"""
Live signal generation — applies the RSI Trend strategy to a freshly fetched
candle window and returns a trade signal (or None).

The logic mirrors backtest.strategies.rsi_trend exactly so live and backtest
behaviour stay in sync.
"""

import logging
from typing import Optional

import pandas as pd

from . import config
from engine import indicators as ind

logger = logging.getLogger(__name__)

# ── signal result ─────────────────────────────────────────────────────────────

class Signal:
    __slots__ = ("symbol", "direction", "sl", "tp", "atr", "rsi")

    def __init__(self, symbol: str, direction: str, sl: float, tp: float,
                 atr: float, rsi: float):
        self.symbol    = symbol
        self.direction = direction   # 'long' | 'short'
        self.sl        = sl
        self.tp        = tp
        self.atr       = atr
        self.rsi       = rsi

    def __repr__(self) -> str:
        return (f"Signal({self.symbol} {self.direction.upper()}  "
                f"sl={self.sl:.5f}  tp={self.tp:.5f}  rsi={self.rsi:.1f})")


# ── signal check ─────────────────────────────────────────────────────────────

def check(df: pd.DataFrame, symbol: str) -> Optional[Signal]:
    """
    Expects a DataFrame with columns [open, high, low, close] indexed by time,
    with at least (LOOKBACK) rows.  Returns a Signal or None.

    We check bar [-2] (the last completed bar) relative to bar [-3] (prev).
    Bar [-1] is the currently forming bar — we never use it for signals.
    """
    if len(df) < config.LOOKBACK:
        logger.debug("%s: insufficient bars (%d < %d)", symbol, len(df), config.LOOKBACK)
        return None

    # M15 indicators on full window
    close = df["close"]
    rsi_s = ind.rsi(close, config.RSI_PERIOD)
    atr_s = ind.atr(df, config.ATR_PERIOD)

    # H1 trend from resampled M15
    h1     = close.resample("1h", label="left", closed="left").last().dropna()
    ema_f  = ind.ema(h1, config.TREND_FAST)
    ema_s  = ind.ema(h1, config.TREND_SLOW)
    trend  = (ema_f - ema_s).reindex(df.index, method="ffill")

    # Use second-to-last bar as signal bar (last fully closed bar)
    bar   = df.iloc[-2]
    prev  = df.iloc[-3]
    rsi_now  = rsi_s.iloc[-2]
    rsi_prev = rsi_s.iloc[-3]
    atr_val  = atr_s.iloc[-2]
    trend_val = trend.iloc[-2]

    if any(pd.isna(v) for v in [rsi_now, rsi_prev, atr_val, trend_val]):
        return None

    # session filter on signal bar
    hour = bar.name.hour
    if not (config.SESSION_START <= hour < config.SESSION_END):
        return None

    ref = bar["close"]

    if trend_val > 0 and rsi_prev < config.OS_LEVEL and rsi_now >= config.OS_LEVEL:
        sl = ref - config.SL_ATR * atr_val
        tp = ref + config.TP_ATR * atr_val
        return Signal(symbol, "long",  sl, tp, atr_val, rsi_now)

    if trend_val < 0 and rsi_prev > config.OB_LEVEL and rsi_now <= config.OB_LEVEL:
        sl = ref + config.SL_ATR * atr_val
        tp = ref - config.TP_ATR * atr_val
        return Signal(symbol, "short", sl, tp, atr_val, rsi_now)

    return None