input: Write a python function to tokenize a list of words and return their parts of speech using NLTK.
  assert pos_tagging(['horse', 'dog', 'cat']) == ['NN', 'NN', 'NN']
  assert pos_tagging(['run', 'jump', 'swim']) == ['VB', 'VB', 'VB']
  assert pos_tagging(['beautiful', 'quick', 'bright']) == ['JJ', 'JJ', 'JJ']
output: def pos_tagging(words):
      import nltk
      from nltk import pos_tag
      nltk.download('averaged_perceptron_tagger', quiet=True)
      tagged_words = pos_tag(words)
      return [tag for word, tag in tagged_words]