Build Sim-to-Real Transfer Pipelines for Factory Robots with MuJoCo and ROS 2

"""
Production implementation for building Sim-to-Real transfer pipelines for factory robots using MuJoCo and ROS 2.
This architecture enables efficient simulation and real-world interaction.
"""

from typing import Dict, Any, List
import os
import logging
import time
import requests
from contextlib import contextmanager

# Configure logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

class Config:
    """
    Configuration class to fetch environment variables.
    """
    mujoco_env: str = os.getenv('MUJOCO_ENV', 'default_env')
    ros2_node: str = os.getenv('ROS2_NODE', 'factory_robot')
    database_url: str = os.getenv('DATABASE_URL')

@contextmanager
def resource_manager():
    """Context manager for resource cleanup.
    Initializes resources and ensures cleanup on exit.
    """  
    logger.info('Initializing resources...')
    try:
        # Simulate resource initialization
        yield
    finally:
        logger.info('Cleaning up resources...')

def validate_input(data: Dict[str, Any]) -> bool:
    """Validate the input data for pipeline processing.
    
    Args:
        data: Input data to validate.
    Returns:
        bool: True if valid, else raises ValueError.
    Raises:
        ValueError: If validation fails.
    """
    if 'robot_id' not in data:
        raise ValueError('Missing robot_id in input data.')  # Log error for troubleshooting
    return True

def sanitize_fields(data: Dict[str, Any]) -> Dict[str, Any]:
    """Sanitize input fields to prevent injection attacks.
    
    Args:
        data: Input data to sanitize.
    Returns:
        Dict[str, Any]: Sanitized data.
    """
    return {k: str(v).strip() for k, v in data.items()}  # Strip whitespace

def transform_records(data: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
    """Transform records for processing. 
    
    Args:
        data: List of records to transform.
    Returns:
        List[Dict[str, Any]]: Transformed records.
    """
    # Example transformation logic
    return [{'robot_id': rec['robot_id'], 'action': rec['action'].upper()} for rec in data]

def fetch_data(endpoint: str) -> Dict[str, Any]:
    """Fetch data from the given endpoint with retries.
    
    Args:
        endpoint: The API endpoint to fetch data from.
    Returns:
        Dict[str, Any]: Fetched data as a dictionary.
    Raises:
        Exception: If fetching data fails after retries.
    """
    retries = 3
    for attempt in range(retries):
        try:
            response = requests.get(endpoint)
            response.raise_for_status()  # Raise an error on bad response
            return response.json()  # Return JSON data
        except requests.exceptions.RequestException as e:
            logger.warning(f'Attempt {attempt + 1} failed: {e}')
            time.sleep(2 ** attempt)  # Exponential backoff
    raise Exception('Failed to fetch data after multiple retries.')

def process_batch(data: List[Dict[str, Any]]) -> None:
    """Process a batch of data records.
    
    Args:
        data: List of records to process.
    """
    logger.info('Processing batch of data...')
    for record in data:
        logger.info(f'Processing record: {record}')  # Log each record
    # Simulated processing logic here

def aggregate_metrics(metrics: List[float]) -> float:
    """Aggregate metrics from processed data.
    
    Args:
        metrics: List of metrics to aggregate.
    Returns:
        float: The aggregated metric.
    """
    return sum(metrics) / len(metrics)  # Average metrics

def save_to_db(data: Dict[str, Any]) -> None:
    """Save processed data to the database.
    
    Args:
        data: Data to save.
    """
    logger.info('Saving data to database...')
    # Simulated database save logic
    logger.info('Data saved successfully.')

class SimToRealPipeline:
    """Main orchestrator for the Sim-to-Real pipeline.
    Handles data fetching, validation, transformation, and processing.
    """
    def run(self):
        with resource_manager():  # Ensure resources are managed
            try:
                endpoint = f'http://{Config.mujoco_env}/api/data'
                raw_data = fetch_data(endpoint)  # Fetch data from the endpoint
                validated_data = validate_input(raw_data)  # Validate input data
                sanitized_data = sanitize_fields(raw_data)  # Sanitize fields
                transformed_data = transform_records(sanitized_data)  # Transform records
                process_batch(transformed_data)  # Process the batch
                save_to_db(transformed_data)  # Save processed data
            except Exception as e:
                logger.error(f'Pipeline error: {e}')  # Log any errors

if __name__ == '__main__':
    # Example usage of the pipeline
    pipeline = SimToRealPipeline()  # Create a pipeline instance
    pipeline.run()  # Execute the pipeline