GUI: Web Interface for Network Exploration

Warning

Development Mode Only: The GUI is intended for local development and exploration. Do not expose it to the public internet without proper authentication and security hardening. See GUI Deployment Guide for production configuration.

The py3plex GUI provides a web-based interface for interactive multilayer network exploration.

Features:

Load networks from various file formats without code
Interactive, zoomable visualizations
Compute statistics via point-and-click menus
Detect communities and visualize them
Export results for further analysis

This section covers:

Py3plex GUI — Loading data, exploring networks, running analyses
GUI Deployment Guide — Running locally, Docker, production setup
GUI API Reference — Backend API documentation
Py3plex GUI Architecture — How the GUI is built
GUI Testing Guide — Testing infrastructure

Running the GUI Locally

Quick start (Docker - Recommended):

# Clone the repository
git clone https://github.com/SkBlaz/py3plex.git
cd py3plex/gui

# Copy environment configuration
cp .env.example .env

# Start all services
make up

# Open browser to http://localhost:8080

Alternative: Install from source:

# Install with GUI extras
pip install py3plex[gui]

# Or install from source
git clone https://github.com/SkBlaz/py3plex.git
cd py3plex
pip install -e ".[gui]"

# Navigate to GUI directory and start services
cd gui
make up

The GUI will be available at http://localhost:8080. See GUI Deployment Guide for detailed setup instructions and troubleshooting.

GUI Actions vs py3plex APIs

The GUI provides a point-and-click interface for common py3plex operations. Here’s how GUI actions map to Python API calls:

GUI Action	Equivalent Python API
Load Network (upload file)	`network = multinet.multi_layer_network().load_network(file_path, input_type="...")`
Compute Statistics → Basic Stats	`network.basic_stats()`
Compute Statistics → Layer Density	`from py3plex.algorithms.statistics import multilayer_statistics as mls` `mls.layer_density(network, layer_name)`
Detect Communities → Louvain	`from py3plex.algorithms.community_detection import community_louvain` `partition = community_louvain.best_partition(network.get_layers()[layer])`
Compute Centrality → Degree	`from py3plex.algorithms.multilayer_algorithms.centrality import MultilayerCentrality` `calc = MultilayerCentrality(network)` `degree = calc.overlapping_degree_centrality()`
Visualize Network	`from py3plex.visualization.multilayer import draw_multilayer_default` `draw_multilayer_default([network], display=True)`
Export → JSON	`network.save_network("output.json", output_type="json")`

This mapping helps you transition from GUI exploration to programmatic analysis.

When to Use the GUI

Use GUI for:

Domain experts who prefer not to write Python
Quick exploratory analysis of new datasets
Demonstrations and teaching
Collaborative work with mixed technical backgrounds

Use Python library for:

Production pipelines and automation
Reproducible analysis workflows
Advanced customization
Large-scale processing

Start with GUI Deployment Guide to run the GUI, then Py3plex GUI for usage.