Zadanie (co 6 h po 200) bralo zawsze 200 najnowszych kandydatow. Przebieg
o 05:00 wzbogacal 14-19 swiezych filmow, trzy kolejne mielily te same 200
bez trafienia z wynikiem zero, a 12,9 tys. starszych kandydatow nie bylo
sprawdzonych ani razu. Teraz movies.tpdb_checked_at (migracja 0051): najpierw
niesprawdzone, film bez trafienia wraca po 30 dniach, blad nie oznacza.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
1745 wystapien w 291 plikach (backend, scripts, mobile). Dominowal jeden ksztalt,
' — ' laczace zdania, wiec poszedl przecinek; myslnik otwierajacy mysl zdjety;
zakresy 0–5 i A–Z na dywiz.
Podzial komentarz/kod robil skaner stanow, nie regex, zeby nie ruszyc myslnika
stojacego w stringu albo w wyrazeniu regularnym. Potwierdzone maszynowo: po wycieciu
komentarzy z wersji HEAD i z dysku obie sa identyczne we wszystkich 291 plikach,
czyli poza komentarzami nie zmienilo sie nic. 233 pliki .py parsuja sie bez bledu,
tsc ma te same 11 bledow w tych samych 3 plikach co przed zmiana.
Dwie rzeczy wymagaly poprawki po automacie: wyrownane listy definicji, gdzie myslnik
byl separatorem kolumny (37 miejsc, kolumna przywrocona), i trzy przeniesienia mysli
do nowej linii, gdzie zostawal wiszacy przecinek na poczatku (poprawione recznie).
Bundla nie republikuje: Hermes i tak nie niesie komentarzy, wiec dla uzytkownika
to zero zmiany.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Generic movie titles ("Monster Tits", "Pirates") map to many different TPDB
films with identical titles (different studios/casts, all title-score 1.0). The
old matcher searched per_page=10 and ranked by title only, so for a generic title
the correct film was often not even in the top 10, and among same-title
candidates it picked arbitrarily. Result: a ~95% no_match rate and silent
misattribution (e.g. "Monster Tits" by Venom Digital Media would get Galaxy
Productions' TPDB entry).
_best_match now:
- searches per_page=40 (the right film for a generic title is often past top 10),
- ranks title-gate survivors by a composite of title + studio similarity +
performer overlap (our studio/cast from the primary source disambiguate which
same-title film it is),
- guards against misattribution: if we have a studio/cast signal and there is
more than one near-identical-title candidate but the winner shares neither
studio nor cast, return no_match instead of attaching a wrong same-title film.
Verified on prod data: a no_match-with-studio sample now matches 18/18 with the
correct studio (fixing Galaxy to Venom, Exquisite to Rodney Moore, and a no_match
to Cherry Boxxx), and an already-enriched sample keeps 16/18 identical picks with
the 2 differences being the same studio (benign TPDB duplicate). No wrong-studio
regressions observed.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Enrich existing movies (from paradisehill/dooplay, which mostly lack cast)
with metadata from TPDB's /movies API: cast, categories (tags), studio,
director + a canonical TPDB UUID for dedup. Chosen over IAFD after a
source-comparison research pass — IAFD has strong cast/studio but ZERO
categories, while TPDB /movies has ~11 tags/movie, cast, studio, director,
a canonical UUID (+ sparse phash), is already an integrated API (no
scraping/anti-bot), and covers ~75-85% of our western-DVD-feature catalog.
Enrichment only ever augments EXISTING movies and never creates new ones
(TPDB has no playback, so a standalone TPDB movie would be unplayable).
Writes to movie_performers / movie_tags / movie.studio_id, which the movies
API + mobile detail already render, so no schema/API/UI change is needed.
- connectors/tpdb.py: search_movies() + fetch_movie() + _parse_movie()
reusing the existing _parse_studio/_parse_performer/_parse_tag.
- enrich/tpdb_movies.py: match our movie to a TPDB /movies result by
token_sort_ratio on normalized titles (sort, not set, to reject the
short-title-subset trap "Fantasies" -> "Tara's Fetish Fantasies") with a
+/-2yr guard; then attach cast/tags/studio/director. Incoming performers
deduped by external_id to avoid the performer_external_refs PK clash.
- resolve/movie_merge.py: merge_movies() mirror of scene_merge; two of our
movies mapping to the same TPDB UUID are the same film -> merge.
- scheduler: _job_tpdb_movie_enrich every 6h, batch 200, prioritizing
playable movies missing cast/studio.
Verified on a 150-movie batch: 119 enriched, 4 deduped, 26 no-match,
0 errors; matched titles/studios spot-checked correct (Big Butts Drive Me
Nuts 4 -> 33 tags, Seinfeld #2 -> 10 cast/17 tags, German BB Video titles
-> categories+studio).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
