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







@pytest.fixture
def 		__a  (      _SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE  )      ->Dict:
  a__:	List[Any]     				=      tmp_path / 'text_with_image.txt'
  with open(_SCREAMING_SNAKE_CASE						,	'w'						,	encoding='utf-8'  ) as f:
    f.write(_SCREAMING_SNAKE_CASE  )
  return str(_SCREAMING_SNAKE_CASE  )







@pytest.mark.parametrize('keep_linebreaks'						,	[True, False]  )
def 		__a  (      _SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE  )      ->Optional[int]:
  with open(_SCREAMING_SNAKE_CASE						,	encoding='utf-8'  ) as f:
    a__:	int     				=      f.read().splitlines(keepends=_SCREAMING_SNAKE_CASE  )
  a__:	Optional[Any]     				=      Text(keep_linebreaks=_SCREAMING_SNAKE_CASE						,	encoding='utf-8'  )
  a__:	List[Any]     				=      text._generate_tables([[text_file]]  )
  a__:	Optional[int]     				=      pa.concat_tables([table for _, table in generator]  ).to_pydict()['text']
  assert generated_content == expected_content







@require_pil
def 		__a  (      _SCREAMING_SNAKE_CASE  )      ->Dict:
  with open(_SCREAMING_SNAKE_CASE						,	encoding='utf-8'  ) as f:
    a__:	List[str]     				=      f.read().splitlines()[0]
  a__:	int     				=      Text(encoding='utf-8'						,	features=Features({'image': Image()}  )  )
  a__:	Optional[Any]     				=      text._generate_tables([[text_file_with_image]]  )
  a__:	int     				=      pa.concat_tables([table for _, table in generator]  )
  assert pa_table.schema.field('image'  ).type == Image()()
  a__:	Any     				=      pa_table.to_pydict()['image']
  assert generated_content == [{"path": image_file, "bytes": None}]







@pytest.mark.parametrize('sample_by'						,	['line', 'paragraph', 'document']  )
def 		__a  (      _SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE  )      ->List[Any]:
  with open(_SCREAMING_SNAKE_CASE						,	encoding='utf-8'  ) as f:
    a__:	int     				=      f.read()
  if sample_by == "line":
    a__:	List[Any]     				=      expected_content.splitlines()
  elif sample_by == "paragraph":
    a__:	Dict     				=      expected_content.split('\n\n'  )
  elif sample_by == "document":
    a__:	List[Any]     				=      [expected_content]
  a__:	Optional[Any]     				=      Text(sample_by=_SCREAMING_SNAKE_CASE						,	encoding='utf-8'						,	chunksize=100  )
  a__:	List[Any]     				=      text._generate_tables([[text_file]]  )
  a__:	List[str]     				=      pa.concat_tables([table for _, table in generator]  ).to_pydict()['text']
  assert generated_content == expected_content










"""simple docstring"""



from string import ascii_uppercase




def       snake_case__		(   _SCREAMING_SNAKE_CASE       ,	_SCREAMING_SNAKE_CASE       ,	_SCREAMING_SNAKE_CASE = False       ,	_SCREAMING_SNAKE_CASE = ascii_uppercase			)    ->str:
 UpperCAmelCase__ 						=				keyword.upper()
 UpperCAmelCase__ 						=				plaintext.upper()
 UpperCAmelCase__ 						=				set(_SCREAMING_SNAKE_CASE			)

 # create a list of unique characters in the keyword - their order matters
 # it determines how we will map plaintext characters to the ciphertext
 UpperCAmelCase__ 						=				[]
 for char in keyword:
  if char in alphabet_set and char not in unique_chars:
   unique_chars.append(_SCREAMING_SNAKE_CASE			)
    # the number of those unique characters will determine the number of rows
 UpperCAmelCase__ 						=				len(_SCREAMING_SNAKE_CASE			)

 # create a shifted version of the alphabet
 UpperCAmelCase__ 						=				unique_chars + [
     char for char in alphabet if char not in unique_chars
 ]

 # create a modified alphabet by splitting the shifted alphabet into rows
 UpperCAmelCase__ 						=				[
     shifted_alphabet[k : k + num_unique_chars_in_keyword]
     for k in range(0       ,	2_6       ,	_SCREAMING_SNAKE_CASE			)
 ]

 # map the alphabet characters to the modified alphabet characters
 # going 'vertically' through the modified alphabet - consider columns first
 UpperCAmelCase__ 						=				{}
 UpperCAmelCase__ 						=				0
 for column in range(_SCREAMING_SNAKE_CASE			):
  for row in modified_alphabet:
   # if current row (the last one) is too short, break out of loop
   if len(_SCREAMING_SNAKE_CASE			) <= column:
    break

   # map current letter to letter in modified alphabet
   UpperCAmelCase__ 						=				row[column]
   letter_index += 1

 if verbose:
  print(_SCREAMING_SNAKE_CASE			)
 # create the encrypted text by mapping the plaintext to the modified alphabet
 return "".join(mapping[char] if char in mapping else char for char in plaintext			)


if __name__ == "__main__":
 # example use
 print(mixed_keyword('''college''', '''UNIVERSITY'''))



