

from statistics import mean

import numpy as np

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

				# Sort by arrival time.
				_UpperCAmelCase    :						Tuple							=      [burst_time[i] for i in np.argsort(lowerCAmelCase	)]
				_UpperCAmelCase    :						Optional[Any]							=      [process_name[i] for i in np.argsort(lowerCAmelCase	)]
				arrival_time.sort()

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

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

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

				return turn_around_time

def 							__SCREAMING_SNAKE_CASE							(			lowerCAmelCase:					list					, lowerCAmelCase:					list					, lowerCAmelCase:					list					, lowerCAmelCase:					int	)				->    list:
				_UpperCAmelCase    :						Dict							=      [0] * no_of_process
				for i in range(0					, lowerCAmelCase	):
								_UpperCAmelCase    :						List[Any]							=      turn_around_time[i] - burst_time[i]
				return waiting_time


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

					SCREAMING_SNAKE_CASE_            = calculate_turn_around_time(
					    process_name, arrival_time, burst_time, no_of_process
					)
					SCREAMING_SNAKE_CASE_            = 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}''')





from __future__ import annotations

from random import choice

def 							__SCREAMING_SNAKE_CASE							(			lowerCAmelCase:					Any	)				->    Optional[int]:
				return choice(lowerCAmelCase	)

def 							__SCREAMING_SNAKE_CASE							(			lowerCAmelCase:					list[int]					, lowerCAmelCase:					int	)				->    int:
				_UpperCAmelCase    :						List[Any]							=      random_pivot(lowerCAmelCase	)

				# partition based on pivot
				# linear time
				_UpperCAmelCase    :						List[str]							=      [e for e in lst if e < pivot]
				_UpperCAmelCase    :						Any							=      [e for e in lst if e > pivot]

				# if we get lucky, pivot might be the element we want.
				# we can easily see this:
				# small (elements smaller than k)
				# + pivot (kth element)
				# + big (elements larger than k)
				if len(lowerCAmelCase	) == k - 1:
								return pivot
				# pivot is in elements bigger than k
				elif len(lowerCAmelCase	) < k - 1:
								return kth_number(lowerCAmelCase					, k - len(lowerCAmelCase	) - 1	)
				# pivot is in elements smaller than k
				else:
								return kth_number(lowerCAmelCase					, lowerCAmelCase	)


if __name__ == "__main__":
					import doctest

					doctest.testmod()


