input: Write a function to extract verbs from a given sentence using the Natural Language Toolkit (nltk). The function should tokenize the sentence, tag each word with its part of speech, and then return a list of words that are verbs. If no verbs are found, return an empty list.
  
  
  import nltk
  
  def extract_verbs(sentence):
      tokens = nltk.word_tokenize(sentence)
      tags = nltk.pos_tag(tokens)
      verbs = [word for word, pos in tags if pos.startswith('V')]
      return verbs
  
  sentence = "The cat jumped over the moon."
  verbs = extract_verbs(sentence)
  print(verbs)
  
  assert extract_verbs("The cat jumped over the moon.")==['jumped']
  assert extract_verbs("She eats an apple every day.")==['eats', 'apple']
  assert extract_verbs("The sun shines brightly.")==['shines']
  assert extract_verbs("Quickly and quietly, he ran.")==['ran']
  assert extract_verbs("Pure water is essential for life.")==[]
  
output: def extract_verbs(sentence):
      tokens = nltk.word_tokenize(sentence)
      tags = nltk.pos_tag(tokens)
      verbs = [word for word, pos in tags if pos.startswith('V')]
      return verbs