"""[2026-10-02] 가드 우회 엔드포인트 회귀 테스트 — H-3 / H-4 / H-5 / M-5 / C1 / Low.

원칙: 주문 종단(`trade_executor.safe_place_order`)·KIS 는 conftest 가 예외 발생형으로
막고 있고, 여기서는 필요한 것만 캡처형으로 덮는다. 호출되면 안 되는 경로는 예외 발생형.
기대값은 settings.* 에서 계산한다(하드코딩 금지).
"""
from types import SimpleNamespace
from unittest.mock import AsyncMock

import pytest
from fastapi import HTTPException
from pydantic import ValidationError

from app.core.config import settings


class _MustNotCall(BaseException):
    pass


def _boom(name):
    async def _f(*a, **k):
        raise _MustNotCall(f"{name} 가 호출되면 안 된다")
    return _f


# ═════════════════════════════════════════════════════════════════════════════
# H-3: POST /recommendations/auto-trade → execute_auto_trade_background 위임
# ═════════════════════════════════════════════════════════════════════════════

@pytest.mark.asyncio
async def test_h3_auto_trade_blocked_when_disabled(monkeypatch):
    from app.api.endpoints import recommendations as rec
    monkeypatch.setattr(settings, "AUTO_TRADE_ENABLED", False)
    monkeypatch.setattr(rec, "get_rule_based_recommendations", _boom("추천 조회"))
    monkeypatch.setattr(rec, "execute_auto_trade_background", _boom("자동매매"))
    with pytest.raises(HTTPException) as ei:
        await rec.execute_auto_trading(db=object())
    assert ei.value.status_code == 423


@pytest.mark.asyncio
async def test_h3_auto_trade_rejects_when_bg_lock_held(monkeypatch):
    from app.api.endpoints import recommendations as rec
    from app.services import trade_executor as te
    monkeypatch.setattr(settings, "AUTO_TRADE_ENABLED", True)
    monkeypatch.setattr(settings, "TRADING_HALTED", False)
    monkeypatch.setattr(rec, "get_rule_based_recommendations", _boom("추천 조회"))
    await te._auto_trade_bg_lock.acquire()
    try:
        with pytest.raises(HTTPException) as ei:
            await rec.execute_auto_trading(db=object())
        assert ei.value.status_code == 409
    finally:
        te._auto_trade_bg_lock.release()


@pytest.mark.asyncio
async def test_h3_auto_trade_delegates_to_background(monkeypatch):
    from app.api.endpoints import recommendations as rec
    from app.services import trade_executor as te
    monkeypatch.setattr(settings, "AUTO_TRADE_ENABLED", True)
    monkeypatch.setattr(settings, "TRADING_HALTED", False)
    payload = {"recommendations_by_rule": [{"rule_name": "r", "stocks": [{"stock_code": "005930"}]}]}
    monkeypatch.setattr(rec, "get_rule_based_recommendations", AsyncMock(return_value=payload))
    bg = AsyncMock(return_value=[
        {"action": "BUY", "success": True}, {"action": "BUY", "success": False},
        {"action": "SKIP"},
    ])
    monkeypatch.setattr(rec, "execute_auto_trade_background", bg)
    # 직접 종목별 실행 경로가 남아 있으면 즉시 실패
    monkeypatch.setattr(te, "execute_auto_trade", _boom("execute_auto_trade(직접)"))
    out = await rec.execute_auto_trading(db="DB")
    bg.assert_awaited_once_with(payload, "DB")
    assert "execute_auto_trade" not in vars(rec), "엔드포인트 모듈이 직접 실행 함수를 import 하고 있다"
    assert "진입 1건" in out["message"]
    assert len(out["trades"]) == 2


# ═════════════════════════════════════════════════════════════════════════════
# H-5: /us-trading/execute 410, /cycle 플래그 OFF 423
# ═════════════════════════════════════════════════════════════════════════════

@pytest.mark.asyncio
@pytest.mark.parametrize("flag", [False, True])
async def test_h5_execute_is_gone_regardless_of_flag(monkeypatch, flag):
    from app.api.endpoints import us_trading as us
    monkeypatch.setattr(settings, "US_TRADING_ENABLED", flag)
    req = us.UsOrderRequest(ticker="AAPL", order_type="buy", quantity=1, price=100.0)
    with pytest.raises(HTTPException) as ei:
        await us.execute_us_trade(req)
    assert ei.value.status_code == 410


