python异步字符串查找，asyncio和marisa_trie

自然语言处理当中经常需要字符串的查找操作，比如通过查找返回字串在文本当中的位置，比如通过匹配实现的ner

import pandas as pd
import asyncio

# data = pd.read_csv("guba_fc_result_20230413.csv")

data = pd.read_csv("guba_all_post_20230413.csv")
filename = "cate_group.txt"

def read_list_from_file(filename):
    with open(filename, 'r') as f:
        lst = [line.strip() for line in f]
    return lst

cate_group = read_list_from_file(filename)


import marisa_trie
# 构建trie
trie = marisa_trie.Trie(cate_group)
 
# 匹配长字符串
# long_string = '宁德时代是做锂电池的'
 
# results = []
# for i in range(len(long_string)):
#     matches = trie.prefixes(long_string[i:])
#     # 输出匹配结果
#     if matches:
#         for matche in matches:
#             results.append(matche)
 
# print(results)


async def match_text(long_string):
    long_string = str(long_string)
    results = []
    for i in range(len(long_string)):
        matches = trie.prefixes(long_string[i:])
        # 输出匹配结果
        if matches:
            for matche in matches:
                results.append(matche)
    return results
 
async def main():
    tasks = []
    for i in data["text"]:
        tasks.append(asyncio.create_task(match_text(i)))
    matches_list = await asyncio.gather(*tasks)

    data["matches"] = matches_list

    print(matches_list)
    data.to_csv("guba_all_matches_20230413.csv")
 
if __name__ == '__main__':
    asyncio.run(main())

多思考也是一种努力，做出正确的分析和选择，因为我们的时间和精力都有限，所以把时间花在更有价值的地方。