def Query(self, handles, status, abort):
result = []
for handle in handles:
status.Advance()
if abort.Aborting():
return result
title = handle.Format("[%title%]")
artist = handle.Format("[%artist%]")
try:
l = get_lyric_list(title, artist)
m = 0xffffffffffffffff
best = None
for url, ti, ar in l:
d = LevenshteinDistance(artist, ar) + LevenshteinDistance(
title, ti)
if m > d:
m = d
best = url
if best == None:
result.append('')
else:
lyric = get_lyric(best)
result.append(lyric)
continue
except Exception, e:
traceback.print_exc(file=sys.stdout)
result.append('')
continue
def Query(self, handles, status, abort):
result = []
for handle in handles:
status.Advance()
if abort.Aborting():
return result
try:
artist = handle.Format("[%artist%]")
title = handle.Format("[%title%]")
s = urllib.urlopen(
"http://ttlrcct2.qianqian.com/dll/lyricsvr.dll?sh?Artist=%s&Title=%s&Flags=0"
% (self.ToQianQianHexString(artist),
self.ToQianQianHexString(title))).read() ##这里是utf-8编码
doc = minidom.parseString(s)
m = 0xFFFFFFFFFFFFFFFF
best = None
for e in doc.getElementsByTagName("lrc"):
# i = LevenshteinDistance(artist, e.getAttribute("artist")) + LevenshteinDistance(title, e.getAttribute("title"))#原来对比的是不同编码的文本
i = LevenshteinDistance(
artist,
e.getAttribute("artist").encode(
"utf-8")) + LevenshteinDistance(
title,
e.getAttribute("title").encode("utf-8"))
if m > i:
m = i
best = e.getAttribute("id"), e.getAttribute(
"artist"), e.getAttribute("title")
if best == None:
result.append('')
continue
Id, artist, title = best
code = self.CreateQianQianCode(Id, artist, title)
txheaders = {
'User-agent':
'Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1)'
}
req = urllib2.Request(
"http://ttlrcct2.qianqian.com/dll/lyricsvr.dll?dl?Id=%s&Code=%d"
% (Id, code), None, txheaders)
lyric = urllib2.urlopen(req).read()
if lyric.find("Search ID or Code error!") >= 0:
result.append('')
continue
else:
result.append(lyric)
except Exception, e:
traceback.print_exc(file=sys.stdout)
result.append('')
continue
def sort_by_weighted_edit_dist(self):
"""
Sort by weighted edit distance from scTIM
again from John
"""
self.clear_weight()
leve = LeveDist(5, 5, 3)
for seq in self.__sequence:
seq.weight = leve.computeDistance(seq.seq, self.__scTIM.seq)
self.__sequence.sort(key=lambda seq:seq.weight, reverse = True)
def sort_by_edit_dist(self):
"""
Sort by edit distance from scTIM
Original from John Wenskovitch in Java
"""
self.clear_weight()
leve = LeveDist(1, 1, 1)
for seq in self.__sequence:
seq.weight = leve.computeDistance(seq.seq, self.__scTIM.seq)
self.__sequence.sort(key=lambda seq:seq.weight, reverse = True)
def sort_by_edit_dist(self):
"""
Sort by edit distance from scTIM
Original from John Wenskovitch in Java
"""
self.clear_weight()
leve = LeveDist(1, 1, 1)
for seq in self.__sequence:
seq.weight = leve.computeDistance(seq.seq, self.__scTIM.seq)
self.__sequence.sort(key=lambda seq:seq.weight, reverse = True)
class SpellChecker:
sim_min = 0.75 # Minimum similarity, inclusive
def __init__(self):
self.keyword = ContextIdentifier().getKeyword()
self.distance_counter = LevenshteinDistance()
def getWordSuggestion(self, text):
word_suggestion = set()
suggested_word_candidate_set = set(self.keyword)
word_set = {word.lower() for word in text.split(" ") if word != ""}
for word in word_set:
current_suggestion = suggested_word_candidate_set - word_suggestion
for suggested_word_candidate in current_suggestion:
distance = self.distance_counter.getDistance(
word, suggested_word_candidate)
if distance == 0:
continue
value = 1 - distance / max(len(word),
len(suggested_word_candidate))
if value > self.sim_min:
word_suggestion.add(suggested_word_candidate)
suggested_word_candidate_set.remove(
suggested_word_candidate)
return list(word_suggestion)
def sort_by_weighted_edit_dist(self):
"""
Sort by weighted edit distance from scTIM
again from John
"""
self.clear_weight()
leve = LeveDist(5, 5, 3)
for seq in self.__sequence:
seq.weight = leve.computeDistance(seq.seq, self.__scTIM.seq)
# set the dTIM_core's weight to a large number, so that it will alway the top one
self.__sequence[0].weight += 9999999999
self.__sequence[-1].weight = self.__sequence[0].weight - 1
# myp = ""
# for seq in self.__sequence:
# myp += str(seq._sequence__name) + " "
# print myp
self.__sequence.sort(key=lambda seq: seq.weight, reverse = True)
def __init__(self):
self.keyword = ContextIdentifier().getKeyword()
self.distance_counter = LevenshteinDistance()
