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Flask API endpoint that updates the conclusions text for a specific data analysis session, with authentication and ownership validation.

Purpose

This endpoint allows authenticated users to update the conclusions field of their data analysis sessions. It validates that the data analysis service is available, verifies user authentication and session ownership, then persists the updated conclusions to the database. Used in data analysis workflows where users need to document findings and insights from their analysis sessions.

Source Code

def update_analysis_conclusions(session_id):
    """Update conclusions for an analysis session"""
    if not DATA_ANALYSIS_AVAILABLE:
        return jsonify({'error': 'Data analysis service not available'}), 503
    
    user_email = get_current_user()
    data = request.get_json()
    
    session = data_analysis_service.get_analysis_session(session_id)
    if not session or session.user_id != user_email:
        return jsonify({'error': 'Session not found or access denied'}), 404
    
    conclusions = data.get('conclusions', '')
    
    try:
        success = data_analysis_service.update_session_conclusions(session_id, conclusions)
        if success:
            return jsonify({'success': True})
        else:
            return jsonify({'error': 'Failed to update conclusions'}), 500
            
    except Exception as e:
        logger.error(f"Error updating conclusions: {e}")
        return jsonify({'error': str(e)}), 500

Parameters

Parameter Details

session_id: String identifier for the analysis session to update. Passed as a URL path parameter. Must correspond to an existing analysis session owned by the authenticated user.

Return Value

Returns a Flask JSON response. On success (200): {'success': True}. On service unavailable (503): {'error': 'Data analysis service not available'}. On not found/unauthorized (404): {'error': 'Session not found or access denied'}. On failure (500): {'error': 'Failed to update conclusions'} or {'error': '<exception message>'}.

Dependencies

• flask
• logging
• data_analysis_service

Required Imports

from flask import jsonify, request
import logging
from data_analysis_service import DataAnalysisService

Usage Example

# Client-side usage example (JavaScript fetch)
fetch('/api/analysis-sessions/abc123/conclusions', {
  method: 'PUT',
  headers: {
    'Content-Type': 'application/json',
    'Authorization': 'Bearer <token>'
  },
  body: JSON.stringify({
    conclusions: 'The analysis shows a strong correlation between variables X and Y with p-value < 0.05.'
  })
})
.then(response => response.json())
.then(data => {
  if (data.success) {
    console.log('Conclusions updated successfully');
  } else {
    console.error('Error:', data.error);
  }
});

Best Practices

• Always check DATA_ANALYSIS_AVAILABLE before attempting to use the service to provide graceful degradation
• Verify both session existence and ownership before allowing updates to prevent unauthorized access
• Include proper error handling with specific HTTP status codes for different failure scenarios
• Log errors with sufficient context for debugging while avoiding sensitive data exposure
• Validate that the conclusions field exists in the request data using .get() with default value
• Use try-except blocks to catch and handle service-level exceptions gracefully
• Return consistent JSON response format across all code paths for easier client-side handling
• Ensure the require_auth decorator is properly configured to validate user sessions
• Consider adding input validation for conclusions length or format if business rules require it

Tags

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