soulsync/core/wishlist/processing.py

"""Wishlist processing helpers."""

from __future__ import annotations

import uuid
from dataclasses import dataclass
from datetime import datetime
from contextlib import AbstractContextManager
from types import SimpleNamespace
from typing import Any, Callable, Dict

from core.wishlist.payloads import build_failed_track_wishlist_context
from core.wishlist.selection import filter_wishlist_tracks_by_category, sanitize_and_dedupe_wishlist_tracks
from core.wishlist.service import get_wishlist_service
from core.wishlist.state import get_wishlist_cycle, set_wishlist_cycle
from utils.logging_config import get_logger


module_logger = get_logger("wishlist.processing")
logger = module_logger


# Album-bundle is wasteful for single-track wishlist items (downloads
# the entire album to claim one file), so the bundle path only engages
# when an album has ``N`` or more missing tracks in the wishlist. Default
# 2 catches the "this user is missing several tracks from one album"
# case while keeping single-track-per-album items on the cheaper
# per-track flow. Configurable via ``wishlist.album_bundle_min_tracks``
# for users who want different behaviour.
_DEFAULT_ALBUM_BUNDLE_MIN_TRACKS = 2


def _resolve_album_bundle_threshold() -> int:
    """Return the configured min-tracks-per-album threshold for the
    wishlist album-bundle grouper. Falls back to the default when the
    config key is missing or carries garbage — same defensive shape as
    the rest of the config-driven knobs in core/."""
    try:
        from config.settings import config_manager
        raw = config_manager.get('wishlist.album_bundle_min_tracks',
                                 _DEFAULT_ALBUM_BUNDLE_MIN_TRACKS)
        value = int(raw)
        if value >= 1:
            return value
    except Exception:  # noqa: S110 — defensive config-read fallback; uses default below
        pass
    return _DEFAULT_ALBUM_BUNDLE_MIN_TRACKS


@dataclass
class WishlistAutoProcessingRuntime:
    """Dependencies needed to run automatic wishlist processing outside the controller."""

    processing_guard: Callable[[], AbstractContextManager[bool]]
    is_actually_processing: Callable[[], bool]
    app_context_factory: Callable[[], AbstractContextManager[Any]]
    get_profiles_database: Callable[[], Any]
    get_music_database: Callable[[], Any]
    download_batches: Dict[str, Dict[str, Any]]
    tasks_lock: Any
    update_automation_progress: Callable[..., Any]
    automation_engine: Any
    missing_download_executor: Any
    run_full_missing_tracks_process: Callable[[str, str, list[dict[str, Any]]], Any]
    get_batch_max_concurrent: Callable[[], int]
    get_active_server: Callable[[], str]
    current_time_fn: Callable[[], float]
    profile_id: int = 1
    logger: Any = module_logger


def remove_completed_tracks_from_wishlist(
    batch: Dict[str, Any],
    download_tasks: Dict[str, Dict[str, Any]],
    remove_from_wishlist: Callable[[Dict[str, Any]], Any],
    *,
    logger=logger,
) -> int:
    """Remove completed batch tasks from the wishlist."""
    removed_count = 0
    for task_id in batch.get('queue', []):
        if task_id in download_tasks:
            task = download_tasks[task_id]
            if task.get('status') == 'completed':
                try:
                    track_info = task.get('track_info', {})
                    context = {'track_info': track_info, 'original_search_result': track_info}
                    remove_from_wishlist(context)
                    removed_count += 1
                except Exception as exc:
                    logger.error(f"[Wishlist Processing] Error removing completed track from wishlist: {exc}")
    return removed_count


def add_cancelled_tracks_to_failed_tracks(
    batch: Dict[str, Any],
    download_tasks: Dict[str, Dict[str, Any]],
    permanently_failed_tracks: list[Dict[str, Any]],
    *,
    logger=logger,
    max_process: int = 100,
) -> int:
    """Promote cancelled-but-missing tasks into the failed-track list."""
    cancelled_tracks = batch.get('cancelled_tracks', set())
    if not cancelled_tracks:
        return 0

    processed_count = 0
    for task_id in batch.get('queue', [])[:max_process]:
        if task_id not in download_tasks:
            continue
        task = download_tasks[task_id]
        track_index = task.get('track_index', 0)
        if track_index not in cancelled_tracks:
            continue

        if task.get('status', 'unknown') == 'completed':
            continue

        original_track_info = task.get('track_info', {})
        cancelled_track_info = build_failed_track_wishlist_context(
            original_track_info,
            track_index=track_index,
            retry_count=0,
            failure_reason='Download cancelled',
            candidates=task.get('cached_candidates', []),
        )

        if any(t.get('table_index') == track_index for t in permanently_failed_tracks):
            continue

        permanently_failed_tracks.append(cancelled_track_info)
        processed_count += 1
        logger.error(
            f"[Wishlist Processing] Added cancelled missing track {cancelled_track_info['track_name']} to failed list for wishlist"
        )

