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Pathfinding Visualizer

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.



A* Search Dijkstra's Search
Greedy Best-First Search Breadth-First Search
Depth-First Search Results


  • 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.

Supported Algorithms

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 (
  • 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

Command Line Arguments

  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!