



'''simple docstring'''


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

from .. import config
from .logging import get_logger


_lowerCamelCase	:       Dict      	=	get_logger(__name__)

class  SCREAMING_SNAKE_CASE (  enum.Enum		):






    """simple docstring"""





    _SCREAMING_SNAKE_CASE	  =  """all_checks"""
    _SCREAMING_SNAKE_CASE	  =  """basic_checks"""
    _SCREAMING_SNAKE_CASE	  =  """no_checks"""

class  SCREAMING_SNAKE_CASE (  _a		):






    """simple docstring"""






class  SCREAMING_SNAKE_CASE (  _a		):






    """simple docstring"""






class  SCREAMING_SNAKE_CASE (  _a		):






    """simple docstring"""






class  SCREAMING_SNAKE_CASE (  _a		):






    """simple docstring"""












def 				__lowerCamelCase				(   A__    ,						A__    ,						A__=None    )       ->	List[Any]:






   """simple docstring"""
   if expected_checksums is None:
      logger.info('Unable to verify checksums.'    )
      return
   if len(set(A__    ) - set(A__    )    ) > 0:
      raise ExpectedMoreDownloadedFiles(str(set(A__    ) - set(A__    )    )    )
   if len(set(A__    ) - set(A__    )    ) > 0:
      raise UnexpectedDownloadedFile(str(set(A__    ) - set(A__    )    )    )
   UpperCamelCase					=  [url for url in expected_checksums if expected_checksums[url] != recorded_checksums[url]]
   UpperCamelCase					=  ' for ' + verification_name if verification_name is not None else ''
   if len(A__    ) > 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  SCREAMING_SNAKE_CASE (  _a		):






    """simple docstring"""






class  SCREAMING_SNAKE_CASE (  _a		):






    """simple docstring"""






class  SCREAMING_SNAKE_CASE (  _a		):






    """simple docstring"""






class  SCREAMING_SNAKE_CASE (  _a		):






    """simple docstring"""












def 				__lowerCamelCase				(   A__    ,						A__    )       ->	Tuple:






   """simple docstring"""
   if expected_splits is None:
      logger.info('Unable to verify splits sizes.'    )
      return
   if len(set(A__    ) - set(A__    )    ) > 0:
      raise ExpectedMoreSplits(str(set(A__    ) - set(A__    )    )    )
   if len(set(A__    ) - set(A__    )    ) > 0:
      raise UnexpectedSplits(str(set(A__    ) - set(A__    )    )    )
   UpperCamelCase					=  [
       {'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(A__    ) > 0:
      raise NonMatchingSplitsSizesError(str(A__    )    )
   logger.info('All the splits matched successfully.'    )







def 				__lowerCamelCase				(   A__    ,						A__ = True    )       ->	dict:






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







def 				__lowerCamelCase				(   A__    )       ->	Optional[int]:






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



'''simple docstring'''




import pytest

import datasets.config
from datasets.utils.info_utils import is_small_dataset







@pytest.mark.parametrize('''dataset_size'''		,				[None, 400 * 2**20, 600 * 2**20]						)
@pytest.mark.parametrize('''input_in_memory_max_size'''		,				['''default''', 0, 100 * 2**20, 900 * 2**20]						)
def 		lowerCAmelCase_				(   snake_case__		,				snake_case__		,				snake_case__						):




    '''simple docstring'''



    if input_in_memory_max_size != "default":
        monkeypatch.setattr(datasets.config		,				'''IN_MEMORY_MAX_SIZE'''		,				snake_case__						)
    A       :   Dict					=						datasets.config.IN_MEMORY_MAX_SIZE
    if input_in_memory_max_size == "default":
        assert in_memory_max_size == 0
    else:
        assert in_memory_max_size == input_in_memory_max_size
    if dataset_size and in_memory_max_size:
        A       :   Dict					=						dataset_size < in_memory_max_size
    else:
        A       :   Tuple					=						False
    A       :   int					=						is_small_dataset(snake_case__						)
    assert result == expected




