




from statistics import mean

import numpy as np




def     __magic_name__       (				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     __magic_name__       (				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__":
		__lowerCAmelCase	:       str     =	5
		__lowerCAmelCase	:       int     =	['A', 'B', 'C', 'D', 'E']
		__lowerCAmelCase	:       Union[str, Any]     =	[1, 2, 3, 4, 5]
		__lowerCAmelCase	:       Optional[Any]     =	[1, 2, 3, 4, 5]

		__lowerCAmelCase	:       Union[str, Any]     =	calculate_turn_around_time(
		    process_name, arrival_time, burst_time, no_of_process
		)
		__lowerCAmelCase	:       Any     =	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}''')












# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
#   python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under git won't be considered
# since the output of this script is fed into Makefile commands it doesn't print a newline after the results

import re
import subprocess
import sys


__lowerCAmelCase	:       Tuple     =	subprocess.check_output('git merge-base main HEAD'.split()).decode('utf-8')
__lowerCAmelCase	:       Tuple     =	subprocess.check_output(F'''git diff --name-only {fork_point_sha}'''.split()).decode('utf-8').split()

__lowerCAmelCase	:       Dict     =	'|'.join(sys.argv[1:])
__lowerCAmelCase	:       List[Any]     =	re.compile(rF'''^({joined_dirs}).*?\.py$''')

__lowerCAmelCase	:       List[Any]     =	[x for x in modified_files if regex.match(x)]
print(' '.join(relevant_modified_files), end='')






