AiTradeSystem — 全天候量化生命周期

# alerts/notification_engine.py — NotificationEngine 核心

class NotificationEngine:
    async def send(self, alert: Alert):
        # 优先级路由：CRITICAL/HIGH → Telegram+Webhook
        #             NORMAL → Email+Webhook
        tasks = []
        if alert.priority <= Priority.HIGH:
            tasks.append(_send_telegram(alert))   # 毫秒级触达手机
        if alert.priority == Priority.NORMAL:
            tasks.append(_send_email(alert))       # HTML富文本报告
        if "webhook" in alert.channels:
            tasks.append(_send_webhook(alert))     # 接入本地大屏
        await asyncio.gather(*tasks, return_exceptions=True)

    # 快捷方法
    async def signal_alert(self, symbol, signal, price, reason, strategy):
        await self.send(Alert(
            title=f"{'🟢买入' if signal=='BUY' else '🔴卖出'} {symbol}",
            body=f"策略:{strategy}\n信号:{signal}\n价格:${price:.2f}\n理由:{reason}",
            priority=Priority.HIGH,
            channels=["telegram", "webhook"],
        ))

    async def premarket_report(self, symbol, text, html):
        await self.send(Alert(
            title=f"📋 {symbol} 盘前交易剧本",
            body=text, html_body=html,
            priority=Priority.NORMAL,        # → Email 富文本报告
            channels=["email", "telegram", "webhook"],
        ))

# strategy/indicators.py — 修复 BUG-1 (rolling_high) & BUG-4 (daily_vwap)

def rolling_high(series, period):
    """修复 BUG-1: 不覆写原始列，内置 shift(1) 防前视"""
    return series.rolling(period).max().shift(1)   # shift已内置！

def daily_vwap(df):
    """修复 BUG-4: 每日重置 VWAP（按 index.normalize() 分组）"""
    typical = (df["High"] + df["Low"] + df["Close"]) / 3
    dates = df.index.normalize()
    vwap_vals = pd.Series(index=df.index, dtype=float)
    for date, grp_idx in df.groupby(dates).groups.items():
        tp = typical.loc[grp_idx]
        vol = df["Volume"].loc[grp_idx]
        # 每个交易日独立累计，互不影响
        vwap_vals.loc[grp_idx] = (tp * vol).cumsum() / (vol.cumsum() + 1e-10)
    return vwap_vals

# 修复 BUG-5: 策略信号全部基于 shift(1)
def strategy_trend(df, fast=12, slow=26):
    prev_fast = ema(df["Close"], fast).shift(1)   # 前一根已确认
    prev_slow = ema(df["Close"], slow).shift(1)
    df["Signal"] = 0
    df.loc[prev_fast > prev_slow, "Signal"] = 1
    df.loc[prev_fast < prev_slow, "Signal"] = -1
    return df

# backtest/engine.py — 修复 BUG-2 (胜率) & BUG-6 (equity_curve)

class BacktestEngine:
    def run(self, df, symbol, strategy_name, params=None, ...):
        equity = np.empty(len(df))   # 修复 BUG-6: 与 df 等长

        for i in range(len(df)):
            ...
            # 每根 K 线统一记录权益（含未实现 PnL）
            equity[i] = capital + position * price if position > 0 else capital

    def _compute_metrics(self, result):
        pnl_pcts = np.array([t.pnl_pct for t in trades])
        wins = pnl_pcts[pnl_pcts > 0]    # 修复 BUG-2: 按 PnL% 判断
        losses = pnl_pcts[pnl_pcts <= 0]

        result.win_rate = len(wins) / len(trades) * 100
        result.profit_factor = wins.sum() / abs(losses.sum())  # 真实盈亏比

        # Sharpe / Sortino / Calmar（均基于正确 equity_curve）
        rets = pd.Series(equity).pct_change().dropna()
        result.sharpe = rets.mean() / rets.std() * np.sqrt(252)

# .env 配置说明（复制 .env.example 填入真实值）

# ── Telegram Bot ────────────────────────────────
# 1. 在 @BotFather 创建 Bot → 获取 TOKEN
# 2. 给 Bot 发消息 → 访问 /getUpdates → 获取 chat_id
TELEGRAM_TOKEN=7123456789:AAF_your_token
TELEGRAM_CHAT_ID=123456789

# ── Gmail App Password（不是登录密码！）────────
# Gmail → 账号 → 安全 → 两步验证 → 应用专用密码（16位）
EMAIL_SENDER=you@gmail.com
EMAIL_PASSWORD=xxxx xxxx xxxx xxxx
EMAIL_RECIPIENT=target@example.com

# ── Webhook（接入本地 Open WebUI / 仪表盘）──────
WEBHOOK_URL=http://localhost:8080/webhook/ait
WEBHOOK_SECRET=your_secret_here

# ── FMP API（免费250次/天，新闻+数据）──────────
FMP_API_KEY=your_fmp_key

# ── 风控参数 ─────────────────────────────────────
CAPITAL_USDC=100000

# 测试: python main.py --test-alerts
# 离线回测: python main.py --backtest
# 全天候守护: python main.py