A lightweight Maze Solver built from scratch with a focus on clean architecture, pathfinding algorithms, optimization, and problem-solving fundamentals.
The goal of this project is to create a simple and efficient maze solving system while understanding search algorithms, navigation logic, and decision-making processes.
- Maze generation system
- Grid-based environment
- Start and goal points
- Wall and path handling
- Pathfinding algorithms
- Shortest path calculation
- Step-by-step visualization
- Performance tracking
The project focuses on separating important components:
- Maze Engine
- Grid System
- Node System
- Pathfinding System
- Search Algorithms
- Visualization System
- State Management
- Performance Analyzer
- Setup project structure
- Create maze grid
- Add walls and paths
- Create visualization system
- Implement Breadth First Search (BFS)
- Implement Depth First Search (DFS)
- Add shortest path detection
- Add path tracking
- Implement A* Search
- Add Dijkstra Algorithm
- Add maze generation algorithms
- Compare algorithm performance
- Improve solving speed
- Optimize memory usage
- Refactor architecture
- Add documentation
- Release stable version
- Python
- Minimal dependencies
Build a lightweight maze solving system that demonstrates pathfinding, search algorithms, optimization, and intelligent navigation.
Open source for learning and experimentation.