'''simple docstring'''






from __future__ import annotations

import numpy as np






def 			UpperCamelCase__       (       _lowercase     :					list[float]  )				->						Optional[Any]:
  return np.maximum(0 ,     _lowercase  )


if __name__ == "__main__":
    print(np.array(relu([-1, 0, 5])))  # --> [0, 0, 5]

'''simple docstring'''
lowerCAmelCase					:    Optional[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						:		dict		,     A						:		str		,     A						:		Optional[Any]):
							UpperCamelCase   			=     set()
							# keep track of all the paths to be checked
							UpperCamelCase   			=     [[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
														UpperCamelCase   			=     queue.pop(0)
														# get the last node from the path
														UpperCamelCase   			=     path[-1]
														if node not in explored:
																					UpperCamelCase   			=     graph[node]
																					# go through all neighbour nodes, construct a new path and
																					# push it into the queue
																					for neighbour in neighbours:
																												UpperCamelCase   			=     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						:		dict		,     A						:		str		,     A						:		Tuple):
							if not graph or start not in graph or target not in graph:
														return -1
							if start == target:
														return 0
							UpperCamelCase   			=     [start]
							UpperCamelCase   			=     set(A)
							# Keep tab on distances from `start` node.
							UpperCamelCase   			=     {start: 0, target: -1}
							while queue:
														UpperCamelCase   			=     queue.pop(0)
														if node == target:
																					UpperCamelCase   			=     (
																					    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)
																												UpperCamelCase   			=     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




