python中读取附件Who Moved My Cheese.txt中的内容，要求拆分为中英两个文件，文件名为词频数量最多的词。

在Python中，首先你需要使用`email`库来解析附件，因为通常邮件附件是以`.txt`格式存储的，我们先读取正文内容。然后，可以使用`jieba`库进行中文分词，并统计词频。最后，根据词频选择最高频的单词作为文件名。以下是基本步骤：

import email
from email.parser import Parser
import os
import jieba
from collections import Counter

def read_email_attachment(filename):
    with open(filename, 'rb') as fp:
        msg = Parser().parse(fp)
        for part in msg.walk():
            if part.get_content_maintype() == 'multipart':
                continue
            if part.get('Content-Disposition') is None:
                continue
            if part.get_filename() == "Who Moved My Cheese.txt":
                return part.get_payload(decode=True).decode('utf-8')

content = read_email_attachment('your_email.eml')
text = content.replace('\n', '')

# 分割中文和英文
chinese_words = jieba.lcut(text)
english_words = [word for word in text.split() if word.isalpha()]

# 统计词频
chinese_freq = Counter(chinese_words)
english_freq = Counter(english_words)

# 获取词频最高的单词
most_common_chinese = chinese_freq.most_common(1)[0][0]
most_common_english = english_freq.most_common(1)[0][0]

# 创建并保存文件
os.makedirs('files', exist_ok=True)
with open(f'files/{most_common_chinese}.txt', 'w', encoding='utf-8') as ch_file:
    ch_file.write(content)

with open(f'files/{most_common_english}.txt', 'w', encoding='utf-8') as en_file:
    en_file.write(text)