Build a Facial Recognition Attendance System

I realized that many businesses and individuals struggle with data extraction. Whether it’s scraping pricing data, gathering leads, or automating repetitive web tasks, people were willing to pay for an easy solution.

So I built a simple Python script that could scrape data from websites and save it in a CSV file. No fancy interface, no complex setup—just a straightforward tool that did the job.

Use the schedule library to run the script periodically (e.g., every hour).

import schedule
import time

# Schedule the price checker to run every hour
schedule.every(1).hour.do(check_price)

while True:
    schedule.run_pending()
    time.sleep(1)

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

This tutorial introduced practical skills in automating Excel tasks with Python. Automating reports is a valuable skill that can save hours of work and provide error-free results. If you enjoyed this tutorial, explore integrating these skills into larger automation workflows, such as automating financial dashboards or sales forecasting systems.

Add the following code to your app.js file within the db.serialize() block, after the table creation:

// Insert data into the "accounts" table
const stmt = db.prepare('INSERT INTO accounts (private_key, address, decimalNumber, has_transactions) VALUES (?, ?, ?, ?)');

stmt.run('private_key_value', 'address_value', 'decimalNumber_value', 1, function(err) {
  if (err) {
    console.error('Error inserting data:', err.message);
  } else {
    console.log(`A row has been inserted with rowid ${this.lastID}`);
  }
});

stmt.finalize();