refactor: enhance Optuna backtesting framework, optimize orderbook filtering, and update database management utilities.

scratch/print_optuna_results.py

@@ -0,0 +1,45 @@
+import os
+import glob
+import json
+import fnmatch
+
+results_dir = "kis_trader/backtest/results"
+strats = ["MOMENTUM", "BREAKOUT", "SCALP", "TAIL"]
+
+for strat in strats:
+    # Find latest json file for this strategy
+    pattern = f"optuna_{strat.lower()}_fast_20*.json"
+    files = glob.glob(os.path.join(results_dir, pattern))
+    if not files:
+        print(f"[{strat}] No JSON file found.")
+        continue
+        
+    latest_file = max(files, key=os.path.getmtime)
+    
+    with open(latest_file, 'r', encoding='utf-8') as f:
+        data = json.load(f)
+        
+    ob = data.get("orderbook_recommend", {})
+    ws = data.get("whipsaw_recommend", {})
+    
+    print(f"=== {strat} ===")
+    if ob.get("ok"):
+        p = ob.get("params", {})
+        s = ob.get("recommended_stats", {})
+        print(f"  [호가 필터]")
+        print(f"    - 승률: {s.get('win_rate', 0)}% (모수: {s.get('count', 0)}건)")
+        print(f"    - PnL 보정치: +{s.get('pnl_diff', 0):,}원")
+        print(f"    - 파라미터: max_spread={p.get('orderbook_max_spread_pct')}%, min_ratio={p.get('orderbook_min_bid_ask_ratio')}, ask_mult={p.get('orderbook_entry_ask_max_mult')}, bid_mult={p.get('orderbook_entry_bid_depth_mult')}")
+    else:
+        print(f"  [호가 필터] 추천 없음 ({ob.get('reason', 'N/A')})")
+        
+    if ws.get("ok"):
+        p = ws.get("params", {})
+        s = ws.get("recommended_stats", {})
+        print(f"  [휩쏘 필터]")
+        print(f"    - 승률: {s.get('win_rate', 0)}% (모수: {s.get('count', 0)}건)")
+        print(f"    - PnL 보정치: +{s.get('pnl_diff', 0):,}원")
+        print(f"    - 파라미터: subbar={p.get('whipsaw_subbar_sec')}초, lookback={p.get('whipsaw_lookback_sec')}초, dip_pct={p.get('whipsaw_dip_pct')}")
+    else:
+        print(f"  [휩쏘 필터] 추천 없음 ({ws.get('reason', 'N/A')})")
+    print("")