#-*- coding=utf8 -*-
import jieba
import re
from tokenizer import cut_hanlp


# jieba.load_userdict("dict.txt")

# # 设置高词频：一个
# jieba.suggest_freq('台中',tune=True)

# 设置高词频：dict.txt中的每一行都设置一下
# fp=open("dict.txt",'r',encoding='utf8')
# for line in fp:
#     line=line.strip()
#     jieba.suggest_freq(line, tune=True)

# # 设置高词频：dict.txt中的每一行都设置一下快速方法
# [jieba.suggest_freq(line.strip(), tune=True) for line in open("dict.txt",'r',encoding='utf8')]

if __name__=="__main__":
    string="台中正确应该不会被切开。"
    jieba.load_userdict("dict.txt")
    # jieba.suggest_freq('台中', tune=True)
    words_jieba = " ".join(jieba.cut(string,HMM=False))

    words_hanlp=cut_hanlp(string)
    print("words_jieba:"+words_jieba,'\n',"words_hanlp:"+words_hanlp)

#encoding=utf8
import os,gc,re,sys

from jpype import *
# root_path="/home/lhq/桌面/NLP_basis/hanlp"
# djclass_path="-Djava.class.path="+root_path+os.sep+"hanlp-1.6.2.jar:"+root_path
startJVM(getDefaultJVMPath(), "-Djava.class.path=/home/lhq/桌面/NLP_basis/hanlp/hanlp-1.7.3.jar:/home/lhq/桌面/NLP_basis/hanlp",
         "-Xms1g",
         "-Xmx1g")

Tokenizer = JClass('com.hankcs.hanlp.tokenizer.StandardTokenizer')

def to_string(sentence,return_generator=False):
    if return_generator:
        return (word_pos_item.toString().split('/') for word_pos_item in Tokenizer.segment(sentence))
    else:
        return " ".join([word_pos_item.toString().split('/')[0] for word_pos_item in Tokenizer.segment(sentence)])
                                                  # 这里的“”.split('/')可以将string拆分成list 如：'ssfa/fsss'.split('/') => ['ssfa', 'fsss']

def seg_sentences(sentence,with_filter=True,return_generator=False):
    segs=to_string(sentence,return_generator=return_generator)
    if with_filter:
        g = [word_pos_pair[0] for word_pos_pair in segs if len(word_pos_pair)==2 and word_pos_pair[0]!=' ' and word_pos_pair[1] not in drop_pos_set]
    else:
        g = [word_pos_pair[0] for word_pos_pair in segs if len(word_pos_pair)==2 and word_pos_pair[0]!=' ']
    return iter(g) if return_generator else g

def cut_hanlp(raw_sentence,return_list=True):
    if len(raw_sentence.strip())>0:
        return to_string(raw_sentence) if return_list else iter(to_string(raw_sentence))