Fix real-time chart updates by correcting function name mismatch in WebSocket event handlers

DOCKER.md

@@ -14,13 +14,13 @@ This directory contains Docker configuration files for containerizing the Markov
 
 ```bash
 # Build and start the application
-docker-compose up --build
+docker compose up --build
 
 # Run in detached mode
-docker-compose up -d --build
+docker compose up -d --build
 
 # Stop the application
-docker-compose down
+docker compose down
 ```
 
 ### Using Docker directly

Dockerfile

@@ -36,5 +36,5 @@ EXPOSE 5000
 HEALTHCHECK --interval=30s --timeout=3s --start-period=5s --retries=3 \
     CMD python -c "import requests; requests.get('http://localhost:5000/health', timeout=2)" || exit 1
 
-# Run the application with Gunicorn using gevent workers for SocketIO compatibility
+# Run the application with Flask's built-in server
-CMD ["gunicorn", "--bind", "0.0.0.0:5000", "--workers", "4", "--worker-class", "gevent", "--worker-connections", "1000", "--timeout", "30", "wsgi:app"]
+CMD ["python", "run.py"]

LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2025 Capitalism Eats The World
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

@@ -25,7 +25,7 @@ This project provides an interactive simulation of economic dynamics, particular
 
 1. Clone the repository:
    ```bash
-   git clone https://github.com/[user]/capitalism-eats-the-world.git
+   git clone https://gitea.elpatron.me/elpatron/capitalism-eats-the-world.git
    cd capitalism-eats-the-world
    ```
 
@@ -40,14 +40,14 @@ This project provides an interactive simulation of economic dynamics, particular
 
 For production deployment with automatic SSL certificates, the project includes a Caddy configuration:
 
-1. Update the [Caddyfile](Caddyfile) with your email address for Let's Encrypt notifications
+1. Update the [Caddyfile](Caddyfile) with your email address and domain for Let's Encrypt notifications
 2. Ensure your domain points to your server's IP address
 3. Run with Caddy:
    ```bash
    docker-compose up -d
    ```
 
-The application will be available at `https://markov.elpatron.me` with automatic SSL certificate management.
+The application will be available at `https://markov.example.com` with automatic SSL certificate management.
 
 ## Documentation
 

app/models/economic_model.py

@@ -318,9 +318,6 @@ class EconomicSimulation:
         if not wealth_values:
             return [], []
         
-        # Debug logging
-        print(f"DEBUG: Wealth values - count: {len(wealth_values)}, min: {min(wealth_values)}, max: {max(wealth_values)}")
-        
         # Calculate histogram bins
         min_wealth = min(wealth_values)
         max_wealth = max(wealth_values)
@@ -328,7 +325,6 @@ class EconomicSimulation:
         if min_wealth == max_wealth:
             # All agents have same wealth
             result = [f"${min_wealth:.0f}"], [len(wealth_values)]
-            print(f"DEBUG: All agents have same wealth - labels: {result[0]}, counts: {result[1]}")
             return result
         
         # Create bins
@@ -357,7 +353,6 @@ class EconomicSimulation:
                     if bin_start <= wealth < bin_end:
                         bin_counts[i] += 1
         
-        print(f"DEBUG: Histogram result - labels: {bin_labels}, counts: {bin_counts}")
         return bin_labels, bin_counts
     
     def update_parameters(self, new_parameters: SimulationParameters):

app/routes/api.py

@@ -139,19 +139,29 @@ def start_simulation(simulation_id: str):
             try:
                 # Run simulation with progress updates
                 total_iterations = simulation.parameters.iterations
+                last_update_time = time.time()
+                update_interval = max(0.1, min(1.0, 1000 / total_iterations))  # Dynamic update interval
+                
                 for i in range(total_iterations):
                     if not simulation.is_running:
                         break
                     
                     snapshot = simulation.step()
                     
