input: 
  from collections import Counter
  
  def extract_top_words(text: str) -> list:
      """ Extract the top 10 most frequent words from a given text.
      >>> extract_top_words("Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.")
      [('dolor', 1), ('Lorem', 1), ('ipsum', 1), ('amet', 1), ('consectetur', 1), ('adipiscing', 1), ('elit,', 1), ('sed', 1), ('do', 1), ('eiusmod', 1)]
      """
      # Split the text into individual words
      words = text.split()
      
      # Create a counter object
      counter = Counter(words)
      
      # Get the top 10 most frequent words
      top_words = counter.most_common(10)
      
      return top_words
  
output:     # Remove punctuation and convert to lowercase
      words = [word.strip(".,!?()[]{}:;\"'").lower() for word in words]
      
      # Filter out empty strings
      words = [word for word in words if word]
      
      # Create a counter object
      counter = Counter(words)
      
      # Get the top 10 most frequent words
      top_words = counter.most_common(10)
      
      return top_words