app.py

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()