"""Bulk auto-merge wysokocrediblowych pending merge_candidates.

Strategia: pending kandydaci scena↔scena spełniający WSZYSTKIE:
  - score >= 0.85
  - cross-source: jeden bok ma TPDB ref, drugi ma StashDB ref (źródła zaufane)
  - studio match: oba scenes mają studio_id i są równe (lub oba NULL — rzadko)
  - data pasuje: |release_date_left - release_date_right| <= 7 dni
                 (lub jedna strona ma NULL date i druga też — wtedy pomijamy bo niepewne)

Side keep: preferuje TPDB (więcej metadanych: studio aliases, performers, dłuższe descs).
Jeśli oba mają TPDB lub oba mają StashDB → keep_left (deterministyczne).

Reżim:
  python bulk_auto_merge.py [--dry-run] [--score-min 0.85] [--max N]

Run z VPS:
  docker cp scripts/bulk_auto_merge.py goon-api-1:/tmp/
  docker exec goon-api-1 python /tmp/bulk_auto_merge.py [args]
"""
from __future__ import annotations

import argparse
import logging
import sys
from datetime import timedelta

from sqlalchemy import select
from sqlalchemy.orm import Session

from app.db import session_scope
from app.models.merge_candidate import MergeCandidate, MergeKind, MergeStatus
from app.models.scene import Scene, ScenePerformer, SceneExternalRef
from app.models.source import Source, SourceKind
from app.resolve.scene_merge import MergeError, resolve_candidate

log = logging.getLogger("bulk_auto_merge")


def main() -> None:
    parser = argparse.ArgumentParser()
    parser.add_argument("--dry-run", action="store_true")
    parser.add_argument("--score-min", type=float, default=0.85)
    parser.add_argument("--date-window-days", type=int, default=7)
    parser.add_argument("--max", type=int, default=10000)
    parser.add_argument(
        "--allow-same-source-above",
        type=float,
        default=None,
        help="Score >= X auto-merge regardless of cross-source (np. 0.95 dla perfect fingerprint)",
    )
    parser.add_argument(
        "--include-pornapp",
        action="store_true",
        help=(
            "Akceptuj canon (TPDB|StashDB) ↔ pornapp jako cross-source. Pomija twardy "
            "studio match (porn-app tube != canonical studio). Wymaga ≥1 wspólnego "
            "performera (jeśli oba mają) i title_fuzzy >= --min-title-fuzzy."
        ),
    )
    parser.add_argument(
        "--min-title-fuzzy",
        type=float,
        default=0.7,
        help=(
            "Min token_set_ratio dla canon↔pornapp (default 0.7). Bypass dla score≥0.95 "
            "(fingerprint/external_id match — tytuły mogą się różnić bo tube SEO != studio)."
        ),
    )
    parser.add_argument(
        "--max-duration-diff-sec",
        type=int,
        default=30,
        help=(
            "Max różnica duration_sec między canon i pornapp dla auto-merge (default 30s). "
            "Bez tego scen z tym samym performerem dostają 0.91+ score nawet gdy są różne "
            "(np. 35min VR vs 8min anal). Bypass: score≥0.95."
        ),
    )
    args = parser.parse_args()

    logging.basicConfig(level=logging.INFO, format="%(asctime)s %(levelname)s %(message)s")

    with session_scope() as s:
        # Pull all pending scene candidates above threshold
        cands = (
            s.execute(
                select(MergeCandidate)
                .where(MergeCandidate.status == MergeStatus.pending)
                .where(MergeCandidate.kind == MergeKind.scene)
                .where(MergeCandidate.score >= args.score_min)
                .order_by(MergeCandidate.score.desc())
                .limit(args.max)
            )
            .scalars()
            .all()
        )
        log.info("pending candidates >= %.2f: %d", args.score_min, len(cands))

        # Pre-fetch source kinds for left/right scenes (TPDB vs StashDB vs scraper)
        scene_ids = {c.left_id for c in cands} | {c.right_id for c in cands}
        kinds_per_scene: dict = {}
        for sid, kind in s.execute(
            select(SceneExternalRef.scene_id, Source.kind)
            .join(Source, Source.id == SceneExternalRef.source_id)
            .where(SceneExternalRef.scene_id.in_(scene_ids))
        ):
            kinds_per_scene.setdefault(sid, set()).add(kind)

        # Pre-fetch scene meta (studio_id, release_date, duration_sec)
        scene_meta: dict = {}
        for sid, studio_id, rel_date, dur in s.execute(
            select(Scene.id, Scene.studio_id, Scene.release_date, Scene.duration_sec)
            .where(Scene.id.in_(scene_ids))
        ):
            scene_meta[sid] = (studio_id, rel_date, dur)

        # Pre-fetch performer sets per scene (for overlap check w canon↔pornapp).
        perf_per_scene: dict = {}
        for sid, pid in s.execute(
            select(ScenePerformer.scene_id, ScenePerformer.performer_id)
            .where(ScenePerformer.scene_id.in_(scene_ids))
        ):
            perf_per_scene.setdefault(sid, set()).add(pid)

