






from __future__ import annotations
def       a__						(  A					):
   lowercase__						:	str         = [0] * len(A					)
   for i in range(1		,				len(A					)					):
      lowercase__						:	Tuple         = duration_times[i - 1] + waiting_times[i - 1]
   return waiting_times
def       a__						(  A		,				A					):
   return [
       duration_time + waiting_times[i]
       for i, duration_time in enumerate(A					)
   ]
def       a__						(  A					):
   return sum(A					) / len(A					)
def       a__						(  A					):
   return sum(A					) / len(A					)


if __name__ == "__main__":
 # process id's
 a      =       [1, 2, 3]

 # ensure that we actually have processes
 if len(processes) == 0:
  print('Zero amount of processes')
  raise SystemExit(0)

 # duration time of all processes
 a      =       [19, 8, 9]

 # ensure we can match each id to a duration time
 if len(duration_times) != len(processes):
  print('Unable to match all id\'s with their duration time')
  raise SystemExit(0)

 # get the waiting times and the turnaround times
 a      =       calculate_waiting_times(duration_times)
 a      =       calculate_turnaround_times(duration_times, waiting_times)

 # get the average times
 a      =       calculate_average_waiting_time(waiting_times)
 a      =       calculate_average_turnaround_time(turnaround_times)

 # print all the results
 print('Process ID\tDuration Time\tWaiting Time\tTurnaround Time')
 for i, process in enumerate(processes):
  print(
      F'{process}\t\t{duration_times[i]}\t\t{waiting_times[i]}\t\t'
      F'{turnaround_times[i]}'
  )
 print(F'Average waiting time = {average_waiting_time}')
 print(F'Average turn around time = {average_turnaround_time}')










from dataclasses import dataclass
from typing import Callable, Optional

import datasets
@dataclass
class        __snake_case(					datasets.BuilderConfig      ):
 lowercase :       Optional[Callable]		      =		None
 lowercase :       Optional[dict]		      =		None
 lowercase :       Optional[datasets.Features]		      =		None



 def 						UpperCAmelCase    (	self   :   int	):

    """simple docstring"""






    assert self.generator is not None, "generator must be specified"

    if self.gen_kwargs is None:
       lowercase__						:	List[Any]         = {}
class        __snake_case(					datasets.GeneratorBasedBuilder      ):
 lowercase :       Dict		      =		GeneratorConfig



 def 						UpperCAmelCase    (	self   :   Any	):

    """simple docstring"""






    return datasets.DatasetInfo(features=self.config.features	)



 def 						UpperCAmelCase    (	self   :   List[str] ,		UpperCAmelCase__   :   Optional[int]	):

    """simple docstring"""






    return [datasets.SplitGenerator(name=datasets.Split.TRAIN ,		gen_kwargs=self.config.gen_kwargs	)]







 def 						UpperCAmelCase    (	self   :   Dict ,		**UpperCAmelCase__   :   List[str]	):

    """simple docstring"""






    for idx, ex in enumerate(self.config.generator(**UpperCAmelCase__	)	):
       yield idx, ex


