





from __future__ import annotations

from random import randrange



def   __lowercase  ( _SCREAMING_SNAKE_CASE      )					->  list:


      '''simple docstring'''


      if len(_SCREAMING_SNAKE_CASE      ) < 2:
            return collection
      SCREAMING_SNAKE_CASE						=		randrange(len(_SCREAMING_SNAKE_CASE      )      )  # Use random element as pivot
      SCREAMING_SNAKE_CASE						=		collection[pivot_index]
      SCREAMING_SNAKE_CASE						=		[]  # All elements greater than pivot
      SCREAMING_SNAKE_CASE						=		[]  # All elements less than or equal to pivot

      for element in collection[:pivot_index]:
            (greater if element > pivot else lesser).append(_SCREAMING_SNAKE_CASE      )

      for element in collection[pivot_index + 1 :]:
            (greater if element > pivot else lesser).append(_SCREAMING_SNAKE_CASE      )

      return [*quick_sort(_SCREAMING_SNAKE_CASE      ), pivot, *quick_sort(_SCREAMING_SNAKE_CASE      )]


if __name__ == "__main__":
      SCREAMING_SNAKE_CASE_		  =			input("""Enter numbers separated by a comma:\n""").strip()
      SCREAMING_SNAKE_CASE_		  =			[int(item) for item in user_input.split(""",""")]
      print(quick_sort(unsorted))









import os
from string import ascii_letters

SCREAMING_SNAKE_CASE_		  =			ascii_letters + """ \t\n"""



def   __lowercase  ( )					->  dict[str, None]:


      '''simple docstring'''


      SCREAMING_SNAKE_CASE						=		os.path.split(os.path.realpath(_SCREAMING_SNAKE_CASE      )      )
      SCREAMING_SNAKE_CASE						=		{}
      with open(path[0] + """/dictionary.txt"""      ) as dictionary_file:
            for word in dictionary_file.read().split("""\n"""      ):
                  SCREAMING_SNAKE_CASE						=		None
      return english_words


SCREAMING_SNAKE_CASE_		  =			load_dictionary()



def   __lowercase  ( _SCREAMING_SNAKE_CASE      )					->  float:


      '''simple docstring'''


      SCREAMING_SNAKE_CASE						=		message.upper()
      SCREAMING_SNAKE_CASE						=		remove_non_letters(_SCREAMING_SNAKE_CASE      )
      SCREAMING_SNAKE_CASE						=		message.split()
      SCREAMING_SNAKE_CASE						=		len([word for word in possible_words if word in ENGLISH_WORDS]      )
      return float(_SCREAMING_SNAKE_CASE      ) / len(_SCREAMING_SNAKE_CASE      )



def   __lowercase  ( _SCREAMING_SNAKE_CASE      )					->  str:


      '''simple docstring'''


      return "".join(symbol for symbol in message if symbol in LETTERS_AND_SPACE      )



def   __lowercase  ( _SCREAMING_SNAKE_CASE					,		_SCREAMING_SNAKE_CASE = 20					,		_SCREAMING_SNAKE_CASE = 85      )					->  bool:


      '''simple docstring'''


      SCREAMING_SNAKE_CASE						=		get_english_count(_SCREAMING_SNAKE_CASE      ) * 1_00 >= word_percentage
      SCREAMING_SNAKE_CASE						=		len(remove_non_letters(_SCREAMING_SNAKE_CASE      )      )
      SCREAMING_SNAKE_CASE						=		(float(_SCREAMING_SNAKE_CASE      ) / len(_SCREAMING_SNAKE_CASE      )) * 1_00
      SCREAMING_SNAKE_CASE						=		message_letters_percentage >= letter_percentage
      return words_match and letters_match


if __name__ == "__main__":
      import doctest

      doctest.testmod()


