from typing import Dict, Any
import time
import random
import math
from .base import BaseQuantStrategy, strategy


@strategy
class MovingAverageCrossover(BaseQuantStrategy):
    """이동평균선 교차 전략"""

    @property
    def name(self) -> str:
        return "MovingAverageCrossover"

    @property
    def description(self) -> str:
        return "단기 이동평균선이 장기 이동평균선을 상향 돌파할 때 매수, 하향 돌파할 때 매도하는 전략"

    @property
    def version(self) -> str:
        return "1.0.0"

    @property
    def default_parameters(self) -> Dict[str, Any]:
        return {
            "short_window": 20,
            "long_window": 50,
            "initial_capital": 100000,
            "position_size": 0.1
        }

    def validate_parameters(self, parameters: Dict[str, Any]) -> bool:
        required_params = ["short_window", "long_window", "initial_capital"]
        for param in required_params:
            if param not in parameters:
                return False

        if parameters["short_window"] >= parameters["long_window"]:
            return False

        return True

    def execute(self, parameters: Dict[str, Any] = None) -> Dict[str, Any]:
        if parameters is None:
            parameters = self.default_parameters

        if not self.validate_parameters(parameters):
            raise ValueError("Invalid parameters")

        # 시뮬레이션 실행
        time.sleep(1)  # 실행 시간 시뮬레이션

        # 모의 결과 생성
        profit_rate = random.uniform(-0.15, 0.25)
        trades_count = random.randint(15, 60)
        win_rate = random.uniform(0.45, 0.75)

        return {
            "strategy": self.name,
            "version": self.version,
            "profit_loss": round(parameters["initial_capital"] * profit_rate, 2),
            "profit_rate": round(profit_rate * 100, 2),
            "trades_executed": trades_count,
            "win_rate": round(win_rate, 3),
            "execution_time": "1.2s",
            "parameters_used": parameters,
            "final_capital": round(parameters["initial_capital"] * (1 + profit_rate), 2)
        }


@strategy
class RSIMeanReversion(BaseQuantStrategy):
    """RSI 평균회귀 전략"""

    @property
    def name(self) -> str:
        return "RSIMeanReversion"

    @property
    def description(self) -> str:
        return "RSI 지표를 이용한 평균회귀 전략. RSI가 과매수/과매도 구간에서 반대 방향으로 거래"

    @property
    def version(self) -> str:
        return "1.0.0"

    @property
    def default_parameters(self) -> Dict[str, Any]:
        return {
            "rsi_period": 14,
            "oversold_threshold": 30,
            "overbought_threshold": 70,
            "initial_capital": 100000,
            "position_size": 0.05
        }

    def validate_parameters(self, parameters: Dict[str, Any]) -> bool:
        required_params = ["rsi_period", "oversold_threshold", "overbought_threshold", "initial_capital"]
        for param in required_params:
            if param not in parameters:
                return False

        if not (0 < parameters["oversold_threshold"] < parameters["overbought_threshold"] < 100):
            return False

        return True

    def execute(self, parameters: Dict[str, Any] = None) -> Dict[str, Any]:
        if parameters is None:
            parameters = self.default_parameters

        if not self.validate_parameters(parameters):
            raise ValueError("Invalid parameters")

        # 시뮬레이션 실행
        time.sleep(1.5)  # 실행 시간 시뮬레이션

        # 모의 결과 생성
        profit_rate = random.uniform(-0.10, 0.18)
        trades_count = random.randint(25, 80)
        win_rate = random.uniform(0.40, 0.65)

        return {
            "strategy": self.name,
            "version": self.version,
            "profit_loss": round(parameters["initial_capital"] * profit_rate, 2),
            "profit_rate": round(profit_rate * 100, 2),
            "trades_executed": trades_count,
            "win_rate": round(win_rate, 3),
            "execution_time": "1.5s",
            "parameters_used": parameters,
            "final_capital": round(parameters["initial_capital"] * (1 + profit_rate), 2),
            "max_drawdown": round(random.uniform(0.05, 0.20), 3)
        }


@strategy
class BollingerBandBreakout(BaseQuantStrategy):
    """볼린저 밴드 돌파 전략"""

    @property
    def name(self) -> str:
        return "BollingerBandBreakout"

    @property
    def description(self) -> str:
        return "볼린저 밴드 상한선 돌파시 매수, 하한선 돌파시 매도하는 돌파 전략"

    @property
    def version(self) -> str:
        return "2.0.0"

    @property
    def default_parameters(self) -> Dict[str, Any]:
        return {
            "period": 20,
            "std_dev": 2.0,
            "initial_capital": 100000,
            "position_size": 0.08,
            "stop_loss": 0.05
        }

    def validate_parameters(self, parameters: Dict[str, Any]) -> bool:
        required_params = ["period", "std_dev", "initial_capital"]
        for param in required_params:
            if param not in parameters:
                return False

        if parameters["std_dev"] <= 0 or parameters["period"] <= 0:
            return False

        return True

    def execute(self, parameters: Dict[str, Any] = None) -> Dict[str, Any]:
        if parameters is None:
            parameters = self.default_parameters

        if not self.validate_parameters(parameters):
            raise ValueError("Invalid parameters")

        # 시뮬레이션 실행
        time.sleep(2)  # 실행 시간 시뮬레이션

        # 모의 결과 생성
        profit_rate = random.uniform(-0.20, 0.30)
        trades_count = random.randint(10, 40)
        win_rate = random.uniform(0.35, 0.70)

        return {
            "strategy": self.name,
            "version": self.version,
            "profit_loss": round(parameters["initial_capital"] * profit_rate, 2),
            "profit_rate": round(profit_rate * 100, 2),
            "trades_executed": trades_count,
            "win_rate": round(win_rate, 3),
            "execution_time": "2.0s",
            "parameters_used": parameters,
            "final_capital": round(parameters["initial_capital"] * (1 + profit_rate), 2),
            "sharpe_ratio": round(random.uniform(0.5, 2.5), 2),
            "volatility": round(random.uniform(0.15, 0.35), 3)
        }