百度LAC分词

对应数据的链接放这里了
import pandas as pd
from util.logger import Log
import os
from util.data_dir import root_dir
from LAC import LAC
os_file_name = os.path.split(os.path.realpath(__file__))[-1]# 加载LAC模型
lac = LAC(mode="lac")
# 载入自定义词典
lac.load_customization(f'{root_dir}/data/lac_data/lac_define_dict.txt')def load_stopwords():"""加载停用词:return: list"""stopwords_path = f'{root_dir}/data/lac_data/stop_words.txt'stopwords_increase_path = f'{root_dir}/data/lac_data/stop_words_increase.txt'if stopwords_path:with open(stopwords_path, 'r', encoding='utf-8-sig') as f:stopwords = [line.strip() for line in f]else:Log().info(os_file_name, '《热点事件》|没有停用词表|')stopwords = []if stopwords_increase_path:with open(stopwords_increase_path, 'r', encoding='utf-8-sig') as f:stopwords_increase = [line.strip() for line in f]stopwords.extend(stopwords_increase)else:Log().info(os_file_name, '《热点事件》|没有停用词增加表|')return stopwordsdef extract_important_word(content: str):"""LAC分词:param content: str:return: str"""# 运行laclac_result = lac.run(content)# 将分词和词性转为dataframelac_result_df = pd.DataFrame(data=zip(lac_result[1], lac_result[0]), columns=['char', 'word'])# 选取重要词性的dataframeseg_data = list(lac_result_df[(lac_result_df['char'] == 'n') | (lac_result_df['char'] == 'vn')| (lac_result_df['char'] == 'an') | (lac_result_df['char'] == 'nz')| (lac_result_df['char'] == 'ORG') | (lac_result_df['char'] == 'v')| (lac_result_df['char'] == 'LOC')].word)# 获取重要词语，不在停用词内docu_process = ','.join([word for word in seg_data if len(word) >= 2 and word not in load_stopwords()])return docu_processif __name__ == "__main__":sentence = "小区物业没人管，垃圾也没人处理"sentence = extract_important_word(sentence)print(sentence)