Prime Day ends soon: We hand-picked the 95+ best deals still live, before they disappear

Introduction

Amazon Prime Day is one of the biggest shopping events of the year, offering incredible deals on tech gadgets, electronics, and more. In this beginner-friendly tutorial, you'll learn how to track and analyze Prime Day deals using Python and web scraping techniques. You'll build a simple tool that can monitor product prices and alert you when deals drop below a certain threshold. This tutorial is perfect for anyone who wants to automate their shopping and never miss a great deal again.

Prerequisites

Before you begin this tutorial, you'll need:

• A computer with Python installed (version 3.6 or higher)
• Basic understanding of Python programming concepts
• Internet access to browse Amazon and install Python packages

Step-by-Step Instructions

Step 1: Set Up Your Python Environment

Install Required Python Packages

First, you'll need to install the necessary Python packages for web scraping and data handling. Open your terminal or command prompt and run:

pip install requests beautifulsoup4 pandas

Why this step? These packages will help us fetch web pages, parse HTML content, and organize our data in a readable format.

Step 2: Create Your Main Python Script

Initialize Your Project

Create a new file called prime_day_tracker.py and start with this basic structure:

import requests
from bs4 import BeautifulSoup
import time
import pandas as pd

print("Prime Day Deal Tracker Initialized")

Why this step? This sets up the foundation of our script and imports all the necessary libraries we'll be using throughout the tutorial.

Step 3: Create a Function to Fetch Product Data

Build the Web Scraping Function

Add this function to your script to fetch product information from Amazon:

def get_product_info(url):
    headers = {
        'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36'
    }
    response = requests.get(url, headers=headers)
    soup = BeautifulSoup(response.content, 'html.parser')
    
    # Extract product title
    title = soup.find('span', {'id': 'productTitle'})
    title = title.text.strip() if title else 'Title not found'
    
    # Extract current price
    price = soup.find('span', {'class': 'a-price-whole'})
    price = price.text.strip() if price else 'Price not found'
    
    return {
        'title': title,
        'price': price,
        'url': url
    }

Why this step? This function uses requests to get the webpage content and BeautifulSoup to parse the HTML, extracting the product title and current price.

Step 4: Define Products to Track

Set Up Your Product List

Add this code to create a list of products you want to monitor:

# List of products to track
products_to_track = [
    {
        'name': 'MacBook Air M1',
        'url': 'https://www.amazon.com/Apple-MacBook-Air-M1-chip/dp/B08L5QVFGL'
    },
    {
        'name': 'Samsung 55" 4K TV',
        'url': 'https://www.amazon.com/Samsung-55-Inch-4K-Ultra-HD/dp/B086C5K15Q'
    },
    {
        'name': '1TB SSD Drive',
        'url': 'https://www.amazon.com/Samsung-970-EVO-1TB/dp/B07TF4V621'
    }
]

Why this step? This creates a structured list of products you're interested in tracking, making it easy to add or remove items later.

Step 5: Create a Monitoring Loop

Implement Continuous Monitoring

Add this function to continuously check for price changes:

def monitor_deals(products, target_price):
    print(f"Monitoring deals for prices below ${target_price}")
    
    while True:
        for product in products:
            try:
                info = get_product_info(product['url'])
                current_price = info['price']
                
                # Convert price to number for comparison
                price_value = float(current_price.replace('$', '').replace(',', ''))
                
                if price_value < target_price:
                    print(f"ALERT: {product['name']} is below ${target_price}! Current price: ${current_price}")
                else:
                    print(f"{product['name']}: ${current_price} (Above target)")
                    
            except Exception as e:
                print(f"Error fetching {product['name']}: {e}")
                
        print("\nChecking again in 5 minutes...")
        time.sleep(300)  # Wait 5 minutes before next check

Why this step? This loop continuously checks all products every 5 minutes, alerting you when prices drop below your target threshold.

Step 6: Run Your Deal Tracker

Execute Your Script

Add this final code to your script to start monitoring:

# Start monitoring
if __name__ == "__main__":
    target_price = 1000  # Set your target price here
    monitor_deals(products_to_track, target_price)

Why this step? This starts the monitoring process, running your script continuously to check for deals.

Step 7: Test Your Script

Verify Everything Works

Run your script by typing:

python prime_day_tracker.py

You should see output showing the current prices of your tracked products. If any product drops below your target price, you'll get an alert message.

Why this step? Testing ensures your script works correctly before you leave it running for extended periods.

Summary

In this tutorial, you've built a simple yet effective Prime Day deal tracker that monitors product prices and alerts you when deals drop below your target threshold. The script uses Python's requests and BeautifulSoup libraries to scrape Amazon product pages and continuously checks for price changes. While this is a basic implementation, it demonstrates the core concepts of web scraping and automated monitoring that you can expand upon for more sophisticated tracking systems.

This tool helps you stay ahead of Prime Day deals by automatically checking prices and notifying you when products drop to attractive prices. You can easily modify the script to track more products, adjust the monitoring frequency, or add email notifications for more advanced features.