Update app.py

app.py

@@ -8,6 +8,7 @@ from datetime import datetime, timedelta
 import warnings
 warnings.filterwarnings('ignore')
 
+# List of companies with their symbols
 COMPANIES = {
     'Apple (AAPL)': 'AAPL',
     'Microsoft (MSFT)': 'MSFT',
@@ -31,15 +32,16 @@ COMPANIES = {
     'Netflix (NFLX)': 'NFLX'
 }
 
-def calculate_metrics(df: pd.DataFrame) -> pd.DataFrame:
+def calculate_metrics(df):
+    """Calculate technical indicators"""
     data = df.copy()
     
-    # Calculate basic metrics
+    # Basic metrics
     data['Returns'] = data['Close'].pct_change()
     data['SMA_20'] = data['Close'].rolling(window=20).mean()
     data['SMA_50'] = data['Close'].rolling(window=50).mean()
     
-    # Calculate RSI
+    # RSI
     delta = data['Close'].diff()
     gain = delta.clip(lower=0)
     loss = -delta.clip(upper=0)
@@ -48,23 +50,25 @@ def calculate_metrics(df: pd.DataFrame) -> pd.DataFrame:
     rs = avg_gain / avg_loss
     data['RSI'] = 100 - (100 / (1 + rs))
     
-    # Calculate Bollinger Bands
-    rolling_mean = data['Close'].rolling(window=20).mean()
-    rolling_std = data['Close'].rolling(window=20).std()
-    data['BB_middle'] = rolling_mean
-    data['BB_upper'] = rolling_mean + (rolling_std * 2)
-    data['BB_lower'] = rolling_mean - (rolling_std * 2)
+    # Bollinger Bands
+    data['BB_middle'] = data['Close'].rolling(window=20).mean()
+    bb_std = data['Close'].rolling(window=20).std()
+    data['BB_upper'] = data['BB_middle'] + (2 * bb_std)
+    data['BB_lower'] = data['BB_middle'] - (2 * bb_std)
     
     return data
 
-def create_analysis_plots(data: pd.DataFrame) -> list:
+def create_plots(data):
+    """Create analysis plots"""
     # Price and Volume Plot
-    fig1 = make_subplots(rows=2, cols=1, shared_xaxes=True,
-                        subplot_titles=('Price and Moving Averages', 'Volume'),
-                        row_heights=[0.7, 0.3],
-                        vertical_spacing=0.1)
-    
-    # Price and SMAs
+    fig1 = make_subplots(
+        rows=2, cols=1,
+        shared_xaxes=True,
+        vertical_spacing=0.1,
+        subplot_titles=('Price and Moving Averages', 'Volume'),
+        row_heights=[0.7, 0.3]
+    )
+
     fig1.add_trace(
         go.Scatter(x=data.index, y=data['Close'], name='Close', line=dict(color='blue')),
         row=1, col=1
@@ -78,20 +82,22 @@ def create_analysis_plots(data: pd.DataFrame) -> list:
         row=1, col=1
     )
     
-    # Volume
     fig1.add_trace(
         go.Bar(x=data.index, y=data['Volume'], name='Volume', marker_color='lightblue'),
         row=2, col=1
     )
     
     fig1.update_layout(height=600, title_text="Price Analysis")
-    
-    # Technical Indicators Plot
-    fig2 = make_subplots(rows=2, cols=1, shared_xaxes=True,
-                        subplot_titles=('RSI', 'Bollinger Bands'),
-                        row_heights=[0.5, 0.5],
-                        vertical_spacing=0.1)
-    
+
+    # Technical Analysis Plot
+    fig2 = make_subplots(
+        rows=2, cols=1,
+        shared_xaxes=True,
+        vertical_spacing=0.1,
+        subplot_titles=('RSI', 'Bollinger Bands'),
+        row_heights=[0.5, 0.5]
+    )
+
     # RSI
     fig2.add_trace(
         go.Scatter(x=data.index, y=data['RSI'], name='RSI', line=dict(color='purple')),
@@ -105,53 +111,52 @@ def create_analysis_plots(data: pd.DataFrame) -> list:
         go.Scatter(x=data.index, y=data['Close'], name='Close', line=dict(color='blue')),
         row=2, col=1
     )
-    fig2.add_trace(
-        go.Scatter(x=data.index, y=data['BB_upper'], name='Upper BB', 
-                  line=dict(color='gray', dash='dash')),
-        row=2, col=1
-    )
-    fig2.add_trace(
-        go.Scatter(x=data.index, y=data['BB_middle'], name='Middle BB',
-                  line=dict(color='red', dash='dash')),
-        row=2, col=1
-    )
-    fig2.add_trace(
-        go.Scatter(x=data.index, y=data['BB_lower'], name='Lower BB',
-                  line=dict(color='gray', dash='dash')),
-        row=2, col=1
-    )
+    for band, color in [('BB_upper', 'gray'), ('BB_middle', 'red'), ('BB_lower', 'gray')]:
+        fig2.add_trace(
+            go.Scatter(x=data.index, y=data[band], name=band, line=dict(color=color, dash='dash')),
+            row=2, col=1
+        )
     
     fig2.update_layout(height=600, title_text="Technical Analysis")
     
     return [fig1, fig2]
 
