#!/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()