"""simple docstring"""







from __future__ import annotations

from statistics import mean



def      lowercase__(			__SCREAMING_SNAKE_CASE				:	int	,     __SCREAMING_SNAKE_CASE				:	Any	,     __SCREAMING_SNAKE_CASE				:	Dict ):
     lowercase_      :							Any						=      [0] * no_of_processes
     lowercase_      :							str						=      [0] * no_of_processes

     # Initialize remaining_time to waiting_time.

     for i in range(UpperCAmelCase_ ):
          lowercase_      :							Tuple						=      burst_time[i]
     lowercase_      :							list[int]						=      []

     lowercase_      :							Union[str, Any]						=      0
     lowercase_      :							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:
          lowercase_      :							str						=      []
          lowercase_      :							Optional[Any]						=      -1

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

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

     return waiting_time



def      lowercase__(			__SCREAMING_SNAKE_CASE				:	Union[str, Any]	,     __SCREAMING_SNAKE_CASE				:	Optional[Any]	,     __SCREAMING_SNAKE_CASE				:	str ):
     lowercase_      :							str						=      [0] * no_of_processes
     for i in range(UpperCAmelCase_ ):
          lowercase_      :							Any						=      burst_time[i] + waiting_time[i]
     return turn_around_time


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

       __SCREAMING_SNAKE_CASE             =4
       __SCREAMING_SNAKE_CASE             =[2, 5, 3, 7]
       __SCREAMING_SNAKE_CASE             =[0, 0, 0, 0]
       __SCREAMING_SNAKE_CASE             =calculate_waitingtime(arrival_time, burst_time, no_of_processes)
       __SCREAMING_SNAKE_CASE             =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'''
from typing import List

import numpy as np






def A__       (	UpperCAmelCase_				):
						_UpperCamelCase   :						Any												=  {key: len(UpperCAmelCase_				) for key, value in gen_kwargs.items() if isinstance(UpperCAmelCase_    ,    UpperCAmelCase_				)}
						if len(set(lists_lengths.values()				)				) > 1:
												raise RuntimeError(
												    (
												        'Sharding is ambiguous for this dataset: '
												        + 'we found several data sources lists of different lengths, and we don\'t know over which list we should parallelize:\n'
												        + '\n'.join(f'\t- key {key} has length {length}' for key, length in lists_lengths.items()				)
												        + '\nTo fix this, check the \'gen_kwargs\' and make sure to use lists only for data sources, '
												        + 'and use tuples otherwise. In the end there should only be one single list, or several lists with the same length.'
												    )				)
						_UpperCamelCase   :						Tuple												=  max(lists_lengths.values()    ,    default=0				)
						return max(1    ,    UpperCAmelCase_				)






def A__       (	UpperCAmelCase_    ,    UpperCAmelCase_				):
						_UpperCamelCase   :						Dict												=  []
						for group_idx in range(UpperCAmelCase_				):
												_UpperCamelCase   :						int												=  num_shards // max_num_jobs + (group_idx < (num_shards % max_num_jobs))
												if num_shards_to_add == 0:
																		break
												_UpperCamelCase   :						Tuple												=  shards_indices_per_group[-1].stop if shards_indices_per_group else 0
												_UpperCamelCase   :						Tuple												=  range(UpperCAmelCase_    ,    start + num_shards_to_add				)
												shards_indices_per_group.append(UpperCAmelCase_				)
						return shards_indices_per_group






def A__       (	UpperCAmelCase_    ,    UpperCAmelCase_				):
						_UpperCamelCase   :						Tuple												=  _number_of_shards_in_gen_kwargs(UpperCAmelCase_				)
						if num_shards == 1:
												return [dict(UpperCAmelCase_				)]
						else:
												_UpperCamelCase   :						str												=  _distribute_shards(num_shards=UpperCAmelCase_    ,    max_num_jobs=UpperCAmelCase_				)
												return [
												    {
												        key: [value[shard_idx] for shard_idx in shard_indices_per_group[group_idx]]
												        if isinstance(UpperCAmelCase_    ,    UpperCAmelCase_				)
												        else value
												        for key, value in gen_kwargs.items()
												    }
												    for group_idx in range(len(UpperCAmelCase_				)				)
												]






def A__       (	UpperCAmelCase_				):
						return {
						    key: [value for gen_kwargs in gen_kwargs_list for value in gen_kwargs[key]]
						    if isinstance(gen_kwargs_list[0][key]    ,    UpperCAmelCase_				)
						    else gen_kwargs_list[0][key]
						    for key in gen_kwargs_list[0]
						}






def A__       (	UpperCAmelCase_    ,    UpperCAmelCase_				):
						_UpperCamelCase   :						int												=  {len(UpperCAmelCase_				) for value in gen_kwargs.values() if isinstance(UpperCAmelCase_    ,    UpperCAmelCase_				)}
						_UpperCamelCase   :						Union[str, Any]												=  {}
						for size in list_sizes:
												_UpperCamelCase   :						str												=  list(range(UpperCAmelCase_				)				)
												rng.shuffle(indices_per_size[size]				)
						# Now let's copy the gen_kwargs and shuffle the lists based on their sizes
						_UpperCamelCase   :						Union[str, Any]												=  dict(UpperCAmelCase_				)
						for key, value in shuffled_kwargs.items():
												if isinstance(UpperCAmelCase_    ,    UpperCAmelCase_				):
																		_UpperCamelCase   :						Dict												=  [value[i] for i in indices_per_size[len(UpperCAmelCase_				)]]
						return shuffled_kwargs


