A pathfinding visualizer made in Python and Pygame. This project aims to provide a fun and interactive way to learn about popular pathfinding algorithms such as Dijkstra's, A* and other supported algorithms.

• Visualizes popular pathfinding algorithms such as Dijkstra's and A*.
• Visualizes popular maze generation algorithms like Recursive division and Prim's algorithm.
• Feature to run all algorithms b2b to compare their performance.
• Step-by-step animation of the search process, allowing you to see how the algorithms work.
• Option to place obstacles on the grid to create custom maps.
• Selectable starting and ending points on the grid.
• Configurable speed of the animation.
• Configurable grid size
• Clean and intuitive user interface.

The following pathfinding algorithms are currently supported in this visualizer:

1. Depth First Search (DFS): A traversal-based algorithm that goes as far as possible along each branch before backtracking. Not commonly used for pathfinding.
2. Breadth First Search (BFS): A traversal-based algorithm that explores all neighbors of a node before moving on to the next level. Guaranteed to find the shortest path in unweighted graphs.
3. Greedy Best First Search: A heuristic search algorithm that prioritizes visiting nodes closest to the goal. Not guaranteed to find the shortest path, but often faster.
4. A* Search: A heuristic search algorithm that combines the strengths of BFS and greedy best first search. Efficient for many types of graphs.
5. Dijkstra's Search: A shortest path algorithm that uses a priority queue to prioritize visiting nodes with the smallest known cost. Guaranteed to find the shortest path in weighted graphs.

Each algorithm uses a different approach to finding the shortest path between two points on a graph. Choose the one that best fits your use case and watch it in action.

• Python 3.10 and above: You can download the latest version of Python from the official website (https://www.python.org/downloads/).
• Pygame: You can install Pygame by running 'pip install pygame' in your terminal.

• Download the project repository to your local machine.
• Navigate to the project directory.
• Run python3 run.pyw if on Linux or Mac
• Run python run.pyw if on Windows

1. --cell-size Usage: python run.pyw --cell-size:<int>

This project is open to contributions, bug reports, and suggestions. If you've found a bug or have a suggestion, please open an issue.

This project is licensed under the MIT License.

Enjoy visualizing pathfinding algorithms!