from freqtrade.strategy import IStrategy
from freqtrade.strategy.parameters import RealParameter, IntParameter
import talib.abstract as ta
import numpy as np
import pandas as pd
from pandas import DataFrame

from entry_signals.alligator_atr import AlligatorAtrSignal
from entry_signals.ema_crossover import EMACrossoverSignal
from entry_signals.rsi_momentum import RSIMomentumSignal
from entry_signals.vw_macd import VWMacdSignal

from exit_signals.trailing_stop_exit import TrailingStopExit
from exit_signals.ema_cross_exit import EMACrossExit

from risk.dynamic_stoploss import DynamicStoploss



class HybridAlligatorATRRelaxedStrategy(IStrategy):
    # Freqtrade 필수 기본 설정
    timeframe = '5m'
    startup_candle_count = 50

    # 파라미터 (하이퍼옵트 대상)
    sl_atr_multiplier = RealParameter(0.5, 3.0, default=1.5, space='sell', optimize=True, load=True)
    stoploss = -0.23
    stoploss_param = RealParameter(-0.10, -0.01, default=-0.02441, space='sell', optimize=True, load=True)

    minimal_roi = {
        "0":   0.245,
        "26":  0.048,
        "50":  0.021,
        "121": 0
    }

    trailing_stop = True
    trailing_stop_positive = 0.03
    trailing_stop_positive_offset = 0.05
    trailing_only_offset_is_reached = False

    process_only_new_candles = True
    use_custom_stoploss = True

    atr_period      = IntParameter(8, 21,  default=14,  space='buy', optimize=True, load=True)
    vol_multiplier  = RealParameter(1.0, 3.0, default=1.2,  space='buy', optimize=True, load=True)
    volat_threshold = RealParameter(0.003,0.02, default=0.005, space='buy', optimize=True, load=True)
    high_lookback   = IntParameter(1, 7,   default=3,    space='buy', optimize=True, load=True)

    def __init__(self, config: dict) -> None:
        super().__init__(config)
        # 전략별 신호 리스트화 (신호별 파라미터는 각 신호에서 처리 or 전달)
        self.entry_signals = [
            AlligatorAtrSignal(),
            EMACrossoverSignal(),
            RSIMomentumSignal(),
            VWMacdSignal(),
            # ... 필요하면 추가
        ]
        self.exit_signals = [
            TrailingStopExit(),
            EMACrossExit(),
            # ... 필요하면 추가
        ]
        self.risk_modules = [
            DynamicStoploss(),
            # ... 필요하면 추가
        ]

    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        # Alligator + 각종 지표 예시 (진입 신호 모듈에서 추가 지표 쓸 수도 있음)
        hl2 = (dataframe['high'] + dataframe['low']) / 2
        dataframe['jaw']   = pd.Series(ta.EMA(hl2, timeperiod=13), index=dataframe.index).shift(8)
        dataframe['teeth'] = pd.Series(ta.EMA(hl2, timeperiod=8),  index=dataframe.index).shift(5)
        dataframe['lips']  = pd.Series(ta.EMA(hl2, timeperiod=5),  index=dataframe.index).shift(3)
        dataframe['adx']     = ta.ADX(dataframe, timeperiod=14)
        dataframe['plusdi']  = ta.PLUS_DI(dataframe, timeperiod=14)
        dataframe['minusdi'] = ta.MINUS_DI(dataframe, timeperiod=14)
        dataframe['atr']    = ta.ATR(dataframe, timeperiod=self.atr_period.value)
        dataframe['vol_ma'] = dataframe['volume'].rolling(10).mean()
        return dataframe

    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        # 여러 신호 OR/AND 조합 - 예: 하나라도 True면 진입(OR), 다 True여야 진입(AND)
        # 각 신호 generate 함수가 pd.Series(bool) 반환해야 정상 작동
        entry_results = [sig.generate(dataframe, metadata['pair'], {}) for sig in self.entry_signals]
        dataframe['enter_long'] = np.logical_or.reduce(entry_results)  # OR 조합, AND 조합이면 logical_and로!
        return dataframe

    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        exit_results = [sig.generate(dataframe, metadata['pair'], {}) for sig in self.exit_signals]
        dataframe['exit_long'] = np.logical_or.reduce(exit_results)
        return dataframe

    def custom_stoploss(self, pair: str, trade, current_time, current_rate, current_profit, **kwargs) -> float:
        df = self.dp.get_pair_dataframe(pair)
        period = int(self.atr_period.value)
        atr_series = ta.ATR(df, timeperiod=period)
        atr = atr_series.iloc[-1]
        # 여러 risk 모듈을 쓸 경우, 가장 보수적인(최소) 손절로 설정 가능
        stoploss_prices = [risk.calculate_stoploss(trade.open_rate, atr) for risk in self.risk_modules]
        stoploss_price = min(stoploss_prices)
        return stoploss_price / trade.open_rate - 1