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Flask route handler that accepts file uploads via POST request, validates the file, saves it with a timestamp, and loads the data into an analysis session.

Purpose

This endpoint handles data file uploads for statistical analysis sessions. It validates file types against allowed extensions, securely saves uploaded files with timestamped filenames, creates a DataSource object, and initiates data loading through the analysis service. The function returns metadata about the uploaded data including shape, columns, and a summary.

Source Code

def upload_data(session_id):
    """Upload data file for analysis"""
    try:
        if 'file' not in request.files:
            return jsonify({'success': False, 'error': 'No file provided'}), 400
        
        file = request.files['file']
        if file.filename == '':
            return jsonify({'success': False, 'error': 'No file selected'}), 400
        
        if not allowed_file(file.filename):
            return jsonify({
                'success': False, 
                'error': f'File type not allowed. Supported: {app_config.ALLOWED_EXTENSIONS}'
            }), 400
        
        # Save uploaded file
        filename = secure_filename(file.filename)
        timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
        filename = f"{timestamp}_{filename}"
        file_path = os.path.join(app_config.UPLOAD_FOLDER, filename)
        file.save(file_path)
        
        # Create data source
        data_source = DataSource(
            source_type=DataSourceType.FILE_UPLOAD,
            file_path=file_path
        )
        
        # Load data for session
        result = analysis_service.load_data_for_session(session_id, data_source)
        
        if result['success']:
            return jsonify({
                'success': True,
                'message': 'Data uploaded and processed successfully',
                'data_summary': result['data_summary'],
                'shape': result['shape'],
                'columns': result['columns']
            })
        else:
            return jsonify(result), 500
            
    except Exception as e:
        logger.error(f"Error uploading data: {str(e)}")
        return jsonify({
            'success': False,
            'error': str(e)
        }), 500

Parameters

Parameter Details

session_id: String identifier for the analysis session. Used to associate the uploaded data with a specific user session. This parameter is extracted from the URL path and passed to the analysis service to load data for the correct session.

Return Value

Returns a Flask JSON response tuple containing (response_body, status_code). On success (200): {'success': True, 'message': str, 'data_summary': dict, 'shape': tuple, 'columns': list}. On error (400/500): {'success': False, 'error': str}. Status codes: 200 for success, 400 for validation errors (no file, empty filename, invalid file type), 500 for processing errors.

Dependencies

• flask
• werkzeug
• pandas
• pathlib
• datetime
• os
• logging
• typing

Required Imports

from flask import request, jsonify
from werkzeug.utils import secure_filename
from datetime import datetime
import os
import logging

Usage Example

# Client-side usage (JavaScript fetch example):
const formData = new FormData();
formData.append('file', fileInput.files[0]);

fetch('/upload_data/session_123', {
  method: 'POST',
  body: formData
})
.then(response => response.json())
.then(data => {
  if (data.success) {
    console.log('Data shape:', data.shape);
    console.log('Columns:', data.columns);
    console.log('Summary:', data.data_summary);
  } else {
    console.error('Upload failed:', data.error);
  }
});

# Server-side setup required:
# app_config.py
ALLOWED_EXTENSIONS = {'.csv', '.xlsx', '.json', '.txt'}
UPLOAD_FOLDER = '/path/to/uploads'

# Helper function
def allowed_file(filename):
    return Path(filename).suffix.lower() in app_config.ALLOWED_EXTENSIONS

# Initialize services
analysis_service = StatisticalAnalysisService()
logger = logging.getLogger(__name__)

Best Practices

• Always validate file extensions using allowed_file() before processing to prevent security vulnerabilities
• Use secure_filename() to sanitize user-provided filenames and prevent directory traversal attacks
• Timestamp filenames to prevent collisions and maintain upload history
• Ensure UPLOAD_FOLDER exists and has appropriate write permissions before deployment
• Implement file size limits in Flask configuration (MAX_CONTENT_LENGTH) to prevent DoS attacks
• Clean up old uploaded files periodically to manage disk space
• Consider implementing virus scanning for uploaded files in production environments
• Log errors with sufficient context for debugging but avoid logging sensitive data
• Return appropriate HTTP status codes (400 for client errors, 500 for server errors)
• Handle the case where analysis_service.load_data_for_session() fails gracefully
• Consider implementing rate limiting to prevent abuse of the upload endpoint

Tags

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