Price Trackers

How to Build Your Own Price Tracker with Python (Step-by-Step)

If you’ve ever wished you could create your own tool to monitor prices automatically — this guide is for you.
In 2025, developers and data enthusiasts alike are building custom Python price trackers to monitor products, flights, or crypto prices without relying on third-party apps.

Here’s a full breakdown of how to build a simple but powerful price tracker from scratch using Python — no external platform required.

🧰 What You’ll Need

Before we start, make sure you have:

  • Python 3.10+ installed
  • A text editor (like VS Code)
  • The following Python libraries: pip install requests beautifulsoup4 smtplib
  • A URL from any e-commerce product page (e.g., Amazon, Best Buy, or Walmart)

⚙️ Step 1: Understand What You’re Tracking

Price trackers work by fetching product data from a webpage, parsing the HTML, and extracting the price.
You can run this on a schedule (daily, hourly, etc.) and get notified when the price drops below your target.

Example flow:

Fetch page → Parse HTML → Extract price → Compare → Alert

🕸️ Step 2: Fetch Product Data with Requests

We’ll start by sending a request to the product URL.

import requests

url = "https://www.amazon.com/dp/B08N5WRWNW"  # Example product
headers = {
    "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64)",
    "Accept-Language": "en-US,en;q=0.9"
}

response = requests.get(url, headers=headers)
html = response.text

This simulates a browser request so Amazon doesn’t block it.

🧩 Step 3: Parse the HTML with BeautifulSoup

Now, let’s extract the product title and price.

from bs4 import BeautifulSoup

soup = BeautifulSoup(html, "html.parser")

title = soup.find(id="productTitle").get_text().strip()
price_str = soup.find(class_="a-price-whole").get_text().replace(",", "")
price = float(price_str)

💡 Note: HTML elements vary by website. You may need to inspect each page’s structure using your browser’s developer tools.

🧮 Step 4: Set a Target Price

You can define a target price and check if the current price falls below it.

target_price = 900.00

if price < target_price:
    print(f"🔥 Price dropped for {title}! Now at ${price}")
else:
    print(f"Still too high at ${price}. Waiting for a deal...")

📧 Step 5: Add Email Notifications (Optional)

When the price drops, send yourself an email alert automatically.

import smtplib
from email.mime.text import MIMEText

def send_email(product, price):
    sender = "your_email@gmail.com"
    password = "your_app_password"
    recipient = "your_email@gmail.com"

    msg = MIMEText(f"The price for {product} just dropped to ${price}!\nCheck it out: {url}")
    msg["Subject"] = f"Price Alert: {product}"
    msg["From"] = sender
    msg["To"] = recipient

    with smtplib.SMTP("smtp.gmail.com", 587) as server:
        server.starttls()
        server.login(sender, password)
        server.send_message(msg)

# Trigger alert
if price < target_price:
    send_email(title, price)

Now your tracker notifies you automatically when the price falls — no more manual checking.

⏰ Step 6: Automate the Script

You can automate your tracker using:

  • Windows Task Scheduler
  • macOS Automator
  • Cron Jobs on Linux or servers

Run it daily and let Python handle the monitoring while you sleep.

🧠 Step 7: (Optional) Add AI Prediction

If you want to go next level, connect your tracker to a simple AI model that predicts future price trends.
For example:

  • Use a linear regression model on historical prices
  • Visualize patterns with Matplotlib or Plotly
  • Add “Buy/Wait” recommendations

This turns your script into a personalized AI price tracker.

📊 Final Thoughts

Building your own price tracker is one of the most practical coding projects you can take on in 2025.
You’ll learn how web data works, how to parse HTML, and how automation can save you money.

Start small — track one product, get one email alert, and expand from there.
Soon, you’ll have your very own AI-powered savings bot running in the background. 💻💰

⚙️ Ready to go from shopper to builder?


Explore more tutorials, code templates, and automation ideas at Price-Trackers.com — your hub for smarter shopping through data and Python. 🧠💸

Latest Articles