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cutter.py
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cutter.py
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import os
from collections import Counter
import jieba
import json
from tqdm import tqdm
"""
该文件主要是进行分词获取词表
"""
def read_json_file(path, encoding="utf-8"):
with open(path, "r", encoding=encoding) as fp:
data = json.load(fp)
return data
def get_words_by_text(text):
words = jieba.lcut(text, cut_all=False)
return words
class SFKSProcess:
def get_words_by_data(self, data):
word_list = []
for d in tqdm(data, ncols=100):
option_list = d["option_list"]
options = option_list.values()
for option in options:
words = get_words_by_text(option)
word_list.extend(words)
statement = d['statement']
words = get_words_by_text(statement)
word_list.extend(words)
return word_list
def sfks_process(self):
train_data = read_json_file("data/sfks/raw_data/train.json")
train_word_list = self.get_words_by_data(train_data)
train_data = read_json_file("data/sfks/raw_data/test_input.json")
test_word_list = self.get_words_by_data(train_data)
word_list = train_word_list test_word_list
word_count = Counter(word_list)
word_count = sorted(word_count.items(), key=lambda x: x[1], reverse=True)
word_count = {i: j for (i, j) in word_count}
mid_data_path = 'data/sfks/mid_data/'
if not os.path.exists(mid_data_path):
os.mkdir(mid_data_path)
with open(os.path.join(mid_data_path, "words.json"), "w", encoding="utf-8") as fp:
fp.write(json.dumps(word_count, ensure_ascii=False))
if __name__ == '__main__':
sfksprocess = SFKSProcess()
sfksprocess.sfks_process()