

'''simple docstring'''



from collections import deque



class 				_snake_case					:

  def __init__(				self      , _SCREAMING_SNAKE_CASE      , _SCREAMING_SNAKE_CASE      , _SCREAMING_SNAKE_CASE	):





      '''simple docstring'''

      lowerCAmelCase 						=							process_name  # process name
      lowerCAmelCase 						=							arrival_time  # arrival time of the process
      # completion time of finished process or last interrupted time
      lowerCAmelCase 						=							arrival_time
      lowerCAmelCase 						=							burst_time  # remaining burst time
      lowerCAmelCase 						=							0  # total time of the process wait in ready queue
      lowerCAmelCase 						=							0  # time from arrival time to completion time



class 				_snake_case					:

  def __init__(				self      , _SCREAMING_SNAKE_CASE      , _SCREAMING_SNAKE_CASE      , _SCREAMING_SNAKE_CASE      , _SCREAMING_SNAKE_CASE      , ):





      '''simple docstring'''

      lowerCAmelCase 						=							number_of_queues
      # time slice of queues that round robin algorithm applied
      lowerCAmelCase 						=							time_slices
      # unfinished process is in this ready_queue
      lowerCAmelCase 						=							queue
      # current time
      lowerCAmelCase 						=							current_time
      # finished process is in this sequence queue
      lowerCAmelCase 						=							deque()

  def   _SCREAMING_SNAKE_CASE				(				self	):





      '''simple docstring'''

      lowerCAmelCase 						=							[]
      for i in range(len(self.finish_queue	)	):
          sequence.append(self.finish_queue[i].process_name	)
      return sequence

  def   _SCREAMING_SNAKE_CASE				(				self      , _SCREAMING_SNAKE_CASE	):





      '''simple docstring'''

      lowerCAmelCase 						=							[]
      for i in range(len(_SCREAMING_SNAKE_CASE	)	):
          waiting_times.append(queue[i].waiting_time	)
      return waiting_times

  def   _SCREAMING_SNAKE_CASE				(				self      , _SCREAMING_SNAKE_CASE	):





      '''simple docstring'''

      lowerCAmelCase 						=							[]
      for i in range(len(_SCREAMING_SNAKE_CASE	)	):
          turnaround_times.append(queue[i].turnaround_time	)
      return turnaround_times

  def   _SCREAMING_SNAKE_CASE				(				self      , _SCREAMING_SNAKE_CASE	):





      '''simple docstring'''

      lowerCAmelCase 						=							[]
      for i in range(len(_SCREAMING_SNAKE_CASE	)	):
          completion_times.append(queue[i].stop_time	)
      return completion_times

  def   _SCREAMING_SNAKE_CASE				(				self      , _SCREAMING_SNAKE_CASE	):





      '''simple docstring'''

      return [q.burst_time for q in queue]

  def   _SCREAMING_SNAKE_CASE				(				self      , _SCREAMING_SNAKE_CASE	):





      '''simple docstring'''

      process.waiting_time += self.current_time - process.stop_time
      return process.waiting_time

  def   _SCREAMING_SNAKE_CASE				(				self      , _SCREAMING_SNAKE_CASE	):





      '''simple docstring'''

      lowerCAmelCase 						=							deque()  # sequence deque of finished process
      while len(_SCREAMING_SNAKE_CASE	) != 0:
          lowerCAmelCase 						=							ready_queue.popleft()  # current process

          # if process's arrival time is later than current time, update current time
          if self.current_time < cp.arrival_time:
              self.current_time += cp.arrival_time

          # update waiting time of current process
          self.update_waiting_time(_SCREAMING_SNAKE_CASE	)
          # update current time
          self.current_time += cp.burst_time
          # finish the process and set the process's burst-time 0
          lowerCAmelCase 						=							0
          # set the process's turnaround time because it is finished
          lowerCAmelCase 						=							self.current_time - cp.arrival_time
          # set the completion time
          lowerCAmelCase 						=							self.current_time
          # add the process to queue that has finished queue
          finished.append(_SCREAMING_SNAKE_CASE	)

      self.finish_queue.extend(_SCREAMING_SNAKE_CASE	)  # add finished process to finish queue
      # FCFS will finish all remaining processes
      return finished

  def   _SCREAMING_SNAKE_CASE				(				self      , _SCREAMING_SNAKE_CASE      , _SCREAMING_SNAKE_CASE	):





