

"""simple docstring"""






def 	lowercase      (   __UpperCamelCase						) ->      int:
 if not isinstance(__UpperCamelCase      ,   __UpperCamelCase						):
  raise ValueError('''Input must be an integer'''						)
 if input_num <= 0:
  raise ValueError('''Input must be positive'''						)
 return sum(
     divisor for divisor in range(1      ,   input_num // 2 + 1						) if input_num % divisor == 0						)


if __name__ == "__main__":
  import doctest

  doctest.testmod()




"""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 	lowercase      (   __UpperCamelCase      ,   __UpperCamelCase						) ->      List[str]:
 __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(__UpperCamelCase						)
 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 	lowercase      (   __UpperCamelCase      ,   __UpperCamelCase						) ->      Tuple:
 __magic_name__     =      str(__UpperCamelCase						)
 dataset_info.write_to_directory(__UpperCamelCase						)
 __magic_name__     =      DatasetInfo.from_directory(__UpperCamelCase						)
 assert dataset_info == reloaded
 assert os.path.exists(os.path.join(__UpperCamelCase      ,   '''dataset_info.json'''						)						)





def 	lowercase      (   ) ->      Any:
 __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(__UpperCamelCase						) == 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(__UpperCamelCase						)
 __magic_name__     =      yaml.safe_load(__UpperCamelCase						)
 assert dataset_info_yaml_dict == reloaded





def 	lowercase      (   ) ->      str:
 __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 	lowercase      (   __UpperCamelCase      ,   __UpperCamelCase						) ->      str:
 __magic_name__     =      str(__UpperCamelCase						)
 dataset_infos_dict.write_to_directory(__UpperCamelCase						)
 __magic_name__     =      DatasetInfosDict.from_directory(__UpperCamelCase						)

 # 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(__UpperCamelCase      ,   '''README.md'''						)						)

