feat: auto-discover similar tracks during autoplay via Last.fm/MusicBrainz
Every Nth autoplay pick (configurable via discover_ratio), query Last.fm for similar tracks. When Last.fm has no key or returns nothing, fall back to MusicBrainz tag-based recording search (no API key needed). Discovered tracks are resolved via yt-dlp and deduplicated within the session. If discovery fails, the kept-deck shuffle continues as before. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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118
plugins/_musicbrainz.py
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118
plugins/_musicbrainz.py
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"""MusicBrainz API helper for music discovery fallback.
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Private module (underscore prefix) -- plugin loader skips it.
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All functions are blocking; callers should run them in an executor.
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"""
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from __future__ import annotations
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import json
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import logging
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import time
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from urllib.request import Request
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log = logging.getLogger(__name__)
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_BASE = "https://musicbrainz.org/ws/2"
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_UA = "derp-bot/2.0.0 (https://git.mymx.me/username/derp)"
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# Rate limit: MusicBrainz requires max 1 request/second.
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# We use 1.1s between calls to stay well within limits.
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_RATE_INTERVAL = 1.1
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_last_request: float = 0.0
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def _mb_request(path: str, params: dict | None = None) -> dict:
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"""Rate-limited GET to MusicBrainz API. Blocking."""
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global _last_request
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from derp.http import urlopen
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elapsed = time.monotonic() - _last_request
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if elapsed < _RATE_INTERVAL:
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time.sleep(_RATE_INTERVAL - elapsed)
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qs = "&".join(f"{k}={v}" for k, v in (params or {}).items())
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url = f"{_BASE}/{path}?fmt=json&{qs}" if qs else f"{_BASE}/{path}?fmt=json"
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req = Request(url, headers={"User-Agent": _UA})
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try:
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resp = urlopen(req, timeout=10, proxy=False)
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_last_request = time.monotonic()
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return json.loads(resp.read().decode())
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except Exception:
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_last_request = time.monotonic()
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log.warning("musicbrainz: request failed: %s", path, exc_info=True)
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return {}
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def mb_search_artist(name: str) -> str | None:
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"""Search for an artist by name, return MBID or None."""
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from urllib.parse import quote
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data = _mb_request("artist", {"query": quote(name), "limit": "1"})
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artists = data.get("artists", [])
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if not artists:
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return None
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# Require a reasonable score to avoid false matches
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score = artists[0].get("score", 0)
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if score < 50:
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return None
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return artists[0].get("id")
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def mb_artist_tags(mbid: str) -> list[str]:
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"""Fetch top 5 tags for an artist by MBID."""
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data = _mb_request(f"artist/{mbid}", {"inc": "tags"})
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tags = data.get("tags", [])
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if not tags:
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return []
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# Sort by count descending, take top 5
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sorted_tags = sorted(tags, key=lambda t: t.get("count", 0), reverse=True)
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return [t["name"] for t in sorted_tags[:5] if t.get("name")]
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def mb_find_similar_recordings(artist: str, tags: list[str],
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limit: int = 10) -> list[dict]:
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"""Find recordings by other artists sharing top tags.
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Searches MusicBrainz for recordings tagged with the top 2 tags,
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excluding the original artist. Returns [{"artist": str, "title": str}].
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"""
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from urllib.parse import quote
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if not tags:
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return []
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# Use top 2 tags for the query
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tag_query = " AND ".join(f'tag:"{t}"' for t in tags[:2])
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query = f'({tag_query}) AND NOT artist:"{artist}"'
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data = _mb_request("recording", {
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"query": quote(query),
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"limit": str(limit),
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})
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recordings = data.get("recordings", [])
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if not recordings:
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return []
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seen = set()
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results = []
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for rec in recordings:
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title = rec.get("title", "")
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credits = rec.get("artist-credit", [])
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if not credits or not title:
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continue
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rec_artist = credits[0].get("name", "") if credits else ""
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if not rec_artist:
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continue
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# Skip the original artist (case-insensitive)
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if rec_artist.lower() == artist.lower():
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continue
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# Deduplicate by artist+title
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key = f"{rec_artist.lower()}:{title.lower()}"
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if key in seen:
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continue
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seen.add(key)
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results.append({"artist": rec_artist, "title": title})
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return results
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