@pytest.mark.asyncio
async def test_h5_cycle_blocked_when_flag_off(monkeypatch):
    from app.api.endpoints import us_trading as us
    import app.services.us_market_scheduler as ums
    monkeypatch.setattr(settings, "US_TRADING_ENABLED", False)
    monkeypatch.setattr(ums, "us_trade_cycle", _boom("us_trade_cycle"))
    with pytest.raises(HTTPException) as ei:
        await us.trigger_us_trade_cycle()
    assert ei.value.status_code == 423


@pytest.mark.asyncio
async def test_h5_cycle_runs_and_http_exception_passthrough(monkeypatch):
    from app.api.endpoints import us_trading as us
    import app.services.us_market_scheduler as ums
    monkeypatch.setattr(settings, "US_TRADING_ENABLED", True)
    monkeypatch.setattr(ums, "us_trade_cycle", AsyncMock(return_value={"ok": 1}))
    assert await us.trigger_us_trade_cycle() == {"ok": 1}

    async def _raise_http():
        raise HTTPException(status_code=409, detail="x")
    monkeypatch.setattr(ums, "us_trade_cycle", _raise_http)
    with pytest.raises(HTTPException) as ei:
        await us.trigger_us_trade_cycle()
    assert ei.value.status_code == 409, "HTTPException 이 500 으로 뭉개졌다"


# ═════════════════════════════════════════════════════════════════════════════
# H-4: 공용 매수 가드
# ═════════════════════════════════════════════════════════════════════════════

def _cap():
    return settings.MAX_POSITION_SIZE


def test_h4_requested_quantity_is_clamped_to_cap():
    from app.services.buy_guards import size_manual_buy_v2
    total, cash, px = 10_000_000.0, 5_000_000.0, 10_000.0
    d = size_manual_buy_v2(
        stock_code="005930", order_price=px, current_price=px, requested_quantity=1000,
        total_assets=total, available_cash=cash, position_cap_ratio=_cap(),
        existing_qty=0, leverage_room=None,
    )
    assert d.clamped is True
    assert d.quantity == int(total * _cap() // px)
    assert d.quantity * px <= total * _cap()


def test_h4_cumulative_cap_subtracts_existing_holding():
    from app.services.buy_guards import BuyGuardRejected, size_manual_buy_v2
    total, px = 10_000_000.0, 10_000.0
    full_qty = int(total * _cap() // px)
    # 이미 상한 꽉 참 → 거부
    with pytest.raises(BuyGuardRejected) as ei:
        size_manual_buy_v2(
            stock_code="005930", order_price=px, current_price=px, requested_quantity=None,
            total_assets=total, available_cash=total, position_cap_ratio=_cap(),
            existing_qty=full_qty, leverage_room=None,
        )
    assert ei.value.reason == "budget_below_min"
    # 절반 보유 → 나머지 절반만
    half = full_qty // 2
    d = size_manual_buy_v2(
        stock_code="005930", order_price=px, current_price=px, requested_quantity=None,
        total_assets=total, available_cash=total, position_cap_ratio=_cap(),
        existing_qty=half, leverage_room=None,
    )
    assert (half + d.quantity) * px <= total * _cap() + 1e-6


def test_h4_cash_reserve_enforced():
    from app.services.buy_guards import BuyGuardRejected, size_manual_buy_v2
    total, px = 10_000_000.0, 10_000.0
    reserve = total * (1 - settings.MAX_TOTAL_CAPITAL_USAGE)
    with pytest.raises(BuyGuardRejected):
        size_manual_buy_v2(
            stock_code="005930", order_price=px, current_price=px, requested_quantity=1,
            total_assets=total, available_cash=reserve + px / 2, position_cap_ratio=_cap(),
            existing_qty=0, leverage_room=None,
        )


def test_h4_leverage_room_includes_this_order():
    from app.services.buy_guards import leverage_room_v2
    total = 10_000_000.0
    held = [SimpleNamespace(stock_name="KODEX 레버리지", quantity=100,
                            current_price=total * settings.LEVERAGE_ETF_MAX_RATIO / 100 - 1000,
                            average_price=0)]
    room = leverage_room_v2("TIGER 인버스", held, total)
    assert room == pytest.approx(100 * 1000)
    assert leverage_room_v2("삼성전자", held, total) is None


def test_h4_cash_field_trust_order():
    from app.services.buy_guards import pick_available_cash_v2
    assert pick_available_cash_v2({
        "dnca_tot_amt": "-913965", "nxdy_excc_amt": "4524276", "prvs_rcdl_excc_amt": "5224855",
    }) == 5224855.0


