



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__						(							_SCREAMING_SNAKE_CASE       :			str				,     _SCREAMING_SNAKE_CASE       :			int    ):
				"""simple docstring"""







				__a       =		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       =		DatasetInfosDict.from_directory(_SCREAMING_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__						(							_SCREAMING_SNAKE_CASE       :			Optional[Any]				,     _SCREAMING_SNAKE_CASE       :			List[str]    ):
				"""simple docstring"""







				__a       =		str(_SCREAMING_SNAKE_CASE    )
				dataset_info.write_to_directory(_SCREAMING_SNAKE_CASE    )
				__a       =		DatasetInfo.from_directory(_SCREAMING_SNAKE_CASE    )
				assert dataset_info == reloaded
				assert os.path.exists(os.path.join(_SCREAMING_SNAKE_CASE				,     """dataset_info.json"""    )    )

def   lowerCAmelCase__						(							):
				"""simple docstring"""







				__a       =		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       =		dataset_info._to_yaml_dict()
				assert sorted(_SCREAMING_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       =		yaml.safe_dump(_SCREAMING_SNAKE_CASE    )
				__a       =		yaml.safe_load(_SCREAMING_SNAKE_CASE    )
				assert dataset_info_yaml_dict == reloaded

def   lowerCAmelCase__						(							):
				"""simple docstring"""







				__a       =		DatasetInfo()
				__a       =		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__						(							_SCREAMING_SNAKE_CASE       :			str				,     _SCREAMING_SNAKE_CASE       :			int    ):
				"""simple docstring"""







				__a       =		str(_SCREAMING_SNAKE_CASE    )
				dataset_infos_dict.write_to_directory(_SCREAMING_SNAKE_CASE    )
				__a       =		DatasetInfosDict.from_directory(_SCREAMING_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       =		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       =		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(_SCREAMING_SNAKE_CASE				,     """README.md"""    )    )





def   lowerCAmelCase__						(							_SCREAMING_SNAKE_CASE       :			list				,     _SCREAMING_SNAKE_CASE       :			list				,     _SCREAMING_SNAKE_CASE       :			int				,     _SCREAMING_SNAKE_CASE       :			int				,     _SCREAMING_SNAKE_CASE       :			int    ):
				"""simple docstring"""







				if index == number_of_items:
								return 0
				__a       =		0
				__a       =		0
				__a       =		knapsack(_SCREAMING_SNAKE_CASE				,     _SCREAMING_SNAKE_CASE				,     _SCREAMING_SNAKE_CASE				,     _SCREAMING_SNAKE_CASE				,     index + 1    )
				if weights[index] <= max_weight:
								__a       =		values[index] + knapsack(
								    _SCREAMING_SNAKE_CASE				,     _SCREAMING_SNAKE_CASE				,     _SCREAMING_SNAKE_CASE				,     max_weight - weights[index]				,     index + 1    )
				return max(_SCREAMING_SNAKE_CASE				,     _SCREAMING_SNAKE_CASE    )


if __name__ == "__main__":
						import doctest

						doctest.testmod()
