    self.html_content = self._generate_html_with_data()

hypergraph_db instance-attribute

hypergraph_db = hypergraph_db

port instance-attribute

port = port

html_content instance-attribute

html_content = _generate_html_with_data()

start_server

start_server(open_browser: bool = True)

Start simple HTTP server

Source code in hyperdb/draw.py

def start_server(self, open_browser: bool = True):
    """Start simple HTTP server"""

    class CustomHTTPRequestHandler(http.server.BaseHTTPRequestHandler):
        def __init__(self, html_content, *args, **kwargs):
            self.html_content = html_content
            super().__init__(*args, **kwargs)

        def do_GET(self):
            self.send_response(200)
            self.send_header('Content-type', 'text/html; charset=utf-8')
            self.end_headers()
            self.wfile.write(self.html_content.encode('utf-8'))

        def log_message(self, format, *args):
            # Disable log output
            pass

    def run_server():
        handler = lambda *args, **kwargs: CustomHTTPRequestHandler(self.html_content, *args, **kwargs)
        self.httpd = socketserver.TCPServer(("127.0.0.1", self.port), handler)
        self.httpd.serve_forever()

    # Start server in new thread
    server_thread = threading.Thread(target=run_server, daemon=True)
    server_thread.start()

    if open_browser:
        # Wait for server to start
        import time
        time.sleep(1)

        # Open browser
        url = f"http://127.0.0.1:{self.port}"
        print(f"🚀 Hypergraph visualization server started: {url}")
        webbrowser.open(url)

    return server_thread

stop_server

stop_server()

Stop the HTTP server

Source code in hyperdb/draw.py

def stop_server(self):
    """Stop the HTTP server"""
    if hasattr(self, 'httpd'):
        self.httpd.shutdown()
        self.httpd.server_close()

Usage Example

from hyperdb import HypergraphDB

# Create and populate hypergraph
hg = HypergraphDB()
hg.add_v(1, {"name": "Alice"})
hg.add_v(2, {"name": "Bob"})
hg.add_v(3, {"name": "Charlie"})

hg.add_e((1, 2), {"relation": "friends"})
hg.add_e((1, 2, 3), {"relation": "team"})

# Visualize - opens in browser
hg.draw()

Visualization Features

• Interactive Display: Click and drag to explore the hypergraph structure
• Vertex Information: Hover over vertices to see their attributes
• Hyperedge Visualization: Visual representation of multi-way connections
• Web-based: Runs in your default web browser
• Real-time Updates: Reflects current hypergraph state

Customization

The visualization can be customized by modifying the HTML template located in:

hyperdb/templates/hypergraph_viewer.html

Available Options

When calling draw(), you can specify:

• port: Port number for the web server (default: 8080)
• open_browser: Whether to automatically open the browser (default: True)

# Use custom port
hg.draw(port=9000)

# Don't automatically open browser
hg.draw(open_browser=False)

Technical Details

The visualization system:

1. Converts hypergraph data to JSON format
2. Generates HTML with embedded data and D3.js visualization
3. Starts a local web server
4. Opens the visualization in your default browser

The visualization uses: - D3.js for interactive graphics - Local HTTP server for serving content - JSON data embedding for efficient data transfer

Troubleshooting

Common Issues

Port already in use:

# Try a different port
hg.draw(port=8081)

Browser doesn't open: - Manually navigate to http://localhost:8080 (or your specified port) - Check firewall settings

Visualization appears empty: - Ensure your hypergraph has vertices and edges - Check browser console for JavaScript errors

Performance Considerations

• Large hypergraphs (>1000 vertices) may render slowly
• Consider filtering or sampling for very large datasets
• The visualization loads all data into browser memory

Future Enhancements

Planned improvements include:

• Export capabilities (PNG, SVG, PDF)
• Layout algorithms for better visualization
• Filtering options for large graphs
• Custom styling and themes
• Interactive editing capabilities