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import os

# 设置文件夹路径

folder_path = 'path/to/your/folder'

# 获取文件夹中的所有文件

files = os.listdir(folder_path)

# 过滤出图片文件（以.jpg结尾）

image_files = [f for f in files if f.endswith('.jpg')]

# 重命名文件

for i, file_name in enumerate(image_files, start=1):

    new_file_name = f'{i}.jpg'

    old_file_path = os.path.join(folder_path, file_name)

    new_file_path = os.path.join(folder_path, new_file_name)

    os.rename(old_file_path, new_file_path)

print('文件重命名完成！')

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import requests

# 设置目标URL

url = 'http://example.com'

# 发起HTTP GET请求

response = requests.get(url)

# 检查请求是否成功

if response.status_code == 200:

    # 获取网页内容

    web_content = response.text

    # 设置保存路径和文件名

    save_path = 'path/to/save/file.html'

    # 将网页内容写入文件

    with open(save_path, 'w', encoding='utf-8') as file:

        file.write(web_content)

    print('网页内容已保存为文件！')

else:

    print(f'请求失败，状态码：{response.status_code}')

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import schedule

import time

import smtplib

from email.mime.text import MIMEText

# 设置邮件发送函数

def send_email():

    # 邮件服务器设置

    smtp_server = 'smtp.example.com'

    smtp_port = 587

    sender_email = 'your_email@example.com'

    sender_password = 'your_password'

    # 邮件内容设置

    receiver_email = 'receiver_email@example.com'

    subject = '工作提醒'

    body = '今天是XX月XX日，别忘了完成以下工作任务：...'

    # 创建邮件对象

    message = MIMEText(body, 'plain', 'utf-8')

    message['From'] = sender_email

    message['To'] = receiver_email

    message['Subject'] = subject

    # 发送邮件

    with smtplib.SMTP(smtp_server, smtp_port) as server:

        server.starttls()

        server.login(sender_email, sender_password)

        server.sendmail(sender_email, receiver_email, message.as_string())

    print('邮件已发送！')

# 设置定时任务：每天下午5点发送邮件

schedule.every().day.at("17:00").do(send_email)

# 运行定时任务

while True:

    schedule.run_pending()

    time.sleep(1)

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import pandas as pd

# 读取CSV文件

df = pd.read_csv('path/to/your/file.csv')

# 查看数据

print(df.head())

# 删除缺失值

df_dropna = df.dropna()

# 删除异常值（假设异常值为小于0或大于100的值）

df_clean = df_dropna[(df_dropna >= 0) & (df_dropna <= 100)]

# 保存清洗后的数据

df_clean.to_csv('path/to/save/cleaned_file.csv', index=False)

print('数据清洗完成！')