




def    lowerCamelCase_   (  _lowercase    )							->	bool:





		if not isinstance(SCREAMING_SNAKE_CASE_ ,     SCREAMING_SNAKE_CASE_    ):
				__A							:   List[str]	  =				F"Input value of [number={number}] must be an integer"
				raise TypeError(SCREAMING_SNAKE_CASE_    )
		if number < 0 or number % 2 == 1:
				return False
		__A							:   Tuple	  =				int(number**0.5    )
		return number == number_sqrt * (number_sqrt + 1)


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   )





