Automation & scripting
CLI tools, scheduled jobs, filesystem tasks, and glue scripts that save time.
Detect and Remove Blurry Images in Python with OpenCV
Automatically scan a directory of images, detect blur using Laplacian variance, and remove blurry images with a dry-run option for safety.
from pathlib import Path
import cv2
import numpy as np
def is_blurry(image_path, threshold=100.0):
"""
Detect if an image is blurry using Laplacian variance.
Returns True if blurry, False otherwise.
"""
img = cv2.imread(str(image_path), cv2.IMREAD_GRAYSCALE)
if img is None:
return True…Download Images from a Web Page Automatically in Python
Scrape all images from a webpage, filter by extension, and save them to a local folder using requests and BeautifulSoup.
import requests
from bs4 import BeautifulSoup
from urllib.parse import urljoin
import os
def download_images(url, output_folder="downloaded_images"):
"""Download all images from a given URL."""
os.makedirs(output_folder, exist_ok=True)
response = requests.get(url)
response.raise_for_status()
…How to Detect Unused Images in a Project with Python
A Python script that scans a website project folder, identifies all image files, and checks HTML/CSS/JS files to find which images are never referenced.
import os
import re
from pathlib import Path
def find_unused_images(project_path):
image_exts = {'.png', '.jpg', '.jpeg', '.gif', '.svg', '.webp'}
used_images = set()
all_images = set()
# Find all image files
for root, _, files in os.walk(project_path):
for file in files:
…Browse by section
Each section groups closely related Python snippets.
Automation & scripting — Python code examples
What you will find here
This page collects automation & scripting snippets — short, copy-ready Python you can paste into our free online IDE and run without installing anything. Each sample includes a plain-English explanation and the full source code.
Samples vs tutorials and challenges
Samples are quick reference — one concept per page. For step-by-step teaching, use our Python tutorials. To test yourself, try quizzes or coding challenges. Clean up style with the Python formatter.