https://github.com/lakshayd02/pathfinding_visualization_tool_python
Visualize A* and BFS pathfinding algorithms in real-time with an interactive graphical interface. Explore how these algorithms find the shortest path! 🤖
https://github.com/lakshayd02/pathfinding_visualization_tool_python
astar-algorithm breadth-first-search datastructures-algorithms pathfinding-visualizer pygame python python3
Last synced: 2 months ago
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Visualize A* and BFS pathfinding algorithms in real-time with an interactive graphical interface. Explore how these algorithms find the shortest path! 🤖
- Host: GitHub
- URL: https://github.com/lakshayd02/pathfinding_visualization_tool_python
- Owner: LakshayD02
- Created: 2024-08-26T15:45:10.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2025-02-01T14:17:03.000Z (5 months ago)
- Last Synced: 2025-03-31T16:13:59.045Z (3 months ago)
- Topics: astar-algorithm, breadth-first-search, datastructures-algorithms, pathfinding-visualizer, pygame, python, python3
- Language: Python
- Homepage:
- Size: 32.2 KB
- Stars: 5
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Pathfinding_Visualization_Tool_Python
## Description
This Python tool allows users to visualize the behavior of two popular pathfinding algorithms: A* (A-star) and Breadth-First Search (BFS). It features an intuitive graphical interface where users can interactively set up obstacles, start, and end points on a grid. Users can then watch in real-time as the algorithms calculate and display the shortest path. This tool is excellent for understanding how these algorithms work and comparing their performance.
## Features
* **Algorithm Implementations:** Implements A* (A-star) and Breadth-First Search (BFS) pathfinding algorithms. 🤖
* **Real-time Visualization:** Visualizes the search process of the algorithms in real-time using a graphical user interface. 👀
* **Interactive Grid:** Users can interactively set start and end points, and place obstacles (walls) on the grid. 🧱
* **User Control:** Options to step through the algorithm or run it in real-time. ⏯️
* **Start/End Point Placement:** Click to set the start (green) and end (blue) points. 🟢🔵
* **Obstacle Placement:** Click to place obstacles (walls) on the grid (gray). 🚧
* **Removal:** Right-click to remove obstacles or clear start/end points (back to black). ⬛
* **A* Algorithm Execution:** Press SPACE to run the A* algorithm. ✨
* **BFS Algorithm Execution:** Press B to run the BFS algorithm. 🔍
* **Visual Feedback:**
* **Open Cells (Explored):** Cells being explored turn white. ◻️
* **Closed Cells (Fully Explored):** Cells that have been fully explored turn gray. ⬛
* **Path:** The final shortest path is highlighted in red. 🟥
## Technologies Used
* **Python:** The primary programming language. 🐍
* **Pygame (or similar GUI library):** For creating the graphical user interface. 🎮
## Ideal For
* **Students:** Learning about pathfinding algorithms and data structures. 🧑🎓
* **Game Developers:** Visualizing pathfinding for game AI. 🎮
* **Algorithm Enthusiasts:** Exploring and comparing different search algorithms. 🤓
## How to Run
1. **Clone the repository:** `git clone `
2. **Install Pygame:** `pip install pygame` (or `pip install -r requirements.txt` if you have one)
3. **Run the program:** `python pathfinding_visualizer.py` (or `python3 pathfinding_visualizer.py`)
## How to Use
1. Click on the grid to set the start (green) and end (blue) points.
2. Click on cells to create obstacles (walls - gray).
3. Right-click to remove obstacles or clear start/end points.
4. Press SPACE to run the A* algorithm.
5. Press B to run the BFS algorithm.
6. Observe the visualization of the search process and the final path (red).
# A* Algorithm
# Breadth First Search (BFS)
