Repository files navigation

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.

• 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. 🟥

• Python: The primary programming language. 🐍

• Pygame (or similar GUI library): For creating the graphical user interface. 🎮

• Students: Learning about pathfinding algorithms and data structures. 🧑‍🎓

• Game Developers: Visualizing pathfinding for game AI. 🎮

• Algorithm Enthusiasts: Exploring and comparing different search algorithms. 🤓

1. Clone the repository:git clone <repo url>

2. Install Pygame:pip install pygame (orpip install -r requirements.txt if you have one)

3. Run the program:python pathfinding_visualizer.py (orpython3 pathfinding_visualizer.py)

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).