A web-based graph exploration and visualization tool built with a plugin-based architecture. Load graphs from multiple data sources (CSV, JSON, XML) and explore them interactively through three synchronized views — Tree, Bird's Eye, and Main — using two distinct visualizer styles.
Load graphs from CSV, JSON, or XML sources. All active workspaces are listed with their node and edge counts.
Nodes are rendered as rich attribute cards. Ideal for exploring graphs with detailed node properties.
Nodes are rendered as compact circles connected by edges. Best suited for large graphs where structure matters more than individual node details. Click any node to inspect its properties.
Switch between visualizers at any time using the dropdown in the toolbar.
The toolbar exposes a search bar for finding nodes by name and a filter input
for attribute-based queries (e.g. Age > 30). For more direct control, the built-in
CLI at the bottom of the screen lets you create and delete nodes and edges without
leaving the visualizer.
- Aleksa Ćurčić
- Maksim Vasić
- Milan Kačarević
- Miomir Dujanović
- Sara Stojkov
First, activate your virtual environment from the project root:
Windows:
.venv\Scripts\activate
Unix/Mac:
source .venv/bin/activateThen run the install script to install all components:
Windows:
scripts/installation/install.batUnix/Mac:
./scripts/installation/install.shIf the script is not executable, run:
chmod +x scripts/installation/install.sh
./scripts/installation/install.shBoth Django and Flask are fully independent web applications. Each can be run and used on its own. They do not depend on each other.
cd graph_explorer/django_app
python manage.py runserverDjango will be available at http://127.0.0.1:8000
cd graph_explorer/flask_app
python -m runFlask will be available at http://127.0.0.1:5000
Both apps provide the same functionality independently. You do not need to run both at the same time - each one is a complete standalone application.