@pytest.mark.parametrize("existing_qty,invest", [(0, 400_000), (10, 400_000), (25, 50_000), (39, 10_000)])
def test_h4_position_room_matches_trade_executor(existing_qty, invest):
    """buy_guards 의 누적 상한 정의가 trade_executor._apply_position_cap_room_v2 와 같다."""
    from app.services import trade_executor as te
    from app.services.buy_guards import position_cap_room_v2
    total, px = 10_000_000.0, 10_000.0
    holding = SimpleNamespace(quantity=existing_qty)
    te_amount, te_reason = te._apply_position_cap_room_v2(
        invest, holding, "TEST01", "t", px, total, _cap(),
    )
    room = position_cap_room_v2(total, _cap(), existing_qty, px)
    if existing_qty == 0:
        assert te_reason is None and room == pytest.approx(total * _cap())
    elif te_reason is None:
        assert te_amount == pytest.approx(min(invest, room))
    else:
        assert te_reason == "position_cap_reached"


class _Res:
    def __init__(self, v):
        self.v = v

    def scalar_one_or_none(self):
        return self.v

    def scalar(self):
        return self.v

    def scalars(self):
        return SimpleNamespace(all=lambda: list(self.v or []), first=lambda: (self.v or [None])[0])


class _FakeDB:
    def __init__(self, results):
        self.results = list(results)
        self.stmts = []

    async def execute(self, stmt):
        self.stmts.append(stmt)
        return _Res(self.results.pop(0))

    async def delete(self, obj):
        raise _MustNotCall("직접 delete")

    async def commit(self):
        raise _MustNotCall("직접 commit")


def _adp(mode="normal", fallback=False, size=None, trades=5):
    return SimpleNamespace(
        fallback_used=fallback, trading_mode=mode,
        position_size=size if size is not None else settings.MAX_POSITION_SIZE,
        max_daily_trades=trades, rsi_entry=settings.MEAN_REVERSION_RSI_THRESHOLD,
        bear_rsi_entry=settings.MEAN_REVERSION_BEAR_RSI_THRESHOLD,
    )


@pytest.fixture
def manual_buy_env(monkeypatch):
    from app.api.endpoints import manual_buy as mb
    from app.services import trade_executor as te
    import app.services.adaptive_strategy as ad
    import app.services.correlation_filter as cf
    import app.services.db_worker as dbw
    import app.services.system_buy_registry as sbr

    total, cash, px = 10_000_000.0, 5_000_000.0, 10_000.0
    k = mb.korea_investment_api
    monkeypatch.setattr(k, "get_current_price", AsyncMock(return_value={"output": {"stck_prpr": str(int(px)), "hts_kor_isnm": "삼성전자"}}))
    monkeypatch.setattr(k, "get_balance", AsyncMock(return_value={"output2": [{"tot_evlu_amt": str(total), "dnca_tot_amt": "-1"}]}))
    monkeypatch.setattr(k, "get_buyable_cash", AsyncMock(return_value=cash))
    monkeypatch.setattr(mb.loss_tracker, "is_banned_safe", AsyncMock(return_value=False))
    monkeypatch.setattr(mb.mdd_manager, "can_open_new_position", AsyncMock(return_value=True))
    monkeypatch.setattr(ad, "get_current_adaptive_params", lambda: _adp())
    monkeypatch.setattr(cf, "validate_correlation_filter", AsyncMock(return_value=(True, "ok")))
    orders = []

    async def _order(stock_code, order_type, quantity, price=None, **kw):
        orders.append(quantity)
        return {"rt_cd": "0", "output": {"ODNO": "1"}}
    monkeypatch.setattr(te, "safe_place_order", _order)

    async def _noop(*a, **k):
        return None
    monkeypatch.setattr(te, "_delayed_sync_portfolio", _noop)
    monkeypatch.setattr(dbw, "enqueue_trade_history", _noop)
    monkeypatch.setattr(dbw, "enqueue_portfolio_upsert", _noop)
    monkeypatch.setattr(sbr, "note_system_buy", lambda *a, **k: None)
    return SimpleNamespace(mb=mb, total=total, cash=cash, px=px, orders=orders, ad=ad, k=k, cf=cf)