    return processed_count


def recover_uncaptured_failed_tracks(
    batch: Dict[str, Any],
    download_tasks: Dict[str, Dict[str, Any]],
    permanently_failed_tracks: list[Dict[str, Any]],
    *,
    logger=logger,
) -> int:
    """Recover tasks force-marked failed/not_found so wishlist processing does not skip them."""
    recovered_count = 0
    for task_id in batch.get('queue', []):
        if task_id not in download_tasks:
            continue
        task = download_tasks[task_id]
        if task.get('status') not in ('failed', 'not_found'):
            continue

        track_index = task.get('track_index', 0)
        if any(t.get('table_index') == track_index for t in permanently_failed_tracks):
            continue

        original_track_info = task.get('track_info', {})
        recovered_track_info = build_failed_track_wishlist_context(
            original_track_info,
            track_index=track_index,
            retry_count=task.get('retry_count', 0),
            failure_reason=task.get('error_message', 'Download failed'),
            candidates=task.get('cached_candidates', []),
        )
        permanently_failed_tracks.append(recovered_track_info)
        recovered_count += 1
        logger.error(
            f"[Wishlist Processing] Recovered uncaptured failed track for wishlist: {recovered_track_info['track_name']}"
        )

    return recovered_count


def resolve_wishlist_source_type_for_batch(batch: Dict[str, Any]) -> str:
    """Pick the wishlist ``source_type`` for failed tracks coming out of a
    download batch.

    Album-context batches must produce ``'album'`` provenance — the legacy
    hardcoded ``'playlist'`` mislabels every album-batch failure, breaks
    the wishlist UI's source filter, and makes ``by_source_type`` stats
    look like all wishlist work came from playlists.
    """
    return 'album' if batch.get('is_album_download') else 'playlist'


def build_wishlist_source_context(batch: Dict[str, Any], current_time: datetime | None = None) -> Dict[str, Any]:
    """Build the source_context payload used when adding failed tracks back to the wishlist."""
    current_time = current_time or datetime.now()
    context = {
        'playlist_name': batch.get('playlist_name', 'Unknown Playlist'),
        'playlist_id': batch.get('playlist_id', None),
        'added_from': 'webui_modal',
        'timestamp': current_time.isoformat(),
    }
    # Preserve album-batch provenance so wishlist requeue has a real signal
    # for album-vs-single routing instead of relying on per-track album dicts
    # that may have been mangled by reconstruction fallbacks.
    if batch.get('is_album_download'):
        context['is_album_download'] = True
        album_ctx = batch.get('album_context')
        if isinstance(album_ctx, dict):
            context['album_context'] = album_ctx
        artist_ctx = batch.get('artist_context')
        if isinstance(artist_ctx, dict):
            context['artist_context'] = artist_ctx
    return context


def _wishlist_run_has_siblings_still_active(
    download_batches: Dict[str, Dict[str, Any]],
    run_id: str,
    completing_batch_id: str,
) -> bool:
    """Return True if any sibling batch sharing ``run_id`` is still
    pre-terminal.

    Used by ``finalize_auto_wishlist_completion`` to gate the run-
    level cycle toggle. The caller already holds ``tasks_lock``.

    The completing batch may or may not have its phase flipped to
    'complete' yet by the time we land here; either way we skip it
    in the sibling scan since we're handling its completion now."""
    terminal_phases = {'complete', 'error', 'cancelled'}
    for sibling_id, sibling in download_batches.items():
        if sibling_id == completing_batch_id:
            continue
        if not isinstance(sibling, dict):
            continue
        if sibling.get('wishlist_run_id') != run_id:
            continue
        if sibling.get('phase') in terminal_phases:
            continue
        return True
    return False


def finalize_auto_wishlist_completion(
    batch_id: str,
    completion_summary: Dict[str, Any],
    *,
    download_batches: Dict[str, Dict[str, Any]],
    tasks_lock,
    reset_processing_state: Callable[[], None],
    add_activity_item: Callable[[Any, Any, Any, Any], Any],
    automation_engine,
    db_factory: Callable[[], Any],
    logger=logger,
) -> Dict[str, Any]:
    """Finalize auto wishlist processing after a batch finishes.

    For wishlist runs that split into multiple sub-batches (Phase
    1c.2.1: per-album bundle dispatch), the cycle toggle + state
    reset only fire when the LAST sibling sub-batch of the same
    ``wishlist_run_id`` completes. Earlier completions just record
    their per-batch summary and return without toggling.

