etf/framework/execution/__init__.py

"""
执行层抽象设计

核心组件：
- Executor: 执行器抽象基类
- BacktestExecutor: 回测执行器
- DryRunExecutor: 模拟盘执行器
"""

import pandas as pd
from abc import ABC, abstractmethod
from typing import Dict, Any, Optional, List
from dataclasses import dataclass
from datetime import datetime


@dataclass
class Portfolio:
    """持仓组合"""
    positions: Dict[str, Any]  # {code: Position}
    cash: float
    nav: float
    trades: List[Any]
    
    def get_total_value(self) -> float:
        """获取总价值"""
        position_value = sum(
            pos.quantity * pos.current_price 
            for pos in self.positions.values()
        )
        return self.cash + position_value
    
    def get_position_codes(self) -> List[str]:
        """获取持仓代码列表"""
        return list(self.positions.keys())


class Executor(ABC):
    """
    执行器抽象基类
    
    支持不同执行模式：
    - backtest: 回测模式
    - dry_run: 模拟盘模式
    - live: 实盘模式（TODO）
    """
    
    mode: str = "base"
    
    def __init__(self, config: Optional[Dict] = None):
        self._config = config or {}
        self._portfolio = None
    
    @abstractmethod
    def execute(self, signals: pd.DataFrame, data: pd.DataFrame) -> Portfolio:
        """
        执行信号
        
        Args:
            signals: 信号DataFrame
            data: 价格数据
            
        Returns:
            持仓组合
        """
        pass
    
    @abstractmethod
    def get_mode(self) -> str:
        """获取执行模式"""
        pass
    
    @property
    def portfolio(self) -> Optional[Portfolio]:
        """获取当前持仓"""
        return self._portfolio


class BacktestExecutor(Executor):
    """
    回测执行器
    
    执行回测逻辑：
    - 处理信号
    - 计算净值
    - 记录交易
    """
    
    mode = "backtest"
    
    def __init__(
        self,
        initial_capital: float = 100000.0,
        trade_cost: float = 0.001
    ):
        super().__init__()
        self.initial_capital = initial_capital
        self.trade_cost = trade_cost
    
    def execute(self, signals: pd.DataFrame, data: pd.DataFrame) -> Portfolio:
        """执行回测"""
        # 初始化持仓
        self._portfolio = Portfolio(
            positions={},
            cash=self.initial_capital,
            nav=1.0,
            trades=[]
        )
        
        # 回测逻辑（简化版）
        result = pd.DataFrame(index=signals.index)
        result['nav'] = 1.0
        result['daily_return'] = 0.0
        
        # TODO: 完整回测逻辑迁移
        
        return self._portfolio
    
    def get_mode(self) -> str:
        return "backtest"


class DryRunExecutor(Executor):
    """
    模拟盘执行器
    
    执行模拟交易：
    - 模拟下单
    - 模拟成交
    - 模拟持仓更新
    """
    
    mode = "dry_run"
    
    def __init__(
        self,
        initial_capital: float = 100000.0,
        simulated_exchange = None
    ):
        super().__init__()
        self.initial_capital = initial_capital
        self.simulated_exchange = simulated_exchange
    
    def execute(self, signals: pd.DataFrame, data: pd.DataFrame) -> Portfolio:
        """执行模拟盘"""
        # 初始化持仓
        self._portfolio = Portfolio(
            positions={},
            cash=self.initial_capital,
            nav=1.0,
            trades=[]
        )
        
        # 模拟执行逻辑
        # TODO: 模拟订单执行
        
        return self._portfolio
    
    def get_mode(self) -> str:
        return "dry_run"
    
    def simulate_order(self, code: str, direction: str, quantity: float, price: float):
        """模拟下单"""
        # 记录模拟订单
        print(f"[DRY_RUN] {direction} {quantity} {code} @ {price}")
        
        # 更新持仓
        if direction == 'BUY':
            # 模拟买入
            cost = quantity * price
            if cost <= self._portfolio.cash:
                self._portfolio.cash -= cost
                # TODO: 创建Position对象
        elif direction == 'SELL':
            # 模拟卖出
            if code in self._portfolio.positions:
                # TODO: 平仓逻辑
                pass