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# -*- coding: utf-8 -*-
import os
import jieba
import csv
def process_text(text):
"""
使用jieba分词并过滤不需要的字符
"""
filter_list = ['\n', '\t', '\r', '\b', '\f', '\v', '', '', '', '10', '', '', '', '', '', '', ' ', '', '', '', '',
'/', '', '', '', '_', '-', ')', '(', '', '', '', '', '', '', '', '...', '', '%', '&', '+', ',', '.',
':', ';', '<', '=', '>', '?', '[', ']', '|', '', ''
]
text_list = jieba.lcut(text)
results = []
for tl in text_list:
should_include = True
for fl in filter_list:
if fl == tl:
should_include = False
break
if should_include:
results.append(tl)
if results:
return list(set(results)) # 去重
else:
return None
def search_data_sets_by_keywords(csv_file_path, keywords):
"""
根据关键词搜索csv文件中的匹配项
Args:
csv_file_path: CSV文件路径
keywords: 关键词列表
Returns:
匹配的数据集列表
"""
if not os.path.exists(csv_file_path):
print(f"文件不存在: {csv_file_path}")
return []
data_dict = {} # 使用字典来存储,以id为键去重
with open(csv_file_path, 'r', encoding='utf-8') as f:
reader = csv.reader(f)
for row in reader:
# 检查每一行的第12列(索引11)和第13列(索引12)是否包含任意关键词
for key in keywords:
if key in row[11] or key in row[12]:
item_id = row[0]
# 如果id不存在,或者想要保留第一个出现的记录
if item_id not in data_dict:
data_dict[item_id] = {
'id': item_id,
'data_set_name': row[1],
'description': row[2],
'description_cn': row[11],
}
# 将字典的值转换为列表
return list(data_dict.values())
def extract_keywords_from_text(text_file_path):
"""
从文本文件中提取关键词
Args:
text_file_path: 文本文件路径
Returns:
提取的关键词列表
"""
if not os.path.exists(text_file_path):
print(f"文件不存在: {text_file_path}")
return None
with open(text_file_path, 'r', encoding='utf-8') as f:
text_list = [line.strip() for line in f if line.strip()]
if not text_list:
print('关键词文本无数据')
return None
# 将所有文本合并并用分号连接,然后进行处理
result_str = process_text(';'.join(text_list))
if result_str:
print(f'关键词提取结果: {result_str}')
return result_str
else:
return None
def main():
keys_text_path = "keys_text.txt"
keywords = extract_keywords_from_text(keys_text_path)
if not keywords:
print("无法提取关键词")
return
csv_file_path = "all_data_combined.csv"
matched_data_sets = search_data_sets_by_keywords(csv_file_path, keywords)
print(f'从数据集中提取了 {len(matched_data_sets)} 条匹配数据')
for data_set in matched_data_sets:
print(f"数据集: {data_set['data_set_name']}")
print(f"英文描述: {data_set['description']}")
print(f"中文描述: {data_set['description_cn']}")
print("-" * 50)
if __name__ == "__main__":
main()