


from __future__ import annotations

import requests





def   _lowerCAmelCase				(   UpperCamelCase__:     str						) ->   dict:





	"""simple docstring"""







	A								=				f'https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty'
	return requests.get(UpperCamelCase__						).json()





def   _lowerCAmelCase				(   UpperCamelCase__:     int = 10						) ->   list[dict]:





	"""simple docstring"""







	A								=				"""https://hacker-news.firebaseio.com/v0/topstories.json?print=pretty"""
	A								=				requests.get(UpperCamelCase__						).json()[:max_stories]
	return [get_hackernews_story(UpperCamelCase__						) for story_id in story_ids]





def   _lowerCAmelCase				(   UpperCamelCase__:     int = 10						) ->   str:





	"""simple docstring"""







	A								=				hackernews_top_stories(UpperCamelCase__						)
	return "\n".join("""* [{title}]({url})""".format(**UpperCamelCase__						) for story in stories						)


if __name__ == "__main__":
			print(hackernews_top_stories_as_markdown())







import sys
from collections import defaultdict






class       _UpperCamelCase    :

				"""simple docstring"""







				def __init__(						self   )	->				Any:
					A								=				[]

				def      _UpperCAmelCase					(						self				,   a__   )	->				List[str]:
					return self.node_position[vertex]

				def      _UpperCAmelCase					(						self				,   a__				,   a__   )	->				Optional[int]:
					A								=				pos

				def      _UpperCAmelCase					(						self				,   a__				,   a__				,   a__				,   a__   )	->				Any:
					if start > size // 2 - 1:
						return
					else:
						if 2 * start + 2 >= size:
							A								=				2 * start + 1
						else:
							if heap[2 * start + 1] < heap[2 * start + 2]:
								A								=				2 * start + 1
							else:
								A								=				2 * start + 2
						if heap[smallest_child] < heap[start]:
							A					,			A								=				heap[smallest_child], positions[smallest_child]
							A					,			A								=				(
							    heap[start],
							    positions[start],
							)
							A					,			A								=				temp, tempa

							A								=				self.get_position(positions[smallest_child]   )
							self.set_position(
							    positions[smallest_child]				,   self.get_position(positions[start]   )   )
							self.set_position(positions[start]				,   a__   )

							self.top_to_bottom(a__				,   a__				,   a__				,   a__   )

				def      _UpperCAmelCase					(						self				,   a__				,   a__				,   a__				,   a__   )	->				Dict:
					A								=				position[index]

					while index != 0:
						A								=				int((index - 2) / 2   ) if index % 2 == 0 else int((index - 1) / 2   )

						if val < heap[parent]:
							A								=				heap[parent]
							A								=				position[parent]
							self.set_position(position[parent]				,   a__   )
						else:
							A								=				val
							A								=				temp
							self.set_position(a__				,   a__   )
							break
						A								=				parent
					else:
						A								=				val
						A								=				temp
						self.set_position(a__				,   0   )

				def      _UpperCAmelCase					(						self				,   a__				,   a__   )	->				Optional[int]:
					A								=				len(a__   ) // 2 - 1
					for i in range(a__				,   -1				,   -1   ):
						self.top_to_bottom(a__				,   a__				,   len(a__   )				,   a__   )

				def      _UpperCAmelCase					(						self				,   a__				,   a__   )	->				Any:
					A								=				positions[0]
					A								=				sys.maxsize
					self.top_to_bottom(a__				,   0				,   len(a__   )				,   a__   )
					return temp





def   _lowerCAmelCase				(   UpperCamelCase__:     List[str]						) ->   List[str]:





	"""simple docstring"""







	A								=				Heap()

	A								=				[0] * len(UpperCamelCase__						)
	A								=				[-1] * len(UpperCamelCase__						)  # Neighboring Tree Vertex of selected vertex
	# Minimum Distance of explored vertex with neighboring vertex of partial tree
	# formed in graph
	A								=				[]  # Heap of Distance of vertices from their neighboring vertex
	A								=				[]

	for vertex in range(len(UpperCamelCase__						)						):
		distance_tv.append(sys.maxsize						)
		positions.append(UpperCamelCase__						)
		heap.node_position.append(UpperCamelCase__						)

	A								=				[]
	A								=				1
	A								=				sys.maxsize
	for neighbor, distance in adjacency_list[0]:
		A								=				0
		A								=				distance
	heap.heapify(UpperCamelCase__							,					UpperCamelCase__						)

	for _ in range(1							,					len(UpperCamelCase__						)						):
		A								=				heap.delete_minimum(UpperCamelCase__							,					UpperCamelCase__						)
		if visited[vertex] == 0:
			tree_edges.append((nbr_tv[vertex], vertex)						)
			A								=				1
			for neighbor, distance in adjacency_list[vertex]:
				if (
				    visited[neighbor] == 0
				    and distance < distance_tv[heap.get_position(UpperCamelCase__						)]
				):
					A								=				distance
					heap.bottom_to_top(
					    UpperCamelCase__							,					heap.get_position(UpperCamelCase__						)							,					UpperCamelCase__							,					UpperCamelCase__						)
					A								=				vertex
	return tree_edges


if __name__ == "__main__":  # pragma: no cover
				# < --------- Prims Algorithm --------- >
				_lowercase       :      Tuple	=	int(input("Enter number of edges: ").strip())
				_lowercase       :      int	=	defaultdict(list)
				for _ in range(edges_number):
								_lowercase       :      Optional[Any]	=	[int(x) for x in input().strip().split()]
								adjacency_list[edge[0]].append([edge[1], edge[2]])
								adjacency_list[edge[1]].append([edge[0], edge[2]])
				print(prisms_algorithm(adjacency_list))



