def _suggestions(self, text, maxdist, prefix):
from whoosh.automata.lev import levenshtein_automaton
from whoosh.automata.fsa import find_all_matches
seen = set()
for i in range(1, maxdist + 1):
dfa = levenshtein_automaton(text, maxdist, prefix).to_dfa()
sk = self.Skipper(self.wordlist)
for sug in find_all_matches(dfa, sk):
if sug not in seen:
seen.add(sug)
yield (0 - maxdist), sug
def _suggestions(self, text, maxdist, prefix):
from whoosh.automata.lev import levenshtein_automaton
from whoosh.automata.fsa import find_all_matches
seen = set()
for i in xrange(1, maxdist + 1):
dfa = levenshtein_automaton(text, maxdist, prefix).to_dfa()
sk = self.Skipper(self.wordlist)
for sug in find_all_matches(dfa, sk):
if sug not in seen:
seen.add(sug)
yield (0 - maxdist), sug
def find_auto(target, k):
dfa = lev.levenshtein_automaton(target, k, prefix=prefixlen).to_dfa()
sk = Skipper(words)
return fsa.find_all_matches(dfa, sk)
def find_auto(target, k):
dfa = lev.levenshtein_automaton(target, k, prefix=prefixlen).to_dfa()
sk = Skipper(words)
return fsa.find_all_matches(dfa, sk)