Foundation for multi-listener playback. Today web_server.py keeps ONE global
stream_state dict + one lock (web_server.py:747), so the whole server shares a
single 'currently playing' — every tab/device is a remote for the same
playback and two listeners collide. That global is woven through ~22 sites and
isn't unit-testable where it lives.
Lifted into core/streaming/state.py WITHOUT changing behavior:
- StreamSession: one playback's state, dict-compatible (s['k'], s.get,
s.update, 'k' in s) so existing call sites work unchanged, each with its
OWN RLock so distinct sessions never block/clobber each other.
- StreamStateStore: registry of named sessions; lazy + race-safe create;
DEFAULT session reproduces today's exact single-global behavior. Also
drop()/active_ids()/session_ids() for the eventual per-listener wiring.
web_server.py now binds (DEFAULT) and
. Drop-in: every .update()/[k]/.get()/ site behaves identically. _set_stream_state routes a reassign
through session.replace() so the store's session stays the live object (it's
effectively dead — prepare.py only mutates in place — but safe now).
Honest scope: this is the PROVABLE half of Phase 3. The remaining half (3b:
derive a per-browser session id, per-session Stream/ staging, executor
concurrency, disconnect cleanup) is browser-coupled and can't be verified
without driving 2+ live clients — deferred to a live session. The store API is
already shaped for it.
Tests (tests/streaming/, 33 total):
- test_stream_state_store.py (19): session dict-compat, isolation, lazy
create, drop rules, active_ids, concurrent-create race safety.
- test_stream_state_callsite_compat.py (7): every real web_server access
pattern (library/play, stream/start, status, audio guard, stop, prepare
in-place mutation, set->replace) against the exact object web_server binds.
- test_prepare.py +1: real prepare worker drives an actual StreamSession.
76 streaming+radio tests green; ruff clean; web_server.py parses.
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.
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.