    Back-compat: legacy single-batch runs (no ``wishlist_run_id``
    field on the batch) keep the original toggle-immediately
    behavior — the gate treats a missing run_id as "lone batch"."""
    tracks_added = completion_summary.get('tracks_added', 0)
    total_failed = completion_summary.get('total_failed', 0)
    logger.error(
        f"[Auto-Wishlist] Background processing complete: {tracks_added} added to wishlist, {total_failed} failed"
    )

    if tracks_added > 0:
        add_activity_item("", "Wishlist Updated", f"{tracks_added} failed tracks added to wishlist", "Now")

    # Run-level gate: if siblings of the same wishlist run are still
    # active, defer cycle toggle + state reset until they finish.
    with tasks_lock:
        run_id = ''
        if batch_id in download_batches:
            run_id = download_batches[batch_id].get('wishlist_run_id') or ''
        siblings_active = bool(run_id) and _wishlist_run_has_siblings_still_active(
            download_batches, run_id, batch_id,
        )
    if siblings_active:
        logger.info(
            f"[Auto-Wishlist] Sub-batch {batch_id[:8]} done; waiting on sibling sub-batches "
            f"of run {run_id[:8]} before toggling cycle"
        )
        return completion_summary

    try:
        with tasks_lock:
            if batch_id in download_batches:
                current_cycle = download_batches[batch_id].get('current_cycle', 'albums')
            else:
                current_cycle = 'albums'

        next_cycle = 'singles' if current_cycle == 'albums' else 'albums'

        db = db_factory()
        with db._get_connection() as conn:
            cursor = conn.cursor()
            cursor.execute(
                """
                    INSERT OR REPLACE INTO metadata (key, value, updated_at)
                    VALUES ('wishlist_cycle', ?, CURRENT_TIMESTAMP)
                """,
                (next_cycle,),
            )
            conn.commit()

        logger.info(f"[Auto-Wishlist] Cycle toggled after completion: {current_cycle} → {next_cycle}")
    except Exception as cycle_error:
        logger.error(f"[Auto-Wishlist] Error toggling cycle: {cycle_error}")

    reset_processing_state()

    try:
        if automation_engine:
            automation_engine.emit('wishlist_processing_completed', {
                'tracks_processed': str(total_failed),
                'tracks_found': str(tracks_added),
                'tracks_failed': str(total_failed - tracks_added),
            })
    except Exception as e:
        logger.debug("emit wishlist_processing_completed failed: %s", e)

    return completion_summary


def remove_tracks_already_in_library(
    wishlist_service,
    profiles_database,
    music_database,
    active_server: str,
    *,
    logger=logger,
    skip_track_fn: Callable[[dict[str, Any]], bool] | None = None,
    log_prefix: str = "[Auto-Wishlist]",
) -> int:
    """Remove wishlist entries that are already present in the library."""
    from core.library import manual_library_match as _mlm

    all_profiles = profiles_database.get_all_profiles()
    # Carry (profile_id, track) so the match check can be profile-scoped.
    cleanup_tracks: list[tuple[int, dict]] = []
    for profile in all_profiles:
        pid = profile["id"]
        for t in wishlist_service.get_wishlist_tracks_for_download(profile_id=pid):
            cleanup_tracks.append((pid, t))

    cleanup_removed = 0
    for profile_id, track in cleanup_tracks:
        if skip_track_fn and skip_track_fn(track):
            continue

        track_name = track.get('name', '')
        artists = track.get('artists', [])
        spotify_track_id = track.get('spotify_track_id') or track.get('id')
        track_album = track.get('album', {}).get('name') if isinstance(track.get('album'), dict) else track.get('album')

        if not track_name or not artists or not spotify_track_id:
            continue

        # Manual match check — skip fuzzy search if user already linked this track.
        if _mlm.get_match_for_track(music_database, profile_id, track, default_source='wishlist'):
            try:
                removed = wishlist_service.mark_track_download_result(spotify_track_id, success=True)
                if removed:
                    cleanup_removed += 1
                    logger.info(f"{log_prefix} [Manual Match] Skipped already-matched track: '{track_name}'")
            except Exception as _mlm_err:
                logger.error(f"{log_prefix} [Manual Match] Error removing track: {_mlm_err}")
            continue

        found_in_db = False
        matched_artist_name = ''
        for artist in artists:
            if isinstance(artist, str):
                artist_name = artist
            elif isinstance(artist, dict) and 'name' in artist:
                artist_name = artist['name']
            else:
                artist_name = str(artist)

            try:
                db_track, confidence = music_database.check_track_exists(
                    track_name,
                    artist_name,
                    confidence_threshold=0.7,
                    server_source=active_server,
                    album=track_album,
                )

                if db_track and confidence >= 0.7:
                    found_in_db = True
                    matched_artist_name = artist_name
                    break
            except Exception:
                continue

        if found_in_db:
            try:
                removed = wishlist_service.mark_track_download_result(spotify_track_id, success=True)
                if removed:
                    cleanup_removed += 1
                    logger.info(f"{log_prefix} Removed already-owned track: '{track_name}' by {matched_artist_name or artist_name}")
            except Exception as remove_error:
                logger.error(f"{log_prefix} Error removing track from wishlist: {remove_error}")

    return cleanup_removed


@dataclass
class WishlistManualDownloadRuntime:
    """Dependencies needed to start a manual wishlist download batch outside the controller."""

    get_music_database: Callable[[], Any]
    download_batches: Dict[str, Dict[str, Any]]
    tasks_lock: Any
    missing_download_executor: Any
    run_full_missing_tracks_process: Callable[[str, str, list[dict[str, Any]]], Any]
    get_batch_max_concurrent: Callable[[], int]
    add_activity_item: Callable[[Any, Any, Any, Any], Any]
    active_server: str
    profile_id: int
    logger: Any = module_logger


def start_manual_wishlist_download_batch(
    runtime: WishlistManualDownloadRuntime,
    *,
    track_ids=None,
    category: str | None = None,
    force_download_all: bool = False,
) -> tuple[Dict[str, Any], int]:
    """Submit a manual wishlist batch.