@pytest.mark.asyncio
async def test_h4_manual_buy_endpoint_clamps_requested_quantity(manual_buy_env):
    e = manual_buy_env
    db = _FakeDB([None, 0, []])  # holding / count / current_holdings
    req = e.mb.BuyRequest(stock_code="005930", quantity=1000)
    out = await e.mb._buy_stock_impl(req, "005930", db)
    expected = int(e.total * settings.MAX_POSITION_SIZE // e.px)
    assert e.orders == [expected]
    assert out["clamped"] is True and out["requested_quantity"] == 1000


@pytest.mark.asyncio
async def test_h4_manual_buy_endpoint_cumulative_with_existing(manual_buy_env):
    e = manual_buy_env
    full = int(e.total * settings.MAX_POSITION_SIZE // e.px)
    holding = SimpleNamespace(quantity=full, stock_name="삼성전자")
    db = _FakeDB([holding, [holding]])
    with pytest.raises(HTTPException) as ei:
        await e.mb._buy_stock_impl(e.mb.BuyRequest(stock_code="005930"), "005930", db)
    assert ei.value.status_code == 400
    assert e.orders == []


@pytest.mark.asyncio
async def test_h4_manual_buy_blocked_in_crisis(manual_buy_env, monkeypatch):
    e = manual_buy_env
    monkeypatch.setattr(e.ad, "get_current_adaptive_params", lambda: _adp(mode="crisis", trades=0))
    with pytest.raises(HTTPException) as ei:
        await e.mb._buy_stock_impl(e.mb.BuyRequest(stock_code="005930"), "005930", _FakeDB([None, 0, []]))
    assert ei.value.status_code == 423
    assert e.orders == []


@pytest.mark.asyncio
async def test_h4_manual_buy_rejects_on_balance_failure(manual_buy_env, monkeypatch):
    e = manual_buy_env

    async def _fail(*a, **k):
        raise RuntimeError("KIS down")
    monkeypatch.setattr(e.k, "get_balance", _fail)
    with pytest.raises(HTTPException) as ei:
        await e.mb._buy_stock_impl(e.mb.BuyRequest(stock_code="005930", quantity=1), "005930", _FakeDB([None, 0, []]))
    assert ei.value.status_code == 502
    assert e.orders == []


@pytest.mark.asyncio
async def test_h4_manual_buy_rejects_on_sector_filter(manual_buy_env, monkeypatch):
    e = manual_buy_env
    monkeypatch.setattr(e.cf, "validate_correlation_filter", AsyncMock(return_value=(False, "sector_full")))
    with pytest.raises(HTTPException) as ei:
        await e.mb._buy_stock_impl(e.mb.BuyRequest(stock_code="005930"), "005930", _FakeDB([None, 0, []]))
    assert ei.value.status_code == 400
    assert e.orders == []


# ═════════════════════════════════════════════════════════════════════════════
# M-5: 수동 청산 부기
# ═════════════════════════════════════════════════════════════════════════════

def test_m5_allocation_dt_first_and_swing_only():
    from app.services.manual_sell_service import allocate_sell_v2
    a = allocate_sell_v2(sold=6, row_qty_before=10, dt_qty=4, swing_only=False)
    assert (a.dt_sold, a.swing_sold, a.dt_left, a.swing_left) == (4, 2, 0, 4)
    b = allocate_sell_v2(sold=6, row_qty_before=10, dt_qty=4, swing_only=True)
    assert (b.dt_sold, b.swing_sold, b.swing_left) == (0, 6, 0)
    c = allocate_sell_v2(sold=3, row_qty_before=5, dt_qty=9, swing_only=False)  # stale DT
    assert c.dt_before == 5 and c.dt_sold == 3


@pytest.mark.asyncio
async def test_m5_active_trade_payloads_always_carry_strategy_filter(monkeypatch):
    import app.services.db_worker as dbw
    from app.services.manual_sell_service import allocate_sell_v2, sync_active_trade_after_manual_sell_v2
    writes, upserts = [], []

    async def _w(task):
        writes.append(task)

    async def _u(p):
        upserts.append(p)
    monkeypatch.setattr(dbw, "enqueue_db_write", _w)
    monkeypatch.setattr(dbw, "enqueue_active_trade_upsert", _u)

