Parse ISO Standards Documents for Compliance Checks with PyMuPDF and Haystack

"""
Production implementation for parsing ISO Standards documents for compliance checks.
Provides secure and scalable operations using PyMuPDF and Haystack.
"""

from typing import Dict, Any, List, Optional
import os
import logging
import fitz  # PyMuPDF
import requests
from haystack.document_stores import InMemoryDocumentStore
from haystack.nodes import TextConverter, DensePassageRetriever
from haystack.pipelines import ExtractiveQAPipeline

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

class Config:
    database_url: str = os.getenv('DATABASE_URL')
    haystack_api_url: str = os.getenv('HAYSTACK_API_URL')


def validate_input_data(data: Dict[str, Any]) -> bool:
    """Validate input data for compliance checks.
    
    Args:
        data: Dictionary containing document metadata.
    Returns:
        bool: True if validation succeeds.
    Raises:
        ValueError: If validation fails.
    """
    if 'document_path' not in data:
        raise ValueError('Missing document path in input data.')
    return True


def sanitize_fields(data: Dict[str, Any]) -> Dict[str, Any]:
    """Sanitize input fields to prevent injection attacks.
    
    Args:
        data: Input data dictionary.
    Returns:
        Dict[str, Any]: Sanitized data dictionary.
    """
    sanitized_data = {key: str(value).strip() for key, value in data.items()}
    logger.debug('Sanitized data: %s', sanitized_data)
    return sanitized_data


def fetch_data(document_path: str) -> str:
    """Fetch document content from file.
    
    Args:
        document_path: Path to the ISO document.
    Returns:
        str: Content of the document.
    Raises:
        FileNotFoundError: If the document does not exist.
    """
    if not os.path.exists(document_path):
        raise FileNotFoundError(f'Document not found: {document_path}')
    with fitz.open(document_path) as doc:
        return "\n".join([page.get_text() for page in doc])


def transform_records(content: str) -> List[Dict[str, Any]]:
    """Transform raw document content into structured records.
    
    Args:
        content: Raw text content from the document.
    Returns:
        List[Dict[str, Any]]: List of structured records.
    """
    records = [{'text': line} for line in content.split('\n') if line]
    logger.debug('Transformed records: %s', records)
    return records


def save_to_db(records: List[Dict[str, Any]]) -> None:
    """Save structured records to the document store.
    
    Args:
        records: List of records to save.
    """
    document_store = InMemoryDocumentStore()
    document_store.write_documents(records)
    logger.info('Saved %d records to the database.', len(records))


def process_batch(document_path: str) -> None:
    """Main processing batch function for compliance checks.
    
    Args:
        document_path: Path to the ISO document.
    Raises:
        Exception: If any processing step fails.
    """
    try:
        validate_input_data({'document_path': document_path})  # Validate input
        content = fetch_data(document_path)  # Fetch document content
        records = transform_records(content)  # Transform content into records
        save_to_db(records)  # Save records to the database
    except Exception as e:
        logger.error('Error processing document: %s', e)
        raise


def aggregate_metrics(records: List[Dict[str, Any]]) -> Dict[str, int]:
    """Aggregate metrics from processed records.
    
    Args:
        records: List of processed records.
    Returns:
        Dict[str, int]: Aggregated metrics.
    """
    metrics = {'total_records': len(records)}
    logger.info('Aggregated metrics: %s', metrics)
    return metrics


class DocumentParser:
    """Main class for parsing ISO documents for compliance checks.
    """
    def __init__(self, document_path: str) -> None:
        self.document_path = document_path

    def run(self) -> None:
        """Execute the parsing workflow.
        """
        logger.info('Starting document parsing for: %s', self.document_path)
        process_batch(self.document_path)  # Call to main processing function
        records = fetch_data(self.document_path)  # Fetch records again for metrics
        aggregate_metrics(records)  # Aggregate metrics


if __name__ == '__main__':
    # Example usage
    example_path = 'path/to/iso_document.pdf'
    parser = DocumentParser(example_path)
    parser.run()  # Run the document parser