Python 自动化入门：高效处理重复任务

Python 自动化入门：高效处理重复任务 | 极客日志

python -m venv myenv
source myenv/bin/activate  # Windows: myenv\Scripts\activate
pip install pandas requests beautifulsoup4 pillow selenium schedule

import pandas as pd

# Load data from CSV
data = pd.read_csv('data.csv')

# Perform data analysis
summary = data.describe()

# Display the results
print(summary)

import os
import shutil

# Source and destination directories
source_dir = '/path/to/source'
destination_dir = '/path/to/destination'

# Create destination if not exists
os.makedirs(destination_dir, exist_ok=True)

# Move and rename files
for filename in os.listdir(source_dir):
    if filename.endswith('.txt'):
        new_filename = filename.replace('old', 'new')
        source_path = os.path.join(source_dir, filename)
        destination_path = os.path.join(destination_dir, new_filename)
        
        try:
            shutil.move(source_path, destination_path)
            print(f'Moved: {filename} -> {new_filename}')
        except Exception as e:
            print(f'Error moving {filename}: {e}')

import smtplib
from email.mime.text import MIMEText
from email.header import Header

# Email configurations
smtp_server = 'smtp.example.com'
smtp_port = 587
sender_email = '[email protected]'
password = 'your_password'  # 建议从环境变量读取密码

# Recipients and message content
recipients = ['[email protected]', '[email protected]']
subject = 'Automated Greetings'
message = 'Hey there! Just wanted to say hi.'

# Compose the email
msg = MIMEText(message, 'plain', 'utf-8')
msg['Subject'] = Header(subject, 'utf-8')
msg['From'] = sender_email

try:
    with smtplib.SMTP(smtp_server, smtp_port) as server:
        server.starttls()
        server.login(sender_email, password)
        server.sendmail(sender_email, recipients, msg.as_string())
    print('Email sent successfully.')
except Exception as e:
    print(f'Send failed: {e}')

import requests
from bs4 import BeautifulSoup
import time

# URL to scrape
url = 'https://example.com'
headers = {'User-Agent': 'Mozilla/5.0'}

try:
    # Fetch the HTML content
    response = requests.get(url, headers=headers, timeout=10)
    response.raise_for_status()  # Check for HTTP errors
    soup = BeautifulSoup(response.text, 'html.parser')
    
    # Extract relevant information
    titles = soup.find_all('h2')
    for title in titles:
        print(title.text.strip())
    
    # Respect robots.txt and rate limiting
    time.sleep(1)
except requests.exceptions.RequestException as e:
    print(f'Request error: {e}')

import pandas as pd

# Load data from Excel 
data = pd.read_excel('data.xlsx', sheet_name='Sheet1')

# Perform data manipulation
filtered_data = data[data['Category'] == 'Books']

# Save the result back to a new Excel file
filtered_data.to_excel('filtered_data.xlsx', index=False)
print('Excel processing complete.')

from PIL import Image, ImageFilter

# Open the image
image = Image.open('image.jpg')

# Resize the image
width, height = 800, 600
resized_image = image.resize((width, height))

# Apply a filter
blurred_image = image.filter(ImageFilter.BLUR)

# Save the processed images
resized_image.save('resized_image.jpg')
blurred_image.save('blurred_image.jpg')
print('Image processing done.')

from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC

# Set up the web driver (ensure you have the appropriate driver installed)
options = webdriver.ChromeOptions()
options.add_argument('--headless')  # Run in background
driver = webdriver.Chrome(options=options)

try:
    # Navigate to a website
    driver.get('https://www.google.com')
    
    # Interact with elements
    search_box = driver.find_element(By.NAME, 'q')
    search_box.send_keys('Python automation')
    search_box.submit()
    
    # Wait for results
    wait = WebDriverWait(driver, 10)
    results = wait.until(EC.presence_of_all_elements_located((By.CSS_SELECTOR, '.g h3')))
    
    for result in results[:5]:  # Limit output
        print(result.text)
finally:
    # Close the web driver
    driver.quit()

import requests
import json

# Make a GET request to an API endpoint
response = requests.get('https://api.example.com/data', params={'limit': 10})

# Check if the request was successful
if response.status_code == 200:
    data = response.json()
    for item in data:
        print(item.get('name'), item.get('age'))
else:
    print('Failed to fetch data. Error:', response.status_code)

import schedule
import time

def task_to_be_automated():
    print('Automated task executed!')

# Schedule the task to run every day at 8:00 AM
schedule.every().day.at('08:00').do(task_to_be_automated)

# Run the schedule loop
while True:
    schedule.run_pending()
    time.sleep(1)

try:
    # risky operation
    pass
except FileNotFoundError:
    print('File not found')
except PermissionError:
    print('Permission denied')
finally:
    print('Cleanup resources')

import os
password = os.getenv('MY_PASSWORD')

Python 自动化入门：高效处理重复任务

Python 自动化入门：高效处理重复任务

为什么使用 Python 实现自动化？

环境准备

数据处理与分析

简化文件组织

自动化电子邮件通讯

以自信迎接复杂性

轻松处理 Excel 电子表格

自动图像处理

使用 Selenium 进行 Web 自动化

从 API 中提取数据

定时任务自动化

最佳实践与注意事项

错误处理

安全性

常见问题

总结

更多推荐文章

相关免费在线工具

Python 自动化入门：高效处理重复任务

Python 自动化入门：高效处理重复任务

为什么使用 Python 实现自动化？

环境准备

数据处理与分析

简化文件组织

自动化电子邮件通讯

以自信迎接复杂性

轻松处理 Excel 电子表格

自动图像处理

使用 Selenium 进行 Web 自动化

从 API 中提取数据

定时任务自动化

最佳实践与注意事项

错误处理

安全性

常见问题

总结

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更多推荐文章

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