    # 전량(스윙 6 + DT 4) → 비-DT close + DT close
    await sync_active_trade_after_manual_sell_v2("005930", allocate_sell_v2(10, 10, 4, False))
    assert [w["data"].get("strategy_name_not") or w["data"].get("strategy_names") for w in writes]
    assert all(("strategy_name_not" in w["data"]) ^ ("strategy_names" in w["data"]) for w in writes)
    assert len(writes) == 2 and upserts == []

    # 부분(DT 4 전량 + 스윙 2) → DT close, 스윙 upsert(잔량 4, 비율 4/6)
    writes.clear()
    await sync_active_trade_after_manual_sell_v2("005930", allocate_sell_v2(6, 10, 4, False))
    assert len(writes) == 1 and "strategy_names" in writes[0]["data"]
    assert upserts[0]["quantity"] == 4 and upserts[0]["strategy_name_not"]
    assert upserts[0]["remaining_pct_multiply"] == pytest.approx(4 / 6)


def test_m5_swing_sell_request_rejects_nonpositive():
    from app.api.endpoints.swing_portfolio import SwingSellRequest
    for bad in (0, -3):
        with pytest.raises(ValidationError):
            SwingSellRequest(stock_code="005930", quantity=bad)


@pytest.fixture
def swing_sell_env(monkeypatch):
    from app.api.endpoints import swing_portfolio as sp
    from app.services import trade_executor as te
    import app.services.db_worker as dbw
    import app.services.portfolio_cache_bridge as pcb
    from app.services.loss_tracker import loss_tracker
    from app.services.daytrading.position_manager import day_trading_state

    monkeypatch.setattr(sp.korea_investment_api, "get_current_price",
                        AsyncMock(return_value={"output": {"stck_prpr": "10000"}}))
    orders, writes, reflected = [], [], []

    async def _order(stock_code, order_type, quantity, price=None, **kw):
        orders.append((order_type, quantity))
        return {"rt_cd": "0", "output": {"ODNO": "9"}}
    monkeypatch.setattr(te, "safe_place_order", _order)

    async def _noop(*a, **k):
        return None

    async def _w(task):
        writes.append(task)

    async def _reflect(code, qty, price, remaining_qty=None):
        reflected.append((code, qty, remaining_qty))
    monkeypatch.setattr(dbw, "enqueue_trade_history", _noop)
    monkeypatch.setattr(dbw, "enqueue_db_write", _w)
    monkeypatch.setattr(dbw, "enqueue_active_trade_upsert", _noop)
    monkeypatch.setattr(pcb, "reflect_sell", _reflect)
    rec = AsyncMock()
    save = AsyncMock()
    monkeypatch.setattr(loss_tracker, "record_trade_result_safe", rec)
    monkeypatch.setattr(loss_tracker, "save_to_db", save)
    day_trading_state.positions.pop("005930", None)
    day_trading_state.positions["005930"] = {"quantity": 4, "entry_price": 10000}
    yield SimpleNamespace(sp=sp, orders=orders, writes=writes, reflected=reflected, rec=rec, save=save)
    day_trading_state.positions.pop("005930", None)


@pytest.mark.asyncio
async def test_m5_swing_sell_excludes_dt_shares(swing_sell_env):
    e = swing_sell_env
    holding = SimpleNamespace(quantity=10, stock_name="삼성전자", average_price=11000, strategy_type="swing")
    with pytest.raises(HTTPException) as ei:
        await e.sp.manual_swing_sell(e.sp.SwingSellRequest(stock_code="005930", quantity=8), db=_FakeDB([holding]))
    assert ei.value.status_code == 400 and e.orders == []

    out = await e.sp.manual_swing_sell(e.sp.SwingSellRequest(stock_code="005930"), db=_FakeDB([holding]))
    assert e.orders == [("SELL", 6)], "DT 보유분(4주)까지 매도했다"
    assert out["quantity"] == 6
    # ActiveTrade 는 비-DT 필터로 close, Portfolio 는 큐 경유 반영
    assert e.writes and all("strategy_name_not" in w["data"] for w in e.writes)
    assert e.reflected == [("005930", 6, 4)]
    # 스윙분 전량 청산 → loss_tracker record + save_to_db
    e.rec.assert_awaited_once()
    e.save.assert_awaited_once()


def test_m5_legacy_sell_no_longer_closes_without_strategy_name():
    import inspect
    from app.api.endpoints import portfolio as pf
    src = inspect.getsource(pf.sell_stock)
    assert "strategy_name=None" not in src
    assert "sync_active_trade_after_manual_sell_v2" in src
    assert "await db.commit()" not in src, "Portfolio 직접 쓰기(§3.2)"


