Follow-up to the prior compilation-album scanner fix. That patch
made the scanner read `tracks.track_artist` (per-track artist
column) via COALESCE so compilation tracks would compare against
the right value. But tracks downloaded BEFORE the `track_artist`
column existed have track_artist=NULL — COALESCE falls back to
album artist (the curator) and the wrong-comparison case returns.
Fix: explicit 3-tier resolution in `_scan_file`:
1. DB `tracks.track_artist` if populated → trust it. Respects
manual edits from the enhanced library view (user who curated
the DB value but didn't re-tag the file gets their edit
respected, not overridden by stale file tag).
2. File's ARTIST tag via mutagen if present → use it. Tidal /
Spotify / Deezer all write the per-track artist into the
audio file at download time regardless of SoulSync's DB
schema, so it's ground truth even when the DB column is
stale or NULL. File is already open for fingerprinting so
mutagen tag-read is essentially free.
3. Album artist → final fallback for files without proper ARTIST
tags AND no DB track_artist. Existing pre-fix behavior.
`_load_db_tracks` SELECT now surfaces `track_artist` (raw, may be
empty/NULL via NULLIF) and `album_artist` separately in addition
to the COALESCE'd `artist` field — so `_scan_file` can tell the
difference between 'DB has a curated value' and 'DB fell back to
album artist'. Without this distinction, the file-tag fallback
would create false positives when DB is curated but file is stale.
5 new tests (11 total in the file) pin:
- File-tag-trumps-DB resolves the legacy NULL case (DB says
'Andromedik' (album curator), file says 'Eclypse', AcoustID
says 'Eclypse' → no flag)
- Tag-missing falls back to album artist (preserves existing
genuine-mismatch contract — file without tag + AcoustID
mismatch still flags)
- Mutagen exception swallowed (debug log, fall-through)
- File-tag matches DB → no behavioral change
- DB curated value trumps stale file tag (false-positive guard
— user edited DB without re-tagging file shouldn't get flagged)
Two existing test fixtures (`_make_context` callers) updated to
the new 10-column row shape.
SQL behavior verified empirically against real SQLite: NULL and
empty-string both flow through NULLIF → None in Python →
file-tag-fallback path. Modern populated values trump file tag.
416 lines
18 KiB
Python
416 lines
18 KiB
Python
"""AcoustID Scanner Job — fingerprints library tracks to detect wrong downloads.
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Scans the entire library (not just Transfer) by resolving DB file paths to
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actual files on disk. Creates actionable findings that can be fixed:
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- 'retag': Update DB metadata to match what the file actually is
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- 'redownload': Add the expected track to wishlist and delete the wrong file
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- 'delete': Remove the wrong file and its DB record
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"""
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import os
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import re
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from difflib import SequenceMatcher
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from typing import Optional
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from core.repair_jobs import register_job
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from core.repair_jobs.base import JobContext, JobResult, RepairJob
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from utils.logging_config import get_logger
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logger = get_logger("repair_job.acoustid")
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AUDIO_EXTENSIONS = {'.mp3', '.flac', '.ogg', '.opus', '.m4a', '.aac', '.wav', '.wma', '.aiff', '.aif'}
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@register_job
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class AcoustIDScannerJob(RepairJob):
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job_id = 'acoustid_scanner'
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display_name = 'AcoustID Scanner'
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description = 'Fingerprints library tracks to detect wrong downloads'
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help_text = (
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'Scans your music library by fingerprinting audio files and comparing '
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'them against the AcoustID database. Detects cases where the wrong song '
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'was downloaded — even if the filename and tags look correct.\n\n'
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'When a mismatch is found, you can:\n'
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'• Retag — update the DB record to match the actual audio content\n'
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'• Redownload — add the correct track to your wishlist and remove the wrong file\n'
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'• Delete — remove the wrong file entirely\n\n'
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'The job processes tracks in batches with checkpointing so it resumes '
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'where it left off across runs. Requires an AcoustID API key (Settings).\n\n'
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'Settings:\n'
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'- Fingerprint Threshold: Minimum AcoustID match confidence (0.0–1.0)\n'
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'- Title Similarity: How closely the identified title must match\n'
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'- Artist Similarity: How closely the identified artist must match\n'
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'- Batch Size: Tracks per scan run (checkpoint saved between batches)'
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)
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icon = 'repair-icon-acoustid'
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default_enabled = True
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default_interval_hours = 24
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default_settings = {
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'fingerprint_threshold': 0.80,
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'title_similarity': 0.70,
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'artist_similarity': 0.60,
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'batch_size': 200,
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}
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auto_fix = False # User chooses fix action per finding
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def scan(self, context: JobContext) -> JobResult:
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result = JobResult()
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settings = self._get_settings(context)
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fp_threshold = settings.get('fingerprint_threshold', 0.80)
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title_threshold = settings.get('title_similarity', 0.70)
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artist_threshold = settings.get('artist_similarity', 0.60)
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batch_size = settings.get('batch_size', 200)
