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from __future__ import absolute_import, unicode_literals
import os
import re
import sys
import jieba
import pickle
from .._compat import *
from .viterbi import viterbi
PROB_START_P = "prob_start.p"
PROB_TRANS_P = "prob_trans.p"
PROB_EMIT_P = "prob_emit.p"
CHAR_STATE_TAB_P = "char_state_tab.p"
re_han_detail = re.compile("([\u4E00-\u9FD5]+)")
re_skip_detail = re.compile("([\.0-9]+|[a-zA-Z0-9]+)")
re_han_internal = re.compile("([\u4E00-\u9FD5a-zA-Z0-9+#&\._]+)")
re_skip_internal = re.compile("(\r\n|\s)")
re_eng = re.compile("[a-zA-Z0-9]+")
re_num = re.compile("[\.0-9]+")
re_eng1 = re.compile('^[a-zA-Z0-9]$', re.U)
def load_model():
# For Jython
start_p = pickle.load(get_module_res("posseg", PROB_START_P))
trans_p = pickle.load(get_module_res("posseg", PROB_TRANS_P))
emit_p = pickle.load(get_module_res("posseg", PROB_EMIT_P))
state = pickle.load(get_module_res("posseg", CHAR_STATE_TAB_P))
return state, start_p, trans_p, emit_p
if sys.platform.startswith("java"):
char_state_tab_P, start_P, trans_P, emit_P = load_model()
else:
from .char_state_tab import P as char_state_tab_P
from .prob_start import P as start_P
from .prob_trans import P as trans_P
from .prob_emit import P as emit_P
class pair(object):
def __init__(self, word, flag):
self.word = word
self.flag = flag
def __unicode__(self):
return '%s/%s' % (self.word, self.flag)
def __repr__(self):
return 'pair(%r, %r)' % (self.word, self.flag)
def __str__(self):
if PY2:
return self.__unicode__().encode(default_encoding)
else:
return self.__unicode__()
def __iter__(self):
return iter((self.word, self.flag))
def __lt__(self, other):
return self.word < other.word
def __eq__(self, other):
return isinstance(other, pair) and self.word == other.word and self.flag == other.flag
def __hash__(self):
return hash(self.word)
def encode(self, arg):
return self.__unicode__().encode(arg)
class POSTokenizer(object):
def __init__(self, tokenizer=None):
self.tokenizer = tokenizer or jieba.Tokenizer()
self.load_word_tag(self.tokenizer.get_dict_file())
def __repr__(self):
return '<POSTokenizer tokenizer=%r>' % self.tokenizer
def __getattr__(self, name):
if name in ('cut_for_search', 'lcut_for_search', 'tokenize'):
# may be possible?
raise NotImplementedError
return getattr(self.tokenizer, name)
def initialize(self, dictionary=None):
self.tokenizer.initialize(dictionary)
self.load_word_tag(self.tokenizer.get_dict_file())
def load_word_tag(self, f):
self.word_tag_tab = {}
f_name = resolve_filename(f)
for lineno, line in enumerate(f, 1):
try:
line = line.strip().decode("utf-8")
if not line:
continue
word, _, tag = line.split(" ")
self.word_tag_tab[word] = tag
except Exception:
raise ValueError(
'invalid POS dictionary entry in %s at Line %s: %s' % (f_name, lineno, line))
f.close()
def makesure_userdict_loaded(self):
if self.tokenizer.user_word_tag_tab:
self.word_tag_tab.update(self.tokenizer.user_word_tag_tab)
self.tokenizer.user_word_tag_tab = {}
def __cut(self, sentence):
prob, pos_list = viterbi(
sentence, char_state_tab_P, start_P, trans_P, emit_P)
begin, nexti = 0, 0
for i, char in enumerate(sentence):
pos = pos_list[i][0]
if pos == 'B':
begin = i
elif pos == 'E':
yield pair(sentence[begin:i + 1], pos_list[i][1])
nexti = i + 1
elif pos == 'S':
