321 lines
13 KiB
Python
321 lines
13 KiB
Python
import os, tempfile
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def _fresh_db(monkeypatch):
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tmp = tempfile.mkdtemp()
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path = os.path.join(tmp, "lotto.db")
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from app import db
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monkeypatch.setattr(db, "DB_PATH", path)
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db.init_db()
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return db
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def test_backtest_tables_exist(monkeypatch):
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db = _fresh_db(monkeypatch)
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with db._conn() as conn:
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tables = {r["name"] for r in conn.execute(
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"SELECT name FROM sqlite_master WHERE type='table'").fetchall()}
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assert "backtest_runs" in tables
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assert "winner_calibration" in tables
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def test_backtest_runs_unique(monkeypatch):
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db = _fresh_db(monkeypatch)
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db.save_backtest_run(draw_no=100, strategy="random_null", weight_label="-",
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weight_json=None, trial_id=None, n_tickets=10,
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hist={"m3":1,"m4":0,"m5":0,"m6":0,"bonus_hits":0},
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best_match=3, avg_meta_score=0.5)
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db.save_backtest_run(draw_no=100, strategy="random_null", weight_label="-",
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weight_json=None, trial_id=None, n_tickets=10,
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hist={"m3":2,"m4":0,"m5":0,"m6":0,"bonus_hits":0},
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best_match=3, avg_meta_score=0.6) # 멱등 upsert
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rows = db.get_backtest_runs(draw_no=100)
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assert len(rows) == 1
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assert rows[0]["m3"] == 2 # 마지막 값으로 갱신
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_SCORES = {
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"score_total": 1.23,
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"score_frequency": 0.30,
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"score_fingerprint": 0.25,
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"score_gap": 0.20,
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"score_cooccur": 0.28,
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"score_diversity": 0.20,
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}
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def test_winner_calibration_upsert(monkeypatch):
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"""save_winner_calibration 두 번 호출 시 upsert — 행 1개, 값은 마지막 것."""
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db = _fresh_db(monkeypatch)
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winning = [3, 7, 15, 22, 33, 41]
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db.save_winner_calibration(draw_no=200, winning=winning,
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scores=_SCORES, percentile=75.0,
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my_pick_avg=0.9, cache_draws=100)
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# 두 번째 저장 — percentile, my_pick_avg 업데이트
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scores2 = {**_SCORES, "score_total": 2.00}
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db.save_winner_calibration(draw_no=200, winning=winning,
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scores=scores2, percentile=80.0,
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my_pick_avg=1.1, cache_draws=110)
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row = db.get_winner_calibration(200)
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assert row is not None
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# 행이 1개만 존재하는지 확인
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with db._conn() as conn:
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cnt = conn.execute(
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"SELECT COUNT(*) AS c FROM winner_calibration WHERE draw_no=200"
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).fetchone()["c"]
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assert cnt == 1
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assert row["percentile"] == 80.0
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assert row["score_total"] == 2.00
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def _seed_draws(db, n=40):
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rows = []
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import random as _r; _r.seed(2)
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for i in range(1, n + 1):
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s = sorted(_r.sample(range(1, 46), 6))
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rows.append({"drw_no": i, "drw_date": f"2020-01-{(i%28)+1:02d}",
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"n1": s[0], "n2": s[1], "n3": s[2], "n4": s[3],
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"n5": s[4], "n6": s[5], "bonus": ((s[5] % 45) + 1)})
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db.upsert_many_draws(rows)
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def test_backfill_calibration_idempotent(monkeypatch):
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db = _fresh_db(monkeypatch)
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_seed_draws(db, 40)
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from app import backtest as bt
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r1 = bt.backfill_calibration(batch=15, sample_m=200)
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# 첫 회차는 point-in-time 데이터가 빈약 → min_history 이후만 처리
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done1 = len(db.get_calibrated_draw_nos())
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assert done1 > 0
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r2 = bt.backfill_calibration(batch=100, sample_m=200) # 나머지
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done2 = len(db.get_calibrated_draw_nos())
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assert done2 >= done1
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r3 = bt.backfill_calibration(batch=100, sample_m=200) # 재실행 → 추가 0
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assert r3["calibrated"] == 0
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def test_run_forward_purchase_persists_all_strategies(monkeypatch):
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db = _fresh_db(monkeypatch)
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_seed_draws(db, 40)
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from app import backtest as bt
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# 작은 규모로 빠르게
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res = bt.run_forward_purchase(draw_no=40, k=20, pool_n=500, sample_seed=5)
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assert res["ok"] is True
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rows = db.get_backtest_runs(draw_no=40)
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strategies = {r["strategy"] for r in rows}
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assert "random_null" in strategies
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assert "coverage" in strategies
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assert "engine_w" in strategies # base 가중치로 최소 1건
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for r in rows:
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assert r["n_tickets"] == 20
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def test_calibrate_winner_no_draw(monkeypatch):
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"""DB에 없는 회차 번호 → ok=False, reason='no_draw'."""
