code: 
  
  
  """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 							_snake_case			(      __snake_case       :			List[str]      ):
  
  
  
  
     """simple docstring"""
  
  
  
  
  
  
  
     _lowerCamelCase  :				Any      =		tmp_path / """text.txt"""
     _lowerCamelCase  :				Optional[Any]      =		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(__snake_case	,   """w"""	,   encoding="""utf-8"""      ) as f:
        f.write(__snake_case      )
     return str(__snake_case      )
  
  @pytest.fixture
  def 							_snake_case			(      __snake_case       :			Optional[int]	,   __snake_case       :			Any      ):
  
  
  
  
     """simple docstring"""
  
  
  
  
  
  
  
     _lowerCamelCase  :				Dict      =		tmp_path / """text_with_image.txt"""
     with open(__snake_case	,   """w"""	,   encoding="""utf-8"""      ) as f:
        f.write(__snake_case      )
     return str(__snake_case      )
  
  @pytest.mark.parametrize("""keep_linebreaks"""	,   [True, False]      )
  def 							_snake_case			(      __snake_case       :			Tuple	,   __snake_case       :			str      ):
  
  
  
  
     """simple docstring"""
  
  
  
  
  
  
  
     with open(__snake_case	,   encoding="""utf-8"""      ) as f:
        _lowerCamelCase  :				Any      =		f.read().splitlines(keepends=__snake_case      )
     _lowerCamelCase  :				List[str]      =		Text(keep_linebreaks=__snake_case	,   encoding="""utf-8"""      )
     _lowerCamelCase  :				List[str]      =		text._generate_tables([[text_file]]      )
     _lowerCamelCase  :				int      =		pa.concat_tables([table for _, table in generator]      ).to_pydict()["""text"""]
     assert generated_content == expected_content
  
  @require_pil
  def 							_snake_case			(      __snake_case       :			Optional[Any]      ):
  
  
  
  
     """simple docstring"""
  
  
  
  
  
  
  
     with open(__snake_case	,   encoding="""utf-8"""      ) as f:
        _lowerCamelCase  :				Any      =		f.read().splitlines()[0]
     _lowerCamelCase  :				str      =		Text(encoding="""utf-8"""	,   features=Features({"""image""": Image()}      )      )
     _lowerCamelCase  :				List[Any]      =		text._generate_tables([[text_file_with_image]]      )
     _lowerCamelCase  :				Union[str, Any]      =		pa.concat_tables([table for _, table in generator]      )
     assert pa_table.schema.field("""image"""      ).type == Image()()
     _lowerCamelCase  :				int      =		pa_table.to_pydict()["""image"""]
     assert generated_content == [{"path": image_file, "bytes": None}]
  
  
  
  
  
  @pytest.mark.parametrize("""sample_by"""	,   ["""line""", """paragraph""", """document"""]      )
  def 							_snake_case			(      __snake_case       :			Tuple	,   __snake_case       :			Dict      ):
  
  
  
  
     """simple docstring"""
  
  
  
  
  
  
  
     with open(__snake_case	,   encoding="""utf-8"""      ) as f:
        _lowerCamelCase  :				Dict      =		f.read()
     if sample_by == "line":
        _lowerCamelCase  :				Optional[Any]      =		expected_content.splitlines()
     elif sample_by == "paragraph":
        _lowerCamelCase  :				int      =		expected_content.split("""\n\n"""      )
     elif sample_by == "document":
        _lowerCamelCase  :				Union[str, Any]      =		[expected_content]
     _lowerCamelCase  :				Any      =		Text(sample_by=__snake_case	,   encoding="""utf-8"""	,   chunksize=100      )
     _lowerCamelCase  :				Any      =		text._generate_tables([[text_file]]      )
     _lowerCamelCase  :				Dict      =		pa.concat_tables([table for _, table in generator]      ).to_pydict()["""text"""]
     assert generated_content == expected_content
  
  
style_context: 
  
  
  """simple docstring"""
  from dataclasses import dataclass
  
  UpperCAmelCase   =	"""0.1"""
  UpperCAmelCase   =	"""Lucia Harcekova"""
  
  
  
  
  @dataclass
  class   lowercase__							:
     __UpperCAmelCase       					=				42
     __UpperCAmelCase       					=				42
     __UpperCAmelCase       					=				42
  
  
  
  
  
     def __repr__(       self)     ->     str:
        return F'({self.offset}, {self.length}, {self.indicator})'
  
