Python is a versatile programming language known for its simplicity and readability. It’s widely used in various fields, from web development to data analysis. In this article, we’ll explore ten Python scripts that can make your life easier by automating common tasks.
1. Data Analysis with Pandas
Pandas is a powerful library for data analysis and manipulation. With just a few lines of code, you can read, clean, and analyze data from various sources like CSV files or databases. Here’s a sample script:
import pandas as pd
# Read data from a CSV file
data = pd.read_csv('data.csv')
# Perform basic analysis
mean = data['column_name'].mean()
print(f"Mean: {mean}")2. Web Scraping with BeautifulSoup
BeautifulSoup is a Python library for web scraping. It allows you to extract data from websites with ease. Here’s a simple web scraping script:
import requests
from bs4 import BeautifulSoup
url = 'https://example.com'
response = requests.get(url)
soup = BeautifulSoup(response.text, 'html.parser')
# Extract data from the webpage
data = soup.find('div', class_='content')
print(data.text)3. File Renamer
This script is handy when you need to rename multiple files in a folder based on specific criteria. For example, you can add a prefix, suffix, or replace text in filenames.
import os
folder_path = '/path/to/folder'
for filename in os.listdir(folder_path):
if filename.startswith('prefix_'):
new_filename = filename.replace('prefix_', 'new_prefix_')
os.rename(os.path.join(folder_path, filename), os.path.join(folder_path, new_filename))4. Image Resizer with Pillow
Pillow is a Python Imaging Library that simplifies working with images. This script resizes a batch of images to a specified resolution or aspect ratio:
from PIL import Image
import os
input_folder = '/path/to/images'
output_folder = '/path/to/resized_images'
desired_size = (100, 100)
for filename in os.listdir(input_folder):
with Image.open(os.path.join(input_folder, filename)) as img:
img.thumbnail(desired_size)
img.save(os.path.join(output_folder, filename))5. PDF Generator with ReportLab
ReportLab is a library for creating PDF documents in Python. You can generate PDF files from text or HTML content. Here’s a basic example:
from reportlab.pdfgen import canvas
pdf_file = 'output.pdf'
text = 'Hello, this is a sample PDF.'
c = canvas.Canvas(pdf_file)
c.drawString(100, 750, text)
c.save()6. Automated Email Sender with smtplib
Need to send automated emails? Python’s smtplib library can help. This script sends emails programmatically:
import smtplib
from email.mime.text import MIMEText
from email.mime.multipart import MIMEMultipart
smtp_server = 'smtp.example.com'
sender_email = 'your_email@example.com'
receiver_email = 'recipient@example.com'
password = 'your_password'
message = MIMEMultipart()
message['From'] = sender_email
message['To'] = receiver_email
message['Subject'] = 'Sample Email Subject'
body = 'This is a sample email message.'
message.attach(MIMEText(body, 'plain'))
with smtplib.SMTP(smtp_server, 587) as server:
server.starttls()
server.login(sender_email, password)
server.sendmail(sender_email, receiver_email, message.as_string())7. Data Backup Script
Automate the backup of files and directories to ensure data safety:
import shutil
source_folder = '/path/to/source_folder'
backup_folder = '/path/to/backup_folder'
shutil.copytree(source_folder, backup_folder)8. Password Generator
Generate strong and random passwords for improved security:
import random
import string
def generate_password(length=12):
characters = string.ascii_letters + string.digits + string.punctuation
return ''.join(random.choice(characters) for _ in range(length))
password = generate_password()
print(password)9. Simple Web Server
Create a basic HTTP server for testing and development:
import http.server
import socketserver
port = 8000
with socketserver.TCPServer(('', port), http.server.SimpleHTTPRequestHandler) as httpd:
print(f"Serving at port {port}")
httpd.serve_forever()10. Database Backup and Restore using SQLite
SQLite is a C library that provides a lightweight disk-based database that doesn’t require a separate server process and allows accessing the database using a nonstandard variant of the SQL query language. Some applications can use SQLite for internal data storage. It’s also possible to prototype an application using SQLite and then port the code to a larger database such as PostgreSQL or Oracle.
Below, I’ll provide you with a sample code for backing up and restoring a SQLite database in Python, which is a lightweight and commonly used database system:
import sqlite3
import shutil
# Database file paths
source_db_file = 'source.db'
backup_db_file = 'backup.db'
# Function to create a backup of the SQLite database
def backup_database():
try:
shutil.copy2(source_db_file, backup_db_file)
print("Backup successful.")
except Exception as e:
print(f"Backup failed: {str(e)}")
# Function to restore the SQLite database from a backup
def restore_database():
try:
shutil.copy2(backup_db_file, source_db_file)
print("Restore successful.")
except Exception as e:
print(f"Restore failed: {str(e)}")
# Usage
while True:
print("Options:")
print("1. Backup Database")
print("2. Restore Database")
print("3. Quit")
choice = input("Enter your choice (1/2/3): ")
if choice == '1':
backup_database()
elif choice == '2':
restore_database()
elif choice == '3':
break
else:
print("Invalid choice. Please enter 1, 2, or 3.")In this code:
backup_database()function makes a copy of the source SQLite database file and names it as the backup file. You can run this function to create backup of your database.restore_database()function copies the backup file back to the source file, effectively restoring the database to the state it was when the backup was created.- The user is presented with options to either backup the database, restore it, or quit the program.
- You can adjust the
source_db_fileandbackup_db_filevariables to specify the paths to your SQLite source and backup database files.
