MusicIndexer/main.py
Шурупов Илья Викторович 48bf84bcb7 Track Spotify origin (liked/playlist/top); make top tracks opt-in; clean Ctrl+C
- Tag each Spotify track with its origin (liked / from_playlist / from_top,
  combinable) so genuinely-saved tracks are distinguishable from ones only
  surfaced by the top-tracks endpoint.
- Top tracks are no longer added by default (they inflated "missing" with
  unowned listening stats). --include-top pulls them as full objects so they
  carry an ISRC for real ID matching.
- On --spotify-full, prune Spotify rows that are neither liked nor in a
  playlist (top-only / orphaned), cleaning an existing DB in one pass.
- Cached-ingest fallback honours include_top and prunes too.
- In-place SQLite migration adds the new columns (no DB rebuild needed).
- Ctrl+C exits cleanly (130) with a message instead of a traceback;
  incremental progress is already committed, so re-run to continue.
- Surface origin breakdown in the fetch log, match summary, and GUI.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-16 00:42:44 +03:00

95 lines
3.2 KiB
Python

"""MusicIndexer CLI. Two main workflows plus granular helpers.
python main.py fetch # do all the work: pull + scan + parse + enrich + match
python main.py display # open the GUI to see what you're missing
`fetch` is incremental and DB-backed (see Env.py): the first run is slow
(initial scan + MusicBrainz lookups), later runs only touch what changed.
Helpers: `enrich` (resume MBID resolution), `match` (print the summary).
"""
import argparse
import logging
import sys
def _setup_logging():
logging.basicConfig(level=logging.INFO, format="%(message)s")
def cmd_fetch(args):
_setup_logging()
from src.workflows import run_fetch
run_fetch(enrich_limit=args.enrich_limit, enrich=not args.no_enrich,
spotify_full=args.spotify_full, include_top=args.include_top)
def cmd_display(args):
from src.workflows import run_display
run_display()
def cmd_enrich(args):
_setup_logging()
from src.db.database import init_db
from src.enrich.mbid import resolve_mbids, unresolved_count
init_db()
print(f"unresolved before: {unresolved_count(args.source)}")
print(f"resolved this run: {resolve_mbids(limit=args.limit, source=args.source)}")
print(f"unresolved after: {unresolved_count(args.source)}")
def cmd_match(args):
import json
from src.match.matcher import summary
print(json.dumps(summary(), indent=2))
def build_parser():
parser = argparse.ArgumentParser(prog="musicindexer", description=__doc__)
sub = parser.add_subparsers(dest="cmd", required=True)
fetch = sub.add_parser("fetch", help="incrementally fetch + scan + enrich + match")
fetch.add_argument("--enrich-limit", type=int, default=None,
help="cap MBID lookups this run (default: resolve all)")
fetch.add_argument("--no-enrich", action="store_true",
help="skip MusicBrainz enrichment; use MBIDs already on tracks")
fetch.add_argument("--spotify-full", action="store_true",
help="force a full Spotify resync (ignore snapshot/watermark)")
fetch.add_argument("--include-top", action="store_true",
help="also pull the top-tracks endpoint (off by default; "
"with --spotify-full, top-only tracks are otherwise pruned)")
sub.add_parser("display", help="open the Streamlit GUI")
enrich = sub.add_parser("enrich", help="resume MBID resolution only")
enrich.add_argument("--limit", type=int, default=None)
enrich.add_argument("--source", choices=["spotify", "itunes", "local"], default=None)
sub.add_parser("match", help="print present/missing summary")
return parser
def main():
args = build_parser().parse_args()
try:
{
"fetch": cmd_fetch,
"display": cmd_display,
"enrich": cmd_enrich,
"match": cmd_match,
}[args.cmd](args)
except KeyboardInterrupt:
# Ctrl+C: stop cleanly, no traceback. Work already committed is kept
# (each step writes incrementally), so just re-run to continue.
print("\ninterrupted — partial progress saved; re-run to continue.",
file=sys.stderr)
sys.exit(130)
if __name__ == "__main__":
main()