      '''simple docstring'''

      lowerCAmelCase 						=							deque()  # sequence deque of terminated process
      # just for 1 cycle and unfinished processes will go back to queue
      for _ in range(len(_SCREAMING_SNAKE_CASE	)	):
          lowerCAmelCase 						=							ready_queue.popleft()  # current process

          # if process's arrival time is later than current time, update current time
          if self.current_time < cp.arrival_time:
              self.current_time += cp.arrival_time

          # update waiting time of unfinished processes
          self.update_waiting_time(_SCREAMING_SNAKE_CASE	)
          # if the burst time of process is bigger than time-slice
          if cp.burst_time > time_slice:
              # use CPU for only time-slice
              self.current_time += time_slice
              # update remaining burst time
              cp.burst_time -= time_slice
              # update end point time
              lowerCAmelCase 						=							self.current_time
              # locate the process behind the queue because it is not finished
              ready_queue.append(_SCREAMING_SNAKE_CASE	)
          else:
              # use CPU for remaining burst time
              self.current_time += cp.burst_time
              # set burst time 0 because the process is finished
              lowerCAmelCase 						=							0
              # set the finish time
              lowerCAmelCase 						=							self.current_time
              # update the process' turnaround time because it is finished
              lowerCAmelCase 						=							self.current_time - cp.arrival_time
              # add the process to queue that has finished queue
              finished.append(_SCREAMING_SNAKE_CASE	)

      self.finish_queue.extend(_SCREAMING_SNAKE_CASE	)  # add finished process to finish queue
      # return finished processes queue and remaining processes queue
      return finished, ready_queue


  def   _SCREAMING_SNAKE_CASE				(				self	):





      '''simple docstring'''

      for i in range(self.number_of_queues - 1	):
          lowerCAmelCase						,   lowerCAmelCase 						=							self.round_robin(
              self.ready_queue      , self.time_slices[i]	)
      #  the last queue has first_come_first_served algorithm
      self.first_come_first_served(self.ready_queue	)

      return self.finish_queue


if __name__ == "__main__":
     import doctest

     _UpperCamelCase						:  Dict							       =				Process("P1", 0, 53)
     _UpperCamelCase						:  str							       =				Process("P2", 0, 17)
     _UpperCamelCase						:  Any							       =				Process("P3", 0, 68)
     _UpperCamelCase						:  Optional[Any]							       =				Process("P4", 0, 24)
     _UpperCamelCase						:  Union[str, Any]							       =				3
     _UpperCamelCase						:  int							       =				[17, 25]
     _UpperCamelCase						:  int							       =				deque([Pa, Pa, Pa, Pa])

     if len(time_slices) != number_of_queues - 1:
          raise SystemExit(0)

     doctest.testmod(extraglobs={"queue": deque([Pa, Pa, Pa, Pa])})

     _UpperCamelCase						:  int							       =				Process("P1", 0, 53)
     _UpperCamelCase						:  int							       =				Process("P2", 0, 17)
     _UpperCamelCase						:  str							       =				Process("P3", 0, 68)
     _UpperCamelCase						:  str							       =				Process("P4", 0, 24)
     _UpperCamelCase						:  List[Any]							       =				3
     _UpperCamelCase						:  Optional[Any]							       =				[17, 25]
     _UpperCamelCase						:  Optional[Any]							       =				deque([Pa, Pa, Pa, Pa])
     _UpperCamelCase						:  int							       =				MLFQ(number_of_queues, time_slices, queue, 0)
     _UpperCamelCase						:  str							       =				mlfq.multi_level_feedback_queue()