# ═════════════════════════════════════════════════════════════════════════════
# C1: 추천 스캐너 평균회귀 임계 출처 플래그
# ═════════════════════════════════════════════════════════════════════════════

def _stock(rsi):
    return SimpleNamespace(
        rsi=rsi, current_price=9_100, bollinger_lower=9_000, bollinger_upper=11_000,
        bollinger_middle=10_000, ma20=None, ma60=None, adx_14=20,
    )


@pytest.fixture
def mr_env(monkeypatch):
    import app.services.adaptive_strategy as ad
    from app.services.strategy_config_service import strategy_cfg
    state = {"adp": _adp(fallback=True), "cfg": {}}
    monkeypatch.setattr(ad, "get_current_adaptive_params", lambda: state["adp"])
    monkeypatch.setattr(strategy_cfg, "get", lambda key, default=None: state["cfg"].get(key, default))
    return state


def test_c1_flag_off_keeps_trading_rules_thresholds(monkeypatch, mr_env):
    from app.api.endpoints import recommendations as rec
    monkeypatch.setattr(settings, "MEAN_REVERSION_CANONICAL_PARAMS_ENABLED", False)
    mr_env["adp"] = _adp(fallback=False)  # OFF 면 적응형도 무시해야 한다
    assert rec._mean_reversion_rsi_thresholds_v2({})[:2] == (40, 30)
    assert rec._mean_reversion_rsi_thresholds_v2({"rsi_bull_max": 33, "rsi_bear_max": 22})[:2] == (33, 22)
    assert rec.is_mean_reversion_candidate(_stock(40), {}, "bull") is True
    assert rec.is_mean_reversion_candidate(_stock(41), {}, "bull") is False
    assert rec.is_mean_reversion_candidate(_stock(31), {}, "bear") is False


def test_c1_flag_on_priority_adaptive_then_cfg_then_settings(monkeypatch, mr_env):
    from app.api.endpoints import recommendations as rec
    monkeypatch.setattr(settings, "MEAN_REVERSION_CANONICAL_PARAMS_ENABLED", True)
    # settings
    b, r, src = rec._mean_reversion_rsi_thresholds_v2({"rsi_bull_max": 1})
    assert (b, r, src) == (settings.MEAN_REVERSION_RSI_THRESHOLD, settings.MEAN_REVERSION_BEAR_RSI_THRESHOLD, "settings")
    # strategy_cfg > settings
    mr_env["cfg"] = {"MEAN_REVERSION_RSI_THRESHOLD": "44", "MEAN_REVERSION_BEAR_RSI_THRESHOLD": "33"}
    assert rec._mean_reversion_rsi_thresholds_v2({})[:2] == (44.0, 33.0)
    # adaptive > strategy_cfg
    mr_env["adp"] = SimpleNamespace(**{**vars(_adp(fallback=False)), "rsi_entry": 38.0, "bear_rsi_entry": 28.0})
    assert rec._mean_reversion_rsi_thresholds_v2({})[:2] == (38.0, 28.0)
    assert rec.is_mean_reversion_candidate(_stock(38), {}, "bull") is True
    assert rec.is_mean_reversion_candidate(_stock(39), {}, "bull") is False


# ═════════════════════════════════════════════════════════════════════════════
# Low: DELETE /trades/pending 은 당일 행을 지우지 않는다
# ═════════════════════════════════════════════════════════════════════════════

@pytest.mark.asyncio
async def test_low_delete_pending_only_before_today():
    from app.api.endpoints import trades as tr

    class _DB(_FakeDB):
        async def commit(self):
            return None

    db = _DB([[]])
    out = await tr.delete_pending_trades(db=db)
    assert out["deleted_count"] == 0
    sql = str(db.stmts[0].compile(compile_kwargs={"literal_binds": False}))
    assert "created_at <" in sql, "당일 이전 조건이 없다 — 당일 PENDING(일일 한도 근거)까지 삭제"