input: from typing import List
  
  
  def clean_tweet(tweet: str) -> List[str]:
      """
      Given a tweet (string), remove all punctuation, special characters, and stopwords.
      Return a list of words that are not stopwords.
  
      >>> 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)  # remove punctuation
      tokens = tweet_clean.split()  # split string into individual words
      stop_words = set(stopwords.words("english"))  # get list of stopwords
      filtered_tokens = [w for w in tokens if w not in stop_words]  # remove stopwords
      return filtered_tokens
output:     import re
      import string
      from nltk.corpus import stopwords
  
      tweet_clean = re.sub(r'[^\w\s]', '', tweet)  # remove punctuation
      tokens = tweet_clean.split()  # split string into individual words
      stop_words = set(stopwords.words("english"))  # get list of stopwords
      filtered_tokens = [w for w in tokens if w not in stop_words]  # remove stopwords
      return filtered_tokens