Created
July 28, 2014 21:58
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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) | |
from yhat import Yhat, YhatModel, preprocess | |
class SpellCorrector(YhatModel): | |
@preprocess(in_type=dict, out_type=dict) | |
def execute(self, data): | |
return {"word":data["word"], "corrected": correct(data["word"])} | |
yh = Yhat("USERNAME", "APIKEY", "http://cloud.yhathq.com/") | |
yh.deploy("SpellCorrector", SpellCorrector, globals()) |
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