add type hints

Author: Udaychauhan1724

searches/breadth_first_search_maze.py

@@ -1,7 +1,8 @@
-# MAZE TRAVERSAL 
 """
 Breadth-first search (BFS) is an algorithm for traversing or searching tree or graph data structures. It begins at a root node (or an arbitrary node in a graph) and explores all of the neighbor nodes at the present depth before moving on to the nodes at the next depth level.
-This implementation of BFS is used to traverse a maze represented as a 2D grid. The maze contains walls (#), open paths ( ), a starting point (O), and a target point (X). The algorithm finds the shortest path from the starting point to the target point while avoiding walls."""
+This implementation of BFS is used to traverse a maze represented as a 2D grid. The maze contains walls (#), open paths ( ), a starting point (O), and a target point (X). The algorithm finds the shortest path from the starting point to the target point while avoiding walls.
+"""
+
 import curses
 from curses import wrapper
 import queue
@@ -20,7 +21,7 @@
 #     ["#", "#", "#", "#", "#", "#", "#", "X", "#"]
 # ]
 
-maze = [
+maze: list[list[str]] = [
     ["#", "#", "#", "#", "#", "#", "#", "#", "#", "#", "#", "#", "#", "#", "#", "#", "#", "#", "#", "#"],
     ["#", "O", " ", " ", " ", " ", " ", " ", " ", " ", " ", " ", " ", " ", " ", " ", " ", " ", " ", "#"],
     ["#", "#", "#", "#", "#", " ", "#", "#", "#", "#", "#", "#", "#", " ", "#", "#", "#", "#", " ", "#"],
@@ -43,7 +44,7 @@
     ["#", "#", "#", "#", "#", "#", "#", "#", "#", "#", "#", "#", "#", "#", "#", "#", "#", "#", "#", "#"]
 ]
 
-def print_maze(maze, stdscr, visited, path=[]):
+def print_maze(maze: list[list[str]], stdscr: curses.window, visited: set[tuple[int, int]], path: list[tuple[int, int]] = []) -> None:
     blue = curses.color_pair(1)
     red = curses.color_pair(2)
     green = curses.color_pair(3)
@@ -58,14 +59,14 @@ def print_maze(maze, stdscr, visited, path=[]):
                 stdscr.addstr(row, column*2, j, blue)
 
 
-def find(maze, start): #to check and return starting position in maze
+def find(maze: list[list[str]], start: str) -> tuple[int, int] | None: #to check and return starting position in maze
     for row, i in enumerate(maze):
         for column, j in enumerate(i):
             if j == start:
                 return (row,column) # return tuple of row, column location of element in the maze
     return None
 
-def find_neighbours(maze, row, col): #search and return each neighbour of a particular cell, without checking if its a wall or not
+def find_neighbours(maze: list[list[str]], row: int, col: int) -> list[tuple[int, int]]:
     neighbours = []
 
     if row > 0: # for UP
@@ -79,7 +80,7 @@ def find_neighbours(maze, row, col): #search and return each neighbour of a part
     return neighbours
 
 
-def traverse(maze, stdscr): #implementing bfs traversal
+def traverse(maze: list[list[str]], stdscr: curses.window) -> list[tuple[int, int]] | None: #implementing bfs traversal
     start = "O"
     target = "X"
     start_pos = find(maze, start)
@@ -118,7 +119,7 @@ def traverse(maze, stdscr): #implementing bfs traversal
             visited.add(nbr)
 
 
-def main(stdscr):
+def main(stdscr: curses.window) -> None:
     curses.init_pair(1, curses.COLOR_BLUE, curses.COLOR_BLACK)
     curses.init_pair(2, curses.COLOR_RED, curses.COLOR_BLACK)
     curses.init_pair(3, curses.COLOR_GREEN, curses.COLOR_BLACK)