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_source_with_raising_health_is_skipped_not_fatal(conn):
    insert_watched_artist(conn, mbid="s1", name="Seed")

    class BoomSource:
        name = "boom"
        def health(self):
            raise RuntimeError("boom")
        def similar_artists(self, mbid):
            return []

    good = FakeSimilaritySource(similar={"s1": [SimilarArtist("c1", "X", 0.9)]})
    result = run_discovery(conn, [BoomSource(), good], FakeMbBrowser(), DiscoveryConfig())
    assert result.artists == 1  # good source still processed; boom skipped, no crash


def test_config_from_config_parses_and_defaults():
    cfg = DiscoveryConfig.from_config({"discover.enabled": "true", "discover.chunkSize": "10",
                                       "discover.minScore": "0.3"})
    assert cfg.enabled is True and cfg.chunk_size == 10 and cfg.min_score == 0.3
    d = DiscoveryConfig.from_config({})
    assert (d.enabled, d.interval_hours, d.chunk_size, d.similar_per_seed,
            d.albums_per_artist, d.min_score) == (False, 168, 5, 20, 1, 0.0)


def test_run_discovery_processes_at_most_chunk_size_seeds(conn):
    from lyra_worker.discovery import DiscoveryConfig, run_discovery
    from lyra_worker.adapters.fakes import FakeMbBrowser, FakeSimilaritySource
    from lyra_worker.similarity.base import SimilarArtist
    from tests.conftest import insert_watched_artist
    for i in range(4):
        insert_watched_artist(conn, mbid=f"s{i}", name=f"Seed{i}")
    src = FakeSimilaritySource(similar={f"s{i}": [SimilarArtist(f"c{i}", f"Cand{i}", 0.9)] for i in range(4)})
    cfg = DiscoveryConfig.from_config({"discover.chunkSize": "2"})
    result = run_discovery(conn, [src], FakeMbBrowser(), cfg)
    assert result.seeds == 2          # only chunk_size seeds this call
    # exactly 2 seeds now have lastDiscoveredAt set
    with conn.cursor() as cur:
        cur.execute('SELECT count(*) FROM "WatchedArtist" WHERE "lastDiscoveredAt" IS NOT NULL')
        assert cur.fetchone()[0] == 2