input: Write a function isAffirmativeorNegative(sentence) that determines whether a given sentence is an 'affirmative' sentence or a 'negative' sentence by checking for negation words. If the sentence contains any negation words, the function returns "Negative". Otherwise, it returns "Affirmative". If the input sentence is empty, the function should return "Affirmative".
  import re 
  import nltk
  nltk.download('stopwords')
  from nltk.corpus import stopwords 
  
  def isAffirmativeorNegative(sentence):
       negationwords = findNegation(sentence)
      if len(negationwords)==0: 
          return "Affirmative" 
      else: 
          return "Negative"    
  
  def findNegation(sentence):
      negationwords = {'not', 'never', 'no', 'none', 'non', 'neither',
                       'nobody', 'nowhere', 'cannot', 'couldnt', 'shouldnt', 
                       'wouldnt', 'dont', 'didnt', 'hasnt', 'havent', 'isnt', 'arent'} 
      words = nltk.word_tokenize(sentence)
      neg = []
      for word in words:
          if word in negationwords:
              neg.append(word)
      return neg
  
  assert isAffirmativeorNegative("He always comes late but I dont mind.")== "Negative"
  assert isAffirmativeorNegative("I will definitely complete this task.")== "Affirmative"
  assert isAffirmativeorNegative("No one should be late.")== "Negative"
  assert isAffirmativeorNegative("")== "Affirmative"
output: def isAffirmativeorNegative(sentence):
      negationwords = {'not', 'never', 'no', 'none', 'non', 'neither',
                       'nobody', 'nowhere', 'cannot', 'couldnt', 'shouldnt', 
                       'wouldnt', 'dont', 'didnt', 'hasnt', 'havent', 'isnt', 'arent'}
      words = nltk.word_tokenize(sentence)
      for word in words:
          if word in negationwords:
              return "Negative"
      return "Affirmative"