Create app.py

app.py

@@ -0,0 +1,104 @@
+import gradio as gr
+import yfinance as yf
+import numpy as np
+import pandas as pd
+import plotly.graph_objects as go
+from datetime import datetime
+
+def download_stock_data(ticker, start_date, end_date):
+    stock = yf.Ticker(ticker)
+    df = stock.history(start=start_date, end=end_date)
+    return df
+
+def plot_interactive_logarithmic_stock_chart(ticker, start_date, end_date):
+    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='green')))
+        fig.add_trace(go.Scatter(x=extended_dates, y=inner_lower_band, mode='lines', name='Inner Lower Band', line=dict(color='green')))
+        fig.add_trace(go.Scatter(x=extended_dates, y=outer_upper_band, mode='lines', name='Outer Upper Band', line=dict(color='orange')))
+        fig.add_trace(go.Scatter(x=extended_dates, y=outer_lower_band, mode='lines', name='Outer Lower Band', line=dict(color='orange')))
+
+        fig.update_layout(
+            title=f'{ticker} Stock Price (Logarithmic Scale) with Extended Trend Lines and Outer Bands',
+            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'
+        )
+
+        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)}"
+
+# Get the current date
+current_date = datetime.now().strftime("%Y-%m-%d")
+
+# Custom CSS to make charts full-width and larger
+custom_css = """
+.container {max-width: 100% !important; padding: 0 !important;}
+.plot-container {height: 800px !important; width: 100% !important;}
+.react-plotly-container {height: 100% !important; width: 100% !important;}
+"""
+
+# Create Gradio interface
+with gr.Blocks(css=custom_css, title="Alan's Logarithmic Charting Tool") as iface:
+    gr.Markdown("# Alan's Logarithmic Charting Tool")
+    gr.Markdown("Enter a stock ticker and date range to generate a logarithmic chart.")
+    
+    with gr.Row():
+        ticker = gr.Textbox(label="Stock Ticker", value="MSFT")
+        start_date = gr.Textbox(label="Start Date", value="2015-01-01")
+        end_date = gr.Textbox(label="End Date", value=current_date)
+    
+    submit_button = gr.Button("Generate Chart")
+    
+    with gr.Row():
+        log_plot = gr.Plot(label="Logarithmic Stock Chart")
+    
+    submit_button.click(
+        plot_interactive_logarithmic_stock_chart,
+        inputs=[ticker, start_date, end_date],
+        outputs=[log_plot]
+    )
+
+# Launch the app
+iface.launch()