Logic Visualizer | JavaScript

Flask Route Logic Visualization

This document illustrates the logic behind a Flask route handling both GET and POST requests. It includes a flowchart detailing the request flow, data extraction, code generation, error handling, and responses.

Prompt

@app.route('/', methods=['GET', 'POST'])
def index():
    if request.method == 'POST':
        logging.info(f"Received POST request with scenario: {request.form['scenario']}")
        try:
            scenario = request.form['scenario']
            num_rows = int(request.form['num_rows'])
            num_columns = int(request.form['num_columns'])
            logging.info(f"Received request: scenario='{scenario}', num_rows={num_rows}")
            generated_code = generate_python_code(scenario, num_columns)
            logging.debug(f"Generated code: {generated_code}")
            if generated_code and isinstance(generated_code, str):
                try:
                    exec(generated_code, globals())
                    if 'generate_random_data' not in globals():
                        raise NameError("The function 'generate_random_data' was not defined.")
                    # Check if this is a preview request
                    if 'preview' in request.form:
                        preview_data = globals().get('generate_random_data', lambda num_rows: [])(5)  # Generate 5 rows for preview
                        return jsonify({'success': True, 'preview': preview_data})
                    # If not a preview, generate full data set
                    data = globals().get('generate_random_data', lambda num_rows: [])(num_rows)
                    logging.info(f"Generated {len(data)} rows of data")
                    output = StringIO()
                    writer = csv.DictWriter(output, fieldnames=data[0].keys())
                    writer.writeheader()
                    writer.writerows(data)
                    output.seek(0)
                    return send_file(io.BytesIO(output.getvalue().encode()), 
                                     mimetype='text/csv',
                                     as_attachment=True,
                                     download_name='data_scenario.csv')
                except Exception as e:
                    logging.error(f"Error in executing generated code: {str(e)}")
                    logging.error(traceback.format_exc())
                    return jsonify({'error': f'Error in executing generated code: {str(e)}'}), 500
            else:
                logging.error("Failed to generate code")
                return jsonify({'error': 'Failed to generate code'}), 500
        except Exception as e:
            logging.error(f"Unexpected error: {str(e)}")
            logging.error(traceback.format_exc())
            return jsonify({'error': f'Unexpected error: {str(e)}'}), 500
    else:
        # For GET requests, retrieve the selected scenario from the session
        selected_scenario = session.get('selected_scenario', '')
        return render_template('index.html', scenario=selected_scenario)

Answer

Visualization of Flask Route Logic

This document provides a visual representation of the logic behind the Flask route defined with the @app.route('/') decorator. The flowchart summarizes the key components and the overall control flow, detailing both the GET and POST requests.

Flowchart Representation

graph TD
    A[Start] --> B[Handle '/' Route]
    
    B -->|POST| C[Log POST request]
    
    C --> D{Data Extraction}
    D -->|Extract 'scenario'| E[Scenario]
    D -->|Extract 'num_rows'| F[Num Rows]
    D -->|Extract 'num_columns'| G[Num Columns]
    
    E --> H[Generate Python Code]
    F --> H
    G --> H
    
    H --> I{Code Generation Successful?}
    
    I -->|Yes| J{Execute Generated Code}
    I -->|No| K[Log Code Generation Failure]
    
    K --> L[Return Error: "Failed to generate code"]
    
    J --> M{Function 'generate_random_data' Defined?}
    
    M -->|Yes| N{Preview Requested?}
    M -->|No| O[Log Error and Return]
    
    O --> P[Return Error: "The function 'generate_random_data' was not defined."]
    
    N -->|Yes| Q[Generate Preview Data]
    N -->|No| R[Generate Full Data Set]

    Q --> S[Return Preview Data]
    R --> T[Write Data to CSV]
    
    T --> U[Send File: 'data_scenario.csv']
    
    U --> V[End]
    
    J ---> W[Handle Exceptions]
    W --> X[Log Error]
    X --> Y[Return Error: "Error in executing generated code"]
    
    B -->|GET| Z[Retrieve selected scenario from session]
    Z --> AA[Render: 'index.html']
    AA --> V

Key Components Explained

1. Request Handling

The route is set to handle both GET and POST requests to the root URL ('/').

2. POST Request Flow

Logs the receipt of the POST request and extracts form data (scenario, number of rows, number of columns).
Validates the generation of Python code and executes it if successful.

3. Data Generation Logic

Checks if the generated function generate_random_data exists in the global namespace.
Handles scenarios separately for preview and full data generation:
- Preview Request: Generates a limited number of rows (5 for preview).
- Full Data Generation: Creates the data set according to the user specifications.

4. Error Handling

Detailed logging for errors occurring at multiple stages:
- Execution errors related to generated code.
- General exceptions caught during data extraction and processing.

5. GET Request Flow

For GET requests, it retrieves the selected scenario from the session and renders the index page.

Conclusion

The flowchart and accompanying explanations provide a structured overview of the Flask route's logic. This visualization facilitates the understanding of complex interactions and program flow, bridging the gap between code and conceptual representation. For a deeper dive into coding and data science principles, consider the courses available on the Enterprise DNA Platform.