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db = _fresh_db(monkeypatch)
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_seed_draws(db, 40)
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from app import backtest as bt
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r = bt.calibrate_winner(99999)
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assert r["ok"] is False
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assert r["reason"] == "no_draw"
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def test_calibrate_winner_insufficient_history(monkeypatch):
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"""point-in-time 이력이 MIN_HISTORY(30) 미만인 회차 → reason='insufficient_history'.
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draw_no=20이면 PIT 이력이 19개(draws 1~19)로 30 미만."""
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db = _fresh_db(monkeypatch)
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_seed_draws(db, 40)
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from app import backtest as bt
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r = bt.calibrate_winner(20)
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assert r["ok"] is False
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assert r["reason"] == "insufficient_history"
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def test_run_forward_purchase_with_trials(monkeypatch):
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"""그 주 weight_trials가 존재하면 engine_w 행의 weight_label이 'w0'..'w5' 형식이어야 한다."""
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db = _fresh_db(monkeypatch)
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_seed_draws(db, 40)
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# draw 40: drw_date='2020-01-13' → week_start='2020-01-13'
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from datetime import date, timedelta
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draw_date = date.fromisoformat("2020-01-13")
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ws = (draw_date - timedelta(days=draw_date.weekday())).isoformat()
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# 해당 주에 trial 2개 심기 (day_of_week 0, 1)
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db.save_weight_trial(ws, 0, [0.1, 0.3, 0.2, 0.2, 0.2], "perturb")
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db.save_weight_trial(ws, 1, [0.25, 0.25, 0.25, 0.15, 0.1], "perturb")
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from app import backtest as bt
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res = bt.run_forward_purchase(draw_no=40, k=20, pool_n=500, sample_seed=5)
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assert res["ok"] is True
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rows = db.get_backtest_runs(draw_no=40)
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engine_w_labels = {r["weight_label"] for r in rows if r["strategy"] == "engine_w"}
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# trials가 있으므로 'base'가 아닌 'w0', 'w1' 형식이어야 한다
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assert "base" not in engine_w_labels
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assert any(lbl.startswith("w") for lbl in engine_w_labels)
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def test_run_forward_purchase_idempotent(monkeypatch):
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"""run_forward_purchase 두 번 호출 시 upsert — 행 수 변화 없음."""
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db = _fresh_db(monkeypatch)
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_seed_draws(db, 40)
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from app import backtest as bt
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bt.run_forward_purchase(draw_no=40, k=20, pool_n=500, sample_seed=5)
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count_after_first = len(db.get_backtest_runs(draw_no=40))
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bt.run_forward_purchase(draw_no=40, k=20, pool_n=500, sample_seed=5)
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count_after_second = len(db.get_backtest_runs(draw_no=40))
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assert count_after_second == count_after_first
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def test_get_calibrated_draw_nos(monkeypatch):
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"""저장된 draw_no 집합이 get_calibrated_draw_nos에 포함되어야 한다."""
