
'''simple docstring'''
lowercase__											={
    "A": ["B", "C", "E"],
    "B": ["A", "D", "E"],
    "C": ["A", "F", "G"],
    "D": ["B"],
    "E": ["A", "B", "D"],
    "F": ["C"],
    "G": ["C"],
}






def      UpperCamelCase_				(      A__  ,      A__  ,      A__						):
	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(lowerCAmelCase__						)
				new_path.append(lowerCAmelCase__						)
				queue.append(lowerCAmelCase__						)
				# return path if neighbour is goal
				if neighbour == goal:
					return new_path

            # mark node as explored
			explored.add(lowerCAmelCase__						)

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






def      UpperCamelCase_				(      A__  ,      A__  ,      A__						):
	if not graph or start not in graph or target not in graph:
		return -1
	if start == target:
		return 0
	a_      				=						[start]
	a_      				=						set(lowerCAmelCase__						)
	# 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(lowerCAmelCase__						)
				queue.append(lowerCAmelCase__						)
				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'''

SCREAMING_SNAKE_CASE							:				Union[str, Any]     	=			0  # The first color of the flag.
SCREAMING_SNAKE_CASE							:				List[str]     	=			1  # The second color of the flag.
SCREAMING_SNAKE_CASE							:				Optional[Any]     	=			2  # The third color of the flag.
SCREAMING_SNAKE_CASE							:				Tuple     	=			(red, white, blue)




def 							_UpperCamelCase				(   lowerCAmelCase__:					list   )      -> list:
							if not sequence:
														return []
							if len(lowerCAmelCase__   ) == 1:
														return list(lowerCAmelCase__   )
							SCREAMING_SNAKE_CASE_				=				0
							SCREAMING_SNAKE_CASE_				=				len(lowerCAmelCase__   ) - 1
							SCREAMING_SNAKE_CASE_				=				0
							while mid <= high:
														if sequence[mid] == colors[0]:
																					SCREAMING_SNAKE_CASE_				,    SCREAMING_SNAKE_CASE_				=				sequence[mid], sequence[low]
																					low += 1
																					mid += 1
														elif sequence[mid] == colors[1]:
																					mid += 1
														elif sequence[mid] == colors[2]:
																					SCREAMING_SNAKE_CASE_				,    SCREAMING_SNAKE_CASE_				=				sequence[high], sequence[mid]
																					high -= 1
														else:
																					SCREAMING_SNAKE_CASE_				=				F"""The elements inside the sequence must contains only {colors} values"""
																					raise ValueError(lowerCAmelCase__   )
							return sequence


if __name__ == "__main__":
							import doctest

							doctest.testmod()

							SCREAMING_SNAKE_CASE							:				str     	=			input("Enter numbers separated by commas:\n").strip()
							SCREAMING_SNAKE_CASE							:				List[Any]     	=			[int(item.strip()) for item in user_input.split(",")]
							print(f"{dutch_national_flag_sort(unsorted)}")





