from __future__ import annotations

import pandas as pd

from .constants import TREND_BEAR, TREND_BULL


def backtest_signals(df: pd.DataFrame) -> dict[str, float | int]:
    if len(df) < 4:
        return {"trades": 0, "wins": 0, "losses": 0, "win_rate": 0.0}

    trend_series = df["trend_state"]
    trend_change = trend_series != trend_series.shift(1)
    signal_idx = df.index[trend_change & trend_series.isin([TREND_BULL, TREND_BEAR])]

    wins = 0
    losses = 0

    for idx in signal_idx:
        pos = df.index.get_loc(idx)
        if pos + 1 >= len(df):
            continue

        entry_close = float(df.iloc[pos]["Close"])
        next_close = float(df.iloc[pos + 1]["Close"])
        signal_trend = df.iloc[pos]["trend_state"]

        if signal_trend == TREND_BULL:
            wins += int(next_close > entry_close)
            losses += int(next_close <= entry_close)
        elif signal_trend == TREND_BEAR:
            wins += int(next_close < entry_close)
            losses += int(next_close >= entry_close)

    trades = wins + losses
    win_rate = (wins / trades * 100.0) if trades else 0.0
    return {"trades": trades, "wins": wins, "losses": losses, "win_rate": round(win_rate, 2)}