input: def find_matches(query, choices, threshold):
      """Given a query string, a list of choices and a threshold, return a list of choices that are similar to the query. 
      The similarity is determined by 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.
      Examples:
      >>> find_matches('cat', ['bat', 'hat', 'car'], 1)
      ['bat', 'hat']
      >>> find_matches('python', ['javascript', 'java', 'ruby'], 2)
      []
      """
output:     from Levenshtein import distance
      matches = []
      for choice in choices:
          if distance(query, choice) <= threshold:
              matches.append(choice)
      return matches