from __future__ import annotations
from typing import Optional, Literal
import pandas as pd
from datetime import datetime
from .models import TradePlan, PositionState

def _hits_level(low: float, high: float, level: float) -> bool:
    return low <= level <= high

def _decide_exit_on_bar(
    side: Literal["long", "short"], low: float, high: float, target: float, stoploss: float,
    tiebreaker: Literal["stoploss_first", "target_first"] = "stoploss_first",
) -> Optional[dict]:
    if side == "long":
        hit_target = high >= target
        hit_stop = low <= stoploss
    else:
        hit_target = low <= target
        hit_stop = high >= stoploss

    if not hit_target and not hit_stop:
        return None
    if hit_target and hit_stop:
        return {"reason": "stoploss" if tiebreaker == "stoploss_first" else "target",
                "price": stoploss if tiebreaker == "stoploss_first" else target}
    return {"reason": "target", "price": target} if hit_target else {"reason": "stoploss", "price": stoploss}

def simulate_trade_from_signal(
    df: pd.DataFrame,
    trade: TradePlan,
    *,
    dt_col: str = "datetime",
    tiebreaker: Literal["stoploss_first", "target_first"] = "stoploss_first",
    lookback_minutes: int = 60,
    state: PositionState,
) -> PositionState:
    
    required = {"open","high","low","close", dt_col}
    if missing := [c for c in required if c not in df.columns]:
        raise ValueError(f"Missing columns: {missing}")

    if trade.status == "No trade":
        return state

    side = trade.type
    entry_at = float(trade.entry_at)
    target = float(trade.target)
    stoploss = float(trade.stoploss)

    ts = pd.to_datetime(df[dt_col])

    entered = state.entered
    exited = state.exited
    entry_time = state.entry_time
    entry_price = state.entry_price
    exit_time = state.exit_time
    exit_price = state.exit_price
    exit_reason = state.exit_reason

    if not entered:
        if side=="long" and entry_at<=stoploss:
            return PositionState(
            entered=entered, entry_time=entry_time, entry_price=entry_price, side=side,
            exited=exited, exit_time=exit_time, exit_price=exit_price, exit_reason=exit_reason,
            pnl_pct=state.pnl_pct, open_position=state.open_position, unrealized_pct=state.unrealized_pct,
            note="Error in pricing: Stoploss is higher than entry price for long side position, please adjust stoploss or entry price"
        )
        elif side=="short" and entry_at>=stoploss:
            return PositionState(
            entered=entered, entry_time=entry_time, entry_price=entry_price, side=side,
            exited=exited, exit_time=exit_time, exit_price=exit_price, exit_reason=exit_reason,
            pnl_pct=state.pnl_pct, open_position=state.open_position, unrealized_pct=state.unrealized_pct,
            note="Error in pricing: Stoploss is lower than entry price for short side position, please adjust stoploss or entry price"
            )

    # iterate last 'lookback_minutes' rows (assumes 1m bars)
    start_idx = max(0, abs(len(df) - int(lookback_minutes)))

    for i in range(start_idx, len(df)):
        row = df.iloc[i]
        time_i, o, h, l, c = ts.iloc[i], float(row['open']), float(row['high']), float(row['low']), float(row['close'])

        if not entered:
            if _hits_level(l, h, entry_at):
                entered = True
                entry_time = time_i
                entry_price = entry_at
                out = _decide_exit_on_bar(side, l, h, target, stoploss, tiebreaker)
                if out:
                    exited = True
                    exit_time = time_i
                    exit_price = out["price"]
                    exit_reason = out["reason"]
                    break
        else:
            out = _decide_exit_on_bar(side, l, h, target, stoploss, tiebreaker)
            if out:
                exited = True
                exit_time = time_i
                exit_price = out["price"]
                exit_reason = out["reason"]
                break

    def _pnl_pct(entry: float, exit_: float, side_: str) -> float:
        raw = (exit_ - entry) / entry
        return (raw if side_ == "long" else -raw) * 100.0

    if entered and exited:
        pnl = round(_pnl_pct(entry_price, exit_price, side), 4)
        return PositionState(
            entered=True, entry_time=entry_time, entry_price=entry_price, side=side,
            exited=True, exit_time=exit_time, exit_price=exit_price, exit_reason=exit_reason,
            pnl_pct=pnl, open_position=False, unrealized_pct=None,
        )

    if entered and not exited:
        last_close = float(df.iloc[-1]["close"]) if len(df) else entry_price
        upnl = round(_pnl_pct(entry_price, last_close, side), 4)
        return PositionState(
            entered=True, entry_time=entry_time, entry_price=entry_price, side=side,
            exited=False, open_position=True, unrealized_pct=upnl,
        )

    return state  # entry level never touched

def slice_intraday(df_1m: pd.DataFrame, start: datetime, end: datetime, dt_col: str = "datetime") -> pd.DataFrame:
    mask = (df_1m[dt_col] >= start) & (df_1m[dt_col] < end)
    out = df_1m.loc[mask].copy()
    out.reset_index(drop=True, inplace=True)
    return out