fix: Fix max drawdown calculation and pandas fillna compatibility

- Fix max drawdown calculation in dashboard to use equity curve instead of cumulative profit
- Add pandas fillna(method=...) compatibility fix for older indicator code
- Cap drawdown percentage at 10000% to avoid display issues

Author: tianhe

backend_api_python/app/routes/dashboard.py

@@ -113,9 +113,12 @@ def _calc_pnl_percent(entry_price: float, size: float, pnl: float, leverage: flo
         return 0.0
 
 
-def _compute_performance_stats(trades: List[Dict[str, Any]]) -> Dict[str, Any]:
+def _compute_performance_stats(trades: List[Dict[str, Any]], initial_capital: float = 0.0) -> Dict[str, Any]:
     """
     Compute performance statistics from trade history.
+    Args:
+        trades: List of trade records
+        initial_capital: Initial capital for calculating equity curve (default: 0.0, will use cumulative profit peak as baseline)
     Returns: {
         total_trades, winning_trades, losing_trades, win_rate,
         total_profit, total_loss, profit_factor,
@@ -163,23 +166,49 @@ def _compute_performance_stats(trades: List[Dict[str, Any]]) -> Dict[str, Any]:
     max_win = max(profits) if profits else 0.0
     max_loss = min(profits) if profits else 0.0
 
-    # Calculate max drawdown from cumulative equity
-    cumulative = []
-    acc = 0.0
+    # Calculate max drawdown from equity curve (initial_capital + cumulative profit)
+    # This ensures proper percentage calculation even when cumulative profit is negative
+    cumulative_profit = 0.0
+    equity_curve = []
     for p in profits:
-        acc += p
-        cumulative.append(acc)
+        cumulative_profit += p
+        equity = initial_capital + cumulative_profit
+        equity_curve.append(equity)
 
-    peak = 0.0
+    # Calculate max drawdown from equity curve
+    peak_equity = initial_capital if initial_capital > 0 else (equity_curve[0] if equity_curve else 0.0)
     max_drawdown = 0.0
-    for val in cumulative:
-        if val > peak:
-            peak = val
-        dd = peak - val
-        if dd > max_drawdown:
-            max_drawdown = dd
-
-    max_drawdown_pct = (max_drawdown / peak * 100) if peak > 0 else 0.0
+    for equity in equity_curve:
+        if equity > peak_equity:
+            peak_equity = equity
+        # Drawdown is the drop from peak
+        drawdown = peak_equity - equity
+        if drawdown > max_drawdown:
+            max_drawdown = drawdown
+
+    # Calculate drawdown percentage: drawdown / peak_equity * 100
+    # If peak_equity is 0 or very small, use a fallback calculation
+    if peak_equity > 0:
+        max_drawdown_pct = (max_drawdown / peak_equity * 100)
+    elif initial_capital > 0:
+        # Fallback: use initial capital as baseline
+        max_drawdown_pct = (max_drawdown / initial_capital * 100) if initial_capital > 0 else 0.0
+    else:
+        # Last resort: if no initial capital and peak is 0, calculate from cumulative profit peak
+        cumulative = []
+        acc = 0.0
+        for p in profits:
+            acc += p
+            cumulative.append(acc)
+        peak_profit = max(cumulative) if cumulative else 0.0
+        if peak_profit > 0:
+            max_drawdown_pct = (max_drawdown / peak_profit * 100)
+        else:
+            max_drawdown_pct = 0.0
+    
+    # Cap drawdown percentage at reasonable maximum (e.g., 10000%) to avoid display issues
+    if max_drawdown_pct > 10000:
+        max_drawdown_pct = 10000.0
 
     # Best/worst day
     day_profits: Dict[str, float] = {}
@@ -243,9 +272,9 @@ def _compute_strategy_stats(trades: List[Dict[str, Any]], strategies: List[Dict[
 
     result = []
     for sid, strades in sid_to_trades.items():
-        stats = _compute_performance_stats(strades)
-        total_pnl = sum(_safe_float(t.get("profit"), 0.0) for t in strades)
         capital = sid_to_capital.get(sid, 0.0)
+        stats = _compute_performance_stats(strades, initial_capital=capital)
+        total_pnl = sum(_safe_float(t.get("profit"), 0.0) for t in strades)
         roi = (total_pnl / capital * 100) if capital > 0 else 0.0
 
         result.append({
@@ -374,20 +403,20 @@ def _truthy(v: Any) -> bool:
                 trade['created_at'] = int(trade['created_at'].timestamp())
             recent_trades.append(trade)
 
-        # Compute performance statistics
-        perf_stats = _compute_performance_stats(recent_trades)
-
-        # Compute per-strategy statistics
-        strategy_stats = _compute_strategy_stats(recent_trades, strategies)
-
-        # Total equity/pnl (best-effort)
+        # Total equity/pnl (best-effort) - calculate before performance stats for drawdown calculation
         total_initial_capital = 0.0
         for s in strategies:
             try:
                 total_initial_capital += float(s.get("initial_capital") or 0.0)
             except Exception:
                 pass
 
+        # Compute performance statistics with initial capital for proper drawdown calculation
+        perf_stats = _compute_performance_stats(recent_trades, initial_capital=total_initial_capital)
+
+        # Compute per-strategy statistics
+        strategy_stats = _compute_strategy_stats(recent_trades, strategies)
+
         # Include realized PnL from trades
         total_realized_pnl = sum(_safe_float(t.get("profit"), 0.0) for t in recent_trades)
         total_pnl = float(total_unrealized_pnl + total_realized_pnl)

backend_api_python/app/services/trading_executor.py

@@ -1888,8 +1888,27 @@ def safe_import(name, *args, **kwargs):
             pre_import_code = "import numpy as np\nimport pandas as pd\n"
             exec(pre_import_code, exec_env)
 
+            # 兼容性修复：将旧版pandas的fillna(method=...)语法转换为新版语法
+            # pandas 2.0+ 移除了 fillna() 的 method 参数，需要使用 ffill() 或 bfill()
+            # 旧语法: df.fillna(method='ffill') 或 df.fillna(method="ffill")
+            # 新语法: df.ffill()
+            import re
+            compatibility_fixed_code = indicator_code
+            # 替换 fillna(method='ffill') 或 fillna(method="ffill") 为 ffill()
+            compatibility_fixed_code = re.sub(
+                r'\.fillna\(\s*method\s*=\s*["\']ffill["\']\s*\)',
+                '.ffill()',
+                compatibility_fixed_code
+            )
+            # 替换 fillna(method='bfill') 或 fillna(method="bfill") 为 bfill()
+            compatibility_fixed_code = re.sub(
+                r'\.fillna\(\s*method\s*=\s*["\']bfill["\']\s*\)',
+                '.bfill()',
+                compatibility_fixed_code
+            )
+            
             # 这里的 safe_exec_code 假设已存在
-            exec(indicator_code, exec_env)
+            exec(compatibility_fixed_code, exec_env)
 
             executed_df = exec_env.get('df', df)