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import gradio as gr |
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import yfinance as yf |
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import numpy as np |
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import pandas as pd |
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import plotly.graph_objects as go |
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from datetime import datetime |
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def download_stock_data(ticker, start_date, end_date): |
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stock = yf.Ticker(ticker) |
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df = stock.history(start=start_date, end=end_date) |
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return df |
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def plot_interactive_logarithmic_stock_chart(ticker, start_date, end_date): |
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try: |
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stock = yf.Ticker(ticker) |
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data = stock.history(start=start_date, end=end_date) |
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if data.empty: |
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return "No data available for the specified date range." |
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x = (data.index - data.index[0]).days |
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y = np.log(data['Close']) |
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slope, intercept = np.polyfit(x, y, 1) |
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future_days = 365 * 10 |
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all_days = np.arange(len(x) + future_days) |
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log_trend = np.exp(intercept + slope * all_days) |
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inner_upper_band = log_trend * 2 |
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inner_lower_band = log_trend / 2 |
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outer_upper_band = log_trend * 4 |
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outer_lower_band = log_trend / 4 |
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extended_dates = pd.date_range(start=data.index[0], periods=len(all_days), freq='D') |
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fig = go.Figure() |
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fig.add_trace(go.Scatter(x=data.index, y=data['Close'], mode='lines', name='Close Price', line=dict(color='blue'))) |
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fig.add_trace(go.Scatter(x=extended_dates, y=log_trend, mode='lines', name='Log Trend', line=dict(color='red'))) |
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fig.add_trace(go.Scatter(x=extended_dates, y=inner_upper_band, mode='lines', name='Inner Upper Band', line=dict(color='green'))) |
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fig.add_trace(go.Scatter(x=extended_dates, y=inner_lower_band, mode='lines', name='Inner Lower Band', line=dict(color='green'))) |
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fig.add_trace(go.Scatter(x=extended_dates, y=outer_upper_band, mode='lines', name='Outer Upper Band', line=dict(color='orange'))) |
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fig.add_trace(go.Scatter(x=extended_dates, y=outer_lower_band, mode='lines', name='Outer Lower Band', line=dict(color='orange'))) |
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fig.update_layout( |
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title=f'{ticker} Stock Price (Logarithmic Scale) with Extended Trend Lines and Outer Bands', |
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xaxis_title='Date', |
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yaxis_title='Price (Log Scale)', |
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yaxis_type="log", |
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height=800, |
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legend=dict(x=0.01, y=0.99, bgcolor='rgba(255, 255, 255, 0.8)'), |
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hovermode='x unified' |
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) |
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fig.update_xaxes( |
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rangeslider_visible=True, |
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rangeselector=dict( |
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buttons=list([ |
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dict(count=1, label="1m", step="month", stepmode="backward"), |
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dict(count=6, label="6m", step="month", stepmode="backward"), |
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dict(count=1, label="YTD", step="year", stepmode="todate"), |
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dict(count=1, label="1y", step="year", stepmode="backward"), |
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dict(step="all") |
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]) |
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) |
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) |
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return fig |
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except Exception as e: |
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return f"An error occurred: {str(e)}" |
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current_date = datetime.now().strftime("%Y-%m-%d") |
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custom_css = """ |
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.container {max-width: 100% !important; padding: 0 !important;} |
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.plot-container {height: 800px !important; width: 100% !important;} |
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.react-plotly-container {height: 100% !important; width: 100% !important;} |
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""" |
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with gr.Blocks(css=custom_css, title="Alan's Logarithmic Charting Tool") as iface: |
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gr.Markdown("# Alan's Logarithmic Charting Tool") |
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gr.Markdown("Enter a stock ticker and date range to generate a logarithmic chart.") |
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with gr.Row(): |
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ticker = gr.Textbox(label="Stock Ticker", value="MSFT") |
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start_date = gr.Textbox(label="Start Date", value="2015-01-01") |
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end_date = gr.Textbox(label="End Date", value=current_date) |
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submit_button = gr.Button("Generate Chart") |
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with gr.Row(): |
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log_plot = gr.Plot(label="Logarithmic Stock Chart") |
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submit_button.click( |
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plot_interactive_logarithmic_stock_chart, |
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inputs=[ticker, start_date, end_date], |
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outputs=[log_plot] |
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) |
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iface.launch() |
