optimized backtesting effiency

backend/api/routes.py

@@ -55,4 +55,53 @@ def get_indicators(timeframe: int = 5):
         "liquidity": levels,
         "fvgs": fvgs,
         "order_blocks": obs
+    }
+
+@app.get("/api/backtest")
+def get_backtest(timeframe: int = 5, rr: float = 2.5):
+    candles_1m = load_candles("data/data.csv")
+    candles = resample_candles(candles_1m, period=timeframe)
+
+    from strategies.ict_strategy import ICTStrategy
+    strategy = ICTStrategy(
+        session="london",
+        lookback=7,
+        ob_max_age=50,
+        atr_mult=2.5,
+        use_liquidity_sweep=True,
+        sweep_lookback=5,
+    )
+    from engine.backtester import run_backtest
+    trades = run_backtest(candles, strategy, 10000, risk_reward=rr)
+
+    candle_times = [c.time_open.isoformat() for c in candles]
+
+    trades_data = []
+    for t in trades:
+        trades_data.append({
+            "enter_time": t.enter_time.isoformat(),
+            "exit_time": t.exit_time.isoformat(),
+            "enter_price": t.enter_price,
+            "exit_price": t.exit_price,
+            "direction": t.direction,
+            "pnl": t.pnl,
+        })
+
+    total_pnl = sum(t.pnl for t in trades)
+    winners = [t for t in trades if t.pnl > 0]
+    losers = [t for t in trades if t.pnl <= 0]
+
+    return {
+        "trades": trades_data,
+        "candle_times": candle_times,
+        "stats": {
+            "total_trades": len(trades),
+            "winners": len(winners),
+            "losers": len(losers),
+            "win_rate": len(winners) / len(trades) * 100 if trades else 0,
+            "total_pnl": total_pnl,
+            "avg_win": sum(t.pnl for t in winners) / len(winners) if winners else 0,
+            "avg_loss": sum(t.pnl for t in losers) / len(losers) if losers else 0,
+            "risk_reward": rr,
+        }
     }