  
  
  
  
  
  
  class   lowercase__							:
  
  
  
  
  
     def __init__(       self			,      SCREAMING_SNAKE_CASE = 13			,      SCREAMING_SNAKE_CASE = 6)     ->     None:
        _lowerCamelCase  :				Optional[Any]      =		window_size
        _lowerCamelCase  :				List[str]      =		lookahead_buffer_size
        _lowerCamelCase  :				List[Any]      =		self.window_size - self.lookahead_buffer_size
  
  
  
  
  
     def 		UpperCamelCase_     (       self			,      SCREAMING_SNAKE_CASE)     ->     list[Token]:
        _lowerCamelCase  :				Union[str, Any]      =		[]
        _lowerCamelCase  :				Tuple      =		""""""
  
        # while there are still characters in text to compress
        while text:
           # find the next encoding phrase
           # - triplet with offset, length, indicator (the next encoding character)
           _lowerCamelCase  :				List[Any]      =		self._find_encoding_token(SCREAMING_SNAKE_CASE			,      SCREAMING_SNAKE_CASE)
  
           # update the search buffer:
           # - add new characters from text into it
           # - check if size exceed the max search buffer size, if so, drop the
           #   oldest elements
           search_buffer += text[: token.length + 1]
           if len(SCREAMING_SNAKE_CASE) > self.search_buffer_size:
              _lowerCamelCase  :				int      =		search_buffer[-self.search_buffer_size :]
  
           # update the text
           _lowerCamelCase  :				Tuple      =		text[token.length + 1 :]
  
           # append the token to output
           output.append(SCREAMING_SNAKE_CASE)
  
        return output
  
  
  
  
  
     def 		UpperCamelCase_     (       self			,      SCREAMING_SNAKE_CASE)     ->     str:
        _lowerCamelCase  :				str      =		""""""
  
        for token in tokens:
           for _ in range(token.length):
              output += output[-token.offset]
           output += token.indicator
  
        return output
  
  
  
  
  
     def 		UpperCamelCase_     (       self			,      SCREAMING_SNAKE_CASE			,      SCREAMING_SNAKE_CASE)     ->     Token:
  
        if not text:
           raise ValueError("""We need some text to work with.""")
  
        # Initialise result parameters to default values
        _lowerCamelCase      ,						_lowerCamelCase  :				List[str]      =		0, 0
  
        if not search_buffer:
           return Token(SCREAMING_SNAKE_CASE			,      SCREAMING_SNAKE_CASE			,      text[length])
  
        for i, character in enumerate(SCREAMING_SNAKE_CASE):
           _lowerCamelCase  :				Tuple      =		len(SCREAMING_SNAKE_CASE) - i
           if character == text[0]:
              _lowerCamelCase  :				Any      =		self._match_length_from_index(SCREAMING_SNAKE_CASE			,      SCREAMING_SNAKE_CASE			,      0			,      SCREAMING_SNAKE_CASE)
              # if the found length is bigger than the current or if it's equal,
              # which means it's offset is smaller: update offset and length
              if found_length >= length:
                 _lowerCamelCase      ,						_lowerCamelCase  :				Optional[int]      =		found_offset, found_length
  
        return Token(SCREAMING_SNAKE_CASE			,      SCREAMING_SNAKE_CASE			,      text[length])
  
  
  
  
  
     def 		UpperCamelCase_     (       self			,      SCREAMING_SNAKE_CASE			,      SCREAMING_SNAKE_CASE			,      SCREAMING_SNAKE_CASE			,      SCREAMING_SNAKE_CASE)     ->     int:
        if not text or text[text_index] != window[window_index]:
           return 0
        return 1 + self._match_length_from_index(
            SCREAMING_SNAKE_CASE			,      window + text[text_index]			,      text_index + 1			,      window_index + 1)
  
  
  if __name__ == "__main__":
   from doctest import testmod
  
   testmod()
   # Initialize compressor class
   UpperCAmelCase   =	LZaaCompressor(window_size=13, lookahead_buffer_size=6)
  
   # Example
   UpperCAmelCase   =	"""cabracadabrarrarrad"""
   UpperCAmelCase   =	lzaa_compressor.compress(TEXT)
   print(lzaa_compressor.compress("""ababcbababaa"""))
   UpperCAmelCase   =	lzaa_compressor.decompress(compressed_text)
   assert decompressed_text == TEXT, "The LZ77 algorithm returned the invalid result."
  
  