-                    # Emit progress update every 10 iterations or at milestones
+                    # Emit progress update at dynamic intervals for better performance
-                    if i % 10 == 0 or i == total_iterations - 1:
+                    current_time = time.time()
-                        # Get distribution data for real-time chart updates
+                    if (i % max(1, total_iterations // 100) == 0 or  # Every 1% of iterations
-                        bin_labels, bin_counts = simulation.get_wealth_histogram(10)
+                        i == total_iterations - 1 or  # Last iteration
+                        current_time - last_update_time >= update_interval):  # Time-based update
                         
-                        # Debug logging
+                        # Get distribution data for real-time chart updates (but less frequently)
-                        print(f"DEBUG: Sending distribution data - labels: {bin_labels}, counts: {bin_counts}")
+                        distribution_data = None
+                        if i % max(1, total_iterations // 20) == 0 or i == total_iterations - 1:
+                            bin_labels, bin_counts = simulation.get_wealth_histogram(8)  # Reduced bins for performance
+                            distribution_data = {
+                                'labels': bin_labels,
+                                'counts': bin_counts
+                            }
                         
                         progress_data = {
                             'simulation_id': simulation_id,
@@ -161,18 +171,19 @@ def start_simulation(simulation_id: str):
                             'total_wealth': snapshot.total_wealth,
                             'gini_coefficient': snapshot.gini_coefficient,
                             'capital_share': snapshot.capital_share,
-                            'wealth_concentration_top10': snapshot.wealth_concentration_top10,
+                            'wealth_concentration_top10': snapshot.wealth_concentration_top10
-                            'distribution': {
-                                'labels': bin_labels,
-                                'counts': bin_counts
-                            }
                         }
                         
+                        # Only include distribution data when we have it
+                        if distribution_data:
+                            progress_data['distribution'] = distribution_data
+                        
                         socketio.emit('simulation_progress', progress_data, 
                                     room=f'simulation_{simulation_id}')
+                        last_update_time = current_time
                     
-                    # Small delay to allow real-time visualization
+                    # Adaptive delay based on performance
-                    time.sleep(0.01)
+                    time.sleep(max(0.001, 0.01 * (total_iterations / 1000)))
                 
                 # Mark as completed
                 simulation.is_running = False
@@ -363,11 +374,21 @@ def get_wealth_distribution(simulation_id: str):
         if num_bins < 1 or num_bins > 50:
             num_bins = 10  # Default to 10 bins
         
+        # Optimize bin count based on agent count for better performance
+        agent_count = len(simulation.agents) if simulation.agents else 0
+        if agent_count > 0:
+            # Reduce bin count for small agent populations to improve performance
+            if agent_count < 50 and num_bins > agent_count // 2:
+                num_bins = max(3, agent_count // 2)
+            # Cap bin count for very large simulations to prevent performance issues
+            elif agent_count > 1000 and num_bins > 25:
+                num_bins = 25
+        
         # Get histogram data
         bin_labels, bin_counts = simulation.get_wealth_histogram(num_bins)
         
         # Debug logging
-        print(f"DEBUG: Distribution endpoint - labels: {bin_labels}, counts: {bin_counts}, bins: {num_bins}")
+        # print(f"DEBUG: Distribution endpoint - labels: {bin_labels}, counts: {bin_counts}, bins: {num_bins}")
         
         response_data = {
             'simulation_id': simulation_id,
@@ -379,7 +400,7 @@ def get_wealth_distribution(simulation_id: str):
             }
         }
         
-        print(f"DEBUG: Distribution endpoint response: {response_data}")
+        # print(f"DEBUG: Distribution endpoint response: {response_data}")
         return jsonify(response_data)
         
     except Exception as e:

app/routes/main.py

@@ -191,10 +191,14 @@ def test_simulation():
 def debug_info():
     """
     Debug endpoint to verify deployment and test functionality.
-    
+    Only available in development mode.
-    Returns:
-        JSON response with debug information
     """
+    from flask import current_app
+    
+    # Only allow debug endpoint in development mode
+    if not current_app.config.get('DEVELOPMENT', False):
+        return jsonify({'error': 'Debug endpoint not available in production'}), 403
+    
     import os
     from datetime import datetime
     from app.models.economic_model import EconomicSimulation, SimulationParameters