    The batch entry is created synchronously so the frontend can start polling
    status immediately. The slow library-cleanup pass and master-worker hand-off
    run in the background, freeing the request handler from a 30s+ block on
    per-track DB checks for large wishlists.
    """
    logger = runtime.logger

    try:
        batch_id = str(uuid.uuid4())
        playlist_id = "wishlist"
        playlist_name = "Wishlist"

        with runtime.tasks_lock:
            runtime.download_batches[batch_id] = {
                'phase': 'analysis',
                'playlist_id': playlist_id,
                'playlist_name': playlist_name,
                'queue': [],
                'active_count': 0,
                'max_concurrent': runtime.get_batch_max_concurrent(),
                'queue_index': 0,
                # analysis_total starts at 0; the bg job updates it after cleanup
                # finishes and the real track count is known.
                'analysis_total': 0,
                'analysis_processed': 0,
                'analysis_results': [],
                'permanently_failed_tracks': [],
                'cancelled_tracks': set(),
                'force_download_all': True,
                'profile_id': runtime.profile_id,
            }

        runtime.missing_download_executor.submit(
            _prepare_and_run_manual_wishlist_batch,
            runtime,
            batch_id,
            track_ids,
            category,
        )

        return {"success": True, "batch_id": batch_id}, 200

    except Exception as e:
        logger.error(f"Error starting wishlist download process: {e}")
        import traceback

        traceback.print_exc()
        return {"success": False, "error": str(e)}, 500


def _prepare_and_run_manual_wishlist_batch(
    runtime: WishlistManualDownloadRuntime,
    batch_id: str,
    track_ids,
    category: str | None,
) -> None:
    """Background worker for the manual wishlist batch — does the slow cleanup
    + sanitize + filter + master-worker hand-off off the request thread."""
    logger = runtime.logger

    try:
        wishlist_service = get_wishlist_service()
        db = runtime.get_music_database()
        manual_profile_id = runtime.profile_id

        logger.warning("[Manual-Wishlist] Cleaning duplicate tracks before download...")
        duplicates_removed = db.remove_wishlist_duplicates(profile_id=manual_profile_id)
        if duplicates_removed > 0:
            logger.warning(f"[Manual-Wishlist] Removed {duplicates_removed} duplicate tracks")

        # NOTE: We deliberately do NOT call remove_tracks_already_in_library here.
        # Wishlist tracks are already known-missing (force_download_all=True is set on
        # the batch). The library check duplicates the work the master worker would
        # skip, and on large wishlists costs ~1s per track in serial DB lookups.
        # The standalone /api/wishlist/cleanup endpoint still runs that pass when
        # users explicitly ask for maintenance.

        raw_wishlist_tracks = wishlist_service.get_wishlist_tracks_for_download(profile_id=manual_profile_id)
        if not raw_wishlist_tracks:
            logger.warning("[Manual-Wishlist] No tracks in wishlist after cleanup — marking batch complete")
            with runtime.tasks_lock:
                if batch_id in runtime.download_batches:
                    runtime.download_batches[batch_id]['phase'] = 'complete'
                    runtime.download_batches[batch_id]['error'] = 'No tracks in wishlist'
            return

        wishlist_tracks, duplicates_found = sanitize_and_dedupe_wishlist_tracks(raw_wishlist_tracks)
        if duplicates_found > 0:
            logger.warning(f"[Manual-Wishlist] Found and removed {duplicates_found} duplicate tracks during sanitization")
        logger.info(f"[Manual-Wishlist] Sanitized {len(wishlist_tracks)} tracks from wishlist service")

        if track_ids:
            track_lookup = {}
            for track in wishlist_tracks:
                spotify_track_id = track.get('spotify_track_id') or track.get('id')
                if spotify_track_id and spotify_track_id not in track_lookup:
                    track_lookup[spotify_track_id] = track

            filtered_tracks = []
            seen_track_ids = set()
            for frontend_index, tid in enumerate(track_ids):
                if tid in track_lookup and tid not in seen_track_ids:
                    track = track_lookup[tid]
                    track['_original_index'] = frontend_index
                    filtered_tracks.append(track)
                    seen_track_ids.add(tid)

            wishlist_tracks = filtered_tracks
            logger.info(f"[Manual-Wishlist] Filtered to {len(wishlist_tracks)} specific tracks by ID (preserving frontend display order)")
        elif category:
            wishlist_tracks, _ = filter_wishlist_tracks_by_category(wishlist_tracks, category)
            logger.info(f"[Manual-Wishlist] Filtered to {len(wishlist_tracks)} tracks for category: {category}")

        for i, track in enumerate(wishlist_tracks):
            track['_original_index'] = i

        runtime.add_activity_item("", "Wishlist Download Started", f"{len(wishlist_tracks)} tracks", "Now")

