Build a price tracker for favorite products

Building a price tracker for your favorite products involves combining several key components: product data collection, price monitoring, and alerting when prices change. Here’s a detailed guide and an example approach to create a functional price tracker.

How to Build a Price Tracker for Favorite Products

1. Choose the Products and Platforms to Track

Decide which online stores or marketplaces (e.g., Amazon, eBay, Walmart) you want to track. This determines how you’ll scrape or access product data.

2. Collect Product Information

You need to gather product identifiers like URLs, product IDs, or SKUs. This lets the system know exactly which product’s price to track.

3. Scrape or Use APIs for Price Data

• Web Scraping: Extract price data from product pages using libraries like BeautifulSoup or Selenium in Python.

• APIs: Some platforms offer APIs that provide product info and prices legally and more reliably.

4. Store Data

Save product info and price history in a database (SQLite, PostgreSQL, or a simple JSON file for starters).

5. Monitor Prices Regularly

Set up a scheduled job (cron job or cloud function) to check prices at fixed intervals (e.g., daily).

6. Notify Users of Price Changes

Use email, SMS, or push notifications to alert users when prices drop or reach a target.

Sample Implementation in Python

This is a simplified example tracking prices of products on Amazon via scraping. Note that scraping Amazon can violate their ToS, so use APIs or check legality before production use.

python
CopyEdit
import requests
from bs4 import BeautifulSoup
import sqlite3
import smtplib
from email.mime.text import MIMEText
import time

# Database setup
conn = sqlite3.connect('prices.db')
c = conn.cursor()
c.execute('''CREATE TABLE IF NOT EXISTS products
             (url TEXT PRIMARY KEY, name TEXT, last_price REAL)''')
conn.commit()

def fetch_price_amazon(url):
    headers = {
        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko)"
                      " Chrome/58.0.3029.110 Safari/537.3"}
    response = requests.get(url, headers=headers)
    soup = BeautifulSoup(response.content, 'html.parser')
    price_str = soup.find(id='priceblock_ourprice') or soup.find(id='priceblock_dealprice')
    if price_str:
        price = price_str.text.strip().replace('$', '').replace(',', '')
        try:
            return float(price)
        except ValueError:
            return None
    return None

def send_email(subject, body, to_email):
    from_email = "your_email@example.com"
    from_password = "your_password"

    msg = MIMEText(body)
    msg['Subject'] = subject
    msg['From'] = from_email
    msg['To'] = to_email

    server = smtplib.SMTP_SSL('smtp.gmail.com', 465)
    server.login(from_email, from_password)
    server.sendmail(from_email, to_email, msg.as_string())
    server.quit()

def check_prices():
    c.execute("SELECT url, name, last_price FROM products")
    rows = c.fetchall()
    for url, name, last_price in rows:
        current_price = fetch_price_amazon(url)
        if current_price and current_price < last_price:
            print(f"Price drop detected for {name}: {last_price} -> {current_price}")
            send_email(
                f"Price Drop Alert: {name}",
                f"The price for {name} has dropped from ${last_price} to ${current_price}.nCheck it here: {url}",
                "user_email@example.com"
            )
            c.execute("UPDATE products SET last_price = ? WHERE url = ?", (current_price, url))
            conn.commit()

def add_product(url, name):
    price = fetch_price_amazon(url)
    if price:
        c.execute("INSERT OR REPLACE INTO products (url, name, last_price) VALUES (?, ?, ?)", (url, name, price))
        conn.commit()
        print(f"Added {name} with price ${price}")
    else:
        print("Failed to fetch price.")

# Example usage
if __name__ == "__main__":
    # Add your favorite products here
    add_product("https://www.amazon.com/dp/B08N5WRWNW", "Example Product")

    # Check prices every 24 hours (86400 seconds)
    while True:
        check_prices()
        time.sleep(86400)

Key Features to Expand On

• Multiple Stores: Implement scraping or API calls for other stores.

• User Interface: Build a web or mobile app where users add products and see price history.

• Advanced Notifications: SMS via Twilio, Telegram bots, or push notifications.

• Price History Graphs: Visualize price trends over time.

• User Accounts: Allow saving favorite products per user with login functionality.

This basic blueprint gives you a starting point for creating a fully featured price tracker tailored to your favorite products.