import importlib.util
import sys
from pathlib import Path

import pytest

from okx_codex_trader.models import Candle


def load_module():
    path = Path(__file__).resolve().parents[1] / "scripts" / "search_btc_eth_bbmr_risk_variants.py"
    spec = importlib.util.spec_from_file_location("search_btc_eth_bbmr_risk_variants", path)
    assert spec is not None
    module = importlib.util.module_from_spec(spec)
    assert spec.loader is not None
    sys.modules[spec.name] = module
    spec.loader.exec_module(module)
    return module


def test_add_cost_columns_records_net_metrics():
    module = load_module()
    row = {
        "total_return": 0.12,
        "annualized_return": 0.04,
        "max_drawdown": 0.20,
        "calmar": 0.20,
    }

    module.add_cost_columns(row, "maker_taker", 0.0021)

    assert row["cost_model"] == "maker_taker"
    assert row["roundtrip_cost_on_margin"] == pytest.approx(0.0021)
    assert row["net_total_return"] == pytest.approx(0.12)
    assert row["net_annualized_return"] == pytest.approx(0.04)
    assert row["net_max_drawdown"] == pytest.approx(0.20)
    assert row["net_calmar"] == pytest.approx(0.20)


def test_risk_qualified_keeps_recent_horizons_per_cost_model():
    module = load_module()
    pandas = pytest.importorskip("pandas")
    rows = []
    for cost_model, ret_1y in (("maker_taker", 0.11), ("taker_taker", 0.07)):
        for horizon, total_return in (("full", 0.30), ("3y", 0.20), ("1y", ret_1y), ("6m", 0.08), ("3m", 0.06)):
            rows.append(
                {
                    "cost_model": cost_model,
                    "symbol": "BTC",
                    "label": "bbmr-test",
                    "horizon": horizon,
                    "total_return": total_return,
                    "annualized_return": 0.05,
                    "max_drawdown": 0.20,
                    "calmar": 0.25,
                    "trades_per_month": 12.0,
                }
            )

    qualified = module.risk_qualified(pandas.DataFrame(rows)).sort_values("cost_model").reset_index(drop=True)

    assert qualified["cost_model"].tolist() == ["maker_taker", "taker_taker"]
    assert qualified.loc[0, "ret_1y"] == pytest.approx(0.11)
    assert qualified.loc[1, "ret_1y"] == pytest.approx(0.07)


def test_exit_price_for_risk_hit_uses_open_when_long_stop_is_gapped():
    module = load_module()
    position = {"side": "long", "entry_price": 100.0, "stop_price": 99.0}
    candle = Candle(symbol="BTC-USDT-SWAP", ts=1, open=98.0, high=100.0, low=97.5, close=99.5, volume=1.0)

    assert module.exit_price_for_risk_hit(position, candle, None) == pytest.approx(98.0)


def test_exit_price_for_risk_hit_uses_open_when_short_stop_is_gapped():
    module = load_module()
    position = {"side": "short", "entry_price": 100.0, "stop_price": 101.0}
    candle = Candle(symbol="ETH-USDT-SWAP", ts=1, open=102.0, high=103.0, low=99.0, close=100.0, volume=1.0)

    assert module.exit_price_for_risk_hit(position, candle, None) == pytest.approx(102.0)


def test_exit_price_for_risk_hit_prefers_open_take_profit_before_intrabar_stop():
    module = load_module()
    position = {"side": "long", "entry_price": 100.0, "stop_price": 99.0}
    candle = Candle(symbol="BTC-USDT-SWAP", ts=1, open=102.0, high=103.0, low=98.0, close=100.0, volume=1.0)

    assert module.exit_price_for_risk_hit(position, candle, 101.0) == pytest.approx(102.0)