"""walk_forward: 실전 청산 모델(kr_backtest_engine)을 돌리고, 엔진이 소비하는 키만 탐색한다."""
import asyncio
from datetime import date

import pytest

from app.core.config import settings
from app.services import walk_forward as wf
from app.services.kr_backtest_engine import (
    BacktestMetrics, BacktestResult, KrBacktestEngine, MeanReversionBacktest,
)


class _Trial:
    def __init__(self):
        self.suggested = []

    def suggest_int(self, name, lo, hi):
        self.suggested.append(name)
        return lo

    def suggest_float(self, name, lo, hi, step=None):
        self.suggested.append(name)
        return lo


def _cfg(**kw):
    return wf.WalkForwardConfig(stock_codes=["005930"], start_date=date(2025, 1, 1),
                                end_date=date(2025, 12, 31), **kw)


@pytest.fixture(autouse=True)
def _block_toy_engine(monkeypatch):
    """구 장난감 엔진 호출은 즉시 예외 (거짓 통과 방지)."""
    import app.services.backtest_engine as toy

    def boom(*a, **k):
        raise AssertionError("장난감 backtest_engine 사용")
    monkeypatch.setattr(toy.BacktestEngine, "run_backtest", boom)


def test_search_space_only_engine_consumed_keys():
    t = _Trial()
    params = wf.WalkForwardOptimizer()._build_params_from_trial_v2(t)
    consumed = set(MeanReversionBacktest().default_params())
    assert set(params) <= consumed, set(params) - consumed
    assert "MEAN_REVERSION_RSI_THRESHOLD" not in params
    assert params["stop_loss_pct"] > 0


def test_run_uses_kr_engine_and_normalizes_units(monkeypatch):
    seen = {}

    async def fake_run(self, **kw):
        seen.update(kw)
        return BacktestResult(metrics=BacktestMetrics(
            total_return_pct=10.0, max_drawdown_pct=-5.0, win_rate=60.0,
            sharpe_ratio=1.2, total_trades=7))
    monkeypatch.setattr(KrBacktestEngine, "run", fake_run)

    out = asyncio.run(wf.WalkForwardOptimizer()._run_single_backtest_v2(
        ["005930"], date(2025, 1, 1), date(2025, 6, 1),
        {"bb_period": 20}, _cfg(position_size=0.5, max_positions=99)))
    assert out["mdd_pct"] == pytest.approx(-0.05)
    assert out["win_rate"] == pytest.approx(0.6)
    assert out["total_return_pct"] == pytest.approx(0.10)
    assert out["total_trades"] == 7
    assert seen["params"]["position_size_pct"] <= settings.MAX_POSITION_SIZE
    assert seen["params"]["max_positions"] <= settings.MAX_HOLDINGS_COUNT


def test_default_params_from_settings():
    d = wf.WalkForwardOptimizer._default_params_v2()
    assert d["stop_loss_pct"] == abs(settings.STOP_LOSS_PERCENT)
    assert d["atr_stop_multiplier"] == settings.ATR_STOP_MULTIPLIER


def test_recommended_params_keys():
    wr = wf.WindowResult(0, "a", "b", "c", "d", {"bb_period": 18, "atr_stop_multiplier": 2.0,
                         "stop_loss_pct": 5.0}, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0.0, False)
    rec = wf.WalkForwardOptimizer()._compute_recommended_params([wr])
    assert rec == {"bb_period": 18, "atr_stop_multiplier": 2.0, "stop_loss_pct": 5.0}