

'''simple docstring'''

from collections import deque




class 	A_			:






     '''simple docstring'''



     def __init__(		self			:					Any					,      lowercase_			:					str					,      lowercase_			:					int					,      lowercase_			:					int	)						->     None:
      UpperCAmelCase	:     Optional[int]						 =			process_name  # process name
      UpperCAmelCase	:     Tuple						 =			arrival_time  # arrival time of the process
      # completion time of finished process or last interrupted time
      UpperCAmelCase	:     Optional[int]						 =			arrival_time
      UpperCAmelCase	:     Union[str, Any]						 =			burst_time  # remaining burst time
      UpperCAmelCase	:     str						 =			0  # total time of the process wait in ready queue
      UpperCAmelCase	:     int						 =			0  # time from arrival time to completion time




class 	A_			:






     '''simple docstring'''



     def __init__(		self			:					Optional[Any]					,      lowercase_			:					int					,      lowercase_			:					list[int]					,      lowercase_			:					deque[Process]					,      lowercase_			:					int					,      )						->     None:
      # total number of mlfq's queues
      UpperCAmelCase	:     Dict						 =			number_of_queues
      # time slice of queues that round robin algorithm applied
      UpperCAmelCase	:     Optional[Any]						 =			time_slices
      # unfinished process is in this ready_queue
      UpperCAmelCase	:     int						 =			queue
      # current time
      UpperCAmelCase	:     Any						 =			current_time
      # finished process is in this sequence queue
      UpperCAmelCase	:     deque[Process]						 =			deque()


     def        UpperCAmelCase_	(		self			:					Optional[int]	)						->     list[str]:
      UpperCAmelCase	:     Tuple						 =			[]
      for i in range(len(self.finish_queue	)	):
       sequence.append(self.finish_queue[i].process_name	)
      return sequence


     def        UpperCAmelCase_	(		self			:					str					,      lowercase_			:					list[Process]	)						->     list[int]:
      UpperCAmelCase	:     str						 =			[]
      for i in range(len(lowercase_	)	):
       waiting_times.append(queue[i].waiting_time	)
      return waiting_times


     def        UpperCAmelCase_	(		self			:					int					,      lowercase_			:					list[Process]	)						->     list[int]:
      UpperCAmelCase	:     str						 =			[]
      for i in range(len(lowercase_	)	):
       turnaround_times.append(queue[i].turnaround_time	)
      return turnaround_times


     def        UpperCAmelCase_	(		self			:					Optional[int]					,      lowercase_			:					list[Process]	)						->     list[int]:
      UpperCAmelCase	:     Dict						 =			[]
      for i in range(len(lowercase_	)	):
       completion_times.append(queue[i].stop_time	)
      return completion_times


     def        UpperCAmelCase_	(		self			:					int					,      lowercase_			:					deque[Process]	)						->     list[int]:
      return [q.burst_time for q in queue]


     def        UpperCAmelCase_	(		self			:					Optional[int]					,      lowercase_			:					Process	)						->     int:
      process.waiting_time += self.current_time - process.stop_time
      return process.waiting_time


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

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


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

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




     def        UpperCAmelCase_	(		self			:					Optional[int]	)						->     deque[Process]:

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

 lowercase__         =      Process("P1", 0, 53)
 lowercase__         =      Process("P2", 0, 17)
 lowercase__         =      Process("P3", 0, 68)
 lowercase__         =      Process("P4", 0, 24)
 lowercase__         =      3
 lowercase__         =      [17, 25]
 lowercase__         =      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])})

 lowercase__         =      Process("P1", 0, 53)
 lowercase__         =      Process("P2", 0, 17)
 lowercase__         =      Process("P3", 0, 68)
 lowercase__         =      Process("P4", 0, 24)
 lowercase__         =      3
 lowercase__         =      [17, 25]
 lowercase__         =      deque([Pa, Pa, Pa, Pa])
 lowercase__         =      MLFQ(number_of_queues, time_slices, queue, 0)
 lowercase__         =      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'''

from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar

lowercase__         =      TypeVar("KEY")
lowercase__         =      TypeVar("VAL")




@dataclass(frozen=_snake_case	,       slots=_snake_case							)
class 	A_			(    Generic[KEY, VAL]							):






     '''simple docstring'''



     UpperCAmelCase_						:     KEY
     UpperCAmelCase_						:     VAL




class 	A_			(    _Item							):






     '''simple docstring'''



     def __init__(		self			:					Any	)						->     None:
      super().__init__(lowercase_					,      lowercase_	)




     def __bool__(		self			:					List[str]	)						->     bool:
      return False



lowercase__         =      _DeletedItem()




class 	A_			(    MutableMapping[KEY, VAL]							):






