Personal Project · 2024-07-27
Amazon Scraper
Advanced web scraper designed to navigate and extract product directory information from Amazon and similar large e-commerce platforms with anti-scraping countermeasures.
Problem
Large e-commerce platforms actively block automated access. Naive scrapers fail quickly — rate limits, CAPTCHAs, fingerprinting, and dynamic markup all break simple HTTP requests.
Who it serves
Market research, competitive intelligence, and catalogue operations that need structured product data from platforms that resist extraction.
Ownership
Anti-detection strategy, scraping architecture, data normalisation, and operational reliability patterns.
Architecture
- Request layer — user-agent rotation, IP rotation, throttling, cookie management
- Browser automation — headless browsers for JavaScript-rendered content
- Extraction pipeline — parsing, cleaning, and structured output
- Resilience — retry logic, CAPTCHA handling hooks, session persistence
Technologies
Python · requests · BeautifulSoup · Selenium/Playwright · proxy services · CAPTCHA API integrations
Constraints
- Platform terms of service and legal boundaries must be respected for any production use
- Anti-bot measures evolve — scrapers need modular adapter patterns, not one-off scripts
- Data quality depends on handling partial page loads and variant product structures
Outcome
Demonstrates data engineering and systems resilience applied to hostile extraction environments — relevant to market intelligence, catalogue sync, and competitive monitoring architectures.
Related services
Data pipelines · workflow automation · web applications