How do content sites update so fast? What are you using for metadata?

Been wondering about this for a while. Some content sites (adult/JAV niche in my case) have new stuff up within minutes, posters, titles, actress names, everything filled in. No way they're doing that by hand.

I'm working on a small side project in that space, mostly the data side, and I'm trying to figure out what people actually use for metadata. Are there APIs for JAV stuff that are actually decent, or is everyone just scraping the usual databases and cleaning it up themselves?

The few I've tried so far are either missing half the fields or the data is weeks old, which kind of defeats the point.

Curious what you guys are using, and what you'd want from an API like that if a good one existed.

strong_bae said:

Been wondering about this for a while. Some content sites (adult/JAV niche in my case) have new stuff up within minutes, posters, titles, actress names, everything filled in. No way they're doing that by hand.

I'm working on a small side project in that space, mostly the data side, and I'm trying to figure out what people actually use for metadata. Are there APIs for JAV stuff that are actually decent, or is everyone just scraping the usual databases and cleaning it up themselves?

The few I've tried so far are either missing half the fields or the data is weeks old, which kind of defeats the point.

Curious what you guys are using, and what you'd want from an API like that if a good one existed.

Click to expand...

there usually isn't one good api, the sites that look instant are running a pipeline: a watcher that polls a few sources on a short interval, a queue, and workers that normalize the fields into one schema of your own. the trick is that they never trust a single source, they merge two or three and fill the gaps from each
the stale data problem is usually the merge step rather than the source. store every field with where it came from and when it was fetched, keep the record even when it is incomplete, and re-check the thin ones on a schedule instead of only fetching once. that way a field that was missing on day one gets filled when a source catches up, which is what makes a catalog look fresh

Short answer: an Extract, Transform, Load (ETL) pipeline

Long answer:

The (unlikely) case where one site has all the metadata you need is trivial so I will focus on the case where you need to pull data from many sites with disparate update schedules.

Our objective is to construct a database that is comprehensive (if an item exists, it is included in the database), complete (if an item is included in the database, it contains all the information about the item), and correct (all fields are valid). To do this we need a swarm of scrapers that extract the metadata from all the sources, a scheduler that runs the scrapers and keeps the metadata fresh, a module that merges fields from different sources using a primary key (important!), discards duplicates, marks invalid data, and, in general, runs algorithms that transform and validate the raw data. Lastly, you need a way to to audit and monitor the whole system because things can (and will) go wrong.

The tricky parts are maintaining the distributed scraper and merging the data.

>No way they're doing that by hand.

Well, *someone* needs to generate the metadata.

Thanks both, this is really useful. The merge step being the hard part rings true — I've been leaning on one source a bit too much and the gaps show up exactly like you said, fields missing on day one that only fill in later. Storing where each field came from + when it was fetched is something I haven't been doing properly yet, just overwriting, so that's a concrete thing to fix. Quick question for both of you — when the same title shows up across sources with different IDs, what do you key the merge on? And how do you notice when a source quietly changes its format, or do you just find out when stuff starts breaking?

strong_bae said:

The few I've tried so far are either missing half the fields or the data is weeks old, which kind of defeats the point.

Curious what you guys are using, and what you'd want from an API like that if a good one existed.

Click to expand...

Most of those sites probably automate metadata collection through scraping, scheduled crawlers, and database matching.

They usually combine multiple sources rather than rely on one API, then clean up missing fields automatically, The tricky part is keeping the data accurate and handling duplicate or inconsistent entries.

strong_bae said:

when the same title shows up across sources with different IDs, what do you key the merge on

Click to expand...

A composite key (e.g., title + duration, title + release date). Though, in some cases you will have two different items with the same composite key and you will have to either keep both records, delete both records, or choose one based on an arbitrary criteria (e.g., the item with most views/likes).

strong_bae said:

And how do you notice when a source quietly changes its format,

Click to expand...

Strict validation with pydantic or a similar tool and end-to-end observability (Open Telemetry, Prometheus, Grafana). If you don't validate responses you will only notice that your data is corrupt after you review the affected entries manually, possibly months after the entry has been saved, replicated, and stored in multiple backups.

Lastly, you need redundant sources because your scrapers will break from time to time for one reason or another..

A lot of that speed probably comes from automated metadata feeds combined with human cleanup. The tricky part isn’t just getting the data quickly, but keeping titles, names, and other fields accurate and consistent.

Keep the identity key separate from the matching rule: assign an internal ID, then map each (source, source_id) to it. Title/date/duration can suggest a match, but collisions should go to review while both raw records remain intact. That also lets you split a mistaken merge later. A popularity score can rank results; it doesn't establish that two records represent the same item.