        # Try to split into per-album sub-batches so each album fires
        # ONE slskd / torrent / usenet album-bundle search (gates on
        # ``is_album_download`` + populated album/artist context).
        # When a single category was requested (or no category filter)
        # we apply the same grouping the auto-wishlist path uses.
        # Tracks the grouper can't bucket fall through to a residual
        # batch with the classic per-track flow.
        from core.wishlist.album_grouping import group_wishlist_tracks_by_album
        grouping = group_wishlist_tracks_by_album(
            wishlist_tracks,
            min_tracks_per_album=_resolve_album_bundle_threshold(),
        )

        # Build the final payload list (batch_id, tracks, album_context,
        # artist_context, is_album). The first payload re-uses the
        # caller-allocated ``batch_id`` so the frontend's existing poll
        # against it keeps working. Subsequent payloads get fresh ids.
        payloads = []
        for group in grouping.album_groups:
            payloads.append({
                'tracks': group.tracks,
                'is_album': True,
                'album_context': group.album_context,
                'artist_context': group.artist_context,
                'display_name': f"Wishlist (Album: {group.album_context.get('name', 'Unknown')})",
            })
        if grouping.residual_tracks:
            payloads.append({
                'tracks': grouping.residual_tracks,
                'is_album': False,
                'album_context': None,
                'artist_context': None,
                'display_name': "Wishlist (Residual)",
            })

        if not payloads:
            # Nothing to download — clear out the original batch.
            with runtime.tasks_lock:
                if batch_id in runtime.download_batches:
                    runtime.download_batches[batch_id]['analysis_total'] = 0
                    runtime.download_batches[batch_id]['phase'] = 'complete'
            return

        # Attach the original batch_id to the first payload; allocate
        # fresh batch_ids for the rest.
        payloads[0]['batch_id'] = batch_id
        for payload in payloads[1:]:
            payload['batch_id'] = str(uuid.uuid4())

        # Reify "wishlist run" — one shared id stamped on every sub-
        # batch this manual invocation produces. Mirrors the auto
        # path. Note manual wishlist completion currently doesn't
        # toggle the cycle (only auto does), but the id is set anyway
        # so future code + UI grouping have a consistent hook.
        wishlist_run_id = str(uuid.uuid4())

        # Materialize each sub-batch's row state up-front so the
        # frontend's polling can see them all under the original
        # batch's flow.
        with runtime.tasks_lock:
            if batch_id in runtime.download_batches:
                # Re-purpose the existing row for the first payload.
                first = payloads[0]
                runtime.download_batches[batch_id]['analysis_total'] = len(first['tracks'])
                runtime.download_batches[batch_id]['wishlist_run_id'] = wishlist_run_id
                if first['is_album']:
                    runtime.download_batches[batch_id]['is_album_download'] = True
                    runtime.download_batches[batch_id]['album_context'] = first['album_context']
                    runtime.download_batches[batch_id]['artist_context'] = first['artist_context']
                runtime.download_batches[batch_id]['playlist_name'] = first['display_name']
            for payload in payloads[1:]:
                runtime.download_batches[payload['batch_id']] = {
                    'phase': 'analysis',
                    'playlist_id': 'wishlist',
                    'playlist_name': payload['display_name'],
                    'queue': [],
                    'active_count': 0,
                    'max_concurrent': runtime.get_batch_max_concurrent(),
                    'queue_index': 0,
                    'analysis_total': len(payload['tracks']),
                    'analysis_processed': 0,
                    'analysis_results': [],
                    'permanently_failed_tracks': [],
                    'cancelled_tracks': set(),
                    'force_download_all': True,
                    'profile_id': runtime.profile_id,
                    'is_album_download': bool(payload['is_album']),
                    'album_context': payload['album_context'],
                    'artist_context': payload['artist_context'],
                    'wishlist_run_id': wishlist_run_id,
                }

        logger.info(
            f"[Manual-Wishlist] Split into {len(payloads)} sub-batch(es) "
            f"({sum(1 for p in payloads if p['is_album'])} album + "
            f"{sum(1 for p in payloads if not p['is_album'])} residual)"
        )
        # Serial dispatch — each album-bundle search happens one at a
        # time so the slskd / Prowlarr pipeline doesn't fan out across
        # multiple parallel release searches.
        for payload in payloads:
            label = (
                f"album '{payload['album_context'].get('name')}'"
                if payload['is_album'] else 'residual per-track'
            )
            logger.info(
                f"[Manual-Wishlist] Running sub-batch {payload['batch_id']} "
                f"({label}, {len(payload['tracks'])} tracks)"
            )
            runtime.run_full_missing_tracks_process(
                payload['batch_id'], "wishlist", payload['tracks'],
            )

    except Exception as exc:
        logger.error(f"Error preparing manual wishlist batch {batch_id}: {exc}")
        import traceback

        traceback.print_exc()
        with runtime.tasks_lock:
            if batch_id in runtime.download_batches:
                runtime.download_batches[batch_id]['phase'] = 'error'
                runtime.download_batches[batch_id]['error'] = str(exc)


def cleanup_wishlist_against_library(
    wishlist_service,
    music_database,
    profile_id: int,
    active_server: str,
    *,
    logger=logger,
) -> tuple[Dict[str, Any], int]:
    """Remove wishlist tracks that already exist in the library for one profile."""
    try:
        logger.info("[Wishlist Cleanup] Starting wishlist cleanup process...")

