GraphDisplay – Interactive Graph & Tree Visualizer

Project Overview

GraphDisplay is a Python library designed to simplify the visualization and interaction with graph and tree data structures in educational and analytical contexts. Built for versatility and ease of use, it enables users to visualize, manipulate, and persist custom layouts through an intuitive GUI—with no dependencies beyond Python’s standard libraries.

Key Features

  • Easy to install and use
    Install via pip install graphdisplay, then import core components:

    from graphdisplay import GraphGUI, Graph, BinarySearchTree, AVLTree

  • Supports diverse structures
    Works with directed and undirected graphs, binary search trees, and AVL trees—all using implementations aligned with standard classroom code.

  • Interactive visualization
    Features drag‑and‑drop node positioning, multiple concurrent windows, and layout persistence across sessions.

  • Modular architecture
    Decouples data structures from the GUI, enabling future extensions or integration into other tools.

How It Works (Conceptual Overview)

  1. Define your structure
    In pure Python, create or load a Graph, BinarySearchTree, or AVLTree.

  2. Visualize with ease
    Instantiate GraphGUI(your_structure). A Tkinter‑based window opens, visualizing the structure and enabling intuitive interaction.

  3. Save your progress
    Layouts are auto‑saved (e.g., JSON), allowing users to revisit or share their visual configurations effortlessly.

Tools & Professional Skills Demonstrated

  • Python packaging and distribution – published on PyPI under the MIT license, mastering versioning, setup tools and twine.
  • GUI development with Tkinter – event‑driven interfaces for responsive visualization and multi‑window management.
  • State persistence – automatic saving of graph layouts with session recovery across exits and reopenings.
  • Educational software design – aligned with standard course structures to maximize pedagogical value.

Use Cases & Impact

  • Educational tool – enables intuitive exploration of data structures for students and educators.
  • Rapid prototyping – lets developers visualize custom algorithms and structures without extra setup.
  • Extensible foundation – serves as a base for new structure types or integration with external plotting tools.

Practical Example

from graphdisplay import Graph, GraphGUI

# Create a weighted directed graph
g = Graph(['A', 'B', 'C'])
g.addEdge('A', 'B', 5)
g.addEdge('A', 'C', 7)

GraphGUI(g)

Final Thoughts

GraphDisplay bridges the gap between code and visualization. The project demonstrates a full software‑engineering life‑cycle: conception, development, testing, packaging, and distribution, while fostering understanding of fundamental data structures.

For code, issues, or contributions, visit the GraphDisplay GitHub repository.