



from statistics import mean

import numpy as np

def 			A_      (	__a     :				list ,		__a     :				list ,		__a     :				list ,		__a     :				int		):

				"""simple docstring"""
				a__				      =		0
				# Number of processes finished
				a__				      =		0
				# Displays the finished process.
				# If it is 0, the performance is completed if it is 1, before the performance.
				a__				      =		[0] * no_of_process
				# List to include calculation results
				a__				      =		[0] * no_of_process

				# Sort by arrival time.
				a__				      =		[burst_time[i] for i in np.argsort(__a		)]
				a__				      =		[process_name[i] for i in np.argsort(__a		)]
				arrival_time.sort()

				while no_of_process > finished_process_count:
								a__				      =		0
								while finished_process[i] == 1:
												i += 1
								if current_time < arrival_time[i]:
												a__				      =		arrival_time[i]

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

        # Calculate the turn around time
								a__				      =		current_time + burst_time[loc] - arrival_time[loc]
								current_time += burst_time[loc]
								# Indicates that the process has been performed.
								a__				      =		1
								# Increase finished_process_count by 1
								finished_process_count += 1

				return turn_around_time

def 			A_      (	__a     :				list ,		__a     :				list ,		__a     :				list ,		__a     :				int		):

				"""simple docstring"""
				a__				      =		[0] * no_of_process
				for i in range(0 ,		__a		):
								a__				      =		turn_around_time[i] - burst_time[i]
				return waiting_time


if __name__ == "__main__":
	UpperCAmelCase							 =					5
	UpperCAmelCase							 =					["""A""", """B""", """C""", """D""", """E"""]
	UpperCAmelCase							 =					[1, 2, 3, 4, 5]
	UpperCAmelCase							 =					[1, 2, 3, 4, 5]

	UpperCAmelCase							 =					calculate_turn_around_time(
	    process_name, arrival_time, burst_time, no_of_process
	)
	UpperCAmelCase							 =					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}""")






def 			A_      (	__a     :				int ,		__a     :				int		):

				"""simple docstring"""
				return abs(__a		) if a == 0 else greatest_common_divisor(b % a ,		__a		)

def 			A_      (	__a     :				int ,		__a     :				int		):

				"""simple docstring"""
				while y:  # --> when y=0 then loop will terminate and return x as final GCD.
								a__      ,			a__				      =		y, x % y
				return abs(__a		)

def 			A_      (	):

				"""simple docstring"""
				try:
								a__				      =		input("""Enter two integers separated by comma (,): """		).split(""","""		)
								a__				      =		int(nums[0]		)
								a__				      =		int(nums[1]		)
								print(
								    F'''greatest_common_divisor({num_a}, {num_a}) = '''
								    F'''{greatest_common_divisor(__a ,		__a		)}'''		)
								print(F'''By iterative gcd({num_a}, {num_a}) = {gcd_by_iterative(__a ,		__a		)}'''		)
				except (IndexError, UnboundLocalError, ValueError):
								print("""Wrong input"""		)


if __name__ == "__main__":
	main()

