






'''simple docstring'''







import re
import tempfile
import unittest
from pathlib import Path

from datasets.utils.metadata import DatasetMetadata


def 						_UpperCamelCase							(     snake_case__							):
      __A		   =      min(re.search("^ +"							,			snake_case__							).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(snake_case__							)]							)


__A      :       Optional[int]      =	'\\n---\nlanguage:\n- zh\n- en\ntask_ids:\n- sentiment-classification\n---\n# Begin of markdown\n\nSome cool dataset card\n'

__A      :       List[Any]      =	'\\n---\n---\n# Begin of markdown\n\nSome cool dataset card\n'


__A      :       List[str]      =	'\\n# Begin of markdown\n\nSome cool dataset card\n'






class 					a__    (			unittest.TestCase						):
     '''simple docstring'''







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

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

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






     def     _UpperCamelCase   (self    :	int					)  ->       Optional[int]:
           __A		   =      _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(lowercase__					)

           __A		   =      _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(lowercase__					):
                 DatasetMetadata.from_yaml_string(lowercase__					)

           __A		   =      _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(lowercase__					)










'''simple docstring'''







def 						_UpperCamelCase							(     snake_case__							,			snake_case__							):
      if n < 0:
            return 0
      # table[i] represents the number of ways to get to amount i
      __A		   =      [0] * (n + 1)

      # There is exactly 1 way to get to zero(You pick no coins).
      __A		   =      1

      # Pick all coins one by one and update table[] values
      # after the index greater than or equal to the value of the
      # picked coin
      for coin_val in s:
            for j in range(snake_case__							,			n + 1							):
                  table[j] += table[j - coin_val]

      return table[n]


if __name__ == "__main__":
       import doctest

       doctest.testmod()


