Case study
Product catalogue collector
Collects a complete product catalogue including the detail page behind every listing, rather than only the fields visible on the listing rows themselves.
Overview
A full product catalogue: not the listing rows, which are easy, but the detail page behind each one, which is where the specifications, variants and descriptions actually live.
Complexities tackled
The listing page is a decoy. It is paginated, structured and quick to collect, and it does not contain the data anyone wants. Doing this properly means treating the listing as an index of URLs and then visiting every one of them, which turns a fast job into a slow one and is the only way to get the fields that matter.
Products are not uniformly shaped. Some have variants, some have missing specifications, some have fields the others do not. Flattening that into a single table means deciding what the columns are up front and how an absent value is represented, so that a gap in the data is not mistaken for a zero.
Stack
Python with Requests and BeautifulSoup, CSV output.
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