
'''simple docstring'''



import enum
import os
from hashlib import shaaaa
from typing import Optional

from .. import config
from .logging import get_logger


UpperCamelCase__   :		Union[str, Any]											=	get_logger(__name__)

class  _a					(enum.Enum):





       """simple docstring"""




       SCREAMING_SNAKE_CASE   =	'''all_checks'''
       SCREAMING_SNAKE_CASE   =	'''basic_checks'''
       SCREAMING_SNAKE_CASE   =	'''no_checks'''






class  _a					(_lowercase):





       """simple docstring"""










class  _a					(_lowercase):





       """simple docstring"""










class  _a					(_lowercase):





       """simple docstring"""










class  _a					(_lowercase):





       """simple docstring"""










def  lowerCAmelCase_						(					SCREAMING_SNAKE_CASE_     ,   SCREAMING_SNAKE_CASE_     ,   SCREAMING_SNAKE_CASE_=None    )  ->  Union[str, Any]:




   """simple docstring"""
   if expected_checksums is None:
      logger.info("""Unable to verify checksums."""    )
      return
   if len(set(__UpperCAmelCase    ) - set(__UpperCAmelCase    )    ) > 0:
      raise ExpectedMoreDownloadedFiles(str(set(__UpperCAmelCase    ) - set(__UpperCAmelCase    )    )    )
   if len(set(__UpperCAmelCase    ) - set(__UpperCAmelCase    )    ) > 0:
      raise UnexpectedDownloadedFile(str(set(__UpperCAmelCase    ) - set(__UpperCAmelCase    )    )    )
   _SCREAMING_SNAKE_CASE  			=					[url for url in expected_checksums if expected_checksums[url] != recorded_checksums[url]]
   _SCREAMING_SNAKE_CASE  			=					""" for """ + verification_name if verification_name is not None else """"""
   if len(__UpperCAmelCase    ) > 0:
      raise NonMatchingChecksumError(
          F"Checksums didn't match{for_verification_name}:\n"
          F"{bad_urls}\n"
          """Set `verification_mode=\'no_checks\'` to skip checksums verification and ignore this error"""    )
   logger.info("""All the checksums matched successfully""" + for_verification_name    )

class  _a					(_lowercase):





       """simple docstring"""










class  _a					(_lowercase):





       """simple docstring"""










class  _a					(_lowercase):





       """simple docstring"""










class  _a					(_lowercase):





       """simple docstring"""










def  lowerCAmelCase_						(					SCREAMING_SNAKE_CASE_     ,   SCREAMING_SNAKE_CASE_    )  ->  int:




   """simple docstring"""
   if expected_splits is None:
      logger.info("""Unable to verify splits sizes."""    )
      return
   if len(set(__UpperCAmelCase    ) - set(__UpperCAmelCase    )    ) > 0:
      raise ExpectedMoreSplits(str(set(__UpperCAmelCase    ) - set(__UpperCAmelCase    )    )    )
   if len(set(__UpperCAmelCase    ) - set(__UpperCAmelCase    )    ) > 0:
      raise UnexpectedSplits(str(set(__UpperCAmelCase    ) - set(__UpperCAmelCase    )    )    )
   _SCREAMING_SNAKE_CASE  			=					[
       {"""expected""": expected_splits[name], """recorded""": recorded_splits[name]}
       for name in expected_splits
       if expected_splits[name].num_examples != recorded_splits[name].num_examples
   ]
   if len(__UpperCAmelCase    ) > 0:
      raise NonMatchingSplitsSizesError(str(__UpperCAmelCase    )    )
   logger.info("""All the splits matched successfully."""    )
def  lowerCAmelCase_						(					SCREAMING_SNAKE_CASE_     ,   SCREAMING_SNAKE_CASE_ = True    )  ->  Union[str, Any]:




   """simple docstring"""
   if record_checksum:
      _SCREAMING_SNAKE_CASE  			=					shaaaa()
      with open(__UpperCAmelCase     ,   """rb"""    ) as f:
         for chunk in iter(lambda: f.read(1 << 20    )     ,   b""""""    ):
            m.update(__UpperCAmelCase    )
         _SCREAMING_SNAKE_CASE  			=					m.hexdigest()
   else:
      _SCREAMING_SNAKE_CASE  			=					None
   return {"num_bytes": os.path.getsize(__UpperCAmelCase    ), "checksum": checksum}







def  lowerCAmelCase_						(					SCREAMING_SNAKE_CASE_    )  ->  int:




   """simple docstring"""
   if dataset_size and config.IN_MEMORY_MAX_SIZE:
      return dataset_size < config.IN_MEMORY_MAX_SIZE
   else:
      return False











from statistics import mean

import numpy as np






def     __a					(		__UpperCAmelCase							,  __UpperCAmelCase							,  __UpperCAmelCase							,  __UpperCAmelCase       ):
 a__												= 0
 # Number of processes finished
 a__												= 0
 # Displays the finished process.
 # If it is 0, the performance is completed if it is 1, before the performance.
 a__												= [0] * no_of_process
 # List to include calculation results
 a__												= [0] * no_of_process

 # Sort by arrival time.
 a__												= [burst_time[i] for i in np.argsort(__UpperCAmelCase       )]
 a__												= [process_name[i] for i in np.argsort(__UpperCAmelCase       )]
 arrival_time.sort()

 while no_of_process > finished_process_count:
  a__												= 0
  while finished_process[i] == 1:
   i += 1
  if current_time < arrival_time[i]:
   a__												= arrival_time[i]

  a__												= 0
  # Index showing the location of the process being performed
  a__												= 0
  # Saves the current response ratio.
  a__												= 0
  for i in range(0							,  __UpperCAmelCase       ):
   if finished_process[i] == 0 and arrival_time[i] <= current_time:
    a__												= (burst_time[i] + (current_time - arrival_time[i])) / burst_time[
        i
    ]
   if response_ratio < temp:
    a__												= temp
    a__												= i

        # Calculate the turn around time
  a__												= current_time + burst_time[loc] - arrival_time[loc]
  current_time += burst_time[loc]
  # Indicates that the process has been performed.
  a__												= 1
  # Increase finished_process_count by 1
  finished_process_count += 1

 return turn_around_time






def     __a					(		__UpperCAmelCase							,  __UpperCAmelCase							,  __UpperCAmelCase							,  __UpperCAmelCase       ):
 a__												= [0] * no_of_process
 for i in range(0							,  __UpperCAmelCase       ):
  a__												= turn_around_time[i] - burst_time[i]
 return waiting_time


if __name__ == "__main__":
     a_      :      List[Any]    =     5
     a_      :      Optional[int]    =     ['A', 'B', 'C', 'D', 'E']
     a_      :      Union[str, Any]    =     [1, 2, 3, 4, 5]
     a_      :      Dict    =     [1, 2, 3, 4, 5]

     a_      :      List[Any]    =     calculate_turn_around_time(
         process_name, arrival_time, burst_time, no_of_process
     )
     a_      :      int    =     calculate_waiting_time(
         process_name, turn_around_time, burst_time, no_of_process
     )

     print('Process name \tArrival time \tBurst time \tTurn around time \tWaiting time')
     for i in range(0, no_of_process):
          print(
              f'{process_name[i]}\t\t{arrival_time[i]}\t\t{burst_time[i]}\t\t'
              f'{turn_around_time[i]}\t\t\t{waiting_time[i]}'
          )

     print(f'average waiting time : {mean(waiting_time):.5f}')
     print(f'average turn around time : {mean(turn_around_time):.5f}')





