Build Digital Twins for Automotive Electronics with Synopsys eDT and MLflow

                      
                     
import os
import logging
from typing import Dict, Any
from sklearn.linear_model import LinearRegression
import mlflow
import mlflow.sklearn

# Configure logging
logging.basicConfig(level=logging.INFO)

# Configuration
DATABASE_URL: str = os.getenv('DATABASE_URL')
MLFLOW_TRACKING_URI: str = os.getenv('MLFLOW_TRACKING_URI')

# Initialize MLflow
mlflow.set_tracking_uri(MLFLOW_TRACKING_URI)

# Function to build digital twin model
def build_digital_twin(data: Dict[str, Any]) -> None:
    try:
        # Prepare data
        X = data['features']
        y = data['target']
        model = LinearRegression()
        model.fit(X, y)
        
        # Log the model
        mlflow.sklearn.log_model(model, "digital_twin_model")
        logging.info("Model logged successfully.")
    except Exception as e:
        logging.error(f"Error in building model: {str(e)}")

# Main execution
if __name__ == '__main__':
    # Example data for model
    example_data = {
        'features': [[1.0, 2.0], [2.0, 3.0]],
        'target': [3.0, 5.0]
    }
    build_digital_twin(example_data)