


'''simple docstring'''


_UpperCamelCase 							=  {
    """A""": ["""B""", """C""", """E"""],
    """B""": ["""A""", """D""", """E"""],
    """C""": ["""A""", """F""", """G"""],
    """D""": ["""B"""],
    """E""": ["""A""", """B""", """D"""],
    """F""": ["""C"""],
    """G""": ["""C"""],
}


def 		_lowercase (SCREAMING_SNAKE_CASE       ,					SCREAMING_SNAKE_CASE       ,					SCREAMING_SNAKE_CASE							):




     '''simple docstring'''





     __A	:       List[Any]      =							set()
     # keep track of all the paths to be checked
     __A	:       Dict      =							[[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	:       str      =							queue.pop(0							)
          # get the last node from the path
          __A	:       List[Any]      =							path[-1]
          if node not in explored:
               __A	:       List[Any]      =							graph[node]
               # go through all neighbour nodes, construct a new path and
               # push it into the queue
               for neighbour in neighbours:
                    __A	:       Any      =							list(SCREAMING_SNAKE_CASE							)
                    new_path.append(SCREAMING_SNAKE_CASE							)
                    queue.append(SCREAMING_SNAKE_CASE							)
                    # return path if neighbour is goal
                    if neighbour == goal:
                         return new_path

            # mark node as explored
               explored.add(SCREAMING_SNAKE_CASE							)

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


def 		_lowercase (SCREAMING_SNAKE_CASE       ,					SCREAMING_SNAKE_CASE       ,					SCREAMING_SNAKE_CASE							):




     '''simple docstring'''





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





'''simple docstring'''


def 		_lowercase (SCREAMING_SNAKE_CASE       ,					SCREAMING_SNAKE_CASE = " "							):




     '''simple docstring'''





     __A	:       List[str]      =							[]

     __A	:       Tuple      =							0
     for index, char in enumerate(SCREAMING_SNAKE_CASE							):
          if char == separator:
               split_words.append(string[last_index:index]							)
               __A	:       Union[str, Any]      =							index + 1
          elif index + 1 == len(SCREAMING_SNAKE_CASE							):
               split_words.append(string[last_index : index + 1]							)
     return split_words


if __name__ == "__main__":
      from doctest import testmod

      testmod()

