批量文件重命名神器在工作中，我们常常需要对大量文件进行批量重命名，Python帮你轻松搞定！
import os
def batch_rename(path, prefix='', suffix=''):
for i, filename in enumerate(os.listdir(path)):
new_name = f"{prefix}{i:03d}{suffix}{os.path.splitext(filename)[1]}"
old_file = os.path.join(path, filename)
new_file = os.path.join(path, new_name)
os.rename(old_file, new_file)
# 使用示例：
batch_rename('/path/to/your/directory', 'file_', '.txt')自动发送邮件通知告别手动发送，用Python编写定时发送邮件的自动化脚本。
import smtplib
from email.mime.text import MIMEText
def send_email(to_addr, subject, content):
smtp_server = 'smtp.example.com'
username = 'your-email@example.com'
password = 'your-password'
msg = MIMEText(content)
msg['Subject'] = subject
msg['From'] = username
msg['To'] = to_addr
server = smtplib.SMTP(smtp_server, 587)
server.starttls()
server.login(username, password)
server.sendmail(username, to_addr, msg.as_string())
server.quit()
# 使用示例：
send_email('receiver@example.com', '每日报告提醒', '今日报告已生成，请查收。')定时任务自动化执行使用Python调度库，实现定时执行任务的自动化脚本。
import schedule
import time
def job_to_schedule():
print("当前时间：", time.ctime(), "任务正在执行...")
# 定义每天9点执行任务
schedule.every().day.at("09:00").do(job_to_schedule)
while True:
schedule.run_pending()
time.sleep(1)
# 使用示例：
# 运行此脚本后，每天上午9点会自动打印当前时间及提示信息数据库操作自动化简化数据库管理，Python帮你自动化执行CRUD操作。
import sqlite3
def create_connection(db_file):
conn = None
try:
conn = sqlite3.connect(db_file)
print(f"成功连接到SQLite数据库：{db_file}")
except Error as e:
print(e)
return conn
def insert_data(conn, table_name, data_dict):
keys = ', '.join(data_dict.keys())
values = ', '.join(f"'{v}'" for v in data_dict.values())
sql = f"INSERT INTO {table_name} ({keys}) VALUES ({values});"
try:
cursor = conn.cursor()
cursor.execute(sql)
conn.commit()
print("数据插入成功！")
except sqlite3.Error as e:
print(e)
# 使用示例：
conn = create_connection('my_database.db')
data = {'name': 'John Doe', 'age': 30}
insert_data(conn, 'users', data)
# 在适当时候关闭数据库连接
conn.close()网页内容自动化抓取利用BeautifulSoup和requests库，编写Python爬虫获取所需网页信息。
import requests
from bs4 import BeautifulSoup
def fetch_web_content(url):
response = requests.get(url)
if response.status_code == 200:
soup = BeautifulSoup(response.text, 'html.parser')
# 示例提取页面
title = soup.find('title').text
return title
else:
return "无法获取网页内容"
# 使用示例：
url = 'https://example.com'
web_title = fetch_web_content(url)
print("网页", web_title)数据清洗自动化使用Pandas库，实现复杂数据处理和清洗的自动化。
import pandas as pd
def clean_data(file_path):
df = pd.read_csv(file_path)
# 示例：处理缺失值
df.fillna('N/A', inplace=True)
# 示例：去除重复行
df.drop_duplicates(inplace=True)
# 示例：转换列类型
df['date_column'] = pd.to_datetime(df['date_column'])
return df
# 使用示例：
cleaned_df = clean_data('data.csv')
print("数据清洗完成，已准备就绪！")图片批量压缩用Python快速压缩大量图片以节省存储空间。
from PIL import Image
import os
def compress_images(dir_path, quality=90):
for filename in os.listdir(dir_path):
if filename.endswith(".jpg") or filename.endswith(".png"):
img = Image.open(os.path.join(dir_path, filename))
img.save(os.path.join(dir_path, f'compressed_{filename}'), optimize=True, quality=quality)
# 使用示例：
compress_images('/path/to/images', quality=80)文件内容查找替换Python脚本帮助你一键在多个文件中搜索并替换指定内容。
import fileinput
def search_replace_in_files(dir_path, search_text, replace_text):
for line in fileinput.input([f"{dir_path}/*"], inplace=True):
print(line.replace(search_text, replace_text), end='')
# 使用示例：
search_replace_in_files('/path/to/files', 'old_text', 'new_text')日志文件分析自动化通过Python解析日志文件，提取关键信息进行统计分析。
def analyze_log(log_file):
with open(log_file, 'r') as f:
lines = f.readlines()
error_count = 0
for line in lines:
if "ERROR" in line:
error_count += 1
print(f"日志文件中包含 {error_count} 条错误记录。")
# 使用示例：
analyze_log('application.log')数据可视化自动化利用Matplotlib库，实现数据的自动图表生成。
import matplotlib.pyplot as plt
import pandas as pd
def visualize_data(data_file):
df = pd.read_csv(data_file)
# 示例：绘制柱状图
df.plot(kind='bar', x='category', y='value')
plt.title('数据分布')
plt.xlabel('类别')
plt.ylabel('值')
plt.show()
# 使用示例：
visualize_data('data.csv')邮件附件批量下载通过Python解析邮件，自动化下载所有附件。
import imaplib
import email
from email.header import decode_header
import os
def download_attachments(email_addr, password, imap_server, folder='INBOX'):
mail = imaplib.IMAP4_SSL(imap_server)
mail.login(email_addr, password)
mail.select(folder)
result, data = mail.uid('search', None, "ALL")
uids = data[0].split()
for uid in uids:
_, msg_data = mail.uid('fetch', uid, '(RFC822)')
raw_email = msg_data[0][1].decode("utf-8")
email_message = email.message_from_string(raw_email)
for part in email_message.walk():
if part.get_content_maintype() == 'multipart':
continue
if part.get('Content-Disposition') is None:
continue
filename = part.get_filename()
if bool(filename):
file_data = part.get_payload(decode=True)
with open(os.path.join('/path/to/download', filename), 'wb') as f:
f.write(file_data)
mail.close()
mail.logout()
# 使用示例：
download_attachments('your-email@example.com', 'your-password', 'imap.example.com')定时发送报告自动化根据数据库或文件内容，自动生成并定时发送日报/周报。
import pandas as pd
import smtplib
from email.mime.text import MIMEText
from email.mime.multipart import MIMEMultipart
def generate_report(source, to_addr, subject):
# 假设这里是从数据库或文件中获取数据并生成报告内容
report_content = pd.DataFrame({"Data": [1, 2, 3], "Info": ["A", "B", "C"]}).to_html()
msg = MIMEMultipart()
msg['From'] = 'your-email@example.com'
msg['To'] = to_addr
msg['Subject'] = subject
msg.attach(MIMEText(report_content, 'html'))
server = smtplib.SMTP('smtp.example.com', 587)
server.starttls()
server.login('your-email@example.com', 'your-password')
text = msg.as_string()
server.sendmail('your-email@example.com', to_addr, text)
server.quit()
# 使用示例：
generate_report('data.csv', 'receiver@example.com', '每日数据报告')
# 结合前面的定时任务脚本，可实现定时发送功能自动化性能测试使用Python的locust库进行API接口的压力测试。
from locust import HttpUser, task, between
class WebsiteUser(HttpUser):
wait_time = between(5, 15) # 定义用户操作之间的等待时间
@task
def load_test_api(self):
response = self.client.get("/api/data")
assert response.status_code == 200 # 验证返回状态码为200
@task(3) # 指定该任务在总任务中的执行频率是其他任务的3倍
def post_data(self):
data = {"key": "value"}
response = self.client.post("/api/submit", json=data)
assert response.status_code == 201 # 验证数据成功提交后的响应状态码
# 运行Locust命令启动性能测试：
# locust -f your_test_script.py --host=http://your-api-url.com自动化部署与回滚脚本使用Fabric库编写SSH远程部署工具，这里以部署Django项目为例：
from fabric import Connection
def deploy(host_string, user, password, project_path, remote_dir):
c = Connection(host=host_string, user=user, connect_kwargs={"password": password})
with c.cd(remote_dir):
c.run('git pull origin master') # 更新代码
c.run('pip install -r requirements.txt') # 安装依赖
c.run('python manage.py migrate') # 执行数据库迁移
c.run('python manage.py collectstatic --noinput') # 静态文件收集
c.run('supervisorctl restart your_project_name') # 重启服务
# 使用示例：
deploy(
host_string='your-server-ip',
user='deploy_user',
password='deploy_password',
project_path='/path/to/local/project',
remote_dir='/path/to/remote/project'
)
# 对于回滚操作，可以基于版本控制系统实现或创建备份，在出现问题时恢复上一版本的部署。
