zinating
diff --git a/‎backtracking/all_combinations.py‎
Lines changed: 6 additions & 5 deletions b/‎backtracking/all_combinations.py‎
Lines changed: 6 additions & 5 deletions
diff --git a/‎backtracking/all_permutations.py‎
Lines changed: 9 additions & 5 deletions b/‎backtracking/all_permutations.py‎
Lines changed: 9 additions & 5 deletions
diff --git a/‎backtracking/n_queens.py‎
Lines changed: 6 additions & 4 deletions b/‎backtracking/n_queens.py‎
Lines changed: 6 additions & 4 deletions
diff --git a/‎backtracking/rat_in_maze.py‎
Lines changed: 6 additions & 2 deletions b/‎backtracking/rat_in_maze.py‎
Lines changed: 6 additions & 2 deletions
diff --git a/‎backtracking/sum_of_subsets.py‎
Lines changed: 7 additions & 6 deletions b/‎backtracking/sum_of_subsets.py‎
Lines changed: 7 additions & 6 deletions
@@ -3,15 +3,16 @@
         numbers out of 1 ... n. We use backtracking to solve this problem.
         Time complexity: O(C(n,k)) which is O(n choose k) = O((n!/(k! * (n - k)!)))
 """
+from typing import List
 
 
-def generate_all_combinations(n: int, k: int) -> [[int]]:
+def generate_all_combinations(n: int, k: int) -> List[List[int]]:
     """
     >>> generate_all_combinations(n=4, k=2)
     [[1, 2], [1, 3], [1, 4], [2, 3], [2, 4], [3, 4]]
     """
 
-    result = []
+    result: List[List[int]] = []
     create_all_state(1, n, k, [], result)
     return result
 
@@ -20,8 +21,8 @@ def create_all_state(
     increment: int,
     total_number: int,
     level: int,
-    current_list: [int],
-    total_list: [int],
+    current_list: List[int],
+    total_list: List[List[int]],
 ) -> None:
     if level == 0:
         total_list.append(current_list[:])
@@ -33,7 +34,7 @@ def create_all_state(
         current_list.pop()
 
 
-def print_all_state(total_list: [int]) -> None:
+def print_all_state(total_list: List[List[int]]) -> None:
     for i in total_list:
         print(*i)
 
 
@@ -5,14 +5,18 @@
         Time complexity: O(n! * n),
         where n denotes the length of the given sequence.
 """
+from typing import List, Union
 
 
-def generate_all_permutations(sequence: [int]) -> None:
+def generate_all_permutations(sequence: List[Union[int, str]]) -> None:
     create_state_space_tree(sequence, [], 0, [0 for i in range(len(sequence))])
 
 
 def create_state_space_tree(
-    sequence: [int], current_sequence: [int], index: int, index_used: int
+    sequence: List[Union[int, str]],
+    current_sequence: List[Union[int, str]],
+    index: int,
+    index_used: List[int],
 ) -> None:
     """
     Creates a state space tree to iterate through each branch using DFS.
@@ -40,8 +44,8 @@ def create_state_space_tree(
 sequence = list(map(int, input().split()))
 """
 
-sequence = [3, 1, 2, 4]
+sequence: List[Union[int, str]] = [3, 1, 2, 4]
 generate_all_permutations(sequence)
 
-sequence = ["A", "B", "C"]
-generate_all_permutations(sequence)
+sequence_2: List[Union[int, str]] = ["A", "B", "C"]
+generate_all_permutations(sequence_2)
@@ -7,10 +7,12 @@
  diagonal lines.
 
 """
+from typing import List
+
 solution = []
 
 
-def isSafe(board: [[int]], row: int, column: int) -> bool:
+def isSafe(board: List[List[int]], row: int, column: int) -> bool:
     """
     This function returns a boolean value True if it is safe to place a queen there
     considering the current state of the board.
@@ -38,7 +40,7 @@ def isSafe(board: [[int]], row: int, column: int) -> bool:
     return True
 
 
-def solve(board: [[int]], row: int) -> bool:
+def solve(board: List[List[int]], row: int) -> bool:
     """
     It creates a state space tree and calls the safe function until it receives a
     False Boolean and terminates that branch and backtracks to the next
@@ -53,7 +55,7 @@ def solve(board: [[int]], row: int) -> bool:
         solution.append(board)
         printboard(board)
         print()
-        return
+        return True
     for i in range(len(board)):
         """
         For every row it iterates through each column to check if it is feasible to
@@ -68,7 +70,7 @@ def solve(board: [[int]], row: int) -> bool:
     return False
 
 
-def printboard(board: [[int]]) -> None:
+def printboard(board: List[List[int]]) -> None:
     """
     Prints the boards that have a successful combination.
     """
 
@@ -1,4 +1,7 @@
-def solve_maze(maze: [[int]]) -> bool:
+from typing import List
+
+
+def solve_maze(maze: List[List[int]]) -> bool:
     """
     This method solves the "rat in maze" problem.
     In this problem we have some n by n matrix, a start point and an end point.
@@ -67,7 +70,7 @@ def solve_maze(maze: [[int]]) -> bool:
     return solved
 
 
-def run_maze(maze: [[int]], i: int, j: int, solutions: [[int]]) -> bool:
+def run_maze(maze: List[List[int]], i: int, j: int, solutions: List[List[int]]) -> bool:
     """
     This method is recursive starting from (i, j) and going in one of four directions:
     up, down, left, right.
@@ -106,6 +109,7 @@ def run_maze(maze: [[int]], i: int, j: int, solutions: [[int]]) -> bool:
 
             solutions[i][j] = 0
             return False
+    return False
 
 
 if __name__ == "__main__":
 
@@ -6,23 +6,24 @@
         Summation of the chosen numbers must be equal to given number M and one number
         can be used only once.
 """
+from typing import List
 
 
-def generate_sum_of_subsets_soln(nums: [int], max_sum: [int]) -> [int]:
-    result = []
-    path = []
+def generate_sum_of_subsets_soln(nums: List[int], max_sum: int) -> List[List[int]]:
+    result: List[List[int]] = []
+    path: List[int] = []
     num_index = 0
     remaining_nums_sum = sum(nums)
     create_state_space_tree(nums, max_sum, num_index, path, result, remaining_nums_sum)
     return result
 
 
 def create_state_space_tree(
-    nums: [int],
+    nums: List[int],
     max_sum: int,
     num_index: int,
-    path: [int],
-    result: [int],
+    path: List[int],
+    result: List[List[int]],
     remaining_nums_sum: int,
 ) -> None:
     """