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# Get AcoustID client
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acoustid_client = context.acoustid_client
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if not acoustid_client:
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try:
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from core.acoustid_client import AcoustIDClient
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acoustid_client = AcoustIDClient()
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except Exception as e:
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logger.warning("AcoustID client not available: %s", e)
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return result
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# Load all library tracks from DB with their file paths
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db_tracks = self._load_db_tracks(context)
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if not db_tracks:
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logger.info("No library tracks with file paths found")
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return result
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# Read checkpoint (last processed track ID) to resume from
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checkpoint_id = None
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if context.config_manager:
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checkpoint_id = context.config_manager.get(
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f'repair.jobs.{self.job_id}.checkpoint_id', None
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)
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if checkpoint_id is not None:
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checkpoint_id = str(checkpoint_id)
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# Build ordered list of (track_id, info) sorted by ID for deterministic order
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track_list = sorted(db_tracks.items(), key=lambda x: str(x[0]))
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# Skip past checkpoint if resuming
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if checkpoint_id is not None:
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original_len = len(track_list)
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track_list = [(tid, info) for tid, info in track_list if str(tid) > checkpoint_id]
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if len(track_list) < original_len:
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logger.info("Resuming AcoustID scan from checkpoint ID %s (%d tracks remaining)",
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checkpoint_id, len(track_list))
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total = len(track_list)
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if context.report_progress:
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context.report_progress(phase=f'Scanning {total} library tracks...', total=total)
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if context.update_progress:
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context.update_progress(0, total)
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batch_count = 0
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for i, (track_id, track_info) in enumerate(track_list):
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if context.check_stop():
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self._save_checkpoint_id(context, track_id)
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return result
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if i % 10 == 0 and context.wait_if_paused():
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self._save_checkpoint_id(context, track_id)
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return result
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# Resolve the DB path to an actual file on disk
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file_path = track_info.get('file_path', '')
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resolved = self._resolve_path(file_path, context)
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if not resolved:
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result.skipped += 1
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continue
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result.scanned += 1
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batch_count += 1
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fname = os.path.basename(resolved)
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if context.report_progress:
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context.report_progress(
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scanned=i + 1, total=total,
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phase=f'Fingerprinting {i + 1} / {total}',
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log_line=f'Scanning: {fname}',
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log_type='info'
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)
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try:
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self._scan_file(
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resolved, track_id, track_info, acoustid_client, context, result,
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fp_threshold, title_threshold, artist_threshold
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)
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except Exception as e:
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logger.debug("Error scanning %s: %s", fname, e)
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result.errors += 1
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# Rate limit: pause between batches to avoid hammering AcoustID API
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if batch_count >= batch_size:
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batch_count = 0
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self._save_checkpoint_id(context, track_id)
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if context.sleep_or_stop(2):
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return result
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if context.update_progress and (i + 1) % 10 == 0:
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context.update_progress(i + 1, total)
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# Clear checkpoint on full completion
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self._save_checkpoint_id(context, None)
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if context.update_progress:
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context.update_progress(total, total)
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logger.info("AcoustID scan: %d scanned, %d skipped, %d mismatches, %d errors",
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result.scanned, result.skipped, result.findings_created, result.errors)
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return result
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def _scan_file(self, fpath, track_id, expected, acoustid_client, context, result,
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fp_threshold, title_threshold, artist_threshold):
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"""Fingerprint a single file and check for mismatches."""