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db = _fresh_db(monkeypatch)
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winning = [1, 2, 3, 4, 5, 6]
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for draw_no in (301, 302, 303):
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db.save_winner_calibration(draw_no=draw_no, winning=winning,
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scores=_SCORES, percentile=50.0,
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my_pick_avg=0.5, cache_draws=50)
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nos = db.get_calibrated_draw_nos()
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assert isinstance(nos, set)
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assert {301, 302, 303}.issubset(nos)
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def test_track_record_and_review_payload(monkeypatch):
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db = _fresh_db(monkeypatch)
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_seed_draws(db, 40)
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from app import backtest as bt
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bt.run_forward_purchase(draw_no=40, k=20, pool_n=500, sample_seed=5)
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bt.calibrate_winner(40, sample_m=200)
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tr = bt.track_record()
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assert "random_null" in tr["by_strategy"]
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# 이제 random_null은 N_NULL_TRIALS=6 행이므로 6*20=120장
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assert tr["by_strategy"]["random_null"]["n_tickets"] >= 20
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payload = bt.build_review_payload(40)
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assert payload["draw_no"] == 40
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assert "winner_analysis" in payload # 당첨조합 5분석치
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assert "forward" in payload # 이번 회차 전략별 성적
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assert "calibration_trend" in payload
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assert payload["winner_analysis"] is not None
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assert "score_total" in payload["winner_analysis"]
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def test_run_forward_purchase_random_null_count(monkeypatch):
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"""run_forward_purchase는 random_null을 N_NULL_TRIALS=6개 저장해야 한다."""
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db = _fresh_db(monkeypatch)
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_seed_draws(db, 40)
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from app import backtest as bt
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res = bt.run_forward_purchase(draw_no=40, k=20, pool_n=500, sample_seed=7)
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assert res["ok"] is True
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rows = db.get_backtest_runs(draw_no=40)
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null_rows = [r for r in rows if r["strategy"] == "random_null"]
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assert len(null_rows) == bt.N_NULL_TRIALS # 6개
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null_labels = {r["weight_label"] for r in null_rows}
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assert null_labels == {f"r{i}" for i in range(bt.N_NULL_TRIALS)}
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for r in null_rows:
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assert r["n_tickets"] == 20
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def test_evaluate_weekly_gated_keeps_base_unchanged(monkeypatch):
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"""Fix 5 통합 테스트 (end-to-end gated path).
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접근: DB에 draws, weight_trials, auto_picks, backtest_runs, base_history를 직접 심어
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evaluate_weekly()의 gated 분기가 base를 바꾸지 않음을 검증한다.
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gated 조건: engine_w 최고 prize_score − random_best < LIFT_EPSILON(10.0).
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engine_best=5, random_best=20 → lift=-15 → gated.
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evaluate_weekly 내부 흐름:
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- get_weekly_trials(week_start) : _today_kst() 기준 week_start 사용
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- get_latest_draw() : draws 테이블에서 max(drw_no) 반환
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두 참조가 같은 날짜 기준이어야 하므로 _today_kst를 monkeypatch로 고정하고
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draws의 최신 회차 날짜(drw_date)를 해당 주의 날짜로 맞춘다.