        wishlist_tracks = wishlist_service.get_wishlist_tracks_for_download(profile_id=profile_id)
        if not wishlist_tracks:
            return {"success": True, "message": "No tracks in wishlist to clean up", "removed_count": 0}, 200

        logger.info(f"[Wishlist Cleanup] Found {len(wishlist_tracks)} tracks in wishlist")

        removed_count = remove_tracks_already_in_library(
            wishlist_service,
            SimpleNamespace(get_all_profiles=lambda: [{"id": profile_id}]),
            music_database,
            active_server,
            logger=logger,
            log_prefix="[Wishlist Cleanup]",
        )

        logger.info(f"[Wishlist Cleanup] Completed cleanup: {removed_count} tracks removed from wishlist")
        return {
            "success": True,
            "message": f"Wishlist cleanup completed: {removed_count} tracks removed",
            "removed_count": removed_count,
            "processed_count": len(wishlist_tracks),
        }, 200

    except Exception as e:
        logger.error(f"Error in wishlist cleanup: {e}")
        import traceback

        traceback.print_exc()
        return {"success": False, "error": str(e)}, 500


def process_wishlist_automatically(runtime: WishlistAutoProcessingRuntime, automation_id=None):
    """Run automatic wishlist processing outside the controller."""
    logger = runtime.logger
    logger.info("[Auto-Wishlist] Timer triggered - starting automatic wishlist processing...")

    try:
        # CRITICAL FIX: Use smart stuck detection BEFORE acquiring lock
        # This prevents deadlock and handles stuck flags (2-hour timeout)
        if runtime.is_actually_processing():
            logger.info("[Auto-Wishlist] Already processing (verified with stuck detection), skipping.")
            return

        with runtime.processing_guard() as acquired:
            if not acquired:
                logger.info("[Auto-Wishlist] Already processing (race condition check), skipping.")
                return

            with runtime.app_context_factory():
                wishlist_service = get_wishlist_service()

                # Check if wishlist has tracks across all profiles
                database = runtime.get_profiles_database()
                all_profiles = database.get_all_profiles()
                count = sum(wishlist_service.get_wishlist_count(profile_id=p['id']) for p in all_profiles)
                logger.info(f"[Auto-Wishlist] Wishlist count check: {count} tracks found across {len(all_profiles)} profiles")
                runtime.update_automation_progress(automation_id, progress=10, phase='Checking wishlist',
                                                   log_line=f'{count} tracks across {len(all_profiles)} profiles', log_type='info')
                if count == 0:
                    logger.warning("ℹ️ [Auto-Wishlist] No tracks in wishlist for auto-processing.")
                    return

                logger.info(f"[Auto-Wishlist] Found {count} tracks in wishlist, starting automatic processing...")

                # Check if wishlist processing is already active (auto or manual)
                playlist_id = "wishlist"
                with runtime.tasks_lock:
                    for _batch_id, batch_data in runtime.download_batches.items():
                        batch_playlist_id = batch_data.get('playlist_id')
                        # Check for both auto ('wishlist') and manual ('wishlist_manual') batches
                        if (batch_playlist_id in ['wishlist', 'wishlist_manual'] and
                            batch_data.get('phase') not in ['complete', 'error', 'cancelled']):
                            logger.info(f"Wishlist processing already active in another batch ({batch_playlist_id}), skipping automatic start")
                            return

                # CRITICAL: Clean duplicates BEFORE fetching tracks to prevent count mismatches
                # This prevents the "11 tracks shown but 12 counted" bug
                music_database = runtime.get_music_database()

                logger.warning("[Auto-Wishlist] Cleaning duplicate tracks before processing...")
                for profile in all_profiles:
                    duplicates_removed = music_database.remove_wishlist_duplicates(profile_id=profile['id'])
                    if duplicates_removed > 0:
                        logger.warning(f"[Auto-Wishlist] Removed {duplicates_removed} duplicate tracks from profile {profile['id']}")

                # NOTE: We deliberately do NOT call remove_tracks_already_in_library here.
                # The batch sets force_download_all=True (see comment a few lines below),
                # so wishlist tracks are treated as known-missing and the master worker
                # skips per-track library lookups. Doing the same expensive scan here
                # before submitting the batch defeats that optimization and adds
                # ~1s per track in serial DB queries. The standalone
                # /api/wishlist/cleanup endpoint still exposes that pass for users
                # who want explicit maintenance.
                runtime.update_automation_progress(automation_id, progress=25, phase='Preparing wishlist',
                                                   log_line='Skipped library scan — wishlist tracks treated as known-missing',
                                                   log_type='info')

