from lyra_worker.adapters.fakes import FakeMbBrowser, FakeSimilaritySource from lyra_worker.discovery import DiscoveryConfig, run_discovery from lyra_worker.similarity.base import SimilarArtist from tests.conftest import insert_discovery_suggestion, insert_watched_artist def _artist_rows(conn): with conn.cursor() as cur: cur.execute('SELECT "artistMbid", "artistName", score, "seedCount", sources, status::text ' 'FROM "DiscoverySuggestion" WHERE kind = \'artist\' ORDER BY score DESC') return cur.fetchall() def test_aggregates_scores_across_seeds(conn): insert_watched_artist(conn, mbid="s1", name="Seed One") insert_watched_artist(conn, mbid="s2", name="Seed Two") src = FakeSimilaritySource(similar={ "s1": [SimilarArtist("c1", "Shared", 0.6), SimilarArtist("c2", "Only1", 0.4)], "s2": [SimilarArtist("c1", "Shared", 0.5)], }) result = run_discovery(conn, [src], FakeMbBrowser(), DiscoveryConfig()) assert result.artists == 2 rows = _artist_rows(conn) # c1 recommended by both seeds: score 1.1, seedCount 2; c2 by one seed assert rows[0][0] == "c1" and abs(rows[0][2] - 1.1) < 1e-6 and rows[0][3] == 2 assert rows[0][4] == ["fake"] and rows[0][5] == "pending" assert rows[1][0] == "c2" and rows[1][3] == 1 def test_skips_already_followed_artists(conn): insert_watched_artist(conn, mbid="s1", name="Seed") insert_watched_artist(conn, mbid="c1", name="Already Followed") src = FakeSimilaritySource(similar={"s1": [SimilarArtist("c1", "X", 0.9), SimilarArtist("c2", "New", 0.8)]}) run_discovery(conn, [src], FakeMbBrowser(), DiscoveryConfig()) assert [r[0] for r in _artist_rows(conn)] == ["c2"] # c1 filtered (followed) def test_min_score_filters_weak_candidates(conn): insert_watched_artist(conn, mbid="s1", name="Seed") src = FakeSimilaritySource(similar={"s1": [SimilarArtist("c1", "Strong", 0.9), SimilarArtist("c2", "Weak", 0.1)]}) run_discovery(conn, [src], FakeMbBrowser(), DiscoveryConfig(min_score=0.5)) assert [r[0] for r in _artist_rows(conn)] == ["c1"] def test_dismissed_suggestion_is_never_revived(conn): insert_watched_artist(conn, mbid="s1", name="Seed") insert_discovery_suggestion(conn, kind="artist", artist_mbid="c1", status="dismissed", score=0.0) src = FakeSimilaritySource(similar={"s1": [SimilarArtist("c1", "X", 0.9)]}) run_discovery(conn, [src], FakeMbBrowser(), DiscoveryConfig()) with conn.cursor() as cur: cur.execute('SELECT status::text, score FROM "DiscoverySuggestion" WHERE "artistMbid" = %s', ("c1",)) assert cur.fetchone() == ("dismissed", 0.0) # untouched — WHERE status='pending' blocked the update def test_stamps_last_discovered_and_throttles(conn): insert_watched_artist(conn, mbid="s1", name="Seed") src = FakeSimilaritySource(similar={"s1": [SimilarArtist("c1", "X", 0.9)]}) assert run_discovery(conn, [src], FakeMbBrowser(), DiscoveryConfig()).artists == 1 with conn.cursor() as cur: cur.execute('SELECT "lastDiscoveredAt" IS NOT NULL FROM "WatchedArtist" WHERE mbid = %s', ("s1",)) assert cur.fetchone()[0] is True # second run: seed not due (lastDiscoveredAt recent) -> no seeds -> nothing new assert run_discovery(conn, [src], FakeMbBrowser(), DiscoveryConfig()).artists == 0 def test_unhealthy_source_contributes_nothing(conn): insert_watched_artist(conn, mbid="s1", name="Seed") src = FakeSimilaritySource(similar={"s1": [SimilarArtist("c1", "X", 0.9)]}, healthy=False) assert run_discovery(conn, [src], FakeMbBrowser(), DiscoveryConfig()).artists == 0 assert _artist_rows(conn) == [] def test_config_from_config_parses_and_defaults(): cfg = DiscoveryConfig.from_config({"discover.enabled": "true", "discover.maxSeeds": "10", "discover.minScore": "0.3"}) assert cfg.enabled is True and cfg.max_seeds == 10 and cfg.min_score == 0.3 d = DiscoveryConfig.from_config({}) assert (d.enabled, d.interval_hours, d.max_seeds, d.similar_per_seed, d.albums_per_artist, d.min_score) == (False, 168, 50, 20, 1, 0.0)