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"""
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import json as _json
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from datetime import date, timedelta, datetime as _dt, timezone as _tz, timedelta as _td
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db = _fresh_db(monkeypatch)
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# KST 오늘 날짜 — evaluate_weekly가 이 날짜를 기준으로 week_start 계산
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KST = _tz(_td(hours=9))
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today_kst = _dt.now(KST).date()
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from app import weight_evolver as we
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week_start = we.get_week_start(today_kst)
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# 1) draws 심기 — 최신 회차의 drw_date를 week_start 주 안의 날짜로 맞춤
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import random as _r; _r.seed(99)
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rows = []
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for i in range(1, 41):
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s = sorted(_r.sample(range(1, 46), 6))
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# 마지막 회차(40)는 오늘 날짜 사용 (week_start 주 내)
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if i == 40:
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drw_date = today_kst.isoformat()
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else:
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drw_date = f"2020-01-{(i % 28) + 1:02d}"
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rows.append({
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"drw_no": i, "drw_date": drw_date,
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"n1": s[0], "n2": s[1], "n3": s[2],
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"n4": s[3], "n5": s[4], "n6": s[5],
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"bonus": (s[5] % 45) + 1,
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})
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db.upsert_many_draws(rows)
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latest = db.get_latest_draw()
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assert latest is not None
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assert latest["drw_date"] == today_kst.isoformat()
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# 2) weight trial 1개 심기 (day_of_week=0, week_start=오늘 주)
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trial_w = [0.2, 0.2, 0.2, 0.2, 0.2]
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db.save_weight_trial(week_start, 0, trial_w, "perturb")
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trial_rows = db.get_weekly_trials(week_start)
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assert len(trial_rows) == 1
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trial_id = trial_rows[0]["id"]
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# 3) auto_picks 1개 심기 (winning 번호와 2개 일치 → max_correct=2)
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winning6 = [latest["n1"], latest["n2"], latest["n3"],
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latest["n4"], latest["n5"], latest["n6"]]
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pick = winning6[:2] + [40, 41, 42, 43]
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db.save_auto_pick(trial_id, 1, pick, meta_score=0.5)
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# 4) backtest_runs: engine_w prize_score=5, random_null 6개 prize_score=20 (gated 확실)
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LOW_HIST = {"m3": 5, "m4": 0, "m5": 0, "m6": 0, "bonus_hits": 0} # prize=5
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HIGH_HIST = {"m3": 20, "m4": 0, "m5": 0, "m6": 0, "bonus_hits": 0} # prize=20
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draw_no = latest["drw_no"]
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db.save_backtest_run(
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draw_no=draw_no, strategy="engine_w", weight_label="w0",
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weight_json=_json.dumps(trial_w), trial_id=trial_id, n_tickets=20,
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hist=LOW_HIST, best_match=2, avg_meta_score=0.5,
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)
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from app import backtest as bt
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for i in range(bt.N_NULL_TRIALS):
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db.save_backtest_run(
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draw_no=draw_no, strategy="random_null", weight_label=f"r{i}",
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weight_json=None, trial_id=None, n_tickets=20,
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hist=HIGH_HIST, best_match=3, avg_meta_score=0.5,
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)
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# 5) current base 저장 (이전 주 월요일 effective_from)
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base_w = [0.2, 0.2, 0.2, 0.2, 0.2]
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prev_monday = (today_kst - timedelta(weeks=1, days=today_kst.weekday())).isoformat()
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db.save_base_history(
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effective_from=prev_monday,
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weight=base_w,
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source_trial_id=None,
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update_reason="cold_start",
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winner_score=None,
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winner_max_correct=None,
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)
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assert db.get_current_base() == base_w
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# 6) evaluate_weekly 호출 — _today_kst()를 monkeypatch로 오늘 날짜 고정
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monkeypatch.setattr(we, "_today_kst", lambda: today_kst)
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result = we.evaluate_weekly()
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assert result.get("ok") is True, f"evaluate_weekly 실패: {result}"
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# gated path 검증
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update_reason = result.get("update_reason", "")
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assert update_reason in ("unchanged_gated", "idempotent_skip"), (
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f"gated여야 하는데 reason='{update_reason}' — 게이팅 로직 깨짐"
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)
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# base가 바뀌지 않았는지 검증
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new_base = result.get("new_base")
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assert new_base == base_w, (
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f"gated인데 base가 변경됨: {new_base} != {base_w}"
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)
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