Update app.py

app.py

@@ -63,73 +63,147 @@ def download_stock_data(ticker, start_date, end_date):
     df = stock.history(start=start_date, end=end_date)
     return df
 
-def plot_interactive_logarithmic_stock_chart(ticker, start_date, end_date):
+def plot_chart(ticker, start_date, end_date, chart_type):
     try:
         stock = yf.Ticker(ticker)
         data = stock.history(start=start_date, end=end_date)
 
         if data.empty:
-            return "No data available for the specified date range."
-
-        x = (data.index - data.index[0]).days
-        y = np.log(data['Close'])
-        slope, intercept = np.polyfit(x, y, 1)
-
-        future_days = 365 * 10
-        all_days = np.arange(len(x) + future_days)
-        log_trend = np.exp(intercept + slope * all_days)
-
-        inner_upper_band = log_trend * 2
-        inner_lower_band = log_trend / 2
-        outer_upper_band = log_trend * 4
-        outer_lower_band = log_trend / 4
-
-        extended_dates = pd.date_range(start=data.index[0], periods=len(all_days), freq='D')
-
-        fig = go.Figure()
-
-        fig.add_trace(go.Scatter(x=data.index, y=data['Close'], mode='lines', name='Close Price', line=dict(color='blue')))
-        fig.add_trace(go.Scatter(x=extended_dates, y=log_trend, mode='lines', name='Log Trend', line=dict(color='red')))
-        fig.add_trace(go.Scatter(x=extended_dates, y=inner_upper_band, mode='lines', name='Inner Upper Band', line=dict(color='#6FB1A7')))
-        fig.add_trace(go.Scatter(x=extended_dates, y=inner_lower_band, mode='lines', name='Inner Lower Band', line=dict(color='#6FB1A7')))
-        fig.add_trace(go.Scatter(x=extended_dates, y=outer_upper_band, mode='lines', name='Outer Upper Band', line=dict(color='#FFC2A5')))
-        fig.add_trace(go.Scatter(x=extended_dates, y=outer_lower_band, mode='lines', name='Outer Lower Band', line=dict(color='#FFC2A5')))
-
-        fig.update_layout(
-            title={
-                'text': f'Stock Log Chart: {ticker}',
-                'y': 0.95,
-                'x': 0.5,
-                'xanchor': 'center',
-                'yanchor': 'top'
-            },
-            xaxis_title='Date',
-            yaxis_title='Price (Log Scale)',
-            yaxis_type="log",
-            height=800,
-            legend=dict(x=0.01, y=0.99, bgcolor='rgba(255, 255, 255, 0.8)'),
-            hovermode='x unified',
-            plot_bgcolor='#F5F9F8',
-            paper_bgcolor='#F5F9F8',
-            font=dict(family="Quicksand, sans-serif", size=12, color="#313D38")
+            return "No data available for the specified date range.", None, None, None
+
+        if chart_type == "Log":
+            return plot_logarithmic_chart(data, ticker)
+        else:
+            return plot_candlestick_chart(data, ticker)
+
+    except Exception as e:
+        return f"An error occurred: {str(e)}", None, None, None
+
+def plot_logarithmic_chart(data, ticker):
+    x = (data.index - data.index[0]).days
+    y = np.log(data['Close'])
+    slope, intercept = np.polyfit(x, y, 1)
+
+    future_days = 365 * 10
+    all_days = np.arange(len(x) + future_days)
+    log_trend = np.exp(intercept + slope * all_days)
+
+    inner_upper_band = log_trend * 2
+    inner_lower_band = log_trend / 2
+    outer_upper_band = log_trend * 4
+    outer_lower_band = log_trend / 4
+
+    extended_dates = pd.date_range(start=data.index[0], periods=len(all_days), freq='D')
+
+    fig = go.Figure()
+
+    fig.add_trace(go.Scatter(x=data.index, y=data['Close'], mode='lines', name='Close Price', line=dict(color='blue')))
+    fig.add_trace(go.Scatter(x=extended_dates, y=log_trend, mode='lines', name='Log Trend', line=dict(color='red')))
+    fig.add_trace(go.Scatter(x=extended_dates, y=inner_upper_band, mode='lines', name='Inner Upper Band', line=dict(color='#6FB1A7')))
+    fig.add_trace(go.Scatter(x=extended_dates, y=inner_lower_band, mode='lines', name='Inner Lower Band', line=dict(color='#6FB1A7')))
+    fig.add_trace(go.Scatter(x=extended_dates, y=outer_upper_band, mode='lines', name='Outer Upper Band', line=dict(color='#FFC2A5')))
+    fig.add_trace(go.Scatter(x=extended_dates, y=outer_lower_band, mode='lines', name='Outer Lower Band', line=dict(color='#FFC2A5')))
+
+    fig.update_layout(
+        title={
+            'text': f'Stock Log Chart: {ticker}',
+            'y': 0.95,
+            'x': 0.5,
+            'xanchor': 'center',
+            'yanchor': 'top'
+        },
+        xaxis_title='Date',
+        yaxis_title='Price (Log Scale)',
+        yaxis_type="log",
+        height=800,
+        legend=dict(x=0.01, y=0.99, bgcolor='rgba(255, 255, 255, 0.8)'),
+        hovermode='x unified',
+        plot_bgcolor='#F5F9F8',
+        paper_bgcolor='#F5F9F8',
+        font=dict(family="Quicksand, sans-serif", size=12, color="#313D38")
+    )
+
+    fig.update_xaxes(
+        rangeslider_visible=True,
+        rangeselector=dict(
+            buttons=list([
+                dict(count=1, label="1m", step="month", stepmode="backward"),
+                dict(count=6, label="6m", step="month", stepmode="backward"),
+                dict(count=1, label="YTD", step="year", stepmode="todate"),
+                dict(count=1, label="1y", step="year", stepmode="backward"),
+                dict(step="all")
+            ])
         )
+    )
+
+    current_price = data['Close'].iloc[-1]
+    log_price = log_trend[-len(data):]
+    percent_diff = ((current_price - log_price.iloc[-1]) / log_price.iloc[-1]) * 100
+
+    return fig, current_price, log_price.iloc[-1], percent_diff
+
+def plot_candlestick_chart(data, ticker):
+    fig = go.Figure(data=[go.Candlestick(x=data.index,
+                open=data['Open'],
+                high=data['High'],
+                low=data['Low'],
+                close=data['Close'])])
+
+    fig.update_layout(
+        title={
+            'text': f'Stock Candlestick Chart: {ticker}',
+            'y': 0.95,
+            'x': 0.5,
+            'xanchor': 'center',
+            'yanchor': 'top'
+        },
+        xaxis_title='Date',
+        yaxis_title='Price',
+        height=800,
+        legend=dict(x=0.01, y=0.99, bgcolor='rgba(255, 255, 255, 0.8)'),
+        hovermode='x unified',
+        plot_bgcolor='#F5F9F8',
+        paper_bgcolor='#F5F9F8',
+        font=dict(family="Quicksand, sans-serif", size=12, color="#313D38")
+    )
 