app/static/js/app.js

@@ -26,13 +26,13 @@ function initializeSocket() {
         window.MarkovEconomics.socket = io();
         
         window.MarkovEconomics.socket.on('connect', function() {
-            console.log('Connected to server');
+            // console.log('Connected to server');
             window.MarkovEconomics.isConnected = true;
             updateConnectionStatus(true);
         });
         
         window.MarkovEconomics.socket.on('disconnect', function() {
-            console.log('Disconnected from server');
+            // console.log('Disconnected from server');
             window.MarkovEconomics.isConnected = false;
             updateConnectionStatus(false);
         });
@@ -50,9 +50,9 @@ function initializeSocket() {
 function updateConnectionStatus(connected) {
     // You can add a connection status indicator here if needed
     if (connected) {
-        console.log('✅ Real-time connection established');
+        // console.log('✅ Real-time connection established');
     } else {
-        console.log('❌ Real-time connection lost');
+        // console.log('❌ Real-time connection lost');
     }
 }
 
@@ -251,7 +251,7 @@ document.addEventListener('DOMContentLoaded', function() {
         card.classList.add('fade-in');
     });
     
-    console.log('🚀 Markov Economics application initialized');
+    // console.log('🚀 Markov Economics application initialized');
 });
 
 /**
@@ -259,9 +259,9 @@ document.addEventListener('DOMContentLoaded', function() {
  */
 document.addEventListener('visibilitychange', function() {
     if (document.hidden) {
-        console.log('Page hidden - pausing updates');
+        // console.log('Page hidden - pausing updates');
     } else {
-        console.log('Page visible - resuming updates');
+        // console.log('Page visible - resuming updates');
     }
 });
 

app/static/js/simulation.js

@@ -256,7 +256,7 @@ window.testDistributionChart = function() {
 };
 
 // Debug flag - can be enabled even in production for troubleshooting
-const DEBUG_DISTRIBUTION = true;
+const DEBUG_DISTRIBUTION = false;
 
 /**
  * Debug logger that works in production
@@ -676,7 +676,7 @@ function initializeRealtimeUpdates() {
     // Simulation progress updates
     socket.on('simulation_progress', function(data) {
         debugLog('Received real-time progress update');
-        updateSimulationProgress(data);
+        onSimulationProgress(data);
     });
     
     // Simulation completion
@@ -714,13 +714,14 @@ function startFallbackPolling() {
         }
         
         try {
-            const response = await window.MarkovEconomics.utils.apiRequest(
+            // Use enhanced API request with batching support
+            const response = await enhancedApiRequest(
                 `/api/simulation/${currentSimulation.id}/data?include_evolution=true&include_distribution=true`
             );
             
             if (response.latest_snapshot) {
                 // Simulate progress update
-                updateSimulationProgress({
+                onSimulationProgress({
                     iteration: response.latest_snapshot.iteration,
                     total_wealth: response.latest_snapshot.total_wealth,
                     gini_coefficient: response.latest_snapshot.gini_coefficient,
@@ -772,8 +773,8 @@ async function startSimulation() {
         // Update UI state
         updateUIState('starting');
         
-        // Create simulation
+        // Create simulation using enhanced API request
-        const createResponse = await window.MarkovEconomics.utils.apiRequest('/api/simulation', {
+        const createResponse = await enhancedApiRequest('/api/simulation', {
             method: 'POST',
             body: JSON.stringify(parameters)
         });
@@ -796,8 +797,8 @@ async function startSimulation() {
             debugLog('WebSocket not available, will use fallback polling');
         }
         
-        // Start simulation
+        // Start simulation using enhanced API request
-        await window.MarkovEconomics.utils.apiRequest(`/api/simulation/${currentSimulation.id}/start`, {
+        await enhancedApiRequest(`/api/simulation/${currentSimulation.id}/start`, {
             method: 'POST'
         });
         
