input: Write a function to read in a tweet and remove all punctuation, special characters and stopwords. If the tweet is empty, return an empty list. The function should return a list of cleaned words, with stopwords removed.
  Import libraries `re`, `string`, and `stopwords from nltk.corpus`.
  
  assert tweet_cleanup("I'm so excited to be going to the #MuseumTour! #BigDay #travel")==['excited','going','museumtour','bigday','travel']
  assert tweet_cleanup("@user This isn't a good time to chat #mute")==['good','time','chat','mute']
  assert tweet_cleanup("I have completed my #Assignment. #done")==['completed','assignment','done']
  assert tweet_cleanup("#SyntaxError")==['syntaxerror']
  assert tweet_cleanup("")==[]
output: import re
  import string
  from nltk.corpus import stopwords
  
  def tweet_cleanup(tweet):
      if not tweet:
          return []
      tweet = re.sub(f'[{re.escape(string.punctuation)}]', '', tweet)
      words = tweet.lower().split()
      stop_words = set(stopwords.words('english'))
      cleaned_words = [word for word in words if word not in stop_words]
      return cleaned_words