Overview
A background tool that takes the manual work out of waiting for a sale. You hand it a product URL and a target price; it scrapes the current price on a schedule, keeps a history of what it has seen, and the moment a price drops it emails you. We built it to run unattended across several e-commerce sites at once, so nothing slips past while you're not looking.
The Challenge
Price tracking sounds simple until you try to do it reliably. Each store lays out its pages differently, so the price has to be located accurately on every target. A single check tells you nothing on its own — the tool needs memory to know whether today's price is actually lower than before. And the whole thing has to run on its own schedule and reach the user instantly when it matters, without anyone sitting there refreshing pages.
Our Approach
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1
Target sites & structure
Identified the target e-commerce sites and mapped each page's HTML to find exactly where the price lives, so the scraper reads the right value every time.
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2
Scraper build
Built a polite Python scraper that pulls the current price straight from each product URL, handling the small differences between sites.
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3
Price history & comparison
Added a local database to store each price over time, compare every new check against the last, and flag a genuine drop below the threshold you set.
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4
Alert system
Wired in email notifications that fire automatically the instant a tracked price falls below your target, so you hear about it right away.
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5
Scheduling & hands-off run
Set it to run on a schedule, checking every few hours with no manual input — deploy it once and let it watch prices for you in the background.
The Result
Alerts you within minutes of a price change, fully unattended.
Add a product URL, set your target price, and forget about it — the tool runs quietly in the background and emails you the moment a price drops. It demonstrates the same skills we bring to client work: reliable scraping across messy real-world pages, durable data storage, and scheduled automation that just keeps running.
Tech Stack
- Language: Python
- Scraping: requests + BeautifulSoup
- Data storage: SQLite (price history)
- Alerts: smtplib (email notifications)
- Scheduling: cron / Task Scheduler