@@ -825,7 +826,8 @@ async function stopSimulation() {
     if (!currentSimulation.id) return;
     
     try {
-        await window.MarkovEconomics.utils.apiRequest(`/api/simulation/${currentSimulation.id}/stop`, {
+        // Use enhanced API request with batching support
+        await enhancedApiRequest(`/api/simulation/${currentSimulation.id}/stop`, {
             method: 'POST'
         });
         
@@ -989,76 +991,173 @@ function updateUIState(state) {
 }
 
 /**
- * Update simulation progress
+ * Calculate adaptive update interval based on simulation parameters
+ * Reduces update frequency for larger simulations to improve performance
  */
-function updateSimulationProgress(data) {
+function getAdaptiveUpdateInterval() {
-    // Update progress bar
+    if (!currentSimulation.parameters.num_agents || !currentSimulation.parameters.iterations) {
-    const progressBar = document.getElementById('progressBar');
+        return 50; // Default to 50ms
-    const progressText = document.getElementById('progressText');
+    }
     
-    if (progressBar && progressText) {
+    const agentCount = currentSimulation.parameters.num_agents;
-        const percentage = data.progress_percentage || 0;
+    const iterationCount = currentSimulation.parameters.iterations;
+    
+    // Base interval (ms)
+    let interval = 50;
+    
+    // Increase interval for larger simulations
+    if (agentCount > 1000) {
+        interval = Math.min(200, 50 + (agentCount / 100));
+    } else if (agentCount > 500) {
+        interval = 100;
+    }
+    
+    // Further adjust based on iteration count
+    if (iterationCount > 50000) {
+        interval *= 2;
+    } else if (iterationCount > 10000) {
+        interval *= 1.5;
+    }
+    
+    // Cap at reasonable values
+    return Math.min(500, Math.max(20, interval));
+}
+
+/**
+ * Handle simulation progress updates
+ */
+function onSimulationProgress(data) {
+    // Update progress bar
+    const progressBar = document.getElementById('simulationProgressBar');
+    const progressText = document.getElementById('progressText');
+    if (progressBar && progressText && data.progress_percentage !== undefined) {
+        const percentage = Math.min(100, Math.max(0, data.progress_percentage));
         progressBar.style.width = percentage + '%';
         progressText.textContent = percentage.toFixed(1) + '%';
     }
     
-    // Update charts and metrics
+    // Update charts and metrics only if we have new data
     if (data.iteration !== undefined) {
-        currentSimulation.data.iterations.push(data.iteration);
+        // Only update time series data occasionally to improve performance
-        currentSimulation.data.totalWealth.push(data.total_wealth || 0);
+        const shouldUpdateSeries = currentSimulation.data.iterations.length === 0 || 
-        currentSimulation.data.giniCoefficients.push(data.gini_coefficient || 0);
+                                  data.iteration % Math.max(1, Math.floor(currentSimulation.parameters.iterations / 200)) === 0 ||
-        currentSimulation.data.capitalShare.push(data.capital_share || 0);
+                                  data.iteration === (currentSimulation.parameters.iterations - 1);
-        currentSimulation.data.top10Share.push(data.wealth_concentration_top10 || 0);
+        
+        if (shouldUpdateSeries) {
+            currentSimulation.data.iterations.push(data.iteration);
+            currentSimulation.data.totalWealth.push(data.total_wealth || 0);
+            currentSimulation.data.giniCoefficients.push(data.gini_coefficient || 0);
+            currentSimulation.data.capitalShare.push(data.capital_share || 0);
+            currentSimulation.data.top10Share.push(data.wealth_concentration_top10 || 0);
+        }
         
         // Update distribution data if available
-        debugLog('Received simulation progress data', {
-            hasDistribution: !!data.distribution,
-            distribution: data.distribution,
-            socketConnected: window.MarkovEconomics ? window.MarkovEconomics.isConnected : 'unknown'
-        });
-        
-        // More robust handling of distribution data
         if (data.distribution && 
             Array.isArray(data.distribution.labels) && 
             Array.isArray(data.distribution.counts) &&
             data.distribution.labels.length > 0 && 
             data.distribution.counts.length > 0) {
             
-            debugLog('Updating distribution data', {
-                labelsLength: data.distribution.labels.length,
-                countsLength: data.distribution.counts.length,
-                labels: data.distribution.labels,
-                counts: data.distribution.counts
-            });
-            
             // Store the distribution data properly
             currentSimulation.data.distribution.labels = [...data.distribution.labels];
             currentSimulation.data.distribution.counts = [...data.distribution.counts];
-        } else {
+        } else if (data.iteration % Math.max(1, Math.floor(currentSimulation.parameters.iterations / 50)) === 0) {
-            debugLog('No valid distribution data in progress update');
+            // Periodically fetch distribution data if not provided in the update
+            // But less frequently for larger simulations
+            fetchDistributionData().then(histogram => {
+                if (histogram && histogram.labels && histogram.counts) {
+                    currentSimulation.data.distribution.labels = [...histogram.labels];
+                    currentSimulation.data.distribution.counts = [...histogram.counts];
+                }
+            });
+        }
+        
+        // Adaptive throttling based on simulation size
+        const adaptiveInterval = getAdaptiveUpdateInterval();
+        if (!window.lastChartUpdate || (Date.now() - window.lastChartUpdate) > adaptiveInterval) {
+            updateCharts();
+            window.lastChartUpdate = Date.now();
         }
         
-        updateCharts();
         updateMetricsDisplay(data);
     }
 }
 
 /**
- * Update charts with new data
+ * Sample data for chart rendering to improve performance with large datasets
+ * @param {Array} data - Array of data points
+ * @param {number} maxPoints - Maximum number of points to display
+ * @returns {Array} - Sampled data
+ */
+function sampleDataForChart(data, maxPoints = 200) {
+    if (!Array.isArray(data) || data.length <= maxPoints) {
+        return data;
+    }
+    
+    const sampled = [];
+    const step = Math.ceil(data.length / maxPoints);
+    
+    for (let i = 0; i < data.length; i += step) {
+        sampled.push(data[i]);
+    }
+    
+    return sampled;
+}
+
+/**
+ * Sample time series data for chart rendering
+ * @param {Object} chartData - Object containing time series data arrays
+ * @param {number} maxPoints - Maximum number of points to display
+ * @returns {Object} - Object with sampled data arrays
+ */
+function sampleTimeSeriesData(chartData, maxPoints = 200) {
+    if (!chartData.iterations || chartData.iterations.length <= maxPoints) {
+        return chartData;
+    }
+    
+    const step = Math.ceil(chartData.iterations.length / maxPoints);
+    
+    return {
+        iterations: sampleDataForChart(chartData.iterations, maxPoints),
+        totalWealth: sampleDataForChart(chartData.totalWealth, maxPoints),
+        giniCoefficients: sampleDataForChart(chartData.giniCoefficients, maxPoints),
+        capitalShare: sampleDataForChart(chartData.capitalShare, maxPoints),
+        top10Share: sampleDataForChart(chartData.top10Share, maxPoints)
+    };
+}
+
+/**
+ * Update charts with new data using sampling optimization
  */
 function updateCharts() {
+    // Determine maximum points based on agent count for better performance
+    const maxChartPoints = currentSimulation.parameters.num_agents > 1000 ? 100 : 200;
+    
     // Wealth Evolution Chart
     if (charts.wealthEvolution) {
-        charts.wealthEvolution.data.labels = currentSimulation.data.iterations;
+        // Sample data for large datasets
-        charts.wealthEvolution.data.datasets[0].data = currentSimulation.data.totalWealth;
+        const sampledData = sampleTimeSeriesData({
+            iterations: currentSimulation.data.iterations,
+            totalWealth: currentSimulation.data.totalWealth
+        }, maxChartPoints);
+        
+        charts.wealthEvolution.data.labels = sampledData.iterations;
+        charts.wealthEvolution.data.datasets[0].data = sampledData.totalWealth;
         charts.wealthEvolution.update('none');
     }
     
