input: 
  def clean_tweet(tweet: str) -> str:
      """
      Takes a tweet and removes all punctuation, special characters, and stopwords.
      Returns the cleaned tweet as a string.
      >>> clean_tweet("I'm so excited to be going to the #MuseumTour! #BigDay #travel")
      "['excited', 'going', 'MuseumTour', 'BigDay', 'travel']"
      """
      import re
      import string
      from nltk.corpus import stopwords
      
      tweet_clean = re.sub(r'[^\w\s]','',tweet)
      tokens = tweet_clean.split()
      stop_words = set(stopwords.words("english"))
      filtered_tokens = [w for w in tokens if not w in stop_words]
      return filtered_tokens
  
output:     return str(filtered_tokens)