"""Plex people: cast/crew filter-chip cards + a single person's filmography page.""" import threading import time from fastapi import APIRouter, BackgroundTasks, Depends from sqlalchemy.orm import Session from app import sysconfig from app.auth import current_user from app.db import get_db from app.models import User from app.plex import queries, rollup, service from app.plex import tmdb as plex_tmdb from app.plex.cards import SHOW_NEW, movie_card, norm_lang, show_card from app.plex.query import content_libs, split_csv router = APIRouter(prefix="/api/plex", tags=["plex"]) # How many "Known for" titles the person page shows (the stored pool is deeper; see plex.tmdb). _KNOWN_FOR_SHOWN = 15 def _resolve_known_for( db: Session, known_for: list | None, uid: int, movie_lib_ids: list[int], show_lib_ids: list[int], lang: str, ) -> list[dict]: """The person's TMDB "Known for" credits (most-voted first) that are IN our library, as cards, in that order, at most _KNOWN_FOR_SHOWN. Matched by the canonical guid `tmdb:`; out-of-library credits are dropped.""" if not known_for: return [] # Match each credit to a library row by guid, bucketed by media_type (movie ids and tv ids collide # numerically) and scoped to the enabled libraries — the shared helper owns that collision-safe # logic (the detail-page recs use the same one). movies, shows = plex_tmdb.resolve_library_guids( db, known_for, movie_lib_ids=movie_lib_ids, show_lib_ids=show_lib_ids ) m_states = rollup.item_state_map(db, uid, [m.id for m in movies.values()]) show_statuses = rollup.state_map(db, uid, [s.id for s in shows.values()]) out: list[dict] = [] for k in known_for: g = f"tmdb:{k.get('tmdb_id')}" # A credit resolves against its OWN media_type's bucket only. if k.get("media_type") == "tv": if g in shows: out.append(show_card(shows[g], show_statuses.get(shows[g].id, SHOW_NEW), lang=lang)) elif g in movies: out.append(movie_card(movies[g], m_states.get(movies[g].id), lang=lang)) return out[:_KNOWN_FOR_SHOWN] @router.get("/people/cards") def people_cards( names: str, scope: str = "both", user: User = Depends(current_user), db: Session = Depends(get_db), ) -> dict: """Cards for the actor filter-chips currently applied: each name + its cached headshot + how many movies/shows (in the given scope) feature them. Photos come from the plex_people cache (populated as items are rich-fetched — info-page view + the rich re-sync); counts are live against cast_names. A name with no cached photo yet still returns a card (the UI shows a placeholder).""" wanted = split_csv(names)[:16] if not wanted: return {"people": []} movie_lib_ids, show_lib_ids = content_libs(db) want_movies = scope in ("movie", "both") and bool(movie_lib_ids) want_shows = scope in ("show", "both") and bool(show_lib_ids) photos = queries.person_photos(db, wanted) movies = movie_lib_ids if want_movies else [] shows = show_lib_ids if want_shows else [] out = [ {"name": nm, "photo": photos.get(nm), "count": queries.cast_count(db, nm, movies, shows)} for nm in wanted ] return {"people": out} # Cap each filmography section — a prolific person shouldn't return an unbounded list the client then # mounts a card per row for (the grid paginates at PAGE; this page renders all at once). Ample for a # personal library; the most-recent titles win via the year-desc order. _PERSON_SECTION_MAX = 200 # A person's bio is enriched at most once per this window: it dedups concurrent opens of the same person # (each would otherwise schedule its own 8s TMDB task) AND rate-limits re-triggering when TMDB is # down/slow (a transient failure leaves tmdb_enriched_at NULL, so without this every reload would spawn a # fresh task and pile up on the shared threadpool). In-process + best-effort: a restart just clears it, at # worst costing a few extra fetches. A successful enrich stamps the watermark, so the reservation only # ever expires harmlessly. _ENRICH_COOLDOWN_S = 60.0 _enrich_inflight: dict[int, float] = {} _enrich_lock = threading.Lock() def _should_schedule_enrich(person_id: int) -> bool: """True (and reserves a cooldown) if this person isn't already being enriched / recently attempted.""" now = time.monotonic() with _enrich_lock: deadline = _enrich_inflight.get(person_id) if deadline is not None and now < deadline: return False _enrich_inflight[person_id] = now + _ENRICH_COOLDOWN_S # Bound the map: drop expired reservations once it grows (a large library has many people). if len(_enrich_inflight) > 1024: for pid in [p for p, d in _enrich_inflight.items() if d <= now]: del _enrich_inflight[pid] return True @router.get("/person/{name}") def person_detail( name: str, background_tasks: BackgroundTasks, lang: str = "en", user: User = Depends(current_user), db: Session = Depends(get_db), ) -> dict: """One cast/crew member's filmography: their cached headshot + the movies and shows (in the enabled libraries) whose cast OR directors include this name — the inverse of the cast-name → library-filter link. The name string is the identity key (Plex cast carries no stable per-person id), so distinct people who share a name share a page. Each section is capped at _PERSON_SECTION_MAX. An unknown name simply returns empty sections. The first time a page is opened, the person's TMDB bio + "Known for" credits are lazily fetched (from the linked `tmdb_person_id`) and persisted, then served from the row on every open. The fetch runs OFF the request path (a background task); the first open serves whatever's in the row with `enriching` set, and the page asks again until the bio lands. The people_enrich job fetches everyone ahead of time, so this lazy path is only for a person the job hasn't reached yet. """ lang = norm_lang(lang) person = queries.person(db, name) # Lazy one-time bio enrich, scheduled AFTER the response so the TMDB call is never on the serve path. # Gated by a per-person cooldown so concurrent/rapid opens (or repeated opens while TMDB is degraded) # can't pile background tasks onto the shared threadpool. # `enriching` tells the page the bio is on its way: it asks again shortly instead of showing # an empty page until the next open. True while a fetch is pending, including one an earlier open # already reserved. enriching = ( person is not None and bool(person.tmdb_person_id) and person.tmdb_enriched_at is None and bool(sysconfig.get_str(db, "tmdb_api_key")) ) if enriching and person is not None and _should_schedule_enrich(person.id): background_tasks.add_task(service.enrich_person_bg, person.id) movie_lib_ids, show_lib_ids = content_libs(db) movies: list[dict] = [] if movie_lib_ids: items = queries.filmography(db, "movie", name, movie_lib_ids, lang, _PERSON_SECTION_MAX) states = rollup.item_state_map(db, user.id, [it.id for it in items]) movies = [movie_card(it, states.get(it.id), lang=lang) for it in items] shows: list[dict] = [] if show_lib_ids: show_rows = queries.filmography(db, "show", name, show_lib_ids, lang, _PERSON_SECTION_MAX) statuses = rollup.state_map(db, user.id, [s.id for s in show_rows]) shows = [show_card(sh, statuses.get(sh.id, SHOW_NEW), lang=lang) for sh in show_rows] known_for = _resolve_known_for( db, person.known_for if person else None, user.id, movie_lib_ids, show_lib_ids, lang ) return { "name": name, "photo": person.photo_thumb if person else None, # The Hungarian biography for a Hungarian reader, the instance-language one when TMDB has none. "biography": ((person.biography_hu if lang == "hu" else None) or person.biography) if person else None, "birthday": person.birthday if person else None, "deathday": person.deathday if person else None, "place_of_birth": person.place_of_birth if person else None, "known_for_department": person.known_for_department if person else None, "also_known_as": (person.also_known_as if person else None) or [], "known_for": known_for, "enriching": enriching, "movies": movies, "shows": shows, }