yield pair(char, pos_list[i][1])
nexti = i + 1
if nexti < len(sentence):
yield pair(sentence[nexti:], pos_list[nexti][1])
def __cut_detail(self, sentence):
blocks = re_han_detail.split(sentence)
for blk in blocks:
if re_han_detail.match(blk):
for word in self.__cut(blk):
yield word
else:
tmp = re_skip_detail.split(blk)
for x in tmp:
if x:
if re_num.match(x):
yield pair(x, 'm')
elif re_eng.match(x):
yield pair(x, 'eng')
else:
yield pair(x, 'x')
def __cut_DAG_NO_HMM(self, sentence):
DAG = self.tokenizer.get_DAG(sentence)
route = {}
self.tokenizer.calc(sentence, DAG, route)
x = 0
N = len(sentence)
buf = ''
while x < N:
y = route[x][1] + 1
l_word = sentence[x:y]
if re_eng1.match(l_word):
buf += l_word
x = y
else:
if buf:
yield pair(buf, 'eng')
buf = ''
yield pair(l_word, self.word_tag_tab.get(l_word, 'x'))
x = y
if buf:
yield pair(buf, 'eng')
buf = ''
def __cut_DAG(self, sentence):
DAG = self.tokenizer.get_DAG(sentence)
route = {}
self.tokenizer.calc(sentence, DAG, route)
x = 0
buf = ''
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 buf:
if len(buf) == 1:
yield pair(buf, self.word_tag_tab.get(buf, 'x'))
elif not self.tokenizer.FREQ.get(buf):
recognized = self.__cut_detail(buf)
for t in recognized:
yield t
else:
for elem in buf:
yield pair(elem, self.word_tag_tab.get(elem, 'x'))
buf = ''
yield pair(l_word, self.word_tag_tab.get(l_word, 'x'))
x = y
if buf:
if len(buf) == 1:
yield pair(buf, self.word_tag_tab.get(buf, 'x'))
elif not self.tokenizer.FREQ.get(buf):
recognized = self.__cut_detail(buf)
for t in recognized:
yield t
else:
for elem in buf:
yield pair(elem, self.word_tag_tab.get(elem, 'x'))
def __cut_internal(self, sentence, HMM=True):
self.makesure_userdict_loaded()
sentence = strdecode(sentence)
blocks = re_han_internal.split(sentence)
if HMM:
cut_blk = self.__cut_DAG
else:
cut_blk = self.__cut_DAG_NO_HMM
for blk in blocks:
if re_han_internal.match(blk):
for word in cut_blk(blk):
yield word
else:
tmp = re_skip_internal.split(blk)
for x in tmp:
if re_skip_internal.match(x):
yield pair(x, 'x')
else:
for xx in x:
if re_num.match(xx):
yield pair(xx, 'm')
elif re_eng.match(x):
yield pair(xx, 'eng')
else:
yield pair(xx, 'x')
def _lcut_internal(self, sentence):
return list(self.__cut_internal(sentence))
def _lcut_internal_no_hmm(self, sentence):
return list(self.__cut_internal(sentence, False))
def cut(self, sentence, HMM=True):
for w in self.__cut_internal(sentence, HMM=HMM):
yield w
def lcut(self, *args, **kwargs):
return list(self.cut(*args, **kwargs))
# default Tokenizer instance
dt = POSTokenizer(jieba.dt)
# global functions
initialize = dt.initialize
def _lcut_internal(s):
return dt._lcut_internal(s)
def _lcut_internal_no_hmm(s):
return dt._lcut_internal_no_hmm(s)
def cut(sentence, HMM=True):
"""
Global `cut` function that supports parallel processing.
Note that this only works using dt, custom POSTokenizer
instances are not supported.
"""
global dt
if jieba.pool is None:
for w in dt.cut(sentence, HMM=HMM):
yield w
else:
parts = strdecode(sentence).splitlines(True)
if HMM:
result = jieba.pool.map(_lcut_internal, parts)
else:
result = jieba.pool.map(_lcut_internal_no_hmm, parts)
for r in result:
for w in r:
yield w
def lcut(sentence, HMM=True):
return list(cut(sentence, HMM))
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