from collections import deque
from decimal import Decimal

import pandas as pd

from shared.models import Candle, Signal, OrderSide
from strategies.base import BaseStrategy


class BollingerStrategy(BaseStrategy):
    name: str = "bollinger"

    def __init__(self) -> None:
        super().__init__()
        self._closes: deque[float] = deque(maxlen=500)
        self._period: int = 20
        self._num_std: float = 2.0
        self._min_bandwidth: float = 0.02
        self._quantity: Decimal = Decimal("0.01")
        self._was_below_lower: bool = False
        self._was_above_upper: bool = False

    @property
    def warmup_period(self) -> int:
        return self._period

    def configure(self, params: dict) -> None:
        self._period = int(params.get("period", 20))
        self._num_std = float(params.get("num_std", 2.0))
        self._min_bandwidth = float(params.get("min_bandwidth", 0.02))
        self._quantity = Decimal(str(params.get("quantity", "0.01")))

        if self._period < 2:
            raise ValueError(f"Bollinger period must be >= 2, got {self._period}")
        if self._num_std <= 0:
            raise ValueError(f"Bollinger num_std must be > 0, got {self._num_std}")
        if self._quantity <= 0:
            raise ValueError(f"Quantity must be positive, got {self._quantity}")

        self._init_filters(
            require_trend=False,
            adx_threshold=float(params.get("adx_threshold", 25.0)),
            min_volume_ratio=float(params.get("min_volume_ratio", 0.5)),
            atr_stop_multiplier=float(params.get("atr_stop_multiplier", 2.0)),
            atr_tp_multiplier=float(params.get("atr_tp_multiplier", 3.0)),
        )

    def reset(self) -> None:
        self._closes.clear()
        self._was_below_lower = False
        self._was_above_upper = False

    def _bollinger_conviction(self, price: float, band: float, sma: float) -> float:
        """Map distance from band to conviction (0.1-1.0).

        Further from band (relative to band width) = stronger signal.
        """
        if sma == 0:
            return 0.5
        distance = abs(price - band) / sma
        # Scale: 0% distance -> 0.1, 2%+ distance -> ~1.0
        return min(1.0, max(0.1, distance * 50))

    def on_candle(self, candle: Candle) -> Signal | None:
        self._update_filter_data(candle)
        self._closes.append(float(candle.close))

        if len(self._closes) < self._period:
            return None

        series = pd.Series(list(self._closes))
        sma = series.rolling(window=self._period).mean().iloc[-1]
        std = series.rolling(window=self._period).std().iloc[-1]

        upper = sma + self._num_std * std
        lower = sma - self._num_std * std

        # Bandwidth filter: skip sideways markets
        if sma != 0 and (upper - lower) / sma < self._min_bandwidth:
            return None

        price = float(candle.close)

        # Track band penetration
        if price < lower:
            self._was_below_lower = True
        if price > upper:
            self._was_above_upper = True

        # BUY: was below lower band and recovered back inside
        if self._was_below_lower and price >= lower:
            self._was_below_lower = False
            conviction = self._bollinger_conviction(price, lower, sma)
            signal = Signal(
                strategy=self.name,
                symbol=candle.symbol,
                side=OrderSide.BUY,
                price=candle.close,
                quantity=self._quantity,
                conviction=conviction,
                reason=f"Price recovered above lower Bollinger Band ({lower:.2f})",
            )
            return self._apply_filters(signal)

        # SELL: was above upper band and recovered back inside
        if self._was_above_upper and price <= upper:
            self._was_above_upper = False
            conviction = self._bollinger_conviction(price, upper, sma)
            signal = Signal(
                strategy=self.name,
                symbol=candle.symbol,
                side=OrderSide.SELL,
                price=candle.close,
                quantity=self._quantity,
                conviction=conviction,
                reason=f"Price recovered below upper Bollinger Band ({upper:.2f})",
            )
            return self._apply_filters(signal)

        return None