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2 Commits (adbdda7b0eeecaaabce5f5b2fa52c026ff84400a)
| Author | SHA1 | Message | Date |
|---|---|---|---|
BoulderBadgeDad
|
c3aea58b03 |
Player revamp Phase 2: smart radio ranking (play-count + popularity)
Replaces radio's pure ORDER BY RANDOM() with weighted ranking. Each tier now
fetches a generous random POOL (4x the needed count, floored) and
core/radio/selection ranks it before the collector keeps the best:
score_candidate = play_count(log-damped, w=1.0)
+ lastfm_playcount(log-damped, w=0.5)
- recently_played penalty(w=2.0)
+ stable per-id jitter(w=1.0, hash-derived so runs vary but
tests stay reproducible)
Modest weights so popularity guides without burying lesser-played tracks, and
jitter keeps radio from being identical every run. All intelligence is in pure
functions (rank_candidates / score_candidate) so it's tunable + unit-testable
without SQL.
Defensive: the DB method probes PRAGMA table_info(tracks) and omits
play_count/lastfm_playcount from the SELECT when absent (older DBs predating
the listening-history migration) — the scorer treats missing signals as 0, so
radio degrades to jitter-only instead of crashing on 'no such column'.
Tests (tests/radio/, 43 total):
- score_candidate / rank_candidates: deterministic unit coverage (popularity
ordering, lastfm contribution, recency penalty, garbage→0, stable jitter).
These CANNOT pass against pre-Phase-2 code.
- DB end-to-end: ranking surfaces the heavily-played track first out of a
decoy pool (wiring proof — probabilistic vs old random, documented honestly);
plus a no-rank-columns DB proving the defensive degrade path.
- All Phase-0a behavioral/refactor-equivalence tests still green.
60 radio + adjacent-DB tests pass; ruff clean.
|
4 weeks ago |
|
BoulderBadgeDad
|
cbc001e283 |
Player revamp Phase 0a: extract radio selection into testable core/radio/
First step of the stream/player/radio revamp (see revamp_plan.md). The radio
algorithm lived inline inside database.music_database.get_radio_tracks as raw
SQL tangled with selection logic — untestable without a live DB (which also
throws in the dev sandbox). Lifted the pure DECISIONS into core/radio/selection.py:
- parse_tags / merge_tags — JSON-or-CSV tag fields → ordered deduped list
- same_artist_cap — tier-1 30%-floored-at-5 cap
- build_like_conditions — OR-of-LIKEs SQL fragment + params per tier
- RadioCollector — dedup + cap + exclude-set + NOT-IN placeholder/value tracking
The DB method keeps the cursor work and now delegates every decision to these
helpers. Faithful extraction, not a rewrite — behavior unchanged.
This is the kettui foundation move: radio is now unit-testable, so Phase 2
(smart ranking — play-count / recency / feature seeding) becomes 'evolve a
tested function' instead of 'rewrite SQL and pray'.
Tests (tests/radio/):
- test_selection.py (22): unit coverage of every extracted helper
- test_get_radio_tracks_db.py (7): drive the REAL get_radio_tracks against
in-memory sqlite — tier fallback, dedup, exclude, file_path filter.
Behavior-pinned: these 7 pass against BOTH old inline and new extracted
code (refactor-equivalence proof). 52 adjacent DB+radio tests green.
|
4 weeks ago |