





'''simple docstring'''

import textwrap

import pyarrow as pa
import pytest

from datasets import Features, Image
from datasets.packaged_modules.text.text import Text

from ..utils import require_pil







@pytest.fixture
def       a__       (       lowercase      :  str   )	->	Any:





     """simple docstring"""

     _UpperCamelCase       					= tmp_path / '''text.txt'''
     _UpperCamelCase       					= textwrap.dedent(
         '''\
        Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
        Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.
        Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur.
        Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

        Second paragraph:
        Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
        Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.
        Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur.
        Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.
        '''   )
     with open(lowercase,      '''w''',      encoding='''utf-8'''   ) as f:
          f.write(lowercase   )
     return str(lowercase   )







@pytest.fixture
def       a__       (       lowercase      :  Any,      lowercase      :  Union[str, Any]   )	->	Any:





     """simple docstring"""

     _UpperCamelCase       					= tmp_path / '''text_with_image.txt'''
     with open(lowercase,      '''w''',      encoding='''utf-8'''   ) as f:
          f.write(lowercase   )
     return str(lowercase   )







@pytest.mark.parametrize('''keep_linebreaks''',      [True, False]   )
def       a__       (       lowercase      :  List[str],      lowercase      :  List[str]   )	->	Dict:





     """simple docstring"""

     with open(lowercase,      encoding='''utf-8'''   ) as f:
          _UpperCamelCase       					= f.read().splitlines(keepends=lowercase   )
     _UpperCamelCase       					= Text(keep_linebreaks=lowercase,      encoding='''utf-8'''   )
     _UpperCamelCase       					= text._generate_tables([[text_file]]   )
     _UpperCamelCase       					= pa.concat_tables([table for _, table in generator]   ).to_pydict()['''text''']
     assert generated_content == expected_content







@require_pil
def       a__       (       lowercase      :  str   )	->	Any:





     """simple docstring"""

     with open(lowercase,      encoding='''utf-8'''   ) as f:
          _UpperCamelCase       					= f.read().splitlines()[0]
     _UpperCamelCase       					= Text(encoding='''utf-8''',      features=Features({'''image''': Image()}   )   )
     _UpperCamelCase       					= text._generate_tables([[text_file_with_image]]   )
     _UpperCamelCase       					= pa.concat_tables([table for _, table in generator]   )
     assert pa_table.schema.field('''image'''   ).type == Image()()
     _UpperCamelCase       					= pa_table.to_pydict()['''image''']
     assert generated_content == [{"path": image_file, "bytes": None}]







@pytest.mark.parametrize('''sample_by''',      ['''line''', '''paragraph''', '''document''']   )
def       a__       (       lowercase      :  Union[str, Any],      lowercase      :  List[str]   )	->	int:





     """simple docstring"""

     with open(lowercase,      encoding='''utf-8'''   ) as f:
          _UpperCamelCase       					= f.read()
     if sample_by == "line":
          _UpperCamelCase       					= expected_content.splitlines()
     elif sample_by == "paragraph":
          _UpperCamelCase       					= expected_content.split('''\n\n'''   )
     elif sample_by == "document":
          _UpperCamelCase       					= [expected_content]
     _UpperCamelCase       					= Text(sample_by=lowercase,      encoding='''utf-8''',      chunksize=100   )
     _UpperCamelCase       					= text._generate_tables([[text_file]]   )
     _UpperCamelCase       					= pa.concat_tables([table for _, table in generator]   ).to_pydict()['''text''']
     assert generated_content == expected_content










'''simple docstring'''

import re
import tempfile
import unittest
from pathlib import Path

from datasets.utils.metadata import DatasetMetadata







def       a__       (       lowercase      :  str   )	->	str:





     """simple docstring"""

     _UpperCamelCase       					= 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   )]   )


lowercase__		:    List[str] =       '\\n---\nlanguage:\n- zh\n- en\ntask_ids:\n- sentiment-classification\n---\n# Begin of markdown\n\nSome cool dataset card\n'

lowercase__		:    str =       '\\n---\n---\n# Begin of markdown\n\nSome cool dataset card\n'


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




class        __lowerCAmelCase  (					unittest.TestCase				):






       """simple docstring"""





       def snake_case__		(							self     :	Union[str, Any]  )					->  str:

            '''simple docstring'''




            with tempfile.TemporaryDirectory() as tmp_dir:
                 _UpperCamelCase       					= Path(lowerCAmelCase__  ) / '''README.md'''
                 with open(lowerCAmelCase__ ,				'''w+'''  ) as readme_file:
                      readme_file.write(lowerCAmelCase__  )
                 _UpperCamelCase       					= DatasetMetadata.from_readme(lowerCAmelCase__  )
                 self.assertDictEqual(lowerCAmelCase__ ,				{'''language''': ['''zh''', '''en'''], '''task_ids''': ['''sentiment-classification''']}  )

                 with open(lowerCAmelCase__ ,				'''w+'''  ) as readme_file:
                      readme_file.write(lowerCAmelCase__  )
                 _UpperCamelCase       					= DatasetMetadata.from_readme(lowerCAmelCase__  )
                 self.assertDictEqual(lowerCAmelCase__ ,				{}  )

                 with open(lowerCAmelCase__ ,				'''w+'''  ) as readme_file:
                      readme_file.write(lowerCAmelCase__  )
                 _UpperCamelCase       					= DatasetMetadata.from_readme(lowerCAmelCase__  )
                 self.assertEqual(lowerCAmelCase__ ,				{}  )







       def snake_case__		(							self     :	Dict  )					->  Any:

            '''simple docstring'''




            _UpperCamelCase       					= _dedent(
                '''\
            annotations_creators:
            - found
            language_creators:
            - found
            language:
            - en
            license:
            - unknown
            multilinguality:
            - monolingual
            pretty_name: Test Dataset
            size_categories:
            - 10K<n<100K
            source_datasets:
            - extended|other-yahoo-webscope-l6
            task_categories:
            - question-answering
            task_ids:
            - open-domain-qa
            '''  )
            assert DatasetMetadata.from_yaml_string(lowerCAmelCase__  )

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

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



