jieba/jieba/__init__.py

215 lines
4.6 KiB
Python

import re
import math
import os,sys
import pprint
import finalseg
import time
import tempfile
import marshal
from math import log
import random
FREQ = {}
total =0.0
user_word_tag_tab={}
def gen_trie(f_name):
lfreq = {}
trie = {}
ltotal = 0.0
content = open(f_name,'rb').read().decode('utf-8')
for line in content.split("\n"):
word,freq,_ = line.split(" ")
freq = float(freq)
lfreq[word] = freq
ltotal+=freq
p = trie
for c in word:
if not c in p:
p[c] ={}
p = p[c]
p['']='' #ending flag
return trie, lfreq,ltotal
_curpath=os.path.normpath( os.path.join( os.getcwd(), os.path.dirname(__file__) ) )
print >> sys.stderr, "Building Trie..."
t1 = time.time()
cache_file = os.path.join(tempfile.gettempdir(),"jieba.cache")
load_from_cache_fail = True
if os.path.exists(cache_file) and os.path.getmtime(cache_file)>os.path.getmtime(os.path.join(_curpath,"dict.txt")):
print >> sys.stderr, "loading model from cache"
try:
trie,FREQ,total,min_freq = marshal.load(open(cache_file,'rb'))
load_from_cache_fail = False
except:
load_from_cache_fail = True
if load_from_cache_fail:
trie,FREQ,total = gen_trie(os.path.join(_curpath,"dict.txt"))
FREQ = dict([(k,log(float(v)/total)) for k,v in FREQ.iteritems()]) #normalize
min_freq = min(FREQ.itervalues())
print >> sys.stderr, "dumping model to file cache"
tmp_suffix = "."+str(random.random())
tmp_f = open(cache_file+tmp_suffix,'wb')
marshal.dump((trie,FREQ,total,min_freq),tmp_f)
tmp_f.close()
if os.name=='nt':
import shutil
replace_file = shutil.move
else:
replace_file = os.rename
replace_file(cache_file+tmp_suffix,cache_file)
print >> sys.stderr, "loading model cost ", time.time() - t1, "seconds."
print >> sys.stderr, "Trie has been built succesfully."
def __cut_all(sentence):
dag = get_DAG(sentence)
old_j = -1
for k,L in dag.iteritems():
if len(L)==1 and k>old_j:
yield sentence[k:L[0]+1]
old_j = L[0]
else:
for j in L:
if j>k:
yield sentence[k:j+1]
old_j = j
def calc(sentence,DAG,idx,route):
N = len(sentence)
route[N] = (1.0,'')
for idx in xrange(N-1,-1,-1):
candidates = [ ( FREQ.get(sentence[idx:x+1],min_freq) + route[x+1][0],x ) for x in DAG[idx] ]
route[idx] = max(candidates)
def get_DAG(sentence):
N = len(sentence)
i,j=0,0
p = trie
DAG = {}
while i<N:
c = sentence[j]
if c in p:
p = p[c]
if '' in p:
if not i in DAG:
DAG[i]=[]
DAG[i].append(j)
j+=1
if j>=N:
i+=1
j=i
p=trie
else:
p = trie
i+=1
j=i
for i in xrange(len(sentence)):
if not i in DAG:
DAG[i] =[i]
return DAG
def __cut_DAG(sentence):
DAG = get_DAG(sentence)
route ={}
calc(sentence,DAG,0,route=route)
x = 0
buf =u''
N = len(sentence)
while x<N:
y = route[x][1]+1
l_word = sentence[x:y]
if y-x==1:
buf+= l_word
else:
if len(buf)>0:
if len(buf)==1:
yield buf
buf=u''
else:
regognized = finalseg.cut(buf)
for t in regognized:
yield t
buf=u''
yield l_word
x =y
if len(buf)>0:
if len(buf)==1:
yield buf
else:
regognized = finalseg.cut(buf)
for t in regognized:
yield t
def cut(sentence,cut_all=False):
if not ( type(sentence) is unicode):
try:
sentence = sentence.decode('utf-8')
except:
sentence = sentence.decode('gbk','ignore')
re_han, re_skip = re.compile(ur"([\u4E00-\u9FA5a-zA-Z0-9+#&\.]+)"), re.compile(ur"(\s+)")
if cut_all:
re_han, re_skip = re.compile(ur"([\u4E00-\u9FA5]+)"), re.compile(ur"[^a-zA-Z0-9+#\n]")
blocks = re_han.split(sentence)
cut_block = __cut_DAG
if cut_all:
cut_block = __cut_all
for blk in blocks:
if re_han.match(blk):
#pprint.pprint(__cut_DAG(blk))
for word in cut_block(blk):
yield word
else:
tmp = re_skip.split(blk)
for x in tmp:
if re_skip.match(x):
yield x
else:
for xx in x:
yield xx
def cut_for_search(sentence):
words = cut(sentence)
for w in words:
if len(w)>2:
for i in xrange(len(w)-1):
gram2 = w[i:i+2]
if gram2 in FREQ:
yield gram2
if len(w)>3:
for i in xrange(len(w)-2):
gram3 = w[i:i+3]
if gram3 in FREQ:
yield gram3
yield w
def load_userdict(f):
global trie,total,FREQ
if isinstance(f, (str, unicode)):
f = open(f, 'rb')
content = f.read().decode('utf-8')
line_no = 0
for line in content.split("\n"):
line_no+=1
if line.rstrip()=='': continue
tup =line.split(" ")
word,freq = tup[0],tup[1]
if line_no==1:
word = word.replace(u'\ufeff',u"") #remove bom flag if it exists
if len(tup)==3:
user_word_tag_tab[word]=tup[2].strip()
freq = float(freq)
FREQ[word] = log(freq / total)
p = trie
for c in word:
if not c in p:
p[c] ={}
p = p[c]
p['']='' #ending flag