code: 
  
  
  
  
  '''simple docstring'''
  
  
  
  
  
  
  
  from __future__ import annotations
  
  
  
  
  
  
  def 	_lowercase	(			lowercase_						):
  
  
  
  		'''simple docstring'''
  
  
  
  
  
  
  
  		_snake_case			 = [0] * len(lowercase_						)
  		for i in range(1		,							len(lowercase_						)						):
  				_snake_case			 = duration_times[i - 1] + waiting_times[i - 1]
  		return waiting_times
  
  
  
  
  
  
  def 	_lowercase	(			lowercase_		,							lowercase_						):
  
  
  
  		'''simple docstring'''
  
  
  
  
  
  
  
  		return [
  		    duration_time + waiting_times[i]
  		    for i, duration_time in enumerate(lowercase_						)
  		]
  
  
  
  
  
  
  def 	_lowercase	(			lowercase_						):
  
  
  
  		'''simple docstring'''
  
  
  
  
  
  
  
  		return sum(lowercase_						) / len(lowercase_						)
  
  
  
  
  
  
  def 	_lowercase	(			lowercase_						):
  
  
  
  		'''simple docstring'''
  
  
  
  
  
  
  
  		return sum(lowercase_						) / len(lowercase_						)
  
  
  if __name__ == "__main__":
  						# process id's
  						_lowerCamelCase							:		int										=						[1, 2, 3]
  
  						# ensure that we actually have processes
  						if len(processes) == 0:
  												print('Zero amount of processes')
  												raise SystemExit(0)
  
  						# duration time of all processes
  						_lowerCamelCase							:		Optional[Any]										=						[19, 8, 9]
  
  						# ensure we can match each id to a duration time
  						if len(duration_times) != len(processes):
  												print('Unable to match all id\'s with their duration time')
  												raise SystemExit(0)
  
  						# get the waiting times and the turnaround times
  						_lowerCamelCase							:		List[Any]										=						calculate_waiting_times(duration_times)
  						_lowerCamelCase							:		int										=						calculate_turnaround_times(duration_times, waiting_times)
  
  						# get the average times
  						_lowerCamelCase							:		str										=						calculate_average_waiting_time(waiting_times)
  						_lowerCamelCase							:		int										=						calculate_average_turnaround_time(turnaround_times)
  
  						# print all the results
  						print('Process ID\tDuration Time\tWaiting Time\tTurnaround Time')
  						for i, process in enumerate(processes):
  												print(
  												    F'''{process}\t\t{duration_times[i]}\t\t{waiting_times[i]}\t\t'''
  												    F'''{turnaround_times[i]}'''
  												)
  						print(F'''Average waiting time = {average_waiting_time}''')
  						print(F'''Average turn around time = {average_turnaround_time}''')
  
  
  
  
  
  
style_context: 
  
  
  
  
  '''simple docstring'''
  
  
  
  
  
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import (
      OptionalDependencyNotAvailable,
      _LazyModule,
      is_flax_available,
      is_sentencepiece_available,
      is_tf_available,
      is_tokenizers_available,
      is_torch_available,
  )
  
  
  _lowerCamelCase							:		Any										=						{'configuration_pegasus': ['PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP', 'PegasusConfig']}
  
  try:
  						if not is_sentencepiece_available():
  												raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  						pass
  else:
  						_lowerCamelCase							:		Optional[Any]										=						['PegasusTokenizer']
  
  try:
  						if not is_tokenizers_available():
  												raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  						pass
  else:
  						_lowerCamelCase							:		Optional[Any]										=						['PegasusTokenizerFast']
  
  try:
  						if not is_torch_available():
  												raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  						pass
  else:
  						_lowerCamelCase							:		List[str]										=						[
  						    'PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST',
  						    'PegasusForCausalLM',
  						    'PegasusForConditionalGeneration',
  						    'PegasusModel',
  						    'PegasusPreTrainedModel',
  						]
  
  try:
  						if not is_tf_available():
  												raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  						pass
  else:
  						_lowerCamelCase							:		Union[str, Any]										=						[
  						    'TFPegasusForConditionalGeneration',
  						    'TFPegasusModel',
  						    'TFPegasusPreTrainedModel',
  						]
  
  try:
  						if not is_flax_available():
  												raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  						pass
  else:
  						_lowerCamelCase							:		List[Any]										=						[
  						    'FlaxPegasusForConditionalGeneration',
  						    'FlaxPegasusModel',
  						    'FlaxPegasusPreTrainedModel',
  						]
  
  
  if TYPE_CHECKING:
  						from .configuration_pegasus import PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP, PegasusConfig
  
  						try:
  												if not is_sentencepiece_available():
  																		raise OptionalDependencyNotAvailable()
  						except OptionalDependencyNotAvailable:
  												pass
  						else:
  												from .tokenization_pegasus import PegasusTokenizer
  
  						try:
  												if not is_tokenizers_available():
  																		raise OptionalDependencyNotAvailable()
  						except OptionalDependencyNotAvailable:
  												pass
  						else:
  												from .tokenization_pegasus_fast import PegasusTokenizerFast
  
  						try:
  												if not is_torch_available():
  																		raise OptionalDependencyNotAvailable()
  						except OptionalDependencyNotAvailable:
  												pass
  						else:
  												from .modeling_pegasus import (
  												    PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST,
  												    PegasusForCausalLM,
  												    PegasusForConditionalGeneration,
  												    PegasusModel,
  												    PegasusPreTrainedModel,
  												)
  
  						try:
  												if not is_tf_available():
  																		raise OptionalDependencyNotAvailable()
  						except OptionalDependencyNotAvailable:
  												pass
  						else:
  												from .modeling_tf_pegasus import TFPegasusForConditionalGeneration, TFPegasusModel, TFPegasusPreTrainedModel
  
  						try:
  												if not is_flax_available():
  																		raise OptionalDependencyNotAvailable()
  						except OptionalDependencyNotAvailable:
  												pass
  						else:
  												from .modeling_flax_pegasus import (
  												    FlaxPegasusForConditionalGeneration,
  												    FlaxPegasusModel,
  												    FlaxPegasusPreTrainedModel,
  												)
  
  else:
  						import sys
  
  						_lowerCamelCase							:		List[Any]										=						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
  
  
  
  
  
  