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fname = os.path.basename(fpath)
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# Fingerprint the file
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try:
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fp_result = acoustid_client.fingerprint_and_lookup(fpath)
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except Exception as e:
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logger.debug("Fingerprint failed for %s: %s", fname, e)
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result.errors += 1
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if context.report_progress:
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context.report_progress(log_line=f'Error: {fname} — {e}', log_type='error')
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return
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if not fp_result or not fp_result.get('recordings'):
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if context.report_progress:
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context.report_progress(log_line=f'No match: {fname}', log_type='skip')
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return
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best_score = fp_result.get('best_score', 0)
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if best_score < fp_threshold:
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return
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best_recording = fp_result['recordings'][0]
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aid_title = best_recording.get('title', '')
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aid_artist = best_recording.get('artist', '')
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if not aid_title:
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return
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# Resolve which artist value to compare against, in priority order:
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# 1. DB `track_artist` (per-track, manually curated or scanner-
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# populated) — trust it when populated. Respects user edits
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# from the enhanced library view.
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# 2. File's ARTIST tag — ground truth for what's on disk.
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# Catches legacy compilation tracks where `track_artist`
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# column is NULL because they were downloaded before that
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# column existed; the file itself has the correct per-
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# track artist (Tidal/Spotify/Deezer all write it).
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# 3. Album artist — final fallback for files without proper
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# ARTIST tags AND no DB track_artist.
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track_artist = (expected.get('track_artist') or '').strip()
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if track_artist:
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expected_artist = track_artist
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else:
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file_artist = None
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try:
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from core.tag_writer import read_file_tags
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file_tags = read_file_tags(fpath)
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file_artist = (file_tags.get('artist') or '').strip() or None
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except Exception as e:
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logger.debug("file-tag artist read failed for %s: %s", fname, e)
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expected_artist = (
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file_artist
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or (expected.get('album_artist') or '').strip()
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or expected['artist']
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)
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# Normalize and compare
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norm_expected_title = _normalize(expected['title'])
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norm_aid_title = _normalize(aid_title)
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norm_expected_artist = _normalize(expected_artist)
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norm_aid_artist = _normalize(aid_artist)
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title_sim = SequenceMatcher(None, norm_expected_title, norm_aid_title).ratio()
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# Issue (Foxxify Discord report): AcoustID returns the FULL artist
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# credit (e.g. `Okayracer, aldrch & poptropicaslutz!`) while the
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# library DB carries only the primary artist (`Okayracer`). Raw
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# similarity scores ~43% — well below threshold — so multi-artist
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# tracks get flagged as Wrong Song even though the primary IS in
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# the credit. Route through the shared `artist_names_match` helper
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# which splits the credit on common separators (comma, ampersand,
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# feat./ft./with/vs., etc.) and checks each token. Primary-in-
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# credit cases now resolve at 100% match instead of 43%.
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#
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# Pass RAW artist strings (not pre-normalised) so the splitter
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# can recognise the separators. The helper applies its own
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# case + whitespace normalisation internally per token.
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if norm_expected_artist:
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from core.matching.artist_aliases import artist_names_match
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_, artist_sim = artist_names_match(
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expected_artist,
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aid_artist,
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threshold=artist_threshold,
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)
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else:
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artist_sim = 1.0
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if title_sim >= title_threshold and artist_sim >= artist_threshold:
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return
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# Mismatch detected
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if context.report_progress:
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context.report_progress(
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log_line=f'Mismatch: {fname} — expected "{expected["title"]}", got "{aid_title}"',
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log_type='error'
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)
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if context.create_finding:
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severity = 'warning' if best_score >= 0.90 else 'info'
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inserted = context.create_finding(
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job_id=self.job_id,
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finding_type='acoustid_mismatch',
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severity=severity,
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entity_type='track',
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entity_id=str(track_id),
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file_path=fpath,
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title=f'Wrong download: "{expected["title"]}" is actually "{aid_title}"',
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description=(
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f'Expected "{expected["title"]}" by {expected_artist}, '
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f'but audio fingerprint matches "{aid_title}" by {aid_artist} '
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f'(fingerprint: {best_score:.0%}, title match: {title_sim:.0%}, '
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f'artist match: {artist_sim:.0%})'
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),
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details={
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'expected_title': expected['title'],
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'expected_artist': expected_artist,
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'acoustid_title': aid_title,
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'acoustid_artist': aid_artist,
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'fingerprint_score': round(best_score, 3),
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'title_similarity': round(title_sim, 3),
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'artist_similarity': round(artist_sim, 3),
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'album_thumb_url': expected.get('album_thumb_url'),
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'artist_thumb_url': expected.get('artist_thumb_url'),
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'album_title': expected.get('album_title', ''),
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'track_number': expected.get('track_number'),
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}
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)
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if inserted:
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result.findings_created += 1
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else:
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result.findings_skipped_dedup += 1
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def _load_db_tracks(self, context: JobContext) -> dict:
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"""Load all tracks from DB keyed by track ID."""
