Price Tracker System

Automated web scraping solution for monitoring product prices

Project Overview

This Python-based price tracking system allows users to monitor product prices across e-commerce sites. Users simply add product URLs to a text file, and the system automatically checks prices every 24 hours, logs changes, and sends email alerts for significant price drops. The techniques used in this system are useful for many real-world data-gathering tasks, including mixed-methods (quantitative and qualitative) ethnographic research, and my skills in this area will enhance future research projects, both in the classroom and at the institutional level.

Key Features

  • Automated daily price monitoring
  • Email notifications for price changes
  • Historical price tracking with CSV logging
  • Anti-detection techniques with request rotation
  • Scheduled execution with APScheduler
  • Single-instance enforcement to prevent duplicates

Technical Implementation

The system combines several Python technologies to create a robust, automated tracking solution:

Core Technologies Used

Technology Purpose
BeautifulSoup HTML parsing and data extraction
Requests HTTP requests to product pages
APScheduler Automated daily execution
CSV Module Data persistence and logging
smtplib Email notification system
Logging Module Error tracking and system monitoring

Key Technical Skills Demonstrated

  • Web Scraping: Robust extraction of product data from e-commerce sites
  • Error Handling: Comprehensive exception management for reliability
  • Scheduling: Automated execution using cron-like scheduling
  • Data Persistence: CSV-based storage of historical price data
  • Anti-Bot Measures: Random delays and header rotation to avoid detection
  • Email Integration: HTML-formatted price alerts
  • System Architecture: Single instance enforcement and proper resource management

Future Applications & Enhancements

The core technology can be extended for various applications:

Potential Enhancements

  • Browser extension for easier URL management
  • Price prediction using historical data trends
  • Multi-vendor price comparison
  • Mobile app notifications
  • Dynamic pricing threshold alerts

Business Applications

  • Competitor price monitoring
  • Inventory management systems
  • Price optimization for retailers
  • Affiliate marketing tools
  • Market research data collection

Project Resources

# Sample code snippet
def scrape_product(url):
    """Main scraping function with data persistence"""
    try:
        response = requests.get(url, headers=get_random_headers(), timeout=20)
        soup = BeautifulSoup(response.content, 'html.parser')
        
        # Extract product details
        title = soup.find('span', {'id': 'productTitle'}).get_text(strip=True)
        
        # Price extraction logic
        price_element = soup.select_one('span.a-price span.a-offscreen')
        raw_price = price_element.get_text(strip=True) if price_element else "N/A"
        
        # Save to CSV and check for price changes
        # ... (full implementation in project file)