from __future__ import annotations
from dataclasses import dataclass
import pandas as pd
from market_costs import okx_fee, estimate_slippage_rate
from intrabar import entry_slippage_row


@dataclass
class TradeState:
    cash: float = 1000.0
    qty: float = 0.0
    entry_px: float | None = None
    max_px: float | None = None
    stop_loss_frac: float = 0.02
    fee_bps: float = 10.0
    slippage_bps: float = 2.0


def enter_long(state: TradeState, price: float) -> dict:
    if state.qty > 0:
        return {}
    px = entry_slippage_row(price, 0.0, state.slippage_bps)
    qty = state.cash / px
    fee = okx_fee(state.fee_bps, state.cash)
    state.qty = max(qty - fee / px, 0.0)
    state.cash = 0.0
    state.entry_px = px
    state.max_px = px
    return {"side": "BUY", "price": px, "qty": state.qty, "fee": fee}


def maybe_trailing_stop(state: TradeState, price: float) -> float:
    if state.qty <= 0:
        return float("inf")
    state.max_px = max(state.max_px or price, price)
    trail_px = state.max_px * (1.0 - state.stop_loss_frac)
    return trail_px


def exit_long(state: TradeState, price: float) -> dict:
    if state.qty <= 0:
        return {}
    notional = state.qty * price
    slip = estimate_slippage_rate(state.slippage_bps, notional)
    fee = okx_fee(state.fee_bps, notional)
    cash_back = notional - slip - fee
    event = {"side": "SELL", "price": price, "qty": state.qty, "fee": fee, "slippage": slip}
    state.cash = cash_back
    state.qty = 0.0
    state.entry_px = None
    state.max_px = None
    return event