Accelerate Digital Twin Data Collection with Azure Digital Twins SDK and Weights & Biases

                      
                     
"""
Production implementation for Accelerating Digital Twin Data Collection with Azure Digital Twins SDK and Weights & Biases.
Provides secure, scalable operations for monitoring and managing digital twins.
"""

from typing import Dict, Any, List
import os
import logging
import time
import requests
import json
from azure.digitaltwins import DigitalTwinsClient
from azure.identity import DefaultAzureCredential

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

class Config:
    """
    Configuration class for loading environment variables.
    """
    digital_twins_instance_url: str = os.getenv('AZURE_DTWINS_URL')
    weights_biases_api_key: str = os.getenv('WANDB_API_KEY')

def validate_input(data: Dict[str, Any]) -> bool:
    """Validate request data.
    
    Args:
        data: Input to validate
    Returns:
        True if valid
    Raises:
        ValueError: If validation fails
    """
    if 'id' not in data or 'properties' not in data:
        raise ValueError('Missing id or properties')  # Input validation is crucial
    return True

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

def transform_records(records: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
    """Transform records for consistency.
    
    Args:
        records: List of records
    Returns:
        Transformed records
    """
    return [dict(record, transformed=True) for record in records]  # Example transformation

def fetch_data(url: str) -> Dict[str, Any]:
    """Fetch data from a given URL.
    
    Args:
        url: URL to fetch data from
    Returns:
        JSON response from the URL
    Raises:
        ConnectionError: If the fetch fails
    """
    try:
        response = requests.get(url)
        response.raise_for_status()  # Raise an error for bad responses
        return response.json()
    except requests.exceptions.RequestException as e:
        logger.error(f'Error fetching data: {e}')
        raise ConnectionError('Failed to fetch data')

def save_to_db(data: Dict[str, Any]) -> None:
    """Save data to database or external service.
    
    Args:
        data: Data to save
    """
    # Example saving logic (to be implemented)
    logger.info('Data saved successfully.')

def call_api(api_url: str, payload: Dict[str, Any]) -> None:
    """Call external API with given payload.
    
    Args:
        api_url: URL of the API to call
        payload: Data to send
    Raises:
        Exception: If API call fails
    """
    try:
        response = requests.post(api_url, json=payload)
        response.raise_for_status()
        logger.info('API call successful.')
    except Exception as e:
        logger.error(f'API call failed: {e}')
        raise

class DigitalTwinManager:
    """Orchestrator class for managing digital twin operations.
    """
    def __init__(self, config: Config):
        self.client = DigitalTwinsClient(config.digital_twins_instance_url, DefaultAzureCredential())
        self.wandb_api_key = config.weights_biases_api_key

    def process_batch(self, records: List[Dict[str, Any]]) -> None:
        """Process a batch of records.
        
        Args:
            records: Records to process
        """
        for record in records:
            self.handle_record(record)

    def handle_record(self, record: Dict[str, Any]) -> None:
        """Handle individual record processing.
        
        Args:
            record: Single record to handle
        """
        try:
            validate_input(record)  # Validate each input
            sanitized_data = sanitize_fields(record)
            logger.info(f'Processing record: {sanitized_data}')
            save_to_db(sanitized_data)  # Save to DB
        except Exception as e:
            logger.error(f'Error processing record: {e}')

def aggregate_metrics(data: List[Dict[str, Any]]) -> Dict[str, Any]:
    """Aggregate metrics from processed data.
    
    Args:
        data: List of processed data
    Returns:
        Aggregated metrics
    """
    metrics = {'count': len(data)}  # Simple metric example
    logger.info(f'Aggregated metrics: {metrics}')
    return metrics

def format_output(data: Dict[str, Any]) -> str:
    """Format output data for reporting.
    
    Args:
        data: Data to format
    Returns:
        Formatted string
    """
    return json.dumps(data, indent=2)  # Pretty print JSON

if __name__ == '__main__':
    config = Config()  # Load configuration
    manager = DigitalTwinManager(config)  # Initialize manager
    url = 'https://api.example.com/data'  # Example data source
    data = fetch_data(url)  # Fetch data
    records = transform_records(data)  # Transform records
    manager.process_batch(records)  # Process records
    aggregated_metrics = aggregate_metrics(records)  # Aggregate metrics
    output = format_output(aggregated_metrics)  # Format output
    print(output)  # Print the output for review