


"""simple docstring"""







import re
from pathlib import Path
from unittest import TestCase

import pytest




@pytest.mark.integration
class  UpperCamelCase_	( UpperCamelCase):

	"""simple docstring"""





	def   UpperCAmelCase_      ( self			:				Optional[Any]			,			UpperCAmelCase__			:				str   )       ->	Optional[int]:

						with open(UpperCAmelCase__			,			encoding="utf-8"   ) as input_file:
											__SCREAMING_SNAKE_CASE						   =				re.compile(R"(?!.*\b(?:encoding|rb|w|wb|w+|wb+|ab|ab+)\b)(?<=\s)(open)\((.*)\)"   )
											__SCREAMING_SNAKE_CASE						   =				input_file.read()
											__SCREAMING_SNAKE_CASE						   =				regexp.search(UpperCAmelCase__   )

						return match




	def   UpperCAmelCase_      ( self			:				int			,			UpperCAmelCase__			:				str   )       ->	Union[str, Any]:

						with open(UpperCAmelCase__			,			encoding="utf-8"   ) as input_file:
											__SCREAMING_SNAKE_CASE						   =				re.compile(R"#[^\r\n]*print\(|\"[^\r\n]*print\(|\"\"\".*?print\(.*?\"\"\"|(print\()"			,			re.DOTALL   )
											__SCREAMING_SNAKE_CASE						   =				input_file.read()
											# use `re.finditer` to handle the case where the ignored groups would be matched first by `re.search`
											__SCREAMING_SNAKE_CASE						   =				regexp.finditer(UpperCAmelCase__   )

						__SCREAMING_SNAKE_CASE						   =				[match for match in matches if match is not None and match.group(1   ) is not None]
						return matches[0] if matches else None




	def   UpperCAmelCase_      ( self			:				Dict   )       ->	Dict:
						__SCREAMING_SNAKE_CASE						   =				Path("./datasets"   )
						__SCREAMING_SNAKE_CASE						   =				list(dataset_paths.absolute().glob("**/*.py"   )   )

						for dataset in dataset_files:
											if self._no_encoding_on_file_open(str(UpperCAmelCase__   )   ):
																raise AssertionError(F"""open(...) must use utf-8 encoding in {dataset}"""   )




	def   UpperCAmelCase_      ( self			:				str   )       ->	int:
						__SCREAMING_SNAKE_CASE						   =				Path("./datasets"   )
						__SCREAMING_SNAKE_CASE						   =				list(dataset_paths.absolute().glob("**/*.py"   )   )

						for dataset in dataset_files:
											if self._no_print_statements(str(UpperCAmelCase__   )   ):
																raise AssertionError(F"""print statement found in {dataset}. Use datasets.logger/logging instead."""   )




'''simple docstring'''




from __future__ import annotations

from statistics import mean





def 	a_					( lowerCamelCase	:     list[int]	, lowerCamelCase	:     list[int]	, lowerCamelCase	:     int				):
   lowerCAmelCase     =			[0] * no_of_processes
   lowerCAmelCase     =			[0] * no_of_processes

   # Initialize remaining_time to waiting_time.

   for i in range(lowerCamelCase				):
      lowerCAmelCase     =			burst_time[i]
   lowerCAmelCase     =			[]

   lowerCAmelCase     =			0
   lowerCAmelCase     =			0

   # When processes are not completed,
   # A process whose arrival time has passed \
   # and has remaining execution time is put into the ready_process.
   # The shortest process in the ready_process, target_process is executed.

   while completed != no_of_processes:
      lowerCAmelCase     =			[]
      lowerCAmelCase     =			-1

      for i in range(lowerCamelCase				):
         if (arrival_time[i] <= total_time) and (remaining_time[i] > 0):
            ready_process.append(lowerCamelCase				)

      if len(lowerCamelCase				) > 0:
         lowerCAmelCase     =			ready_process[0]
         for i in ready_process:
            if remaining_time[i] < remaining_time[target_process]:
               lowerCAmelCase     =			i
         total_time += burst_time[target_process]
         completed += 1
         lowerCAmelCase     =			0
         lowerCAmelCase     =			(
             total_time - arrival_time[target_process] - burst_time[target_process]
         )
      else:
         total_time += 1

   return waiting_time





def 	a_					( lowerCamelCase	:     list[int]	, lowerCamelCase	:     int	, lowerCamelCase	:     list[int]				):
   lowerCAmelCase     =			[0] * no_of_processes
   for i in range(lowerCamelCase				):
      lowerCAmelCase     =			burst_time[i] + waiting_time[i]
   return turn_around_time


if __name__ == "__main__":
       print("""[TEST CASE 01]""")

       __snake_case    						=4
       __snake_case    						=[2, 5, 3, 7]
       __snake_case    						=[0, 0, 0, 0]
       __snake_case    						=calculate_waitingtime(arrival_time, burst_time, no_of_processes)
       __snake_case    						=calculate_turnaroundtime(
           burst_time, no_of_processes, waiting_time
       )

       # Printing the Result
       print("""PID\tBurst Time\tArrival Time\tWaiting Time\tTurnaround Time""")
       for i, process_id in enumerate(list(range(1, 5))):
              print(
                  F'''{process_id}\t{burst_time[i]}\t\t\t{arrival_time[i]}\t\t\t\t'''
                  F'''{waiting_time[i]}\t\t\t\t{turn_around_time[i]}'''
              )
       print(F'''\nAverage waiting time = {mean(waiting_time):.5f}''')
       print(F'''Average turnaround time = {mean(turn_around_time):.5f}''')





