This complete guide to bol.com Scraper shows how to run a bol.com scraper from Python through the Apify API and get back structured, typed product records: product titles, prices in euros, reference p

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the reference price section is worth a closer look since your sample record leaves those fields empty. pinning to major v3 is the safer route, cause pip won’t upgrade an existing v2 install on its own. the schema table is missing 13 fields that appear in your own record, such as unitprice, condition and labels.
also the table of contents lists a pricing section and a conclusion that aren’t in the body. the dataset snippet loads everything in one call without checking the total, so iterate_items() with a count check would match the memory claim better
ReventaData
Web scraping, API reverse-engineering & automated data feeds at scale. Creator of ReventaData on Apify.
Thanks for the careful read, you are right on both points. The post now installs with pip install "apify-client~=3.0", because a plain pip install apify-client leaves an existing v2 in place and the code relies on the v3 typed run object. I also added a second sample row from a saved bol.com page that has a reference price, so the referencePrice, referencePriceLabel, referencePriceCrossedOut and discountPercent fields are shown filled in.