PnL in reward, show leveraged power in dash (broken)

2025-07-29 17:42:00 +03:00
parent d35530a9e9
commit 3a532a1220
5 changed files with 553 additions and 49 deletions
--- a/test_dashboard_data_flow.py
+++ b/test_dashboard_data_flow.py
@ -0,0 +1,90 @@
+#!/usr/bin/env python3
+"""
+Test script to debug dashboard data flow issues
+
+This script tests if the dashboard can properly retrieve and display model data.
+"""
+
+import sys
+import os
+sys.path.append(os.path.dirname(os.path.abspath(__file__)))
+
+import logging
+logging.basicConfig(level=logging.DEBUG)
+
+from web.clean_dashboard import CleanTradingDashboard
+from core.orchestrator import TradingOrchestrator
+from core.data_provider import DataProvider
+
+def test_dashboard_data_flow():
+    """Test if dashboard can retrieve model data correctly"""
+    
+    print("🧪 DASHBOARD DATA FLOW TEST")
+    print("=" * 50)
+    
+    try:
+        # Initialize components
+        data_provider = DataProvider()
+        orchestrator = TradingOrchestrator(data_provider=data_provider)
+        
+        print(f"✅ Orchestrator initialized")
+        print(f"   Model registry models: {list(orchestrator.model_registry.get_all_models().keys())}")
+        print(f"   Model toggle states: {list(orchestrator.model_toggle_states.keys())}")
+        
+        # Initialize dashboard
+        dashboard = CleanTradingDashboard(
+            data_provider=data_provider,
+            orchestrator=orchestrator
+        )
+        
+        print(f"✅ Dashboard initialized")
+        
+        # Test available models
+        available_models = dashboard._get_available_models()
+        print(f"   Available models: {list(available_models.keys())}")
+        
+        # Test training metrics
+        print("\n📊 Testing training metrics...")
+        toggle_states = {}
+        for model_name in available_models.keys():
+            toggle_states[model_name] = orchestrator.get_model_toggle_state(model_name)
+        
+        print(f"   Toggle states: {list(toggle_states.keys())}")
+        
+        metrics_data = dashboard._get_training_metrics(toggle_states)
+        print(f"   Metrics data type: {type(metrics_data)}")
+        
+        if metrics_data and isinstance(metrics_data, dict):
+            print(f"   Metrics keys: {list(metrics_data.keys())}")
+            if 'loaded_models' in metrics_data:
+                loaded_models = metrics_data['loaded_models']
+                print(f"   Loaded models count: {len(loaded_models)}")
+                for model_name, model_info in loaded_models.items():
+                    print(f"     - {model_name}: active={model_info.get('active', False)}")
+            else:
+                print("   ❌ No 'loaded_models' in metrics_data!")
+        else:
+            print(f"   ❌ Invalid metrics_data: {metrics_data}")
+        
+        # Test component manager formatting
+        print("\n🎨 Testing component manager...")
+        formatted_components = dashboard.component_manager.format_training_metrics(metrics_data)
+        print(f"   Formatted components type: {type(formatted_components)}")
+        print(f"   Formatted components count: {len(formatted_components) if formatted_components else 0}")
+        
+        if formatted_components:
+            print("   ✅ Component manager returned formatted data")
+        else:
+            print("   ❌ Component manager returned empty data")
+        
+        print("\n🚀 Dashboard data flow test completed!")
+        return True
+        
+    except Exception as e:
+        print(f"❌ Test failed with error: {e}")
+        import traceback
+        traceback.print_exc()
+        return False
+
+if __name__ == "__main__":
+    test_dashboard_data_flow()