A collection of search algorithms for teaching and experimenting.

There’s a heavy separation of concerns which leads to many tiny classes with a small scope. The library might be a bit overwhelming and seem to be an overkill, but it should allow us to solve many different problems with many algorithms to better understand their behavior.

There’s a generic SearchAlgorithm implementation that can be extended to implement (graph)-DFS, BFS, Dijkstra’s Algorithm, A*. Currently only DFS and BFS are implemented.

• space.py: Space, PredefinedSpace, RandomAccessSpace, Problem

• search.py: Node, SearchAlgorithm, Open
• dfs.py: DFS(SearchAlgorithm), DFS.Open(SearchAlgorithm.Open)
• bfs.py: BFS(SearchAlgorithm), BFS.Open(SearchAlgorithm.Open)
• dijkstra.py: Dijkstra(SearchAlgorithm), Dijkstra.Open(SearchAlgorithm.Open)

• nm_puzzle.py: class NMPuzzle(Space, RandomAccessSpace)

-board2d.py: class Board2D(Space, RandomAccessSpace) -bomb.py: class Bombs2D(Space, RandomAccessSpace) -sokoban.py: class Sokoban(Space, RandomAccessSpace)

• main.py: Has a super simple benchmark.