Automated Weekly E-Commerce Data Scraper

I need a robust script or small pipeline that pulls fresh data from a set of e-commerce sites once a week. Each run should capture product details and prices, customer reviews, plus any sales or promotional information that is live on the site at the moment of scraping.

My priority is accuracy and consistency: the scraper must handle pagination, variant listings and occasional layout changes without manual fixes, and it should respect each site’s robots.txt while rotating user-agents or proxies to avoid blocks. Python with Scrapy, Selenium, BeautifulSoup or Playwright is perfectly fine—use whatever you are most efficient with, provided the solution runs headless and can be triggered by a simple cron job or cloud function.

For every weekly crawl I expect two outputs:
• A clean CSV or JSON file containing the raw data (product fields, full pricing breakdown, review text & rating, active promo codes or banners).
• A short comparative report that highlights price changes, new or expired promotions, and shifts in review volume since the previous run.

Acceptance criteria
1. Script scrapes the three requested data categories reliably across my chosen e-commerce sites.
2. Output schema stays identical from week to week.
3. Differential report clearly shows what changed.
4. Full, well-commented source code and a short setup guide are provided so I can redeploy or expand the job myself.

Please tell me which tools or libraries you intend to use, any similar e-commerce scraping work you’ve done, and how quickly you can deliver an initial working version. I’m ready to move forward immediately.