Python Automation Development Tutorials, Guides & Insights

I created a tutorial on "How to Scrape Websites with Python" and added an affiliate link to a web scraping API. Every time someone signed up, I got a commission.

Eventually, I turned my script into a web app with Flask and hosted it on Heroku. I charged $9/month for unlimited scraping, and within a few months, I had over 50 active users paying for access.

pip install opencv-python dlib face-recognition sqlite3

Capture or collect images of individuals whose attendance you want to track. Organize the images in directories named after the individuals for easy labeling.

Here’s an example for scraping product details:

import requests
from bs4 import BeautifulSoup

# Target URL of the product
URL = "https://www.example.com/product-page"

# Headers to mimic a real browser
HEADERS = {
    "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36"
}

def get_product_price():
    response = requests.get(URL, headers=HEADERS)
    soup = BeautifulSoup(response.content, "html.parser")

    # Extract product name and price using CSS selectors
    product_name = soup.find("h1", {"class": "product-title"}).text.strip()
    price = soup.find("span", {"class": "price"}).text.strip()

    return product_name, float(price.replace("$", ""))

product, price = get_product_price()
print(f"{product}: ${price}")

After completing the above steps, you will have a fully automated Excel report with:

• Formatted data for better readability.
• Conditional highlighting for key metrics.
• A summary sheet with actionable insights.