input: Write a function to remove all punctuation, special characters, and stopwords from a given tweet and return the cleaned list of tokens. If the tweet is empty, return an empty list.
  assert clean_tweet("I'm so excited to be going to the #MuseumTour! #BigDay #travel")==['excited', 'going', 'MuseumTour', 'BigDay', 'travel']
  assert clean_tweet("Hello, world! This is a test.")==['Hello', 'world', 'This', 'test']
  assert clean_tweet("")==[]
output: def clean_tweet(tweet):
      import string
      from nltk.corpus import stopwords
      stop_words = set(stopwords.words('english'))
      translator = str.maketrans('', '', string.punctuation)
      tokens = tweet.translate(translator).split()
      cleaned_tokens = [word for word in tokens if word.lower() not in stop_words]
      return cleaned_tokens