feat: add LinkedIn as a fifth platform - #3
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nicogiesen wants to merge 1 commit into
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nicogiesen wants to merge 1 commit into
nicogiesen wants to merge 1 commit into
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ScrapeCreators ships LinkedIn endpoints (person profile incl. recentPosts, post details with engagement + comments, post transcript), so LinkedIn slots into the existing per-platform fetcher architecture: - lib/linkedin.py: fetch_profile chains profile -> per-post enrichment (recentPosts carry no date/engagement; capped at 8 lookups per profile), fetch_post, fetch_comments (from the post response), fetch_transcript - registries: linkedin registered in all four fetcher maps - urls: linkedin.com detection + handle extraction (/in/<h>, /posts/<h>_...) - scoring: likes + 3*comments + 2*reposts - dates: parse_iso_date for LinkedIn's ISO 8601 datePublished - tests: 12 new cases (fetcher chain, enrichment fallback, urls, scoring), fixtures from the documented API response shapes - README/SKILL.md: five platforms + credit-cost note for profile fetches Verified against the live API: profile chain returns real posts with dates and engagement.
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What
Adds LinkedIn as a fifth platform, using the ScrapeCreators LinkedIn endpoints that already ship with the same API key.
Why
LinkedIn is the primary channel for a lot of B2B founders and consultants running this skill — and ScrapeCreators already exposes everything needed (person profile incl.
recentPosts, post details with engagement + comments, post transcript). The FILE-SCHEMAS even namelinkedin.mdas an example, so the data model was ready for it.How
The one quirk:
/v1/linkedin/profilereturnsrecentPostswithout dates or engagement.fetch_profiletherefore chains a/v1/linkedin/postlookup per recent post (capped at 8, so a profile fetch costs at most 1 + 8 credits). Posts whose enrichment fails are kept with preview text and empty engagement instead of being dropped. This cost behavior is documented in the README next to the existing X quirk.lib/linkedin.py—fetch_profile(profile → per-post enrichment chain),fetch_post,fetch_comments(from the post response),fetch_transcriptlib/platforms.py— linkedin registered in all four registrieslib/urls.py—linkedin.comdetection + handle extraction (/in/<handle>,/posts/<handle>_…)lib/scoring.py—likes + 3*comments + 2*repostslib/dates.py—parse_iso_datefor LinkedIn's ISO 8601datePublishedTesting