import os
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional

_PROJECT_DIR = Path(__file__).resolve().parent

try:
    from dotenv import load_dotenv
    load_dotenv()
except ImportError:
    pass


@dataclass
class IBConfig:
    host: str = os.getenv("IB_HOST", "127.0.0.1")
    port: int = int(os.getenv("IB_PORT", "4001"))
    client_id: int = int(os.getenv("IB_CLIENT_ID", "1"))
    account: Optional[str] = os.getenv("IB_ACCOUNT", "U4845070")
    is_paper: bool = os.getenv("IB_PAPER", "false").lower() == "true"

    @property
    def port_label(self) -> str:
        if self.port == 4002:
            return "Gateway Paper (4002)"
        elif self.port == 4001:
            return "Gateway Live (4001)"
        elif self.port == 7497:
            return "TWS Paper (7497)"
        elif self.port == 7496:
            return "TWS Live (7496)"
        return f"Unknown ({self.port})"


@dataclass
class StockStrategyConfig:
    enabled: bool = False  # MAStock disabled 2026-08-11: +101.66(ShortTerm)/-19.98(MeanRev)/-65.47(MAStock) since 08-03
    symbols: list[str] = field(default_factory=lambda: ["AMZN", "AAPL", "NVDA", "NOK"])
    currency: str = "USD"
    exchange: str = "SMART"
    bar_size: str = "1 min"
    lookback_days: int = 5
    fast_ma_period: int = 20
    slow_ma_period: int = 50
    trade_value_usd: float = 2000.0  # per-trade dollar amount; qty = floor(value / price)
    min_profit_pct: float = 1.5
    stop_loss_pct: float = 2.5
    use_hard_stop: bool = True  # place real GTC STP orders at the exchange
    entry_confirm_bars: int = 2  # entry signal must hold for N consecutive bars
    stop_cooldown_minutes: int = 30  # no re-entry on same symbol for N min after a stop-out
    use_trailing_stop: bool = True  # once profit >= min_profit, trail the stop below the peak high
    trailing_stop_pct: float = 2.0  # trailing stop distance below peak high
    adx_min: float = 30.0  # ADX trend filter for entries (was 25; 08-06 raised to avoid weak-trend whipsaw)
    require_slow_ma_slope: bool = True  # only enter if the slow MA is itself rising (no knife-catching in a downtrend) high


@dataclass
class ShortTermConfig:
    enabled: bool = True
    symbols: list[str] = field(default_factory=lambda: ["AMZN", "AAPL", "NVDA", "NOK"])
    currency: str = "USD"
    exchange: str = "SMART"
    bar_size: str = "1 min"
    lookback_days: int = 5
    fast_ma_period: int = 5
    slow_ma_period: int = 10
    trade_value_usd: float = 2000.0
    max_hold_days: int = 0  # 0 = unlimited hold (08-05 撤销 5 天上限)
    min_profit_pct: float = 1.5
    stop_loss_pct: float = 2.5
    use_hard_stop: bool = True
    entry_confirm_bars: int = 2
    stop_cooldown_minutes: int = 30
    use_trailing_stop: bool = True
    trailing_stop_pct: float = 2.0


@dataclass
class ForexStrategyConfig:
    enabled: bool = False
    pairs: list[str] = field(default_factory=lambda: ["EUR.USD", "GBP.USD"])
    exchange: str = "IDEALPRO"
    bar_size: str = "1 min"
    lookback_days: int = 5
    fast_ma_period: int = 12
    slow_ma_period: int = 26
    trade_units: int = 3000
    stop_loss_pct: float = 1.0


@dataclass
class MeanReversionConfig:
    enabled: bool = True
    symbols: list[str] = field(default_factory=lambda: ["AMZN", "AAPL", "NVDA", "NOK"])
    currency: str = "USD"
    exchange: str = "SMART"
    bar_size: str = "1 min"
    lookback_days: int = 5
    trade_value_usd: float = 2000.0
    rsi_period: int = 14
    rsi_oversold: float = 30.0
    rsi_overbought: float = 70.0
    bb_period: int = 20
    bb_std: float = 2.0
    rapid_drop_pct: float = 1.0
    rapid_drop_bars: int = 5
    recovery_pct: float = 1.5
    min_profit_pct: float = 1.5
    stop_loss_pct: float = 2.5
    use_hard_stop: bool = True
    entry_confirm_bars: int = 2
    stop_cooldown_minutes: int = 30
    use_trailing_stop: bool = True
    trailing_stop_pct: float = 2.0
    trend_ma_period: int = 50  # mean-reversion buys only above this SMA


@dataclass
class AppConfig:
    ib: IBConfig = field(default_factory=IBConfig)
    stock: StockStrategyConfig = field(default_factory=StockStrategyConfig)
    short_term: ShortTermConfig = field(default_factory=ShortTermConfig)
    forex: ForexStrategyConfig = field(default_factory=ForexStrategyConfig)
    mean_reversion: MeanReversionConfig = field(default_factory=MeanReversionConfig)
    max_retries: int = 5
    retry_delay: int = 5
    loop_interval: float = 60.0
    order_timeout: float = 30.0
    max_positions: int = 12  # global cap on concurrent open lots across all strategies
    max_daily_loss: float = 150.0  # stop opening new positions for the day beyond this realized loss
    sell_only: bool = False  # liquidation mode: no new buys, strategies only manage exits
    max_symbol_value_usd: float = 2300.0  # per-symbol total position value cap (all strategies combined)
    sell_cooldown_minutes: int = 30  # global: no strategy may (re)buy a symbol within N min of ANY sell
    sell_improvement_pct: float = 0.5  # beyond the cooldown, re-buy only if price is >=0.5% below last sell
    sell_improvement_window_minutes: int = 120  # how long the price-improvement rule applies after a sell
    symbol_trade_value_usd: dict[str, float] = field(
        # per-symbol per-trade dollar value override (halved for gap-prone NOK, 08-06)
        default_factory=lambda: {"NOK": 1000.0}
    )
    # absolute path: independent of the working directory the bot is started from
    state_file: str = str(_PROJECT_DIR / "bot_state.json")


config = AppConfig()