构建自动化Mailbox邮件筛选程序的Python脚本
发布时间:2024-01-14 11:45:58
构建一个自动化Mailbox邮件筛选程序的Python脚本可以通过使用Python的邮件库和自然语言处理库来实现。下面是一个实现的例子:
import imaplib
from email import parser
import re
from nltk.tokenize import word_tokenize
from nltk.corpus import stopwords
from nltk.stem import WordNetLemmatizer
# 连接到邮箱服务器
def connect_to_mailbox(server, username, password):
mailbox = imaplib.IMAP4_SSL(server)
mailbox.login(username, password)
return mailbox
# 获取邮件内容和主题
def get_email_content(mailbox, email_id):
_, data = mailbox.fetch(email_id, '(RFC822)')
msg = parser.BytesParser().parsebytes(data[0][1])
subject = msg['subject']
content = ""
if msg.is_multipart():
for part in msg.walk():
if part.get_content_type() == "text/plain":
content = part.get_payload(decode=True)
break
else:
content = msg.get_payload(decode=True)
return subject, content
# 提取关键词
def extract_keywords(text):
# 分词
tokens = word_tokenize(text.lower())
# 去除停用词
stop_words = set(stopwords.words('english'))
tokens = [token for token in tokens if token not in stop_words]
# 词形还原
lemmatizer = WordNetLemmatizer()
tokens = [lemmatizer.lemmatize(token) for token in tokens if re.match('[a-zA-Z]{2,}', token)]
return tokens
# 邮件筛选
def filter_emails(mailbox):
mailbox.select("inbox")
_, data = mailbox.search(None, "ALL")
email_ids = data[0].split()
for email_id in email_ids:
subject, content = get_email_content(mailbox, email_id)
# 获取关键词
keywords = extract_keywords(content)
# 根据关键词进行筛选操作
if 'important' in keywords:
move_email(mailbox, email_id, "Important")
elif 'promotion' in keywords:
move_email(mailbox, email_id, "Promotions")
else:
move_email(mailbox, email_id, "Other")
# 移动邮件到指定文件夹
def move_email(mailbox, email_id, folder):
mailbox.copy(email_id, folder)
mailbox.store(email_id, '+FLAGS', '\\Deleted')
# 使用示例
def example():
# 设置邮箱信息
server = "mail.example.com"
username = "your_username"
password = "your_password"
# 连接到邮箱
mailbox = connect_to_mailbox(server, username, password)
# 筛选邮件
filter_emails(mailbox)
# 断开连接
mailbox.expunge()
mailbox.close()
mailbox.logout()
# 运行示例程序
if __name__ == "__main__":
example()
在上面的实例中,我们首先使用IMAP4_SSL库连接到邮箱服务器并登录。然后,我们使用fetch方法获取每个电子邮件的主题和内容。接下来,我们使用自然语言处理库(NLTK)来提取关键词。最后,我们根据关键词将邮件移动到不同的文件夹中,或者做其他自定义操作。
在示例中,我们使用了一些简单的关键词(“important”和“promotion”),你可以根据自己的需要自定义关键词列表,并根据关键词将邮件移动到相应的文件夹中。