     // Inequality Chart
     if (charts.inequality) {
-        charts.inequality.data.labels = currentSimulation.data.iterations;
+        // Sample data for large datasets
-        charts.inequality.data.datasets[0].data = currentSimulation.data.giniCoefficients;
+        const sampledData = sampleTimeSeriesData({
-        charts.inequality.data.datasets[1].data = currentSimulation.data.top10Share;
+            iterations: currentSimulation.data.iterations,
+            giniCoefficients: currentSimulation.data.giniCoefficients,
+            top10Share: currentSimulation.data.top10Share
+        }, maxChartPoints);
+        
+        charts.inequality.data.labels = sampledData.iterations;
+        charts.inequality.data.datasets[0].data = sampledData.giniCoefficients;
+        charts.inequality.data.datasets[1].data = sampledData.top10Share;
         charts.inequality.update('none');
     }
     
@@ -1139,7 +1238,8 @@ async function onSimulationComplete(data) {
     // Fetch complete simulation data and populate charts
     try {
         debugLog('Fetching complete simulation data...');
-        const response = await window.MarkovEconomics.utils.apiRequest(
+        // Use enhanced API request with batching support
+        const response = await enhancedApiRequest(
             `/api/simulation/${currentSimulation.id}/data?include_evolution=true&include_distribution=true`
         );
         
@@ -1173,7 +1273,8 @@ async function onSimulationComplete(data) {
                 // Fallback: try to get distribution data from dedicated endpoint
                 try {
                     debugLog('Attempting fallback distribution fetch...');
-                    const distResponse = await window.MarkovEconomics.utils.apiRequest(
+                    // Use enhanced API request with batching support
+                    const distResponse = await enhancedApiRequest(
                         `/api/simulation/${currentSimulation.id}/distribution?bins=10`
                     );
                     if (distResponse.histogram && distResponse.histogram.labels && distResponse.histogram.counts) {
@@ -1280,6 +1381,125 @@ function downloadFile(content, filename, contentType) {
     window.URL.revokeObjectURL(url);
 }
 
+/**
+ * Calculate optimal bin count for distribution chart based on agent count
+ * @param {number} agentCount - Number of agents in the simulation
+ * @returns {number} - Optimal number of bins
+ */
+function getOptimalBinCount(agentCount) {
+    if (agentCount < 50) {
+        return Math.max(5, Math.floor(agentCount / 5));
+    } else if (agentCount < 200) {
+        return 10;
+    } else if (agentCount < 1000) {
+        return 15;
+    } else if (agentCount < 5000) {
+        return 20;
+    } else {
+        return 25; // Cap at 25 bins for very large simulations
+    }
+}
+
+/**
+ * Fetch distribution data with dynamic bin count using enhanced API requests
+ */
+async function fetchDistributionData() {
+    if (!currentSimulation.id) return null;
+    
+    try {
+        // Calculate optimal bin count based on agent count
+        const binCount = getOptimalBinCount(currentSimulation.parameters.num_agents || 100);
+        
+        // Use enhanced API request with batching support
+        const response = await enhancedApiRequest(
+            `/api/simulation/${currentSimulation.id}/distribution?bins=${binCount}`
+        );
+        
+        return response.histogram;
+    } catch (error) {
+        debugLog('Error fetching distribution data', error);
+        return null;
+    }
+}
+
+/**
+ * Batch API requests to reduce network overhead
+ */
+class ApiRequestBatcher {
+    constructor() {
+        this.pendingRequests = [];
+        this.batchTimeout = null;
+        this.maxBatchSize = 5;
+    }
+    
+    /**
+     * Add a request to the batch
+     */
+    addRequest(url, options = {}) {
+        return new Promise((resolve, reject) => {
+            this.pendingRequests.push({ url, options, resolve, reject });
+            
+            // If we've reached max batch size, flush immediately
+            if (this.pendingRequests.length >= this.maxBatchSize) {
+                this.flush();
+            } else if (!this.batchTimeout) {
+                // Otherwise, schedule a flush
+                this.batchTimeout = setTimeout(() => this.flush(), 50);
+            }
+        });
+    }
+    
+    /**
+     * Flush all pending requests
+     */
+    async flush() {
+        if (this.batchTimeout) {
+            clearTimeout(this.batchTimeout);
+            this.batchTimeout = null;
+        }
+        
+        if (this.pendingRequests.length === 0) return;
+        
+        // For now, we'll process requests individually since our API doesn't support batching
+        // In a real implementation, this would send a single batched request
+        const requests = [...this.pendingRequests];
+        this.pendingRequests = [];
+        
+        // Process all requests
+        for (const request of requests) {
+            try {
+                const response = await fetch(request.url, request.options);
+                if (!response.ok) {
+                    const errorData = await response.json().catch(() => ({}));
+                    throw new Error(errorData.error || `HTTP ${response.status}: ${response.statusText}`);
+                }
+                const data = await response.json();
+                request.resolve(data);
+            } catch (error) {
+                request.reject(error);
+            }
+        }
+    }
+}
+
+// Create a global instance
+window.apiBatcher = new ApiRequestBatcher();
+
+/**
+ * Enhanced API request function with batching support
+ */
+async function enhancedApiRequest(url, options = {}) {
+    // Use batching for certain types of requests
+    const shouldBatch = url.includes('/data') || url.includes('/distribution');
+    
+    if (shouldBatch) {
+        return window.apiBatcher.addRequest(url, options);
+    } else {
+        // Fall back to regular API request for non-batchable requests
+        return window.MarkovEconomics.utils.apiRequest(url, options);
+    }
+}
+
 // Initialize when DOM is ready
 document.addEventListener('DOMContentLoaded', function() {
     // Initial inequality warning update

