text: #corrects spelling pretty well
  #Courtesy of Peter Norvig http://norvig.com/spell-correct.html
  import re, collections
  
  def words(text): return re.findall('[a-z]+', text.lower()) 
  
  def train(features):
      model = collections.defaultdict(lambda: 1)
      for f in features:
          model[f] += 1
      return model
  
  NWORDS = train(words(file('big.txt').read()))
  
  alphabet = 'abcdefghijklmnopqrstuvwxyz'
  
  def edits1(word):
     splits     = [(word[:i], word[i:]) for i in range(len(word) + 1)]
     deletes    = [a + b[1:] for a, b in splits if b]
     transposes = [a + b[1] + b[0] + b[2:] for a, b in splits if len(b)>1]
     replaces   = [a + c + b[1:] for a, b in splits for c in alphabet if b]
     inserts    = [a + c + b     for a, b in splits for c in alphabet]
     return set(deletes + transposes + replaces + inserts)
  
  def known_edits2(word):
      return set(e2 for e1 in edits1(word) for e2 in edits1(e1) if e2 in NWORDS)
  
  def known(words): return set(w for w in words if w in NWORDS)
  
  def correct(word):
      candidates = known([word]) or known(edits1(word)) or known_edits2(word) or [word]
      return max(candidates, key=NWORDS.get)