     '''simple docstring'''



     def __init__(		self			:					Optional[int]					,      lowercase_			:					int = 8					,      lowercase_			:					float = 0.75	)						->     None:
      UpperCAmelCase	:     Dict						 =			initial_block_size
      UpperCAmelCase	:     list[_Item | None]						 =			[None] * initial_block_size
      assert 0.0 < capacity_factor < 1.0
      UpperCAmelCase	:     Any						 =			capacity_factor
      UpperCAmelCase	:     Union[str, Any]						 =			0


     def        UpperCAmelCase_	(		self			:					str					,      lowercase_			:					KEY	)						->     int:
      return hash(lowercase_	) % len(self._buckets	)


     def        UpperCAmelCase_	(		self			:					Any					,      lowercase_			:					int	)						->     int:
      return (ind + 1) % len(self._buckets	)


     def        UpperCAmelCase_	(		self			:					Dict					,      lowercase_			:					int					,      lowercase_			:					KEY					,      lowercase_			:					VAL	)						->     bool:
      UpperCAmelCase	:     List[Any]						 =			self._buckets[ind]
      if not stored:
       UpperCAmelCase	:     Dict						 =			_Item(lowercase_					,      lowercase_	)
       self._len += 1
       return True
      elif stored.key == key:
       UpperCAmelCase	:     Dict						 =			_Item(lowercase_					,      lowercase_	)
       return True
      else:
       return False


     def        UpperCAmelCase_	(		self			:					Any	)						->     bool:
      UpperCAmelCase	:     List[str]						 =			len(self._buckets	) * self._capacity_factor
      return len(self	) >= int(lowercase_	)


     def        UpperCAmelCase_	(		self			:					Optional[int]	)						->     bool:
      if len(self._buckets	) <= self._initial_block_size:
       return False
      UpperCAmelCase	:     Optional[int]						 =			len(self._buckets	) * self._capacity_factor / 2
      return len(self	) < limit


     def        UpperCAmelCase_	(		self			:					Dict					,      lowercase_			:					int	)						->     None:
      UpperCAmelCase	:     int						 =			self._buckets
      UpperCAmelCase	:     List[str]						 =			[None] * new_size
      UpperCAmelCase	:     Dict						 =			0
      for item in old_buckets:
       if item:
        self._add_item(item.key					,      item.val	)


     def        UpperCAmelCase_	(		self			:					Dict	)						->     None:
      self._resize(len(self._buckets	) * 2	)


     def        UpperCAmelCase_	(		self			:					Union[str, Any]	)						->     None:
      self._resize(len(self._buckets	) // 2	)


     def        UpperCAmelCase_	(		self			:					Union[str, Any]					,      lowercase_			:					KEY	)						->     Iterator[int]:
      UpperCAmelCase	:     Dict						 =			self._get_bucket_index(lowercase_	)
      for _ in range(len(self._buckets	)	):
       yield ind
       UpperCAmelCase	:     Union[str, Any]						 =			self._get_next_ind(lowercase_	)


     def        UpperCAmelCase_	(		self			:					Dict					,      lowercase_			:					KEY					,      lowercase_			:					VAL	)						->     None:
      for ind in self._iterate_buckets(lowercase_	):
       if self._try_set(lowercase_					,      lowercase_					,      lowercase_	):
        break


     def __setitem__(		self			:					Union[str, Any]					,      lowercase_			:					KEY					,      lowercase_			:					VAL	)						->     None:
      if self._is_full():
       self._size_up()

      self._add_item(lowercase_					,      lowercase_	)


     def __delitem__(		self			:					Tuple					,      lowercase_			:					KEY	)						->     None:
      for ind in self._iterate_buckets(lowercase_	):
       UpperCAmelCase	:     int						 =			self._buckets[ind]
       if item is None:
        raise KeyError(lowercase_	)
       if item is _deleted:
        continue
       if item.key == key:
        UpperCAmelCase	:     Union[str, Any]						 =			_deleted
        self._len -= 1
        break
      if self._is_sparse():
       self._size_down()


     def __getitem__(		self			:					Dict					,      lowercase_			:					KEY	)						->     VAL:
      for ind in self._iterate_buckets(lowercase_	):
       UpperCAmelCase	:     List[str]						 =			self._buckets[ind]
       if item is None:
        break
       if item is _deleted:
        continue
       if item.key == key:
        return item.val
      raise KeyError(lowercase_	)


     def __len__(		self			:					Optional[Any]	)						->     int:
      return self._len


     def __iter__(		self			:					int	)						->     Iterator[KEY]:
      yield from (item.key for item in self._buckets if item)




     def __repr__(		self			:					Optional[Any]	)						->     str:
      UpperCAmelCase	:     int						 =			' ,'.join(
          f"""{item.key}: {item.val}""" for item in self._buckets if item	)
      return f"""HashMap({val_string})"""




