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function create_data_section

Maturity: 50

Flask API endpoint that creates a new data section for authenticated users, accepting title and description from JSON request body.

File:
/tf/active/vicechatdev/vice_ai/new_app.py
Lines:
4234 - 4257
Complexity:
simple

Purpose

This endpoint serves as a REST API handler for creating data analysis sections in a document management system. It authenticates the user, extracts section metadata from the request, delegates creation to a service layer, and returns the created section as JSON. It's designed for web applications that need to organize data analysis work into discrete sections with ownership tracking.

Source Code

def create_data_section():
    """Create a new data section"""
    user_email = get_current_user()
    data = request.get_json()
    
    try:
        title = data.get('title', 'Untitled Data Analysis')
        description = data.get('description', '')
        
        # Create data section
        data_section = data_section_service.create_data_section(
            owner=user_email,
            title=title,
            description=description
        )
        
        return jsonify({
            'success': True,
            'section': data_section.to_dict()
        })
        
    except Exception as e:
        logger.error(f"Error creating data section: {e}")
        return jsonify({'error': str(e)}), 500

Return Value

Returns a Flask JSON response. On success (HTTP 200): {'success': True, 'section': <dict representation of created DataSection>}. On error (HTTP 500): {'error': <error message string>}. The section dictionary contains all attributes of the created DataSection model instance.

Dependencies

  • flask
  • logging

Required Imports

from flask import Flask, request, jsonify
import logging

Conditional/Optional Imports

These imports are only needed under specific conditions:

from models import DataSection

Condition: Required for the DataSection model class used by data_section_service

Required (conditional) 
from services import DataSectionService

Condition: Required for the data_section_service instance that handles business logic

Required (conditional) 
from auth.azure_auth import AzureSSO

Condition: Required for the require_auth decorator and get_current_user() function

Required (conditional)

Usage Example

# Client-side usage (JavaScript fetch example):
fetch('/api/data-sections', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'Authorization': 'Bearer <token>'
  },
  body: JSON.stringify({
    title: 'Q4 Sales Analysis',
    description: 'Quarterly sales data analysis for regional performance'
  })
})
.then(response => response.json())
.then(data => {
  if (data.success) {
    console.log('Created section:', data.section);
    // data.section contains: {id, owner, title, description, created_at, etc.}
  } else {
    console.error('Error:', data.error);
  }
});

# Server-side test example:
# with app.test_client() as client:
#     response = client.post('/api/data-sections',
#         json={'title': 'Test Section', 'description': 'Test description'},
#         headers={'Authorization': 'Bearer test_token'})
#     assert response.status_code == 200
#     assert response.json['success'] == True

Best Practices

  • Always send requests with proper authentication headers as the endpoint is protected by require_auth decorator
  • Include Content-Type: application/json header in requests
  • Handle both success and error responses appropriately on the client side
  • The function provides default values for title and description, so these fields are optional in the request
  • Error responses include descriptive error messages for debugging
  • The service layer (data_section_service) handles the actual business logic and database operations, keeping the endpoint handler thin
  • User ownership is automatically assigned based on authenticated user, preventing unauthorized section creation
  • Consider implementing request validation middleware for more robust input validation
  • The endpoint logs errors for monitoring and debugging purposes
  • Returns proper HTTP status codes (200 for success, 500 for server errors)

Tags

flask api rest-endpoint data-section create authentication json post-request error-handling logging service-layer document-management data-analysis

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