input: def find_matches(query, choices, threshold):
      """This function performs a fuzzy search to find strings in a list that are similar
      to a given query string, based on the Levenshtein distance. The function takes a query
      string, a list of choices, and a threshold value. It converts the query and all choices
      to lower case and then calculates the Levenshtein distance between the query and each
      choice. If the distance is less than or equal to the threshold, the choice is considered
      a match and is added to the list of matches. The function then returns the list of matches.
      
      >>> find_matches('apple', ['apples', 'applet', 'banana', 'peach'], 2)
      ['apples', 'applet']
      >>> find_matches('cat', ['dog', 'car', 'cart', 'cut'], 1)
      ['car', 'cut']
      """
output:     from Levenshtein import distance
  
      query = query.lower()
      matches = []
  
      for choice in choices:
          if distance(query, choice.lower()) <= threshold:
              matches.append(choice)
  
      return matches