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tracks = {}
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conn = None
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try:
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conn = context.db._get_connection()
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cursor = conn.cursor()
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# Discord report (Skowl): compilation albums like "High Tea
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# Music: Vol 1" have a different artist per track but the
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# `tracks.artist_id` foreign key points at the ALBUM artist
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# (curator / label-name applied to every track). AcoustID
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# returns the actual per-track artist → 12% similarity →
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# Wrong Song flag. Fix: prefer `tracks.track_artist` (the
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# per-track artist, populated by every server-scan + auto-
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# import path when different from album artist) and fall
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# back to the album artist only when the per-track column
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# is NULL or empty (legacy rows / single-artist albums).
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# Load `track_artist` (raw, may be empty) AND `album_artist`
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# separately so `_scan_file` can tell the difference between
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# 'DB has a curated per-track value' and 'DB fell back to
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# album artist'. The COALESCE'd `artist` field is kept as a
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# convenience for the existing `expected['artist']` consumers
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# that want a single resolved value, but the resolution
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# priority that actually drives the comparison is reproduced
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# in `_scan_file`: track_artist → file tag → album_artist.
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cursor.execute("""
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SELECT t.id, t.title,
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COALESCE(NULLIF(t.track_artist, ''), ar.name) AS artist,
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t.file_path, t.track_number,
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al.title AS album_title, al.thumb_url, ar.thumb_url,
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NULLIF(t.track_artist, '') AS track_artist,
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ar.name AS album_artist
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FROM tracks t
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LEFT JOIN artists ar ON ar.id = t.artist_id
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LEFT JOIN albums al ON al.id = t.album_id
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WHERE t.file_path IS NOT NULL AND t.file_path != ''
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AND t.title IS NOT NULL AND t.title != ''
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""")
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for row in cursor.fetchall():
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track_id = row[0]
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if track_id is None:
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logger.warning(
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"Skipping track row with null ID while loading AcoustID scan candidates: %s",
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row[3] or "<unknown file>",
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)
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continue
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track_id = str(track_id)
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tracks[track_id] = {
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'title': row[1] or '',
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'artist': row[2] or '',
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'file_path': row[3] or '',
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'track_number': row[4],
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'album_title': row[5] or '',
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'album_thumb_url': row[6] or None,
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'artist_thumb_url': row[7] or None,
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'track_artist': row[8] or '', # raw (may be empty)
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'album_artist': row[9] or '',
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}
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except Exception as e:
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logger.error("Error loading tracks from DB: %s", e)
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finally:
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if conn:
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conn.close()
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return tracks
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def _resolve_path(self, file_path, context):
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"""Resolve a DB file path to an actual file on disk."""
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if not file_path:
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return None
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if os.path.exists(file_path):
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return file_path
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# Use the shared library-path resolver — picks up
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# library.music_paths and Plex library locations too.
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from core.library.path_resolver import resolve_library_file_path
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return resolve_library_file_path(
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file_path,
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transfer_folder=context.transfer_folder,
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config_manager=context.config_manager,
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)
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def _save_checkpoint_id(self, context: JobContext, track_id):
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"""Save or clear the scan checkpoint by track ID."""
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if context.config_manager:
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context.config_manager.set(
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f'repair.jobs.{self.job_id}.checkpoint_id', track_id
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)
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def _get_settings(self, context: JobContext) -> dict:
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if not context.config_manager:
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return self.default_settings.copy()
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cfg = context.config_manager.get(f'repair.jobs.{self.job_id}.settings', {})
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merged = self.default_settings.copy()
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merged.update(cfg)
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return merged
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def estimate_scope(self, context: JobContext) -> int:
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conn = None
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try:
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conn = context.db._get_connection()
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cursor = conn.cursor()
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cursor.execute("""
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SELECT COUNT(*) FROM tracks
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WHERE file_path IS NOT NULL AND file_path != ''
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AND title IS NOT NULL AND title != ''
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""")
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return cursor.fetchone()[0]
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except Exception:
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return 0
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finally:
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if conn:
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conn.close()
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def _normalize(text: str) -> str:
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t = text.lower()
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t = re.sub(r'\(.*?\)', '', t)
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t = re.sub(r'\[.*?\]', '', t)
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t = re.sub(r'[^a-z0-9 ]', '', t)
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return t.strip()
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