        # Pre-fetch title_normalized for fuzzy check.
        title_per_scene: dict = {}
        for sid, tnorm in s.execute(
            select(Scene.id, Scene.title_normalized).where(Scene.id.in_(scene_ids))
        ):
            title_per_scene[sid] = tnorm or ""

    counters = {
        "merged": 0,
        "merged_canon_pornapp": 0,
        "skip_score": 0,
        "skip_not_cross_source": 0,
        "skip_studio_mismatch": 0,
        "skip_date_mismatch": 0,
        "skip_no_performer_overlap": 0,
        "skip_low_title_fuzzy": 0,
        "skip_duration_mismatch": 0,
        "skip_duration_unknown": 0,
        "skip_missing_meta": 0,
        "errored": 0,
    }
    window = timedelta(days=args.date_window_days)
    from rapidfuzz import fuzz

    for c in cands:
        l_kinds = kinds_per_scene.get(c.left_id, set())
        r_kinds = kinds_per_scene.get(c.right_id, set())
        l_has_tpdb = SourceKind.tpdb in l_kinds
        l_has_stash = SourceKind.stashdb in l_kinds
        l_has_pa = SourceKind.scraper in l_kinds
        r_has_tpdb = SourceKind.tpdb in r_kinds
        r_has_stash = SourceKind.stashdb in r_kinds
        r_has_pa = SourceKind.scraper in r_kinds
        l_canon = l_has_tpdb or l_has_stash
        r_canon = r_has_tpdb or r_has_stash
        # 3 typy cross-source:
        #   1. canon↔canon (TPDB↔StashDB) — original mode
        #   2. canon↔pornapp — z --include-pornapp; pornapp side dziedziczy tagi z canon
        #   3. allow-same-source-above bypass dla bardzo wysokich score (fingerprint match)
        canon_canon = (l_has_tpdb and r_has_stash) or (l_has_stash and r_has_tpdb)
        canon_pa = (
            args.include_pornapp
            and ((l_canon and r_has_pa and not r_canon) or (r_canon and l_has_pa and not l_canon))
        )
        bypass = (
            args.allow_same_source_above is not None
            and c.score >= args.allow_same_source_above
        )
        if not canon_canon and not canon_pa and not bypass:
            counters["skip_not_cross_source"] += 1
            continue

        l_meta = scene_meta.get(c.left_id)
        r_meta = scene_meta.get(c.right_id)
        if not l_meta or not r_meta:
            counters["skip_missing_meta"] += 1
            continue
        l_studio, l_date, l_dur = l_meta
        r_studio, r_date, r_dur = r_meta

        if canon_pa:
            # canon↔pornapp: studio + date NIE są informatywne (pornapp daje tube name
            # jako studio, typowo brak release_date). Zamiast tego:
            #
            #   1. ≥1 wspólny performer (jeśli oba mają)
            #   2. duration ±N sekund — KLUCZOWE bo scoring.py boostuje score do 0.91+
            #      przez performer+title-tokens nawet gdy to różne sceny tego samego
            #      performera (np. 7 różnych Lena Paul scen na 1 canonical → 7 false pos).
            #      Duration to twardy fizyczny sygnał: dwie te same sceny mają tę samą
            #      długość. 35min VR scena vs 8min anal scena → różne sceny.
            #   3. title fuzzy ≥ --min-title-fuzzy (bypass score≥0.95)
            #
            # Bypass wszystkich sanity gdy score ≥ 0.95 (to wtedy fingerprint/external_id
            # match, sygnał wyższego rzędu niż heurystyki).
            if c.score < 0.95:
                l_perfs = perf_per_scene.get(c.left_id, set())
                r_perfs = perf_per_scene.get(c.right_id, set())
                if l_perfs and r_perfs and not (l_perfs & r_perfs):
                    counters["skip_no_performer_overlap"] += 1
                    continue
                # Duration check — wymaga znanej duration po obu stronach. Brak duration
                # → reject (nie umiemy bezpiecznie zdecydować).
                if l_dur is None or r_dur is None:
                    counters["skip_duration_unknown"] += 1
                    continue
                if abs(l_dur - r_dur) > args.max_duration_diff_sec:
                    counters["skip_duration_mismatch"] += 1
                    continue
                ltitle = title_per_scene.get(c.left_id, "")
                rtitle = title_per_scene.get(c.right_id, "")
                if ltitle and rtitle:
                    title_fuzz = fuzz.token_set_ratio(ltitle, rtitle) / 100.0
                    if title_fuzz < args.min_title_fuzzy:
                        counters["skip_low_title_fuzzy"] += 1
                        continue
            keep_left = l_canon
        else:
            # canon↔canon (TPDB↔StashDB) lub bypass: standardowe sanity checks.
            if l_studio is None or r_studio is None or l_studio != r_studio:
                counters["skip_studio_mismatch"] += 1
                continue
            if l_date is None or r_date is None:
                counters["skip_date_mismatch"] += 1
                continue
            if abs((l_date - r_date).days) > args.date_window_days:
                counters["skip_date_mismatch"] += 1
                continue
            # TPDB preferowany (więcej metadanych); inaczej keep_left.
            if l_has_tpdb and not r_has_tpdb:
                keep_left = True
            elif r_has_tpdb and not l_has_tpdb:
                keep_left = False
            else:
                keep_left = True

        if args.dry_run:
            counters["merged"] += 1
            if canon_pa:
                counters["merged_canon_pornapp"] += 1
            continue

        try:
            with session_scope() as s:
                resolve_candidate(
                    s,
                    candidate_id=c.id,
                    action="merge",
                    keep_left=keep_left,
                    resolved_by="bulk_auto_merge",
                )
            counters["merged"] += 1
            if canon_pa:
                counters["merged_canon_pornapp"] += 1
            if counters["merged"] % 100 == 0:
                log.info("progress merged=%d", counters["merged"])
        except (MergeError, Exception) as e:
            counters["errored"] += 1
            log.warning("merge %s failed: %s", c.id, e)

    log.info("done: %s", counters)


if __name__ == "__main__":
    main()