refactor(discover): both affinities weigh a watch by one rule

The YouTube channel affinity and the Plex one each had the recency decay, the undated-watch rule and
the scale to the strongest; app.draw now holds them. Tests hold that another user's history leans
neither draw, the rail's blind slot, and that a show leans on show recommendations.

backend/tests/test_surprise_affinity.py

@@ -10,7 +10,7 @@ history the order is exactly the old one. DB lane.
 import hashlib
 from datetime import datetime, timedelta, timezone
 
-from sqlalchemy import text
+from sqlalchemy import select, text
 
 from app import draw
 from app.catalog.models import Channel, Subscription, Video
@@ -267,3 +267,69 @@ def test_the_discover_rail_leans_the_same_way(db, make_user):
     ]
     assert leads.count("comedy_new") > 0
     assert leads.count("horror_new") + leads.count("tipped_new") > 3 * leads.count("comedy_new")
+
+
+# ── whose history: only the user's own ───────────────────────────────────────────────────────────
+
+
+def test_another_users_youtube_history_does_not_lean_my_draw(db, make_user):
+    watcher = _seed_yt(db, make_user, watched_in_fav=12)
+    me = make_user()
+    db.add_all(
+        [
+            Subscription(user_id=me.id, channel_id="UCfav"),
+            Subscription(user_id=me.id, channel_id="UCother"),
+        ]
+    )
+    db.commit()
+    assert queries._channel_affinity(db, watcher)
+    assert queries._channel_affinity(db, me) == {}
+
+
+def test_another_users_plex_history_does_not_lean_my_draw(db, make_user):
+    _seed_plex(db, make_user, history=True)
+    me = make_user()
+    assert not affinity.for_user(db, me.id)
+    keys = ["horror_new", "comedy_new", "tipped_new"] + [f"horror_seen{i}" for i in range(3)]
+    for s in range(12):
+        got = [c["id"] for c in queries.plex_surprise(db, me.id, "any", s, 6, lang="en")]
+        assert got == _md5_order(keys, s)
+
+
+# ── the rail: its blind slot, and a show's own recommendations ───────────────────────────────────
+
+
+def test_the_rails_third_slot_is_the_blind_draw(db, make_user, monkeypatch):
+    # The rail draws with random(), so the blend is watched rather than its odds: every leaning draw
+    # goes through it, with the blind order beside the weighted one and the third slot blind.
+    user, *_ = _seed_plex(db, make_user, history=True)
+    calls = []
+    real = draw.blend
+
+    def spy(weighted, blind, offset, n, key):
+        calls.append((offset, n, sorted(map(key, weighted)), sorted(map(key, blind))))
+        return real(weighted, blind, offset, n, key=key)
+
+    monkeypatch.setattr(draw, "blend", spy)
+    got = plex_discover.surprise(db, user, "movie", "en", 3, [], [], LibraryFilters())["items"]
+    assert calls and all(offset == 1 and n == 3 for offset, n, *_ in calls)
+    pool = sorted(["horror_new", "comedy_new", "tipped_new"])
+    assert calls[0][2] == pool and calls[0][3] == pool
+    assert len(got) == 3
+
+
+def test_a_show_leans_on_the_shows_recommended_not_the_films(db, make_user):
+    lib = PlexLibrary(plex_key="80", title="Shows", kind="show", enabled=True)
+    db.add(lib)
+    db.flush()
+    tipped = PlexShow(rating_key="tv1", library_id=lib.id, title="t", guid="tmdb:1", genres=[])
+    db.add(tipped)
+    db.commit()
+    shows = affinity.Affinity(show_recs={"tmdb:1": 1.0})
+    films = affinity.Affinity(movie_recs={"tmdb:1": 1.0})
+
+    def weight(aff):
+        return db.execute(select(aff.weight(PlexShow)).where(PlexShow.id == tipped.id)).scalar_one()
+
+    assert weight(shows) == 1 + affinity.REC_WEIGHT
+    assert weight(films) == 1