
'''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  snake_case_		(    __SCREAMING_SNAKE_CASE :			List[Any]				,      __SCREAMING_SNAKE_CASE :			List[str]							):



						"""simple docstring"""





						lowercase_     :					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}}'''							)
						lowercase_     :					Optional[Any]													=	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  snake_case_		(    __SCREAMING_SNAKE_CASE :			Optional[Any]				,      __SCREAMING_SNAKE_CASE :			Any							):



						"""simple docstring"""





						lowercase_     :					Tuple													=	str(__SCREAMING_SNAKE_CASE							)
						dataset_info.write_to_directory(__SCREAMING_SNAKE_CASE							)
						lowercase_     :					List[str]													=	DatasetInfo.from_directory(__SCREAMING_SNAKE_CASE							)
						assert dataset_info == reloaded
						assert os.path.exists(os.path.join(__SCREAMING_SNAKE_CASE				,      '''dataset_info.json'''							)							)
def  snake_case_		(    ):



						"""simple docstring"""





						lowercase_     :					Tuple													=	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				,      )
						lowercase_     :					Tuple													=	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)							)
						lowercase_     :					int													=	yaml.safe_dump(__SCREAMING_SNAKE_CASE							)
						lowercase_     :					List[str]													=	yaml.safe_load(__SCREAMING_SNAKE_CASE							)
						assert dataset_info_yaml_dict == reloaded
def  snake_case_		(    ):



						"""simple docstring"""





						lowercase_     :					Any													=	DatasetInfo()
						lowercase_     :					int													=	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  snake_case_		(    __SCREAMING_SNAKE_CASE :			List[str]				,      __SCREAMING_SNAKE_CASE :			Optional[Any]							):



						"""simple docstring"""





						lowercase_     :					int													=	str(__SCREAMING_SNAKE_CASE							)
						dataset_infos_dict.write_to_directory(__SCREAMING_SNAKE_CASE							)
						lowercase_     :					Any													=	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():
												lowercase_     :					Tuple													=	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
												lowercase_     :					int													=	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'''							)							)





'''simple docstring'''







from typing import Optional
from urllib.parse import quote

import huggingface_hub as hfh
from packaging import version
def  snake_case_		(    __SCREAMING_SNAKE_CASE :			str				,				__SCREAMING_SNAKE_CASE :			str				,				__SCREAMING_SNAKE_CASE :			Optional[str] = None							):



						"""simple docstring"""





						if version.parse(hfh.__version__							).release < version.parse('''0.11.0'''							).release:
												# old versions of hfh don't url-encode the file path
												lowercase_     :					int													=	quote(__SCREAMING_SNAKE_CASE							)
						return hfh.hf_hub_url(__SCREAMING_SNAKE_CASE				,				__SCREAMING_SNAKE_CASE				,				repo_type='''dataset'''				,				revision=__SCREAMING_SNAKE_CASE							)



