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import re
from collections import Counter
import string
from cppy.cp_util import stopwordfilepath,testfilepath
# 读取停用词并创建一个集合以便快速查找
stop_words = set()
with open(stopwordfilepath, encoding='utf-8') as f:
for line in f:
stop_words.update(word.strip() for word in line.split(','))
# 停用词集合中添加所有小写英文字母
# 注意:这里我们不直接添加所有字母,而是在过滤时检查单词长度
# 如果单词只包含一个字符,则视为字母,排除在外
stop_words.update(set(string.ascii_lowercase))
# 读取测试文件并计算单词频率
with open(testfilepath, encoding='utf-8') as f:
# 使用正则表达式移除标点并分割单词,排除单个字符
words = re.findall(r'\b\w{2,}\b', f.read().lower()) # 只匹配至少两个字符的单词
# 过滤停用词并计数
word_freqs = Counter(word for word in words if word not in stop_words and len(word) > 1)
# 获取出现频率最高的前10个单词
most_common_words = word_freqs.most_common(10)
# 打印结果
for word, freq in most_common_words:
print(f'{word} - {freq}')
# 修改逻辑A01没有排除逗号的影响同时一遍提取一边排序资源占用大
# 解决方案引入re将逗号去除。并且引入counter进行计数