-def generate_summary(data: pd.DataFrame, symbol: str) -> str:
-    current_price = data['Close'].iloc[-1]
-    prev_price = data['Close'].iloc[-2]
-    daily_return = ((current_price - prev_price) / prev_price) * 100
-    
-    rsi = data['RSI'].iloc[-1]
-    sma_20 = data['SMA_20'].iloc[-1]
-    sma_50 = data['SMA_50'].iloc[-1]
-    
-    summary = f"""Analysis Summary for {symbol}:
-    
+def generate_summary(data, symbol):
+    """Generate analysis summary"""
+    try:
+        current_price = float(data['Close'].iloc[-1])
+        prev_price = float(data['Close'].iloc[-2])
+        daily_return = ((current_price - prev_price) / prev_price) * 100
+        
+        rsi = float(data['RSI'].iloc[-1])
+        sma_20 = float(data['SMA_20'].iloc[-1])
+        sma_50 = float(data['SMA_50'].iloc[-1])
+        volume = float(data['Volume'].iloc[-1])
+        
+        bb_position = "in middle range"
+        if current_price > float(data['BB_upper'].iloc[-1] * 0.95):
+            bb_position = "near upper band (potential resistance)"
+        elif current_price < float(data['BB_lower'].iloc[-1] * 1.05):
+            bb_position = "near lower band (potential support)"
+
+        summary = f"""Analysis Summary for {symbol}:
+
 • Current Price: ${current_price:.2f}
 • Daily Change: {daily_return:+.2f}%
-• Trend: {'Bullish' if sma_20 > sma_50 else 'Bearish'} (20-day MA vs 50-day MA)
-• RSI: {rsi:.2f} ({'Overbought' if rsi > 70 else 'Oversold' if rsi < 30 else 'Neutral'})
-• Volume: {data['Volume'].iloc[-1]:,.0f}
+• Trend: {"Bullish" if sma_20 > sma_50 else "Bearish"} (20-day MA vs 50-day MA)
+• RSI: {rsi:.2f} ({"Overbought" if rsi > 70 else "Oversold" if rsi < 30 else "Neutral"})
+• Volume: {volume:,.0f}
 
 Technical Signals:
-• Moving Averages: Price is {'above' if current_price > sma_20 else 'below'} 20-day MA
-• Bollinger Bands: Price is {
-    'near upper band (potential resistance)' if current_price > data['BB_upper'].iloc[-1] * 0.95
-    else 'near lower band (potential support)' if current_price < data['BB_lower'].iloc[-1] * 1.05
-    else 'in middle range'}
+• Moving Averages: Price is {"above" if current_price > sma_20 else "below"} 20-day MA
+• Bollinger Bands: Price is {bb_position}
 """
-    return summary
+        return summary
+    except Exception as e:
+        return f"Error generating summary: {str(e)}"
 
-def analyze_stock(company: str, lookback_days: int = 180) -> tuple:
+def analyze_stock(company, lookback_days=180):
+    """Main analysis function"""
     try:
         symbol = COMPANIES[company]
         end_date = datetime.now()
@@ -159,26 +164,21 @@ def analyze_stock(company: str, lookback_days: int = 180) -> tuple:
         
         # Download data
         data = yf.download(symbol, start=start_date, end=end_date)
-        
         if len(data) == 0:
             return "No data available for the selected period.", None, None
         
-        # Calculate metrics
+        # Calculate metrics and create analysis
         data = calculate_metrics(data)
-        
-        # Generate analysis
         summary = generate_summary(data, symbol)
-        plots = create_analysis_plots(data)
+        plots = create_plots(data)
         
         return summary, plots[0], plots[1]
-    
+        
     except Exception as e:
         return f"Error analyzing stock: {str(e)}", None, None
 
-def refresh_analysis(company, lookback_days):
-    return analyze_stock(company, lookback_days)
-
-def create_gradio_interface():
+def create_interface():
+    """Create Gradio interface"""
     with gr.Blocks() as interface:
         gr.Markdown("# Stock Market Analysis Dashboard")
         
@@ -199,23 +199,24 @@ def create_gradio_interface():
         
         with gr.Row():
             summary = gr.Textbox(label="Analysis Summary", lines=10)
-        
+            
         with gr.Row():
             plot1 = gr.Plot(label="Price Analysis")
             plot2 = gr.Plot(label="Technical Analysis")
         
+        # Event handlers
         refresh_btn.click(
-            fn=refresh_analysis,
+            fn=analyze_stock,
             inputs=[company, lookback],
             outputs=[summary, plot1, plot2]
         )
         
-        # Auto-update on selection changes
         company.change(
             fn=analyze_stock,
             inputs=[company, lookback],
             outputs=[summary, plot1, plot2]
         )
+        
         lookback.release(
             fn=analyze_stock,
             inputs=[company, lookback],
@@ -225,5 +226,5 @@ def create_gradio_interface():
     return interface
 
 if __name__ == "__main__":
-    interface = create_gradio_interface()
+    interface = create_interface()
     interface.launch(share=True)