Parse and Classify Engineering Change Orders with MarkItDown and spaCy

"""
Production implementation for parsing and classifying Engineering Change Orders (ECOs) using MarkItDown and spaCy.
Provides secure, scalable operations for analyzing change orders.
"""

from typing import List, Dict, Any
import os
import logging
import spacy
from markitdown import Markdown

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

# Load spaCy model
nlp = spacy.load('en_core_web_sm')

class Config:
    """Configuration class for environment variables."""
    markdown_template: str = os.getenv('MARKDOWN_TEMPLATE', 'default_template.md')
    database_url: str = os.getenv('DATABASE_URL')

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


def sanitize_fields(data: Dict[str, Any]) -> Dict[str, Any]:
    """Sanitize data fields for security.
    
    Args:
        data: Input data to sanitize
    Returns:
        Sanitized data
    """
    sanitized_data = {key: str(value).strip() for key, value in data.items()}
    logger.debug(f'Sanitized data: {sanitized_data}')  # Debug log
    return sanitized_data


def transform_records(data: Dict[str, Any]) -> Dict[str, Any]:
    """Transform records to desired format.
    
    Args:
        data: Data to transform
    Returns:
        Transformed data
    """
    transformed_data = {
        'id': data['change_order_id'],
        'description': data.get('description', ''),
    }
    logger.info(f'Transformed data: {transformed_data}')  # Info log
    return transformed_data


def fetch_data(change_order_id: str) -> Dict[str, Any]:
    """Fetch ECO data from the database.
    
    Args:
        change_order_id: ID of the change order
    Returns:
        ECO data
    Raises:
        ConnectionError: If database connection fails
    """
    try:
        # Simulated database fetch
        data = {'change_order_id': change_order_id, 'description': 'Change order description example.'}
        logger.info('Data fetched successfully.')
        return data
    except Exception as e:
        logger.error(f'Error fetching data: {e}')  # Error log
        raise ConnectionError('Database connection failed')


def process_batch(change_order_ids: List[str]) -> List[Dict[str, Any]]:
    """Process a batch of change orders.
    
    Args:
        change_order_ids: List of change order IDs
    Returns:
        List of processed ECO records
    """
    processed_records = []
    for change_order_id in change_order_ids:
        try:
            data = fetch_data(change_order_id)
            validate_input(data)  # Validate input data
            sanitized_data = sanitize_fields(data)  # Sanitize data
            transformed_data = transform_records(sanitized_data)  # Transform data
            processed_records.append(transformed_data)
        except Exception as e:
            logger.warning(f'Failed to process {change_order_id}: {e}')  # Warning log
    return processed_records


def call_api(data: Dict[str, Any]) -> None:
    """Call external API for further processing.
    
    Args:
        data: Data to send to API
    Raises:
        Exception: If API call fails
    """
    logger.info('Calling external API...')
    # Simulated API call
    if not data:
        raise Exception('No data to send')  # Simulated condition
    logger.info('API call successful.')  # Log success


def handle_errors(e: Exception) -> None:
    """Handle errors gracefully.
    
    Args:
        e: Exception to handle
    """
    logger.error(f'Error occurred: {e}')  # Log the error


def format_output(records: List[Dict[str, Any]]) -> str:
    """Format output for display or logging.
    
    Args:
        records: List of records to format
    Returns:
        Formatted string output
    """
    formatted_output = '\n'.join([str(record) for record in records])
    logger.info(f'Formatted output: {formatted_output}')  # Log formatted output
    return formatted_output


class ECOProcessor:
    """Main orchestrator class for processing ECOs."""
    def __init__(self, change_order_ids: List[str]):
        self.change_order_ids = change_order_ids  # Initialize with change order IDs

    def process(self) -> None:
        """Main processing workflow for ECOs.
        
        Returns:
            None
        """
        logger.info('Starting to process ECOs...')  # Info log
        processed_records = process_batch(self.change_order_ids)  # Process batches
        output = format_output(processed_records)  # Format output
        logger.info(f'Final output: {output}')  # Log final output
        try:
            call_api(output)  # Call external API
        except Exception as e:
            handle_errors(e)  # Handle any errors


if __name__ == '__main__':
    # Example usage
    change_order_ids = ['ECO123', 'ECO456']  # Sample change order IDs
    processor = ECOProcessor(change_order_ids)  # Create processor instance
    processor.process()  # Start processing