
'''simple docstring'''
from __future__ import annotations

from statistics import mean

def 						UpperCamelCase_     (	__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       ):
    """simple docstring"""






    snake_case_ :    Any     			=						[0] * no_of_processes
    snake_case_ :    Optional[int]     			=						[0] * no_of_processes

    # Initialize remaining_time to waiting_time.

    for i in range(__SCREAMING_SNAKE_CASE       ):
        snake_case_ :    str     			=						burst_time[i]
    snake_case_ :    list[int]     			=						[]

    snake_case_ :    Tuple     			=						0
    snake_case_ :    Optional[int]     			=						0

    # When processes are not completed,
    # A process whose arrival time has passed \
    # and has remaining execution time is put into the ready_process.
    # The shortest process in the ready_process, target_process is executed.

    while completed != no_of_processes:
        snake_case_ :    Any     			=						[]
        snake_case_ :    Dict     			=						-1

        for i in range(__SCREAMING_SNAKE_CASE       ):
            if (arrival_time[i] <= total_time) and (remaining_time[i] > 0):
                ready_process.append(__SCREAMING_SNAKE_CASE       )

        if len(__SCREAMING_SNAKE_CASE       ) > 0:
            snake_case_ :    Dict     			=						ready_process[0]
            for i in ready_process:
                if remaining_time[i] < remaining_time[target_process]:
                    snake_case_ :    Optional[int]     			=						i
            total_time += burst_time[target_process]
            completed += 1
            snake_case_ :    Tuple     			=						0
            snake_case_ :    int     			=						(
                total_time - arrival_time[target_process] - burst_time[target_process]
            )
        else:
            total_time += 1

    return waiting_time

def 						UpperCamelCase_     (	__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       ):
    """simple docstring"""






    snake_case_ :    Optional[int]     			=						[0] * no_of_processes
    for i in range(__SCREAMING_SNAKE_CASE       ):
        snake_case_ :    Dict     			=						burst_time[i] + waiting_time[i]
    return turn_around_time


if __name__ == "__main__":
  print("[TEST CASE 01]")

  a_											=						4
  a_											=						[2, 5, 3, 7]
  a_											=						[0, 0, 0, 0]
  a_											=						calculate_waitingtime(arrival_time, burst_time, no_of_processes)
  a_											=						calculate_turnaroundtime(
      burst_time, no_of_processes, waiting_time
  )

  # Printing the Result
  print("PID\tBurst Time\tArrival Time\tWaiting Time\tTurnaround Time")
  for i, process_id in enumerate(list(range(1, 5))):
    print(
        f"""{process_id}\t{burst_time[i]}\t\t\t{arrival_time[i]}\t\t\t\t"""
        f"""{waiting_time[i]}\t\t\t\t{turn_around_time[i]}"""
    )
  print(f"""\nAverage waiting time = {mean(waiting_time):.5f}""")
  print(f"""Average turnaround time = {mean(turn_around_time):.5f}""")






'''simple docstring'''
import contextlib
from multiprocessing import Pool, RLock

from tqdm.auto import tqdm

from ..utils import experimental, logging


a_											=						logging.get_logger(__name__)






class    UpperCAmelCase_				:
 UpperCAmelCase_		    =						None


@experimental
def 						UpperCamelCase_     (	__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       ):
    """simple docstring"""






    if ParallelBackendConfig.backend_name is None:
        return _map_with_multiprocessing_pool(
            __SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       )

    return _map_with_joblib(__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       )

def 						UpperCamelCase_     (	__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       ):
    """simple docstring"""






    snake_case_ :    str     			=						num_proc if num_proc <= len(__SCREAMING_SNAKE_CASE       ) else len(__SCREAMING_SNAKE_CASE       )
    snake_case_ :    Optional[int]     			=						[]  # We organize the splits ourselve (contiguous splits)
    for index in range(__SCREAMING_SNAKE_CASE       ):
        snake_case_ :    List[str]     			=						len(__SCREAMING_SNAKE_CASE       ) // num_proc
        snake_case_ :    Optional[Any]     			=						len(__SCREAMING_SNAKE_CASE       ) % num_proc
        snake_case_ :    Optional[Any]     			=						div * index + min(__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       )
        snake_case_ :    Union[str, Any]     			=						start + div + (1 if index < mod else 0)
        split_kwds.append((function, iterable[start:end], types, index, disable_tqdm, desc)       )

    if len(__SCREAMING_SNAKE_CASE       ) != sum(len(i[1]       ) for i in split_kwds       ):
        raise ValueError(
            f'Error dividing inputs iterable among processes. '
            f'Total number of objects {len(__SCREAMING_SNAKE_CASE       )}, '
            f'length: {sum(len(i[1]       ) for i in split_kwds       )}'       )

    logger.info(
        f'Spawning {num_proc} processes for {len(__SCREAMING_SNAKE_CASE       )} objects in slices of {[len(i[1]       ) for i in split_kwds]}'       )
    snake_case_			, snake_case_ :    Tuple     			=						None, None
    if not disable_tqdm:
        snake_case_			, snake_case_ :    int     			=						(RLock(),), tqdm.set_lock
    with Pool(__SCREAMING_SNAKE_CASE,		initargs=__SCREAMING_SNAKE_CASE,		initializer=__SCREAMING_SNAKE_CASE       ) as pool:
        snake_case_ :    Union[str, Any]     			=						pool.map(__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       )
    logger.info(f'Finished {num_proc} processes'       )
    snake_case_ :    str     			=						[obj for proc_res in mapped for obj in proc_res]
    logger.info(f'Unpacked {len(__SCREAMING_SNAKE_CASE       )} objects'       )

    return mapped

def 						UpperCamelCase_     (	__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       ):
    """simple docstring"""






    import joblib

    with joblib.parallel_backend(ParallelBackendConfig.backend_name,		n_jobs=__SCREAMING_SNAKE_CASE       ):
        return joblib.Parallel()(
            joblib.delayed(__SCREAMING_SNAKE_CASE       )((function, obj, types, None, True, None)       ) for obj in iterable       )


@experimental
@contextlib.contextmanager
def 						UpperCamelCase_     (	__SCREAMING_SNAKE_CASE       ):
    """simple docstring"""






    snake_case_ :    Union[str, Any]     			=						backend_name

    if backend_name == "spark":
        from joblibspark import register_spark

        register_spark()

        # TODO: call create_cache_and_write_probe if "download" in steps
        # TODO: raise NotImplementedError when Dataset.map etc is called

    try:
        yield
    finally:
        snake_case_ :    Any     			=						None




