from __future__ import annotations

import pandas as pd

from web_core.analytics import backtest_signals
from web_core.constants import TREND_BEAR, TREND_BULL, TREND_NEUTRAL


def test_backtest_signals_supports_cost_and_hold_controls() -> None:
    idx = pd.date_range("2025-01-01", periods=8, freq="D")
    df = pd.DataFrame(
        {
            "Close": [100.0, 101.0, 103.0, 104.0, 102.0, 99.0, 97.0, 98.0],
            "trend_state": [
                TREND_NEUTRAL,
                TREND_BULL,
                TREND_BULL,
                TREND_BEAR,
                TREND_BEAR,
                TREND_BULL,
                TREND_BULL,
                TREND_BULL,
            ],
        },
        index=idx,
    )

    out = backtest_signals(
        df,
        slippage_bps=5.0,
        fee_bps=2.0,
        stop_loss_pct=2.0,
        take_profit_pct=3.0,
        min_hold_bars=1,
        max_hold_bars=3,
    )

    assert out["trades"] >= 1
    assert "avg_pnl_pct" in out