-        fig.update_xaxes(
-            rangeslider_visible=True,
-            rangeselector=dict(
-                buttons=list([
-                    dict(count=1, label="1m", step="month", stepmode="backward"),
-                    dict(count=6, label="6m", step="month", stepmode="backward"),
-                    dict(count=1, label="YTD", step="year", stepmode="todate"),
-                    dict(count=1, label="1y", step="year", stepmode="backward"),
-                    dict(step="all")
-                ])
-            )
+    fig.update_xaxes(
+        rangeslider_visible=True,
+        rangeselector=dict(
+            buttons=list([
+                dict(count=1, label="1m", step="month", stepmode="backward"),
+                dict(count=6, label="6m", step="month", stepmode="backward"),
+                dict(count=1, label="YTD", step="year", stepmode="todate"),
+                dict(count=1, label="1y", step="year", stepmode="backward"),
+                dict(step="all")
+            ])
         )
+    )
 
-        return fig
-    except Exception as e:
-        return f"An error occurred: {str(e)}"
+    current_price = data['Close'].iloc[-1]
+    return fig, current_price, None, None
+
+def format_price_info(current_price, log_price, percent_diff):
+    if log_price is None or percent_diff is None:
+        return f"Current Price: ${current_price:.2f}"
+    
+    color = "green" if percent_diff > 0 else "red"
+    intensity = min(abs(percent_diff) / 100, 1)  # Normalize to 0-1
+    bg_color = f"rgba({255 if color == 'red' else 0}, {255 if color == 'green' else 0}, 0, {intensity})"
+    
+    return f"""
+    <div style="display: flex; justify-content: space-between; padding: 10px; background-color: {bg_color}; border-radius: 10px;">
+        <div>
+            <p>Current Price: ${current_price:.2f}</p>
+            <p>Log Price: ${log_price:.2f}</p>
+        </div>
+        <div>
+            <p style="font-size: 1.2em; font-weight: bold; color: {color};">
+                {percent_diff:.2f}% {'above' if percent_diff > 0 else 'below'} log price
+            </p>
+        </div>
+    </div>
+    """
 
 # Get the current date
 current_date = datetime.now().strftime("%Y-%m-%d")
@@ -146,24 +220,33 @@ custom_css = """
 """
 
 # Create Gradio interface with custom Seafoam theme
-with gr.Blocks(theme=seafoam, title="Stock Log Charts", css=custom_css) as iface:
-    gr.Markdown("# Stock Log Charts")
-    gr.Markdown("Enter a stock ticker and date range to generate a logarithmic chart.")
+with gr.Blocks(theme=seafoam, title="Stock Charts", css=custom_css) as iface:
+    gr.Markdown("# Stock Charts")
+    gr.Markdown("Enter a stock ticker and date range to generate a chart.")
     
     with gr.Row():
         ticker = gr.Textbox(label="Stock Ticker", value="MSFT", elem_id="ticker-input")
         start_date = gr.Textbox(label="Start Date", value="2015-01-01", elem_id="start-date-input")
         end_date = gr.Textbox(label="End Date", value=current_date, elem_id="end-date-input")
     
+    with gr.Accordion("Chart Options", open=False):
+        chart_type = gr.Radio(["Log", "Candlestick"], label="Chart Type", value="Log")
+    
     submit_button = gr.Button("Generate Chart", elem_id="generate-button")
     
     with gr.Row():
-        log_plot = gr.Plot(label="Logarithmic Stock Chart")
+        chart = gr.Plot(label="Stock Chart")
     
+    price_info = gr.HTML(label="Price Information")
+
     submit_button.click(
-        plot_interactive_logarithmic_stock_chart,
-        inputs=[ticker, start_date, end_date],
-        outputs=[log_plot]
+        plot_chart,
+        inputs=[ticker, start_date, end_date, chart_type],
+        outputs=[chart, price_info]
+    ).then(
+        lambda current_price, log_price, percent_diff: format_price_info(current_price, log_price, percent_diff),
+        inputs=[gr.State(None), gr.State(None), gr.State(None)],
+        outputs=[price_info]
     )
 
 # Launch the app