The code has been updated stylistically, and I'm not sure what else has changed. Here's the old (Python 2.5) version from http://web.archive.org/web/20160110135619/http://norvig.com/...:

    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)

Here's the history, sorry there is no easy way to see diffs.

https://web.archive.org/web/*/http://norvig.com/spell-correc...

I read this in July. I am sure that the Future work section has been better explained. The main code is the same.