

import os
from collections import namedtuple

import pytest

from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict


lowercase_									=   namedtuple(
    '_TestCommandArgs',
    [
        'dataset',
        'name',
        'cache_dir',
        'data_dir',
        'all_configs',
        'save_infos',
        'ignore_verifications',
        'force_redownload',
        'clear_cache',
    ],
    defaults=[None, None, None, False, False, False, False, False],
)
def      a      (			A__	:   List[str]      ,   A__	:   int     )    ->      List[Any]:





      """simple docstring"""



      return (abs(source - target     ) / target) < 0.01







@pytest.mark.integration
def      a      (			A__	:   List[Any]     )    ->      int:





      """simple docstring"""



      _lowercase	       =_TestCommandArgs(dataset=A__      ,   all_configs=A__      ,   save_infos=A__     )
      _lowercase	       =TestCommand(*A__     )
      test_command.run()
      _lowercase	       =os.path.join(A__      ,   'README.md'     )
      assert os.path.exists(A__     )
      _lowercase	       =DatasetInfosDict.from_directory(A__     )
      _lowercase	       =DatasetInfosDict(
          {
              'default': DatasetInfo(
                  features=Features(
                      {
                          'tokens': Sequence(Value('string'     )     ),
                          'ner_tags': Sequence(
                              ClassLabel(names=['O', 'B-PER', 'I-PER', 'B-ORG', 'I-ORG', 'B-LOC', 'I-LOC']     )     ),
                          'langs': Sequence(Value('string'     )     ),
                          'spans': Sequence(Value('string'     )     ),
                      }     )      ,   splits=[
                      {
                          'name': 'train',
                          'num_bytes': 2351563,
                          'num_examples': 10000,
                      },
                      {
                          'name': 'validation',
                          'num_bytes': 238418,
                          'num_examples': 1000,
                      },
                  ]      ,   download_size=3940680      ,   dataset_size=2589981      ,   )
          }     )
      assert dataset_infos.keys() == expected_dataset_infos.keys()
      for key in DatasetInfo._INCLUDED_INFO_IN_YAML:
            _lowercase       ,       _lowercase	       =getattr(dataset_infos['default']      ,   A__     ), getattr(expected_dataset_infos['default']      ,   A__     )
            if key == "num_bytes":
                  assert is_apercent_close(A__      ,   A__     )
            elif key == "splits":
                  assert list(A__     ) == list(A__     )
                  for split in result:
                        assert result[split].name == expected[split].name
                        assert result[split].num_examples == expected[split].num_examples
                        assert is_apercent_close(result[split].num_bytes      ,   expected[split].num_bytes     )
            else:
                  result == expected





import os
def      a      (			)    ->      Any:





      """simple docstring"""



      with open(os.path.dirname(A__     ) + '/p022_names.txt'     ) as file:
            _lowercase	       =str(file.readlines()[0]     )
            _lowercase	       =names.replace('"'      ,   ''     ).split(','     )

      names.sort()

      _lowercase	       =0
      _lowercase	       =0

      for i, name in enumerate(A__     ):
            for letter in name:
                  name_score += ord(A__     ) - 64

            total_score += (i + 1) * name_score
            _lowercase	       =0
      return total_score


if __name__ == "__main__":
  print(solution())


