






__UpperCamelCase      :       Optional[int]      			=      {
    """A""": ["""B""", """C""", """E"""],
    """B""": ["""A""", """D""", """E"""],
    """C""": ["""A""", """F""", """G"""],
    """D""": ["""B"""],
    """E""": ["""A""", """B""", """D"""],
    """F""": ["""C"""],
    """G""": ["""C"""],
}



def    __UpperCAmelCase	(				SCREAMING_SNAKE_CASE__:	dict,					SCREAMING_SNAKE_CASE__:	List[str],					SCREAMING_SNAKE_CASE__:	List[str]    )  ->			list[str]:

   """simple docstring"""
   __a				     =    set()
   # keep track of all the paths to be checked
   __a				     =    [[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				     =    queue.pop(0    )
      # get the last node from the path
      __a				     =    path[-1]
      if node not in explored:
         __a				     =    graph[node]
         # go through all neighbour nodes, construct a new path and
         # push it into the queue
         for neighbour in neighbours:
            __a				     =    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    __UpperCAmelCase	(				SCREAMING_SNAKE_CASE__:	dict,					SCREAMING_SNAKE_CASE__:	Tuple,					SCREAMING_SNAKE_CASE__:	Optional[int]    )  ->			int:

   """simple docstring"""
   if not graph or start not in graph or target not in graph:
      return -1
   if start == target:
      return 0
   __a				     =    [start]
   __a				     =    set(SCREAMING_SNAKE_CASE__    )
   # Keep tab on distances from `start` node.
   __a				     =    {start: 0, target: -1}
   while queue:
      __a				     =    queue.pop(0    )
      if node == target:
         __a				     =    (
             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				     =    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'''



__UpperCamelCase      :       Optional[Any]      			=      [
    """DownloadConfig""",
    """DownloadManager""",
    """DownloadMode""",
    """StreamingDownloadManager""",
]

from .download_config import DownloadConfig
from .download_manager import DownloadManager, DownloadMode
from .streaming_download_manager import StreamingDownloadManager