POST
Ecommerce product monitoring
Build a price and availability feed across an entire product catalog — discover the URLs once, then re-scrape them on a schedule as structured JSON.

Use case

  • Competitor price monitoring across a full catalog, not just a handful of known SKUs
  • Availability and stock-out alerts for products you track
  • Feeding a pricing dashboard or repricing engine with fresh, structured data

Step 1: Discover product URLs with Map

Map returns every URL on the site with a best-effort type category — filter to product-details instead of guessing from the URL string.

Step 2: Scrape every product URL as structured JSON

Hand the filtered URL list to Batch scrape with a schema so every product comes back in the same shape, regardless of page layout differences across categories.

Step 3: Poll for results and save a price feed

Poll the job until it finishes. With output: ["json"], s3PresignedUrls has a json download link: a JSONL file with one line per URL (url, success, status, output, error). This script reads it and writes the successful products to products.csv.
Python
Load products.csv into your pricing dashboard or database. Run the whole pipeline on a schedule and keep each run’s file to build a price history.

Request highlights

Tips

  • Re-run Map periodically (weekly) to catch new products; re-run Batch scrape more often (daily or hourly) for pricing freshness on the URLs you already have.
  • Set a consistent tag per catalog so you can attribute cost and trace runs in Request history.
  • If different categories need different extraction instructions, split them into separate batch jobs instead of one prompt trying to cover every product type.