Created
January 27, 2012 03:28
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T9 python
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import re, sys | |
keys = ('abc', 'def', 'ghi', 'jkl', 'mno', 'pqrs', 'tuv', 'wxyz') | |
m = dict((l, str(n)) for n, letters in enumerate(keys, start=2) for l in letters) | |
data, ocurrences = {}, {} | |
wmatch = re.compile('[^a-z]+') | |
def learn(word): | |
num = ''.join(m[c] for c in word) | |
for i in xrange(1, len(word) + 1): | |
inp = num[:i] | |
if inp not in data: | |
data[inp] = set([word]) | |
else: | |
data[inp].add(word) | |
def train(f): | |
for word in wmatch.split(f.read().lower()): | |
if word in ocurrences: | |
ocurrences[word] += 1 | |
else: | |
learn(word) | |
ocurrences[word] = 1 | |
def search(n): | |
if not n in data: | |
sys.exit(0) | |
results = ([], []) | |
for match in data[n]: | |
results[int(len(match) != len(n))].append((match, ocurrences[match])) | |
k = lambda m: m[1] | |
return (sorted(results[0], key=k, reverse=True), | |
sorted(results[1], key=k, reverse=True)) | |
if __name__ == '__main__': | |
with open('alice_in_wonderland.txt', 'r') as f: | |
train(f) | |
results = search(sys.argv[1]) | |
for i, t in ((0, 'Exact'), (1, 'Prefix')): | |
print "%s matches for %s:" % (t, sys.argv[1]) | |
for match, oc in results[i]: | |
print match |
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