





lowercase      :       Union[str, Any]									=  {
    """A""": ["""B""", """C""", """E"""],
    """B""": ["""A""", """D""", """E"""],
    """C""": ["""A""", """F""", """G"""],
    """D""": ["""B"""],
    """E""": ["""A""", """B""", """D"""],
    """F""": ["""C"""],
    """G""": ["""C"""],
}



def A_	(		A__		,      A__		,      A__				)  ->		list[str]:
       a__						:	List[str] =				set()
       # keep track of all the paths to be checked
       a__						:	Union[str, Any] =				[[start]]

       # return path if start is goal
       if start == goal:
              return [start]

       # keeps looping until all possible paths have been checked
       while queue:
              # pop the first path from the queue
              a__						:	Tuple =				queue.pop(0				)
              # get the last node from the path
              a__						:	Optional[int] =				path[-1]
              if node not in explored:
                     a__						:	List[str] =				graph[node]
                     # go through all neighbour nodes, construct a new path and
                     # push it into the queue
                     for neighbour in neighbours:
                            a__						:	Optional[Any] =				list(A__				)
                            new_path.append(A__				)
                            queue.append(A__				)
                            # return path if neighbour is goal
                            if neighbour == goal:
                                   return new_path

            # mark node as explored
                     explored.add(A__				)

    # in case there's no path between the 2 nodes
       return []



def A_	(		A__		,      A__		,      A__				)  ->		int:
       if not graph or start not in graph or target not in graph:
              return -1
       if start == target:
              return 0
       a__						:	Tuple =				[start]
       a__						:	Union[str, Any] =				set(A__				)
       # Keep tab on distances from `start` node.
       a__						:	Optional[Any] =				{start: 0, target: -1}
       while queue:
              a__						:	str =				queue.pop(0				)
              if node == target:
                     a__						:	List[Any] =				(
                         dist[node] if dist[target] == -1 else min(dist[target]		,      dist[node]				)
                     )
              for adjacent in graph[node]:
                     if adjacent not in visited:
                            visited.add(A__				)
                            queue.append(A__				)
                            a__						:	int =				dist[node] + 1
       return dist[target]


if __name__ == "__main__":
    print(bfs_shortest_path(demo_graph, """G""", """D"""))  # returns ['G', 'C', 'A', 'B', 'D']
    print(bfs_shortest_path_distance(demo_graph, """G""", """D"""))  # returns 4









def 		lowerCAmelCase_    (  __UpperCAmelCase:			int      )      ->	int:
    if not isinstance(__UpperCAmelCase		,   __UpperCAmelCase      ) or number < 0:
        raise ValueError('''Input must be a non-negative integer'''      )

    UpperCamelCase__							:				Optional[Any]          =      0
    while number:
        # This way we arrive at next set bit (next 1) instead of looping
        # through each bit and checking for 1s hence the
        # loop won't run 32 times it will only run the number of `1` times
        number &= number - 1
        count += 1
    return count


if __name__ == "__main__":
  import doctest

  doctest.testmod()