                # Get wishlist tracks for processing - combine all profiles
                raw_wishlist_tracks = []
                for profile in all_profiles:
                    raw_wishlist_tracks.extend(wishlist_service.get_wishlist_tracks_for_download(profile_id=profile['id']))
                if not raw_wishlist_tracks:
                    logger.warning("No tracks returned from wishlist service.")
                    return

                # SANITIZE: Ensure consistent data format from wishlist service
                wishlist_tracks, duplicates_found = sanitize_and_dedupe_wishlist_tracks(raw_wishlist_tracks)
                if duplicates_found > 0:
                    logger.warning(f"[Auto-Wishlist] Found and removed {duplicates_found} duplicate tracks during sanitization")
                logger.info(f"[Auto-Wishlist] Sanitized {len(wishlist_tracks)} tracks from wishlist service")

                # CYCLE FILTERING: Get current cycle and filter tracks by category
                current_cycle = get_wishlist_cycle(lambda: music_database)

                # Filter tracks by current cycle category
                filtered_tracks, _ = filter_wishlist_tracks_by_category(wishlist_tracks, current_cycle)

                logger.info(f"[Auto-Wishlist] Current cycle: {current_cycle}")
                logger.info(f"[Auto-Wishlist] Filtered {len(filtered_tracks)}/{len(wishlist_tracks)} tracks for '{current_cycle}' category")
                runtime.update_automation_progress(automation_id, progress=40, phase=f'Processing {current_cycle}',
                                                   log_line=f'Cycle: {current_cycle} — {len(filtered_tracks)} tracks to process', log_type='info')

                # If no tracks in this category, skip to next cycle immediately
                if len(filtered_tracks) == 0:
                    logger.warning(f"ℹ️ [Auto-Wishlist] No {current_cycle} tracks in wishlist, toggling cycle and scheduling next run")

                    # Toggle cycle
                    next_cycle = 'singles' if current_cycle == 'albums' else 'albums'
                    set_wishlist_cycle(lambda: music_database, next_cycle)
                    logger.info(f"[Auto-Wishlist] Cycle toggled: {current_cycle} → {next_cycle}")
                    return

                # Use filtered tracks for processing — stamp original index
                wishlist_tracks = filtered_tracks
                for i, track in enumerate(wishlist_tracks):
                    track['_original_index'] = i

                # When the cycle is 'albums', try to split the wishlist
                # into per-album sub-batches so each album fires ONE
                # album-bundle search (slskd / torrent / usenet) instead
                # of N per-track searches. Residual tracks (no resolvable
                # album metadata) fall through to a normal per-track
                # batch. Singles cycle keeps its original single-batch
                # shape — Spotify already classifies them away from
                # albums.
                _submitted_batches: list[str] = []
                if current_cycle == 'albums':
                    from core.wishlist.album_grouping import group_wishlist_tracks_by_album
                    grouping = group_wishlist_tracks_by_album(
                        wishlist_tracks,
                        min_tracks_per_album=_resolve_album_bundle_threshold(),
                    )
                else:
                    grouping = None

                # Reify "wishlist run" — one shared id stamped on every
                # sub-batch this invocation produces. The completion
                # handler uses it to gate the once-per-run cycle toggle
                # (so it doesn't fire N times for N sub-batches).
                wishlist_run_id = str(uuid.uuid4())

                if grouping and grouping.album_groups:
                    for album_idx, group in enumerate(grouping.album_groups):
                        album_batch_id = str(uuid.uuid4())
                        album_batch_name = (
                            f"Wishlist (Auto - Album: {group.album_context.get('name', 'Unknown')})"
                        )
                        with runtime.tasks_lock:
                            runtime.download_batches[album_batch_id] = {
                                'phase': 'analysis',
                                'playlist_id': playlist_id,
                                'playlist_name': album_batch_name,
                                'queue': [],
                                'active_count': 0,
                                'max_concurrent': runtime.get_batch_max_concurrent(),
                                'queue_index': 0,
                                'analysis_total': len(group.tracks),
                                'analysis_processed': 0,
                                'analysis_results': [],
                                'permanently_failed_tracks': [],
                                'cancelled_tracks': set(),
                                'force_download_all': True,
                                'auto_initiated': True,
                                'auto_processing_timestamp': runtime.current_time_fn(),
                                'current_cycle': current_cycle,
                                'profile_id': runtime.profile_id,
                                # Album-bundle dispatch gate reads these
                                # three. With them set, the master worker
                                # routes through slskd / torrent / usenet
                                # album-bundle search instead of per-track.
                                'is_album_download': True,
                                'album_context': group.album_context,
                                'artist_context': group.artist_context,
                                'wishlist_run_id': wishlist_run_id,
                            }
                        logger.info(
                            f"[Auto-Wishlist] Album sub-batch {album_idx + 1}/{len(grouping.album_groups)}: "
                            f"'{group.album_context.get('name')}' by '{group.artist_context.get('name')}' "
                            f"({len(group.tracks)} tracks) → {album_batch_id} [run {wishlist_run_id[:8]}]"
                        )
                        _submitted_batches.append(album_batch_id)
                        runtime.missing_download_executor.submit(
                            runtime.run_full_missing_tracks_process,
                            album_batch_id, playlist_id, group.tracks,
                        )

