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Generates a document from a template by populating it with provided data, returning the document content as bytes or None if generation fails.

Purpose

This function serves as a placeholder/stub for document generation functionality. It is intended to retrieve a template by ID, process it with a template engine (such as Jinja2 for DOCX files), populate it with the provided data dictionary, and return the generated document as bytes. Currently, it logs a warning that the feature is not implemented and returns None. In a production implementation, this would be used for automated document generation from templates, such as contracts, reports, or form letters.

Source Code

def generate_document_from_template(template_id: str, 
                                   data: Dict[str, Any]) -> Optional[bytes]:
    """
    Generate a document from a template.
    
    Args:
        template_id: Template identifier
        data: Data to populate template
        
    Returns:
        Document content as bytes or None if generation failed
    """
    try:
        # This is a placeholder for actual template processing
        # In a real implementation, you would:
        # 1. Retrieve the template
        # 2. Process it with a template engine (e.g., Jinja2 for DOCX)
        # 3. Return the generated document
        
        logger.warning("Document template generation not implemented")
        return None
        
    except Exception as e:
        logger.error(f"Error generating document from template: {e}")
        return None

Parameters

Parameter Details

template_id: A string identifier that uniquely identifies the template to be used for document generation. This would typically correspond to a template stored in a database or file system. Expected to be a non-empty string representing a valid template reference.

data: A dictionary containing key-value pairs where keys are placeholder names in the template and values are the data to populate those placeholders. The structure should match the template's expected variables. Can contain any JSON-serializable data types including strings, numbers, lists, and nested dictionaries.

Return Value

Type: Optional[bytes]

Returns Optional[bytes], which means it can return either bytes representing the generated document content (e.g., a DOCX or PDF file in binary format) or None if the generation failed or is not implemented. In the current stub implementation, it always returns None. In a full implementation, successful generation would return the complete document as a bytes object ready to be saved to disk or sent to a client.

Dependencies

• logging
• typing
• docx
• PyPDF2
• CDocs

Required Imports

import logging
from typing import Dict, Any, Optional

Conditional/Optional Imports

These imports are only needed under specific conditions:

from docx import Document as DocxDocument

from CDocs import db

from CDocs.config import settings

Usage Example

import logging
from typing import Dict, Any, Optional

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

# Define the function (as provided)
def generate_document_from_template(template_id: str, data: Dict[str, Any]) -> Optional[bytes]:
    try:
        logger.warning("Document template generation not implemented")
        return None
    except Exception as e:
        logger.error(f"Error generating document from template: {e}")
        return None

# Usage example
template_id = "contract_template_001"
data = {
    "client_name": "John Doe",
    "contract_date": "2024-01-15",
    "amount": 5000.00,
    "terms": ["Payment within 30 days", "Delivery by end of month"]
}

# Generate document
document_bytes = generate_document_from_template(template_id, data)

if document_bytes:
    # Save to file
    with open("generated_document.docx", "wb") as f:
        f.write(document_bytes)
    print("Document generated successfully")
else:
    print("Document generation failed or not implemented")

Best Practices

• This is currently a stub function that always returns None - it needs full implementation before production use
• When implementing, ensure proper template validation before processing to avoid security vulnerabilities
• Sanitize and validate all data inputs to prevent template injection attacks
• Consider implementing template caching to improve performance for frequently used templates
• Use appropriate template engines based on document type (e.g., Jinja2 for DOCX, ReportLab for PDF)
• Implement proper error handling for template not found, invalid data structure, and template processing errors
• Consider adding timeout mechanisms for long-running template processing operations
• Log detailed error information for debugging while avoiding exposure of sensitive data in logs
• Return specific error types or status codes instead of just None to help callers understand failure reasons
• Consider adding data validation against template schema before processing

Tags

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