






'''simple docstring'''







def 				SCREAMING_SNAKE_CASE_ (UpperCamelCase   )   -> List[str]:
							lowerCamelCase__      :			Union[str, Any] 						= [0] * len(UpperCamelCase   )
							lowerCamelCase__      :			List[Any] 						= []
							lowerCamelCase__      :			Optional[Any] 						= [1] * len(UpperCamelCase   )

							for values in graph.values():
														for i in values:
																					indegree[i] += 1

							for i in range(len(UpperCamelCase   )   ):
														if indegree[i] == 0:
																					queue.append(UpperCamelCase   )

							while queue:
														lowerCamelCase__      :			List[str] 						= queue.pop(0   )
														for x in graph[vertex]:
																					indegree[x] -= 1

																					if long_dist[vertex] + 1 > long_dist[x]:
																												lowerCamelCase__      :			Union[str, Any] 						= long_dist[vertex] + 1

																					if indegree[x] == 0:
																												queue.append(UpperCamelCase   )

							print(max(UpperCamelCase   )   )


# Adjacency list of Graph
_A			:    List[Any]					  ={0: [2, 3, 4], 1: [2, 7], 2: [5], 3: [5, 7], 4: [7], 5: [6], 6: [7], 7: []}



longest_distance(graph)









'''simple docstring'''







from statistics import mean

import numpy as np





def 				SCREAMING_SNAKE_CASE_ (UpperCamelCase       ,    UpperCamelCase       ,    UpperCamelCase       ,    UpperCamelCase   )   -> list:
							lowerCamelCase__      :			Optional[int] 						= 0
							# Number of processes finished
							lowerCamelCase__      :			Union[str, Any] 						= 0
							# Displays the finished process.
							# If it is 0, the performance is completed if it is 1, before the performance.
							lowerCamelCase__      :			Tuple 						= [0] * no_of_process
							# List to include calculation results
							lowerCamelCase__      :			List[str] 						= [0] * no_of_process

							# Sort by arrival time.
							lowerCamelCase__      :			Union[str, Any] 						= [burst_time[i] for i in np.argsort(UpperCamelCase   )]
							lowerCamelCase__      :			List[Any] 						= [process_name[i] for i in np.argsort(UpperCamelCase   )]
							arrival_time.sort()

							while no_of_process > finished_process_count:
														lowerCamelCase__      :			str 						= 0
														while finished_process[i] == 1:
																					i += 1
														if current_time < arrival_time[i]:
																					lowerCamelCase__      :			Union[str, Any] 						= arrival_time[i]

														lowerCamelCase__      :			Any 						= 0
														# Index showing the location of the process being performed
														lowerCamelCase__      :			Union[str, Any] 						= 0
														# Saves the current response ratio.
														lowerCamelCase__      :			Any 						= 0
														for i in range(0       ,    UpperCamelCase   ):
																					if finished_process[i] == 0 and arrival_time[i] <= current_time:
																												lowerCamelCase__      :			Optional[int] 						= (burst_time[i] + (current_time - arrival_time[i])) / burst_time[
																												    i
																												]
																					if response_ratio < temp:
																												lowerCamelCase__      :			int 						= temp
																												lowerCamelCase__      :			str 						= i

        # Calculate the turn around time
														lowerCamelCase__      :			Optional[int] 						= current_time + burst_time[loc] - arrival_time[loc]
														current_time += burst_time[loc]
														# Indicates that the process has been performed.
														lowerCamelCase__      :			List[str] 						= 1
														# Increase finished_process_count by 1
														finished_process_count += 1

							return turn_around_time





def 				SCREAMING_SNAKE_CASE_ (UpperCamelCase       ,    UpperCamelCase       ,    UpperCamelCase       ,    UpperCamelCase   )   -> list:
							lowerCamelCase__      :			int 						= [0] * no_of_process
							for i in range(0       ,    UpperCamelCase   ):
														lowerCamelCase__      :			Optional[Any] 						= turn_around_time[i] - burst_time[i]
							return waiting_time


if __name__ == "__main__":
			_A			:    List[str]					  =5
			_A			:    Optional[Any]					  =['''A''', '''B''', '''C''', '''D''', '''E''']
			_A			:    Optional[int]					  =[1, 2, 3, 4, 5]
			_A			:    Dict					  =[1, 2, 3, 4, 5]

			_A			:    Any					  =calculate_turn_around_time(
			    process_name, arrival_time, burst_time, no_of_process
			)
			_A			:    Optional[int]					  =calculate_waiting_time(
			    process_name, turn_around_time, burst_time, no_of_process
			)

			print('''Process name \tArrival time \tBurst time \tTurn around time \tWaiting time''')
			for i in range(0, no_of_process):
						print(
						    F'{process_name[i]}\t\t{arrival_time[i]}\t\t{burst_time[i]}\t\t'
						    F'{turn_around_time[i]}\t\t\t{waiting_time[i]}'
						)

			print(F'average waiting time : {mean(waiting_time):.5f}')
			print(F'average turn around time : {mean(turn_around_time):.5f}')

