Build data integrations with practical examples, endpoint limits and pagination guides.
Scraping Instagram comments looks trivial until you notice pages overlapping or comments silently missing. The route has a pagination contract that is easy to get wrong; this post documents the exact protocol behind the media comments endpoint.
Exporting an Instagram follower list is the canonical scraping task — and the one where half-baked implementations lose people silently. This is the exact contract behind the followers endpoint.
Hashtags are Instagram's own taxonomy. Mined properly, a seed word expands into its whole semantic neighborhood — every competitor tag, sized by volume, with the posts to back it. Three endpoints do it.
Comments tell you what people think; likes tell you how many bothered to react at all — and who. The likes endpoint returns the likers of any public post in a single response.
Locations are Instagram's underrated dimension: every geotagged post carries a place id, and every place id is a filter the platform curated itself. For local research — venues, neighborhoods, events — location mining beats keyword search on precision.
Stories are where the daily attention lives — and highlights turn that ephemeral layer into a permanent archive the account curates itself. Both are one call each, and they compose into a pipeline.
A profile grid is the public face of an account — and a complete grid export is engagement analysis, content auditing and growth tracking in one dataset. The user media endpoint walks it page by page.
Almost every Instagram endpoint wants the numeric user id (pk) — and almost every workflow starts with a handle. The gap between the two is where bad data enters pipelines. This is every resolution path that works, and the one that silently does not.