






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(			lowerCAmelCase__				:		str    ,    lowerCAmelCase__				:		int      ):





				'''simple docstring'''







				SCREAMING_SNAKE_CASE_   :	List[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}}'      )
				SCREAMING_SNAKE_CASE_   :	Optional[Any]													=   DatasetInfosDict.from_directory(lowerCAmelCase__      )
				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(			lowerCAmelCase__				:		Tuple    ,    lowerCAmelCase__				:		DatasetInfo      ):





				'''simple docstring'''







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



def 					_lowerCamelCase(			):





				'''simple docstring'''







				SCREAMING_SNAKE_CASE_   :	Dict													=   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    ,    )
				SCREAMING_SNAKE_CASE_   :	Optional[Any]													=   dataset_info._to_yaml_dict()
				assert sorted(lowerCAmelCase__      ) == 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)      )
				SCREAMING_SNAKE_CASE_   :	int													=   yaml.safe_dump(lowerCAmelCase__      )
				SCREAMING_SNAKE_CASE_   :	Optional[Any]													=   yaml.safe_load(lowerCAmelCase__      )
				assert dataset_info_yaml_dict == reloaded



def 					_lowerCamelCase(			):





				'''simple docstring'''







				SCREAMING_SNAKE_CASE_   :	Any													=   DatasetInfo()
				SCREAMING_SNAKE_CASE_   :	str													=   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(			lowerCAmelCase__				:		List[str]    ,    lowerCAmelCase__				:		DatasetInfosDict      ):





				'''simple docstring'''







				SCREAMING_SNAKE_CASE_   :	List[str]													=   str(lowerCAmelCase__      )
				dataset_infos_dict.write_to_directory(lowerCAmelCase__      )
				SCREAMING_SNAKE_CASE_   :	Optional[int]													=   DatasetInfosDict.from_directory(lowerCAmelCase__      )

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










import math



def 					_lowerCamelCase(			lowerCAmelCase__				:		float    ,    lowerCAmelCase__				:		float      ):





				'''simple docstring'''







				return math.pow(lowerCAmelCase__    ,    2      ) - a



def 					_lowerCamelCase(			lowerCAmelCase__				:		float      ):





				'''simple docstring'''







				return 2 * x



def 					_lowerCamelCase(			lowerCAmelCase__				:		float      ):





				'''simple docstring'''







				SCREAMING_SNAKE_CASE_   :	Optional[Any]													=   2.0

				while start <= a:
								SCREAMING_SNAKE_CASE_   :	str													=   math.pow(lowerCAmelCase__    ,    2      )

				return start



def 					_lowerCamelCase(			lowerCAmelCase__				:		float    ,    lowerCAmelCase__				:		int = 9999    ,    lowerCAmelCase__				:		float = 0.00_000_000_000_001      ):





				'''simple docstring'''







				if a < 0:
								raise ValueError('math domain error'      )

				SCREAMING_SNAKE_CASE_   :	Optional[int]													=   get_initial_point(lowerCAmelCase__      )

				for _ in range(lowerCAmelCase__      ):
								SCREAMING_SNAKE_CASE_   :	Tuple													=   value
								SCREAMING_SNAKE_CASE_   :	Union[str, Any]													=   value - fx(lowerCAmelCase__    ,    lowerCAmelCase__      ) / fx_derivative(lowerCAmelCase__      )
								if abs(prev_value - value      ) < tolerance:
												return value

				return value


if __name__ == "__main__":
				from doctest import testmod

				testmod()