






'''simple docstring'''



from __future__ import annotations

import pandas as pd


def 							lowercase_				(    __A :       list[int]					,      __A :       list[int]					,      __A :       int			)       ->      list[int]:



 """simple docstring"""




 lowercase					:   Tuple				  =[0] * no_of_processes
 lowercase					:   Any				  =[0] * no_of_processes
 # Copy the burst time into remaining_time[]
 for i in range(__A			):
  lowercase					:   List[str]				  =burst_time[i]

 lowercase					:   Any				  =0
 lowercase					:   Optional[Any]				  =0
 lowercase					:   str				  =9_9_9_9_9_9_9_9_9
 lowercase					:   List[str]				  =0
 lowercase					:   Tuple				  =False

 # Process until all processes are completed
 while complete != no_of_processes:
  for j in range(__A			):
   if arrival_time[j] <= increment_time and remaining_time[j] > 0:
    if remaining_time[j] < minm:
     lowercase					:   Optional[Any]				  =remaining_time[j]
     lowercase					:   Optional[int]				  =j
     lowercase					:   Union[str, Any]				  =True

  if not check:
   increment_time += 1
   continue
  remaining_time[short] -= 1

  lowercase					:   Optional[int]				  =remaining_time[short]
  if minm == 0:
   lowercase					:   Optional[Any]				  =9_9_9_9_9_9_9_9_9

  if remaining_time[short] == 0:
   complete += 1
   lowercase					:   Optional[int]				  =False

   # Find finish time of current process
   lowercase					:   Dict				  =increment_time + 1

   # Calculate waiting time
   lowercase					:   Tuple				  =finish_time - arrival_time[short]
   lowercase					:   int				  =finar - burst_time[short]

   if waiting_time[short] < 0:
    lowercase					:   List[Any]				  =0

        # Increment time
  increment_time += 1
 return waiting_time


def 							lowercase_				(    __A :       list[int]					,      __A :       int					,      __A :       list[int]			)       ->      list[int]:



 """simple docstring"""




 lowercase					:   List[Any]				  =[0] * no_of_processes
 for i in range(__A			):
  lowercase					:   Union[str, Any]				  =burst_time[i] + waiting_time[i]
 return turn_around_time


def 							lowercase_				(    __A :       list[int]					,      __A :       list[int]					,      __A :       int			)       ->      None:



 """simple docstring"""




 lowercase					:   Tuple				  =0
 lowercase					:   Tuple				  =0
 for i in range(__A			):
  lowercase					:   Any				  =total_waiting_time + waiting_time[i]
  lowercase					:   Tuple				  =total_turn_around_time + turn_around_time[i]
 print(F'Average waiting time = {total_waiting_time / no_of_processes:.5f}'			)
 print('''Average turn around time ='''					,      total_turn_around_time / no_of_processes			)


if __name__ == "__main__":
      print('Enter how many process you want to analyze')
      SCREAMING_SNAKE_CASE						=	int(input())
      SCREAMING_SNAKE_CASE						=	[0] * no_of_processes
      SCREAMING_SNAKE_CASE						=	[0] * no_of_processes
      SCREAMING_SNAKE_CASE						=	list(range(1, no_of_processes + 1))

      for i in range(no_of_processes):
            print('Enter the arrival time and burst time for process:--' + str(i + 1))
            SCREAMING_SNAKE_CASE		,     SCREAMING_SNAKE_CASE						=	map(int, input().split())

      SCREAMING_SNAKE_CASE						=	calculate_waitingtime(arrival_time, burst_time, no_of_processes)

      SCREAMING_SNAKE_CASE						=	burst_time
      SCREAMING_SNAKE_CASE						=	no_of_processes
      SCREAMING_SNAKE_CASE						=	waiting_time
      SCREAMING_SNAKE_CASE						=	calculate_turnaroundtime(bt, n, wt)

      calculate_average_times(waiting_time, turn_around_time, no_of_processes)

      SCREAMING_SNAKE_CASE						=	pd.DataFrame(
          list(zip(processes, burst_time, arrival_time, waiting_time, turn_around_time)),
          columns=[
              'Process',
              'BurstTime',
              'ArrivalTime',
              'WaitingTime',
              'TurnAroundTime',
          ],
      )

      # Printing the dataFrame
      pd.set_option('display.max_rows', fcfs.shape[0] + 1)
      print(fcfs)











'''simple docstring'''



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


SCREAMING_SNAKE_CASE						=	{
    'configuration_m2m_100': ['M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP', 'M2M100Config', 'M2M100OnnxConfig'],
    'tokenization_m2m_100': ['M2M100Tokenizer'],
}


try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE						=	[
          'M2M_100_PRETRAINED_MODEL_ARCHIVE_LIST',
          'M2M100ForConditionalGeneration',
          'M2M100Model',
          'M2M100PreTrainedModel',
      ]


if TYPE_CHECKING:
      from .configuration_mam_aaa import M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP, MaMaaaConfig, MaMaaaOnnxConfig
      from .tokenization_mam_aaa import MaMaaaTokenizer

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_mam_aaa import (
                M2M_100_PRETRAINED_MODEL_ARCHIVE_LIST,
                MaMaaaForConditionalGeneration,
                MaMaaaModel,
                MaMaaaPreTrainedModel,
            )


else:
      import sys

      SCREAMING_SNAKE_CASE						=	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)



