update

Search_Algorithms/Search_Algorithms.py

@@ -34,6 +34,7 @@ def DepthFirstSearch(state, successor, isgoal):
             if next_state not in explored:
                 explored.add(next_state)
                 path2 = path + [next_state]
+                print(path2)
                 toDo.append(path2)
     return "Error Path not found"
 

Search_Algorithms/solution testing.py

@@ -19,11 +19,11 @@ grid = ((1, 0, 0, 0, 0, 0, 0, 0, 0),
 
 # sln = (Search_Algorithms.BreadthFirstSearch(grid, Sucessors.sudoku_successor, is_goal.is_goal_sudoku)[-1])
 
-sln = (Search_Algorithms.DepthFirstSearch(
-    grid, Sucessors.sudoku_successor, is_goal.is_goal_sudoku)[-1])
-
-for rows in sln:
-    print(rows)
+# sln = (Search_Algorithms.DepthFirstSearch(
+#     grid, Sucessors.sudoku_successor, is_goal.is_goal_sudoku)[-1])
+#
+# for rows in sln:
+#     print(rows)
 
 # N Queens
 board = ((False, False, False, False, False, False, False, False, False),
@@ -38,14 +38,14 @@ board = ((False, False, False, False, False, False, False, False, False),
 
 
 # sln = (Search_Algorithms.BreadthFirstSearch(board, Sucessors.queens_successor, is_goal.is_goal_queens)[-1])
-
-sln = (Search_Algorithms.DepthFirstSearch(
-    board, Sucessors.queens_successor, is_goal.is_goal_queens)[-1])
-
-output_tuple = tuple(tuple("Q" if value else "." for value in sln)
-                     for sln in sln)
-for rows in output_tuple:
-    print(rows)
+#
+# sln = (Search_Algorithms.DepthFirstSearch(
+#     board, Sucessors.queens_successor, is_goal.is_goal_queens)[-1])
+#
+# output_tuple = tuple(tuple("Q" if value else "." for value in sln)
+#                      for sln in sln)
+# for rows in output_tuple:
+#     print(rows)
 
 
 # Sliding Puzzle
@@ -55,8 +55,17 @@ initial_puzzle = (
     (5, 0, 6),
     (8, 3, 1)
 )
+#
+# sln = (Search_Algorithms.BreadthFirstSearch(initial_puzzle, Sucessors.puzzle_successor, is_goal.is_goal_puzzle)[-1])
+#
+# if sln:
+#     for rows in sln:
+#         print(rows)
+# else:
+#     print("No solution found")
+
 
-sln = (Search_Algorithms.BreadthFirstSearch(initial_puzzle, Sucessors.puzzle_successor, is_goal.is_goal_puzzle)[-1])
+sln = (Search_Algorithms.DepthFirstSearch(initial_puzzle, Sucessors.puzzle_successor, is_goal.is_goal_puzzle)[-1])
 
 if sln:
     for rows in sln: