Update app.py

app.py

@@ -4,10 +4,12 @@ import numpy as np
 import pickle
 import os
 from datetime import datetime, timedelta
-import plotly.graph_objects as go
-import plotly.express as px
-from plotly.subplots import make_subplots
-import plotly.io as pio
+import matplotlib
+matplotlib.use('Agg')  # Use non-interactive backend
+import matplotlib.pyplot as plt
+import seaborn as sns
+import base64
+import io
 
 app = Flask(__name__)
 
@@ -125,154 +127,43 @@ def predict_next_7_days(model, scaler, data):
     return predictions_df, last_price[0], total_close_change, total_open_change
 
 def create_prediction_chart(data, predictions_df, last_price):
-    """Create an interactive chart showing historical and predicted prices using Plotly"""
+    """Create a chart showing historical and predicted prices"""
+    plt.style.use('default')
+    fig, ax = plt.subplots(figsize=(12, 8))
     
-    # Get last 30 days of historical data
+    # Plot last 30 days of historical data
     recent_data = data.tail(30)
+    ax.plot(recent_data.index, recent_data['close'], 'b-', label='Historical Close Price', linewidth=2)
+    ax.plot(recent_data.index, recent_data['open'], 'g-', label='Historical Open Price', linewidth=2)
     
-    # Create subplots
-    fig = make_subplots(
-        rows=1, cols=1,
-        subplot_titles=['Prediksi Harga Emas - 7 Hari Kedepan'],
-        x_title='Tanggal',
-        y_title='Harga (IDR)'
-    )
+    # Add current day point
+    ax.plot(recent_data.index[-1], last_price[0], 'ro', markersize=8, label='Current Close Price')
+    ax.plot(recent_data.index[-1], last_price[1], 'go', markersize=8, label='Current Open Price')
     
-    # Add historical close price
-    fig.add_trace(
-        go.Scatter(
-            x=recent_data.index,
-            y=recent_data['close'],
-            mode='lines',
-            name='Harga Tutup Historis',
-            line=dict(color='#1f77b4', width=2),
-            hovertemplate='<b>Tanggal:</b> %{x}<br>' +
-                         '<b>Harga Tutup:</b> IDR %{y:,.0f}<br>' +
-                         '<extra></extra>'
-        )
-    )
+    # Plot predictions
+    ax.plot(predictions_df.index, predictions_df['close'], 'r--', label='Predicted Close Price', linewidth=2, marker='o')
+    ax.plot(predictions_df.index, predictions_df['open'], 'orange', linestyle='--', label='Predicted Open Price', linewidth=2, marker='s')
     
-    # Add historical open price
-    fig.add_trace(
-        go.Scatter(
-            x=recent_data.index,
-            y=recent_data['open'],
-            mode='lines',
-            name='Harga Buka Historis',
-            line=dict(color='#2ca02c', width=2),
-            hovertemplate='<b>Tanggal:</b> %{x}<br>' +
-                         '<b>Harga Buka:</b> IDR %{y:,.0f}<br>' +
-                         '<extra></extra>'
-        )
-    )
+    ax.set_title('Gold Price Prediction - Next 7 Days', fontsize=16, fontweight='bold')
+    ax.set_xlabel('Date', fontsize=12)
+    ax.set_ylabel('Price (IDR)', fontsize=12)
+    ax.legend()
+    ax.grid(True, alpha=0.3)
     
-    # Add current day points
-    fig.add_trace(
-        go.Scatter(
-            x=[recent_data.index[-1]],
-            y=[last_price[0]],
-            mode='markers',
-            name='Harga Tutup Saat Ini',
-            marker=dict(color='red', size=10),
-            hovertemplate='<b>Tanggal:</b> %{x}<br>' +
-                         '<b>Harga Tutup Saat Ini:</b> IDR %{y:,.0f}<br>' +
-                         '<extra></extra>'
-        )
-    )
+    # Format y-axis to show prices in millions
+    ax.yaxis.set_major_formatter(plt.FuncFormatter(lambda x, p: f'{x/1000000:.1f}M'))
     
-    fig.add_trace(
-        go.Scatter(
-            x=[recent_data.index[-1]],
-            y=[last_price[1]],
-            mode='markers',
-            name='Harga Buka Saat Ini',
-            marker=dict(color='green', size=10),
-            hovertemplate='<b>Tanggal:</b> %{x}<br>' +
-                         '<b>Harga Buka Saat Ini:</b> IDR %{y:,.0f}<br>' +
-                         '<extra></extra>'
-        )
-    )
+    plt.xticks(rotation=45)
+    plt.tight_layout()
     
-    # Add predicted close price
-    fig.add_trace(
-        go.Scatter(
-            x=predictions_df.index,
-            y=predictions_df['close'],
-            mode='lines+markers',
-            name='Prediksi Harga Tutup',
-            line=dict(color='red', width=2, dash='dash'),
-            marker=dict(size=6),
-            hovertemplate='<b>Tanggal:</b> %{x}<br>' +
-                         '<b>Prediksi Harga Tutup:</b> IDR %{y:,.0f}<br>' +
-                         '<extra></extra>'
-        )
-    )
+    # Convert plot to base64 string
+    img_buffer = io.BytesIO()
+    plt.savefig(img_buffer, format='png', dpi=150, bbox_inches='tight')
+    img_buffer.seek(0)
+    img_string = base64.b64encode(img_buffer.read()).decode()
+    plt.close()
     
-    # Add predicted open price
-    fig.add_trace(
-        go.Scatter(
-            x=predictions_df.index,
-            y=predictions_df['open'],
-            mode='lines+markers',
-            name='Prediksi Harga Buka',
-            line=dict(color='orange', width=2, dash='dash'),
-            marker=dict(size=6, symbol='square'),
-            hovertemplate='<b>Tanggal:</b> %{x}<br>' +
-                         '<b>Prediksi Harga Buka:</b> IDR %{y:,.0f}<br>' +
-                         '<extra></extra>'
-        )
-    )
-    
-    # Update layout
-    fig.update_layout(
-        title={
-            'text': 'Prediksi Harga Emas - 7 Hari Kedepan',
-            'x': 0.5,
-            'xanchor': 'center',
-            'font': {'size': 20, 'family': 'Arial Black'}
-        },
-        xaxis_title='Tanggal',
-        yaxis_title='Harga (IDR)',
-        hovermode='x unified',
-        showlegend=True,
-        legend=dict(
-            orientation="h",
-            yanchor="bottom",
-            y=1.02,
-            xanchor="right",
-            x=1
-        ),
-        plot_bgcolor='white',
-        paper_bgcolor='white',
-        font=dict(family="Arial", size=12),
-        height=500,
-        margin=dict(l=50, r=50, t=80, b=50)
-    )
-    
-    # Update axes
-    fig.update_xaxes(
-        showgrid=True,
-        gridwidth=1,
-        gridcolor='lightgray',
-        showline=True,
-        linewidth=1,
-        linecolor='black'
-    )
-    
-    fig.update_yaxes(
-        showgrid=True,
-        gridwidth=1,
-        gridcolor='lightgray',
-        showline=True,
-        linewidth=1,
-        linecolor='black',
-        tickformat=',.0f'
-    )
-    
-    # Convert to HTML
-    html_string = pio.to_html(fig, include_plotlyjs='cdn', div_id="prediction-chart")
-    
-    return html_string
+    return img_string
 
 @app.route('/')
 def index():
@@ -306,7 +197,8 @@ def predict():
                 'open_price': round(row['open'], 2),
                 'close_change': round(row['close_change'], 2),
                 'open_change': round(row['open_change'], 2)
-            })        
+            })
+        
         response = {
             'success': True,
             'current_prices': {
@@ -318,7 +210,7 @@ def predict():
                 'close': round(total_close_change, 2),
                 'open': round(total_open_change, 2)
             },
-            'chart_html': chart_img
+            'chart': chart_img
         }
         
         return jsonify(response)
@@ -333,85 +225,25 @@ def data_analysis():
         data = load_data()
         if data is None:
             return render_template('error.html', error='Data file not found.')
-          # Create historical price chart with Plotly
-        fig = go.Figure()
-        
-        # Add close price line
-        fig.add_trace(
-            go.Scatter(
-                x=data.index,
-                y=data['close'],
-                mode='lines',
-                name='Harga Tutup',
-                line=dict(color='#1f77b4', width=1.5),
-                hovertemplate='<b>Tanggal:</b> %{x}<br>' +
-                             '<b>Harga Tutup:</b> IDR %{y:,.0f}<br>' +
-                             '<extra></extra>'
-            )
-        )
-        
-        # Add open price line
-        fig.add_trace(
-            go.Scatter(
-                x=data.index,
-                y=data['open'],
-                mode='lines',
-                name='Harga Buka',
-                line=dict(color='#2ca02c', width=1.5),
-                hovertemplate='<b>Tanggal:</b> %{x}<br>' +
-                             '<b>Harga Buka:</b> IDR %{y:,.0f}<br>' +
-                             '<extra></extra>'
-            )
-        )
-        
-        # Update layout
-        fig.update_layout(
-            title={
-                'text': 'Data Historis Harga Emas',
-                'x': 0.5,
-                'xanchor': 'center',
-                'font': {'size': 20, 'family': 'Arial Black'}
-            },
-            xaxis_title='Tanggal',
-            yaxis_title='Harga (IDR)',
-            hovermode='x unified',
-            showlegend=True,
-            legend=dict(
-                orientation="h",
-                yanchor="bottom",
-                y=1.02,
-                xanchor="right",
-                x=1
-            ),
-            plot_bgcolor='white',
-            paper_bgcolor='white',
-            font=dict(family="Arial", size=12),
-            height=400,
-            margin=dict(l=50, r=50, t=80, b=50)
-        )
-        
-        # Update axes
-        fig.update_xaxes(
-            showgrid=True,
-            gridwidth=1,
-            gridcolor='lightgray',
-            showline=True,
-            linewidth=1,
-            linecolor='black'
-        )
         
-        fig.update_yaxes(
-            showgrid=True,
-            gridwidth=1,
-            gridcolor='lightgray',
-            showline=True,
-            linewidth=1,
-            linecolor='black',
-            tickformat=',.0f'
-        )
+        # Create historical price chart
+        fig, ax = plt.subplots(figsize=(12, 6))
+        ax.plot(data.index, data['close'], 'b-', label='Close Price', linewidth=1.5)
+        ax.plot(data.index, data['open'], 'g-', label='Open Price', linewidth=1.5)
+        ax.set_title('Historical Gold Prices', fontsize=16, fontweight='bold')
+        ax.set_xlabel('Date', fontsize=12)
+        ax.set_ylabel('Price (IDR)', fontsize=12)
+        ax.legend()
+        ax.grid(True, alpha=0.3)
+        ax.yaxis.set_major_formatter(plt.FuncFormatter(lambda x, p: f'{x/1000000:.1f}M'))
+        plt.xticks(rotation=45)
+        plt.tight_layout()
         
-        # Convert to HTML
-        historical_chart = pio.to_html(fig, include_plotlyjs='cdn', div_id="historical-chart")
+        img_buffer = io.BytesIO()
+        plt.savefig(img_buffer, format='png', dpi=150, bbox_inches='tight')
+        img_buffer.seek(0)
+        historical_chart = base64.b64encode(img_buffer.read()).decode()
+        plt.close()
         
         # Calculate statistics
         stats = {
@@ -433,4 +265,4 @@ def data_analysis():
 if __name__ == '__main__':
     # For Hugging Face Spaces, use port 7860
     port = int(os.environ.get('PORT', 7860))
-    app.run(host='0.0.0.0', port=port, debug=False)
+    app.run(host='0.0.0.0', port=port, debug=False)