from __future__ import annotations

from enum import Enum, unique
from typing import TypeVar

# Create a generic variable that can be 'Enum', or any subclass.
UpperCamelCase      			=     TypeVar('T', bound='Enum')


@unique
class _a       (	lowerCAmelCase__ ):

	'''simple docstring'''



	lowerCamelCase_   :      Tuple       =	8_0
	lowerCamelCase_   :      Dict       =	7_0
	lowerCamelCase_   :      int       =	6_0
	lowerCamelCase_   :      int       =	5_0
	lowerCamelCase_   :      Tuple       =	4_0
	lowerCamelCase_   :      Any       =	3_0
	lowerCamelCase_   :      Tuple       =	2_0
	lowerCamelCase_   :      Any       =	1_0


@unique
class _a       (	lowerCAmelCase__ ):

	'''simple docstring'''



	lowerCamelCase_   :      Union[str, Any]       =	2_4
	lowerCamelCase_   :      Any       =	2_1
	lowerCamelCase_   :      Tuple       =	1_8
	lowerCamelCase_   :      List[str]       =	1_5
	lowerCamelCase_   :      Optional[int]       =	1_2
	lowerCamelCase_   :      int       =	9
	lowerCamelCase_   :      Union[str, Any]       =	6
	lowerCamelCase_   :      Any       =	3
	lowerCamelCase_   :      List[str]       =	2
	lowerCamelCase_   :      List[str]       =	1
	lowerCamelCase_   :      Dict       =	-1
	lowerCamelCase_   :      Union[str, Any]       =	-2
	lowerCamelCase_   :      List[Any]       =	-3
	lowerCamelCase_   :      Optional[int]       =	-6
	lowerCamelCase_   :      List[str]       =	-9
	lowerCamelCase_   :      Optional[int]       =	-1_2
	lowerCamelCase_   :      Dict       =	-1_5
	lowerCamelCase_   :      int       =	-1_8
	lowerCamelCase_   :      Tuple       =	-2_1
	lowerCamelCase_   :      List[str]       =	-2_4

	@classmethod
	def 					__UpperCAmelCase(       cls   ):
			return {unit.name: unit.value for unit in cls if unit.value > 0}







	@classmethod
	def 					__UpperCAmelCase(       cls   ):
			return {unit.name: unit.value for unit in cls if unit.value < 0}



def    lowerCamelCase_   (  _lowercase    )							->	str:
		__A							:   int	  =				SIUnit.get_positive() if value > 0 else SIUnit.get_negative()
		for name_prefix, value_prefix in prefixes.items():
				__A							:   Any	  =				value / (10**value_prefix)
				if numerical_part > 1:
						return F"{numerical_part!s} {name_prefix}"
		return str(_lowercase    )



def    lowerCamelCase_   (  _lowercase    )							->	str:
		for prefix in BinaryUnit:
				__A							:   Any	  =				value / (2**prefix.value)
				if numerical_part > 1:
						return F"{numerical_part!s} {prefix.name}"
		return str(_lowercase    )


if __name__ == "__main__":
					import doctest

					doctest.testmod()






import re
import tempfile
import unittest
from pathlib import Path

from datasets.utils.metadata import DatasetMetadata



def    lowerCamelCase_   (  _lowercase    )							->	str:
		__A							:   Optional[int]	  =				min(re.search("^ +" ,     _lowercase    ).end() if t.startswith(" "    ) else 0 for t in string.splitlines()    )
		return "\n".join([line[indent_level:] for line in string.splitlines() if indent_level < len(_lowercase    )]    )


UpperCamelCase      			=     '\\n---\nlanguage:\n- zh\n- en\ntask_ids:\n- sentiment-classification\n---\n# Begin of markdown\n\nSome cool dataset card\n'

UpperCamelCase      			=     '\\n---\n---\n# Begin of markdown\n\nSome cool dataset card\n'


UpperCamelCase      			=     '\\n# Begin of markdown\n\nSome cool dataset card\n'





class _a       (	unittest.TestCase ):