     # print total waiting times of processes(P1, P2, P3, P4)
     print(
         F"""waiting time:\
        \t\t\t{MLFQ.calculate_waiting_time(mlfq, [Pa, Pa, Pa, Pa])}"""
     )
     # print completion times of processes(P1, P2, P3, P4)
     print(
         F"""completion time:\
        \t\t{MLFQ.calculate_completion_time(mlfq, [Pa, Pa, Pa, Pa])}"""
     )
     # print total turnaround times of processes(P1, P2, P3, P4)
     print(
         F"""turnaround time:\
        \t\t{MLFQ.calculate_turnaround_time(mlfq, [Pa, Pa, Pa, Pa])}"""
     )
     # print sequence of finished processes
     print(
         F"""sequence of finished processes:\
        {mlfq.calculate_sequence_of_finish_queue()}"""
     )








'''simple docstring'''



import itertools
from dataclasses import dataclass
from typing import Optional

import pandas as pd
import pyarrow as pa

import datasets
from datasets.table import table_cast



@dataclass
class 				_snake_case					(   datasets.BuilderConfig			):
  SCREAMING_SNAKE_CASE			:       Optional[datasets.Features]				=     None



class 				_snake_case					(   datasets.ArrowBasedBuilder			):
  SCREAMING_SNAKE_CASE			:       Tuple				=     PandasConfig

  def   _SCREAMING_SNAKE_CASE				(				self	):





      '''simple docstring'''

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

  def   _SCREAMING_SNAKE_CASE				(				self      , _SCREAMING_SNAKE_CASE	):





      '''simple docstring'''

      if not self.config.data_files:
          raise ValueError(F'At least one data file must be specified, but got data_files={self.config.data_files}'	)
      lowerCAmelCase 						=							dl_manager.download_and_extract(self.config.data_files	)
      if isinstance(_SCREAMING_SNAKE_CASE      , (str, list, tuple)	):
          lowerCAmelCase 						=							data_files
          if isinstance(_SCREAMING_SNAKE_CASE      , _SCREAMING_SNAKE_CASE	):
              lowerCAmelCase 						=							[files]
          # Use `dl_manager.iter_files` to skip hidden files in an extracted archive
          lowerCAmelCase 						=							[dl_manager.iter_files(_SCREAMING_SNAKE_CASE	) for file in files]
          return [datasets.SplitGenerator(name=datasets.Split.TRAIN      , gen_kwargs={'files': files}	)]
      lowerCAmelCase 						=							[]
      for split_name, files in data_files.items():
          if isinstance(_SCREAMING_SNAKE_CASE      , _SCREAMING_SNAKE_CASE	):
              lowerCAmelCase 						=							[files]
          # Use `dl_manager.iter_files` to skip hidden files in an extracted archive
          lowerCAmelCase 						=							[dl_manager.iter_files(_SCREAMING_SNAKE_CASE	) for file in files]
          splits.append(datasets.SplitGenerator(name=_SCREAMING_SNAKE_CASE      , gen_kwargs={'files': files}	)	)
      return splits

  def   _SCREAMING_SNAKE_CASE				(				self      , _SCREAMING_SNAKE_CASE	):





      '''simple docstring'''

      if self.config.features is not None:
          # more expensive cast to support nested features with keys in a different order
          # allows str <-> int/float or str to Audio for example
          lowerCAmelCase 						=							table_cast(_SCREAMING_SNAKE_CASE      , self.config.features.arrow_schema	)
      return pa_table


  def   _SCREAMING_SNAKE_CASE				(				self      , _SCREAMING_SNAKE_CASE	):





      '''simple docstring'''

      for i, file in enumerate(itertools.chain.from_iterable(_SCREAMING_SNAKE_CASE	)	):
          with open(_SCREAMING_SNAKE_CASE      , 'rb'	) as f:
              lowerCAmelCase 						=							pa.Table.from_pandas(pd.read_pickle(_SCREAMING_SNAKE_CASE	)	)
              yield i, self._cast_table(_SCREAMING_SNAKE_CASE	)