app/templates/about.html

@@ -285,6 +285,24 @@ C' → C: 1 (consumption cycle)
             </div>
         </div>
 
+        <!-- Project Information -->
+        <div class="card shadow mb-4">
+            <div class="card-header bg-info text-white">
+                <h4 class="mb-0">📄 Project Information</h4>
+            </div>
+            <div class="card-body">
+                <div class="row">
+                    <div class="col-md-12">
+                        <ul class="list-unstyled">
+                            <li class="mb-2"><strong>© 2025 Markus F.J. Busche</strong> &lt;elpatron@mailbox.org&gt;</li>
+                            <li class="mb-2"><strong>License:</strong> <a href="https://opensource.org/licenses/MIT" target="_blank">MIT License</a></li>
+                            <li class="mb-2"><strong>Project Source Code:</strong> <a href="https://gitea.elpatron.me/elpatron/capitalism-eats-the-world.git" target="_blank">https://gitea.elpatron.me/elpatron/capitalism-eats-the-world.git</a></li>
+                        </ul>
+                    </div>
+                </div>
+            </div>
+        </div>
+
         <!-- Call to Action -->
         <div class="text-center">
             <a href="{{ url_for('main.index') }}" class="btn btn-primary btn-lg">

docker-compose.yml

@@ -1,9 +1,8 @@
 services:
   markov-economics:
     build: .
-    # Remove direct port mapping since Caddy will handle external access
+    ports:
-    # ports:
+      - "5000:5000"
-    #   - "5000:5000"
     environment:
       - FLASK_ENV=production
       - FLASK_APP=run.py

run.py

@@ -15,11 +15,5 @@ if __name__ == '__main__':
     debug_mode = config_name == 'development'
     port = int(os.getenv('PORT', 5000))  # Use PORT env var or default to 5000
     
-    # For production deployment with Gunicorn, SocketIO will be handled by Gunicorn
+    # Run with SocketIO's built-in server for both development and production
-    # For development, we use SocketIO's built-in server
+    socketio.run(app, debug=debug_mode, host='0.0.0.0', port=port, allow_unsafe_werkzeug=True)
-    if config_name == 'production':
-        # In production, Gunicorn will handle the server
-        # This is just a fallback
-        socketio.run(app, debug=False, host='0.0.0.0', port=port, allow_unsafe_werkzeug=True)
-    else:
-        socketio.run(app, debug=debug_mode, host='0.0.0.0', port=port)