	'''simple docstring'''



	def 					__UpperCAmelCase(       self   ):
			with tempfile.TemporaryDirectory() as tmp_dir:
					__A							:   List[Any]	  =				Path(__UpperCAmelCase   ) / "README.md"
					with open(__UpperCAmelCase							,			"w+"   ) as readme_file:
							readme_file.write(__UpperCAmelCase   )
					__A							:   Tuple	  =				DatasetMetadata.from_readme(__UpperCAmelCase   )
					self.assertDictEqual(__UpperCAmelCase							,			{"language": ["zh", "en"], "task_ids": ["sentiment-classification"]}   )

					with open(__UpperCAmelCase							,			"w+"   ) as readme_file:
							readme_file.write(__UpperCAmelCase   )
					__A							:   Any	  =				DatasetMetadata.from_readme(__UpperCAmelCase   )
					self.assertDictEqual(__UpperCAmelCase							,			{}   )

					with open(__UpperCAmelCase							,			"w+"   ) as readme_file:
							readme_file.write(__UpperCAmelCase   )
					__A							:   Union[str, Any]	  =				DatasetMetadata.from_readme(__UpperCAmelCase   )
					self.assertEqual(__UpperCAmelCase							,			{}   )







	def 					__UpperCAmelCase(       self   ):
			__A							:   List[str]	  =				_dedent(
			    "\\n            annotations_creators:\n            - found\n            language_creators:\n            - found\n            language:\n            - en\n            license:\n            - unknown\n            multilinguality:\n            - monolingual\n            pretty_name: Test Dataset\n            size_categories:\n            - 10K<n<100K\n            source_datasets:\n            - extended|other-yahoo-webscope-l6\n            task_categories:\n            - question-answering\n            task_ids:\n            - open-domain-qa\n            "   )
			assert DatasetMetadata.from_yaml_string(__UpperCAmelCase   )

			__A							:   List[Any]	  =				_dedent(
			    "\\n            annotations_creators:\n            - found\n            language:\n            - en\n            license:\n            - unknown\n            multilinguality:\n            - monolingual\n            pretty_name: Test Dataset\n            size_categories:\n            - 10K<n<100K\n            source_datasets:\n            - extended|other-yahoo-webscope-l6\n            task_categories:\n            - question-answering\n            task_ids:\n            - open-domain-qa\n            task_ids:\n            - open-domain-qa\n            "   )
			with self.assertRaises(__UpperCAmelCase   ):
					DatasetMetadata.from_yaml_string(__UpperCAmelCase   )

			__A							:   Optional[int]	  =				_dedent(
			    "\\n            annotations_creators:\n            - found\n            language_creators:\n            - found\n            language:\n            - en\n            license:\n            - unknown\n            multilinguality:\n            - monolingual\n            pretty_name: Test Dataset\n            size_categories:\n            - 10K<n<100K\n            source_datasets:\n            - extended|other-yahoo-webscope-l6\n            task_categories:\n            - text-classification\n            task_ids:\n            - multi-class-classification\n            paperswithcode_id:\n            - squad\n            configs:\n            - en\n            train-eval-index:\n            - config: en\n              task: text-classification\n              task_id: multi_class_classification\n              splits:\n                train_split: train\n                eval_split: test\n              col_mapping:\n                text: text\n                label: target\n              metrics:\n                - type: accuracy\n                  name: Accuracy\n            extra_gated_prompt: |\n              By clicking on “Access repository” below, you also agree to ImageNet Terms of Access:\n              [RESEARCHER_FULLNAME] (the \"Researcher\") has requested permission to use the ImageNet database (the \"Database\") at Princeton University and Stanford University. In exchange for such permission, Researcher hereby agrees to the following terms and conditions:\n              1. Researcher shall use the Database only for non-commercial research and educational purposes.\n            extra_gated_fields:\n              Company: text\n              Country: text\n              I agree to use this model for non-commerical use ONLY: checkbox\n            "   )
			assert DatasetMetadata.from_yaml_string(__UpperCAmelCase   )





