Replace the JSON-file pipeline with a SQLite/SQLAlchemy store (Postgres via
DATABASE_URL) and an incremental, ID-based matcher whose goal is "which
Spotify/iTunes tracks am I missing locally".
- src/db: models (Track/MbCache/FileState/IngestState) + engine/session.
- src/ingest: upsert prefetched spotify/itunes/local (work_dir/latest-1) by
(source, source_id); pulls ISRC from raw Spotify; preserves enrichment.
- src/enrich: MusicBrainz recording-MBID resolver. Resolves via NORMALIZED
text search (so the same song across sources lands on one MBID + one cached
lookup), ISRC as exact fallback. Only touches unresolved tracks, caches
positive AND negative results, rate-limited and resumable.
- src/match: normalization + cross-source matcher with tiers ISRC > MBID >
normalized text; reports present/missing and the match method.
- main.py: CLI (ingest / enrich / match). Gui.py: missing-tracks viewer.
- README + requirements (SQLAlchemy, musicbrainzngs); ignore *.db.
Incremental everywhere: re-running updates only what changed; enrich continues
where it stopped. Live Spotify/local backends are left intact.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
- Env.py now reads SPOTIFY_CLIENT_ID/SPOTIFY_CLIENT_SECRET (and optional
path overrides) from the environment instead of hardcoding them.
- Add .env.example and ignore .env / .venv.
- Rewrite README with setup, usage and layout (drops the leaked secret).
Note: secrets are also purged from prior history in this push.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