                # Residual tracks (no album group could be formed, OR
                # singles cycle): one classic per-track batch as before.
                residual_tracks = (
                    grouping.residual_tracks if grouping is not None else wishlist_tracks
                )
                if residual_tracks:
                    batch_id = str(uuid.uuid4())
                    playlist_name = f"Wishlist (Auto - {current_cycle.capitalize()})"
                    with runtime.tasks_lock:
                        runtime.download_batches[batch_id] = {
                            'phase': 'analysis',
                            'playlist_id': playlist_id,
                            'playlist_name': playlist_name,
                            'queue': [],
                            'active_count': 0,
                            'max_concurrent': runtime.get_batch_max_concurrent(),
                            'queue_index': 0,
                            'analysis_total': len(residual_tracks),
                            'analysis_processed': 0,
                            'analysis_results': [],
                            'permanently_failed_tracks': [],
                            'cancelled_tracks': set(),
                            'force_download_all': True,
                            'auto_initiated': True,
                            'auto_processing_timestamp': runtime.current_time_fn(),
                            'current_cycle': current_cycle,
                            'profile_id': runtime.profile_id,
                            'wishlist_run_id': wishlist_run_id,
                        }
                    _submitted_batches.append(batch_id)
                    runtime.missing_download_executor.submit(
                        runtime.run_full_missing_tracks_process,
                        batch_id, playlist_id, residual_tracks,
                    )
                    logger.info(
                        f"Starting wishlist residual batch {batch_id} with {len(residual_tracks)} tracks "
                        f"({'singles' if current_cycle == 'singles' else 'unbucketed albums'}) "
                        f"[run {wishlist_run_id[:8]}]"
                    )

                _summary_parts: list[str] = []
                if grouping and grouping.album_groups:
                    _summary_parts.append(f"{len(grouping.album_groups)} album batch(es)")
                if residual_tracks:
                    _summary_parts.append(f"{len(residual_tracks)} per-track")
                _summary_text = ', '.join(_summary_parts) or 'no batches'
                runtime.update_automation_progress(
                    automation_id, progress=50,
                    phase=f'Downloading {len(wishlist_tracks)} tracks',
                    log_line=f'Started: {_summary_text} for cycle {current_cycle}',
                    log_type='success',
                )

    except Exception as e:
        logger.error(f"Error in automatic wishlist processing: {e}")
        import traceback

        traceback.print_exc()
        runtime.update_automation_progress(automation_id, log_line=f'Error: {str(e)}', log_type='error')
        raise


def automatic_wishlist_cleanup_after_db_update(
    *,
    wishlist_service=None,
    profiles_database=None,
    music_database=None,
    active_server: str | None = None,
    logger=logger,
) -> int:
    """Remove wishlist entries that already exist in the library after a DB update."""
    try:
        from config.settings import config_manager
        from database.music_database import MusicDatabase, get_database

        wishlist_service = wishlist_service or get_wishlist_service()
        profiles_database = profiles_database or get_database()
        music_database = music_database or MusicDatabase()
        active_server = active_server or config_manager.get_active_media_server()

        logger.info("[Auto Cleanup] Starting automatic wishlist cleanup after database update...")

        all_profiles = profiles_database.get_all_profiles()
        wishlist_tracks = []
        for profile in all_profiles:
            wishlist_tracks.extend(wishlist_service.get_wishlist_tracks_for_download(profile_id=profile["id"]))

        if not wishlist_tracks:
            logger.warning("[Auto Cleanup] No tracks in wishlist to clean up")
            return 0

        logger.info(f"[Auto Cleanup] Found {len(wishlist_tracks)} tracks in wishlist")

        removed_count = remove_tracks_already_in_library(
            wishlist_service,
            profiles_database,
            music_database,
            active_server,
            logger=logger,
            log_prefix="[Auto Cleanup]",
        )

        logger.info(f"[Auto Cleanup] Completed automatic cleanup: {removed_count} tracks removed from wishlist")
        return removed_count

    except Exception as e:
        logger.error(f"[Auto Cleanup] Error in automatic wishlist cleanup: {e}")
        import traceback

        traceback.print_exc()
        return 0


__all__ = [
    "remove_completed_tracks_from_wishlist",
    "add_cancelled_tracks_to_failed_tracks",
    "recover_uncaptured_failed_tracks",
    "build_wishlist_source_context",
    "finalize_auto_wishlist_completion",
    "automatic_wishlist_cleanup_after_db_update",
    "WishlistAutoProcessingRuntime",
    "WishlistManualDownloadRuntime",
    "process_wishlist_automatically",
    "start_manual_wishlist_download_batch",
    "cleanup_wishlist_against_library",
    "remove_tracks_already_in_library",
]