
'''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 		lowerCAmelCase_				(   snake_case__		,				snake_case__						):




    '''simple docstring'''



    A       :   Union[str, Any]					=						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}}'''						)
    A       :   Optional[int]					=						DatasetInfosDict.from_directory(snake_case__						)
    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 		lowerCAmelCase_				(   snake_case__		,				snake_case__						):




    '''simple docstring'''



    A       :   Optional[Any]					=						str(snake_case__						)
    dataset_info.write_to_directory(snake_case__						)
    A       :   Optional[Any]					=						DatasetInfo.from_directory(snake_case__						)
    assert dataset_info == reloaded
    assert os.path.exists(os.path.join(snake_case__		,				'''dataset_info.json'''						)						)







def 		lowerCAmelCase_				(   ):




    '''simple docstring'''



    A       :   str					=						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		,				)
    A       :   str					=						dataset_info._to_yaml_dict()
    assert sorted(snake_case__						) == 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)						)
    A       :   Optional[Any]					=						yaml.safe_dump(snake_case__						)
    A       :   Optional[int]					=						yaml.safe_load(snake_case__						)
    assert dataset_info_yaml_dict == reloaded







def 		lowerCAmelCase_				(   ):




    '''simple docstring'''



    A       :   str					=						DatasetInfo()
    A       :   Tuple					=						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 		lowerCAmelCase_				(   snake_case__		,				snake_case__						):




    '''simple docstring'''



    A       :   Tuple					=						str(snake_case__						)
    dataset_infos_dict.write_to_directory(snake_case__						)
    A       :   Tuple					=						DatasetInfosDict.from_directory(snake_case__						)

    # the config_name of the dataset_infos_dict take over the attribute
    for config_name, dataset_info in dataset_infos_dict.items():
        A       :   Dict					=						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
        A       :   List[str]					=						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(snake_case__		,				'''README.md'''						)						)






'''simple docstring'''




import os







def 		lowerCAmelCase_				(   ):




    '''simple docstring'''



    A       :   List[Any]					=						os.path.join(os.path.dirname(snake_case__						)		,				'''num.txt'''						)
    with open(snake_case__						) as file_hand:
        return str(sum(int(snake_case__						) for line in file_hand						)						)[:10]


if __name__ == "__main__":
      print(solution())




