input: def clean_tweet(tweet: str) -> list:
      """Remove all punctuation, special characters and stopwords from a given tweet.
      >>> clean_tweet("I'm so excited to be going to the #MuseumTour! #BigDay #travel")
      ['excited', 'going', 'MuseumTour', 'BigDay', 'travel']
      """
output:     import re
      from nltk.corpus import stopwords
      stop_words = set(stopwords.words('english'))
      
      # Remove punctuation and special characters
      tweet = re.sub(r'[^\w\s]', '', tweet)
      
      # Split the tweet into words
      words = tweet.split()
      
      # Remove stopwords and return the cleaned list of words
      return [word for word in words if word.lower() not in stop_words]