Build a Facial Recognition Attendance System

Instead of writing custom scripts for every client, I made a generic scraper that could handle multiple websites. I put it up for sale on Gumroad and Sellix for $19.99, and people started buying it.

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.

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}")

Allow users to specify a desired price threshold and compare it with the current price.

Overview

In this tutorial, we’ll create an automated system for generating Excel reports using Python’s OpenPyXL library. This is a valuable skill for professionals who deal with repetitive Excel tasks, such as data analysts, accountants, and business managers. By the end of this tutorial, you’ll learn how to:

After performing all database operations, it's good practice to close the connection to free up resources.

Add the following code at the end of your app.js file, outside the db.serialize() block:

Run the migration to create the table:

php artisan migrate

• Get all items:

  curl http://127.0.0.1:5000/api/items