Spelling Corrector.py

# Refer to: 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

# to get big.txt, please visit: http://www.norvig.com/big.txt
NWORDS = train(words(file('big.txt').read()))

alphabet = 'abcdefghijklmnopqrstuvwxyz'

def edits1(word):
    n = len(word)
    return set([word[0 : i] + word[i + 1:] for i in range(n)] + # deletion
               [word[0 : i] + word[i + 1] + word[i] + word[i + 2:] for i in range(n - 1)] + # transposition
               [word[0 : i] + c + word[i + 1: ] for i in range(n) for c in alphabet] + # alteration
               [word[0 : i] + c + word[i:] for i in range(n + 1) for c in alphabet]) # insertion

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 = lambda w: NWORDS[w])


print "Did you mean: " + correct("Chineae")