



'''simple docstring'''





import re
from pathlib import Path
from unittest import TestCase

import pytest






@pytest.mark.integration
class 	lowerCAmelCase_(    SCREAMING_SNAKE_CASE_					):
  '''simple docstring'''




  def 							UpperCAmelCase_     (   self  ,__UpperCAmelCase				)   ->		List[Any]:

      with open(__UpperCAmelCase  ,encoding="""utf-8"""				) as input_file:
          lowerCAmelCase__			:  List[str]											= re.compile(R"""(?!.*\b(?:encoding|rb|w|wb|w+|wb+|ab|ab+)\b)(?<=\s)(open)\((.*)\)"""				)
          lowerCAmelCase__			:  List[Any]											= input_file.read()
          lowerCAmelCase__			:  int											= regexp.search(__UpperCAmelCase				)

      return match




  def 							UpperCAmelCase_     (   self  ,__UpperCAmelCase				)   ->		int:

      with open(__UpperCAmelCase  ,encoding="""utf-8"""				) as input_file:
          lowerCAmelCase__			:  List[Any]											= re.compile(R"""#[^\r\n]*print\(|\"[^\r\n]*print\(|\"\"\".*?print\(.*?\"\"\"|(print\()"""  ,re.DOTALL				)
          lowerCAmelCase__			:  Tuple											= input_file.read()
          # use `re.finditer` to handle the case where the ignored groups would be matched first by `re.search`
          lowerCAmelCase__			:  Any											= regexp.finditer(__UpperCAmelCase				)

      lowerCAmelCase__			:  Tuple											= [match for match in matches if match is not None and match.group(1				) is not None]
      return matches[0] if matches else None




  def 							UpperCAmelCase_     (   self				)   ->		Union[str, Any]:
      lowerCAmelCase__			:  List[str]											= Path("""./datasets"""				)
      lowerCAmelCase__			:  Tuple											= list(dataset_paths.absolute().glob("""**/*.py"""				)				)

      for dataset in dataset_files:
          if self._no_encoding_on_file_open(str(__UpperCAmelCase				)				):
              raise AssertionError(F"""open(...) must use utf-8 encoding in {dataset}"""				)






  def 							UpperCAmelCase_     (   self				)   ->		Union[str, Any]:
      lowerCAmelCase__			:  List[str]											= Path("""./datasets"""				)
      lowerCAmelCase__			:  str											= list(dataset_paths.absolute().glob("""**/*.py"""				)				)

      for dataset in dataset_files:
          if self._no_print_statements(str(__UpperCAmelCase				)				):
              raise AssertionError(F"""print statement found in {dataset}. Use datasets.logger/logging instead."""				)







'''simple docstring'''





from PIL import Image
def        _SCREAMING_SNAKE_CASE  (	UpperCamelCase      ):



    """simple docstring"""





    lowerCAmelCase__				,       lowerCAmelCase__			:  Dict											= image.size
    lowerCAmelCase__			:  int											= 0
    lowerCAmelCase__			:  int											= image.load()
    for i in range(UpperCamelCase      ):
        for j in range(UpperCamelCase      ):
            lowerCAmelCase__			:  int											= pixels[j, i]
            mean += pixel
    mean //= width * height

    for j in range(UpperCamelCase      ):
        for i in range(UpperCamelCase      ):
            lowerCAmelCase__			:  Dict											= 255 if pixels[i, j] > mean else 0
    return image


if __name__ == "__main__":
 _lowerCAmelCase										=     mean_threshold(Image.open('''path_to_image''').convert('''L'''))
 image.save('''output_image_path''')


