Hardening Your Costco Scraper: Detecting Soft Bans and Enforcing Data Quality with Pydantic
When scraping high-value e-commerce targets like Costco, an HTTP 200 OK status code is often a lie. While many developers rely on status codes to trigger retries, Costco frequently employs soft bans.
devnoteshub.hashnode.dev6 min read
First off, you'd want batch-level validators that can spot those honeypot red flags - like when everything's priced the same or inventory's flat-lining across a whole product line. Also you gotta nail down the difference between schema drift and soft bans because they need totally different fixes, one's just weird data that needs a human look, the other means rotate your proxy and try again. And throw in exponential backoff with some jitter on retries - hammering the same IP over and over is basically begging to stay blocked. Also you mention Playwright as a fallback, which is smart, but it's kinda vague. Maybe flesh out exactly when you'd flip the switch, like okay, price field disappeared after two attempts, time to spin up Playwright. So you're treating data validation as your actual anti-bot defense layer, and most people straight-up sleep on that