

'''simple docstring'''




import os

import pytest
import yaml

from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict




@pytest.mark.parametrize(
    '''files'''		,						[
        ['''full:README.md''', '''dataset_infos.json'''],
        ['''empty:README.md''', '''dataset_infos.json'''],
        ['''dataset_infos.json'''],
        ['''full:README.md'''],
    ]		,						)
def 						UpperCamelCase	(			a		,						a			)				->     Any:






     '''simple docstring'''
     __magic_name__						       =    tmp_path_factory.mktemp('''dset_infos_dir'''			)
     if "full:README.md" in files:
          with open(dataset_infos_dir / '''README.md'''		,						'''w'''			) as f:
               f.write('''---\ndataset_info:\n  dataset_size: 42\n---'''			)
     if "empty:README.md" in files:
          with open(dataset_infos_dir / '''README.md'''		,						'''w'''			) as f:
               f.write(''''''			)
    # we want to support dataset_infos.json for backward compatibility
     if "dataset_infos.json" in files:
          with open(dataset_infos_dir / '''dataset_infos.json'''		,						'''w'''			) as f:
               f.write('''{"default": {"dataset_size": 42}}'''			)
     __magic_name__						       =    DatasetInfosDict.from_directory(a			)
     assert dataset_infos
     assert dataset_infos["default"].dataset_size == 42




@pytest.mark.parametrize(
    '''dataset_info'''		,						[
        DatasetInfo(),
        DatasetInfo(
            description='''foo'''		,						features=Features({'''a''': Value('''int32'''			)}			)		,						builder_name='''builder'''		,						config_name='''config'''		,						version='''1.0.0'''		,						splits=[{'''name''': '''train'''}]		,						download_size=42		,						),
    ]		,						)
def 						UpperCamelCase	(			a		,						a			)				->     Optional[Any]:






     '''simple docstring'''
     __magic_name__						       =    str(a			)
     dataset_info.write_to_directory(a			)
     __magic_name__						       =    DatasetInfo.from_directory(a			)
     assert dataset_info == reloaded
     assert os.path.exists(os.path.join(a		,						'''dataset_info.json'''			)			)




def 						UpperCamelCase	(			)				->     Dict:






     '''simple docstring'''
     __magic_name__						       =    DatasetInfo(
         description='''foo'''		,						citation='''bar'''		,						homepage='''https://foo.bar'''		,						license='''CC0'''		,						features=Features({'''a''': Value('''int32'''			)}			)		,						post_processed={}		,						supervised_keys=()		,						task_templates=[]		,						builder_name='''builder'''		,						config_name='''config'''		,						version='''1.0.0'''		,						splits=[{'''name''': '''train''', '''num_examples''': 42}]		,						download_checksums={}		,						download_size=1337		,						post_processing_size=442		,						dataset_size=1234		,						size_in_bytes=1337 + 442 + 1234		,						)
     __magic_name__						       =    dataset_info._to_yaml_dict()
     assert sorted(a			) == sorted(DatasetInfo._INCLUDED_INFO_IN_YAML			)
     for key in DatasetInfo._INCLUDED_INFO_IN_YAML:
          assert key in dataset_info_yaml_dict
          assert isinstance(dataset_info_yaml_dict[key]		,						(list, dict, int, str)			)
     __magic_name__						       =    yaml.safe_dump(a			)
     __magic_name__						       =    yaml.safe_load(a			)
     assert dataset_info_yaml_dict == reloaded




def 						UpperCamelCase	(			)				->     Dict:






     '''simple docstring'''
     __magic_name__						       =    DatasetInfo()
     __magic_name__						       =    dataset_info._to_yaml_dict()
     assert dataset_info_yaml_dict == {}




@pytest.mark.parametrize(
    '''dataset_infos_dict'''		,						[
        DatasetInfosDict(),
        DatasetInfosDict({'''default''': DatasetInfo()}			),
        DatasetInfosDict({'''my_config_name''': DatasetInfo()}			),
        DatasetInfosDict(
            {
                '''default''': DatasetInfo(
                    description='''foo'''		,						features=Features({'''a''': Value('''int32'''			)}			)		,						builder_name='''builder'''		,						config_name='''config'''		,						version='''1.0.0'''		,						splits=[{'''name''': '''train'''}]		,						download_size=42		,						)
            }			),
        DatasetInfosDict(
            {
                '''v1''': DatasetInfo(dataset_size=42			),
                '''v2''': DatasetInfo(dataset_size=1337			),
            }			),
    ]		,						)
def 						UpperCamelCase	(			a		,						a			)				->     Union[str, Any]:






     '''simple docstring'''
     __magic_name__						       =    str(a			)
     dataset_infos_dict.write_to_directory(a			)
     __magic_name__						       =    DatasetInfosDict.from_directory(a			)

     # the config_name of the dataset_infos_dict take over the attribute
     for config_name, dataset_info in dataset_infos_dict.items():
          __magic_name__						       =    config_name
          # the yaml representation doesn't include fields like description or citation
          # so we just test that we can recover what we can from the yaml
          __magic_name__						       =    DatasetInfo._from_yaml_dict(dataset_info._to_yaml_dict()			)
     assert dataset_infos_dict == reloaded

     if dataset_infos_dict:
          assert os.path.exists(os.path.join(a		,						'''README.md'''			)			)









'''simple docstring'''




import functools




def 						UpperCamelCase	(			a		,						a			)				->     int:






     '''simple docstring'''
     __magic_name__						       =    len(a			)
     __magic_name__						       =    len(a			)

     @functools.cache
     def min_distance(a		,						a			) -> int:
          # if first word index is overflow - delete all from the second word
          if indexa >= len_worda:
               return len_worda - indexa
          # if second word index is overflow - delete all from the first word
          if indexa >= len_worda:
               return len_worda - indexa
          __magic_name__						       =    int(worda[indexa] != worda[indexa]			)  # current letters not identical
          return min(
              1 + min_distance(indexa + 1		,						a			)		,						1 + min_distance(a		,						indexa + 1			)		,						diff + min_distance(indexa + 1		,						indexa + 1			)		,						)

     return min_distance(0		,						0			)


if __name__ == "__main__":
      import doctest

      doctest.testmod()






