
from collections import deque


class 						__lowerCAmelCase	:



      """simple docstring"""







      def __init__(      self		:       Tuple				,       _snake_case		:       str				,       _snake_case		:       int				,       _snake_case		:       int				):
          __lowercase		:			Dict	    =       process_name  # process name
          __lowercase		:			Optional[int]	    =       arrival_time  # arrival time of the process
          # completion time of finished process or last interrupted time
          __lowercase		:			Optional[int]	    =       arrival_time
          __lowercase		:			List[Any]	    =       burst_time  # remaining burst time
          __lowercase		:			List[Any]	    =       0  # total time of the process wait in ready queue
          __lowercase		:			str	    =       0  # time from arrival time to completion time






class 						__lowerCAmelCase	:



      """simple docstring"""







      def __init__(      self		:       List[str]				,       _snake_case		:       int				,       _snake_case		:       list[int]				,       _snake_case		:       deque[Process]				,       _snake_case		:       int				,       ):
          # total number of mlfq's queues
          __lowercase		:			Optional[Any]	    =       number_of_queues
          # time slice of queues that round robin algorithm applied
          __lowercase		:			Union[str, Any]	    =       time_slices
          # unfinished process is in this ready_queue
          __lowercase		:			Optional[int]	    =       queue
          # current time
          __lowercase		:			List[Any]	    =       current_time
          # finished process is in this sequence queue
          __lowercase		:			deque[Process]	    =       deque()




      def 		snake_case_			(      self		:       Any				):
          __lowercase		:			int	    =       []
          for i in range(len(self.finish_queue				)				):
              sequence.append(self.finish_queue[i].process_name				)
          return sequence




      def 		snake_case_			(      self		:       int				,       _snake_case		:       list[Process]				):
          __lowercase		:			Optional[int]	    =       []
          for i in range(len(_snake_case				)				):
              waiting_times.append(queue[i].waiting_time				)
          return waiting_times




      def 		snake_case_			(      self		:       List[Any]				,       _snake_case		:       list[Process]				):
          __lowercase		:			List[Any]	    =       []
          for i in range(len(_snake_case				)				):
              turnaround_times.append(queue[i].turnaround_time				)
          return turnaround_times




      def 		snake_case_			(      self		:       Union[str, Any]				,       _snake_case		:       list[Process]				):
          __lowercase		:			Any	    =       []
          for i in range(len(_snake_case				)				):
              completion_times.append(queue[i].stop_time				)
          return completion_times




      def 		snake_case_			(      self		:       Tuple				,       _snake_case		:       deque[Process]				):
          return [q.burst_time for q in queue]




      def 		snake_case_			(      self		:       Union[str, Any]				,       _snake_case		:       Process				):
          process.waiting_time += self.current_time - process.stop_time
          return process.waiting_time




      def 		snake_case_			(      self		:       int				,       _snake_case		:       deque[Process]				):
          __lowercase		:			deque[Process]	    =       deque()  # sequence deque of finished process
          while len(_snake_case				) != 0:
              __lowercase		:			str	    =       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(_snake_case				)
              # update current time
              self.current_time += cp.burst_time
              # finish the process and set the process's burst-time 0
              __lowercase		:			Tuple	    =       0
              # set the process's turnaround time because it is finished
              __lowercase		:			List[str]	    =       self.current_time - cp.arrival_time
              # set the completion time
              __lowercase		:			List[str]	    =       self.current_time
              # add the process to queue that has finished queue
              finished.append(_snake_case				)

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




      def 		snake_case_			(      self		:       Optional[Any]				,       _snake_case		:       deque[Process]				,       _snake_case		:       int				):
          __lowercase		:			deque[Process]	    =       deque()  # sequence deque of terminated process
          # just for 1 cycle and unfinished processes will go back to queue
          for _ in range(len(_snake_case				)				):
              __lowercase		:			Optional[int]	    =       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(_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
                  __lowercase		:			Tuple	    =       self.current_time
                  # locate the process behind the queue because it is not finished
                  ready_queue.append(_snake_case				)
              else:
                  # use CPU for remaining burst time
                  self.current_time += cp.burst_time
                  # set burst time 0 because the process is finished
                  __lowercase		:			List[Any]	    =       0
                  # set the finish time
                  __lowercase		:			Optional[int]	    =       self.current_time
                  # update the process' turnaround time because it is finished
                  __lowercase		:			str	    =       self.current_time - cp.arrival_time
                  # add the process to queue that has finished queue
                  finished.append(_snake_case				)

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




      def 		snake_case_			(      self		:       Dict				):

          #  all queues except last one have round_robin algorithm
          for i in range(self.number_of_queues - 1				):
              __lowercase    ,      __lowercase		:			str	    =       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

 __lowerCAmelCase					:			Union[str, Any]			      =		Process("P1", 0, 53)
 __lowerCAmelCase					:			int			      =		Process("P2", 0, 17)
 __lowerCAmelCase					:			List[str]			      =		Process("P3", 0, 68)
 __lowerCAmelCase					:			int			      =		Process("P4", 0, 24)
 __lowerCAmelCase					:			int			      =		3
 __lowerCAmelCase					:			Dict			      =		[17, 25]
 __lowerCAmelCase					:			List[str]			      =		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])})

 __lowerCAmelCase					:			Union[str, Any]			      =		Process("P1", 0, 53)
 __lowerCAmelCase					:			List[Any]			      =		Process("P2", 0, 17)
 __lowerCAmelCase					:			Dict			      =		Process("P3", 0, 68)
 __lowerCAmelCase					:			Optional[Any]			      =		Process("P4", 0, 24)
 __lowerCAmelCase					:			Union[str, Any]			      =		3
 __lowerCAmelCase					:			Any			      =		[17, 25]
 __lowerCAmelCase					:			str			      =		deque([Pa, Pa, Pa, Pa])
 __lowerCAmelCase					:			Union[str, Any]			      =		MLFQ(number_of_queues, time_slices, queue, 0)
 __lowerCAmelCase					:			List[Any]			      =		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()}'
 )




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 						__lowerCAmelCase	(	datasets.BuilderConfig      ):



      """simple docstring"""







      A__	:			Optional[datasets.Features]        =    None






class 						__lowerCAmelCase	(	datasets.ArrowBasedBuilder      ):



      """simple docstring"""







      A__	:			List[str]        =    PandasConfig




      def 		snake_case_			(      self		:       int				):
          return datasets.DatasetInfo(features=self.config.features				)




      def 		snake_case_			(      self		:       int				,       _snake_case		:       Optional[int]				):
          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}'				)
          __lowercase		:			Any	    =       dl_manager.download_and_extract(self.config.data_files				)
          if isinstance(_snake_case				,       (str, list, tuple)				):
              __lowercase		:			str	    =       data_files
              if isinstance(_snake_case				,       _snake_case				):
                  __lowercase		:			Any	    =       [files]
              # Use `dl_manager.iter_files` to skip hidden files in an extracted archive
              __lowercase		:			Optional[int]	    =       [dl_manager.iter_files(_snake_case				) for file in files]
              return [datasets.SplitGenerator(name=datasets.Split.TRAIN				,       gen_kwargs={'''files''': files}				)]
          __lowercase		:			str	    =       []
          for split_name, files in data_files.items():
              if isinstance(_snake_case				,       _snake_case				):
                  __lowercase		:			str	    =       [files]
              # Use `dl_manager.iter_files` to skip hidden files in an extracted archive
              __lowercase		:			int	    =       [dl_manager.iter_files(_snake_case				) for file in files]
              splits.append(datasets.SplitGenerator(name=_snake_case				,       gen_kwargs={'''files''': files}				)				)
          return splits




      def 		snake_case_			(      self		:       Optional[int]				,       _snake_case		:       pa.Table				):
          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
              __lowercase		:			List[str]	    =       table_cast(_snake_case				,       self.config.features.arrow_schema				)
          return pa_table




      def 		snake_case_			(      self		:       int				,       _snake_case		:       Union[str, Any]				):
          for i, file in enumerate(itertools.chain.from_iterable(_snake_case				)				):
              with open(_snake_case				,       '''rb'''				) as f:
                  __lowercase		:			Dict	    =       pa.Table.from_pandas(pd.read_pickle(_snake_case				)				)
                  yield i, self._cast_table(_snake_case				)


