app.py

import gradio as gr
from gradio.themes import Base
from gradio.themes.utils import colors, sizes, fonts
from typing import Iterable
import yfinance as yf
import numpy as np
import pandas as pd
import plotly.graph_objects as go
from datetime import datetime

# Custom Seafoam theme definition
class Seafoam(Base):
    def __init__(
        self,
        *,
        primary_hue: colors.Color | str = colors.emerald,
        secondary_hue: colors.Color | str = colors.blue,
        neutral_hue: colors.Color | str = colors.blue,
        spacing_size: sizes.Size | str = sizes.spacing_md,
        radius_size: sizes.Size | str = sizes.radius_md,
        text_size: sizes.Size | str = sizes.text_lg,
        font: fonts.Font | str | Iterable[fonts.Font | str] = (
            fonts.GoogleFont("Quicksand"),
            "ui-sans-serif",
            "sans-serif",
        ),
        font_mono: fonts.Font | str | Iterable[fonts.Font | str] = (
            fonts.GoogleFont("IBM Plex Mono"),
            "ui-monospace",
            "monospace",
        ),
    ):
        super().__init__(
            primary_hue=primary_hue,
            secondary_hue=secondary_hue,
            neutral_hue=neutral_hue,
            spacing_size=spacing_size,
            radius_size=radius_size,
            text_size=text_size,
            font=font,
            font_mono=font_mono,
        )
        super().set(
            body_background_fill="linear-gradient(to bottom right, *primary_50, *primary_100, *primary_200)",
            body_background_fill_dark="linear-gradient(to bottom right, *primary_900, *primary_800, *primary_700)",
            button_primary_background_fill="linear-gradient(90deg, *primary_300, *secondary_400)",
            button_primary_background_fill_hover="linear-gradient(90deg, *primary_200, *secondary_300)",
            button_primary_text_color="white",
            button_primary_background_fill_dark="linear-gradient(90deg, *primary_600, *secondary_800)",
            slider_color="*secondary_300",
            slider_color_dark="*secondary_600",
            block_title_text_weight="600",
            block_border_width="3px",
            block_shadow="*shadow_drop_lg",
            button_shadow="*shadow_drop_lg",
            button_large_padding="32px",
        )

seafoam = Seafoam()

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='#3A9184')))
        fig.add_trace(go.Scatter(x=extended_dates, y=log_trend, mode='lines', name='Log Trend', line=dict(color='#FF8C61')))
        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': 'Stock Log Charts',
                '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")
                ])
            )
        )

        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")

# Create Gradio interface with custom Seafoam theme
with gr.Blocks(theme=seafoam, title="Stock Log Charts") as iface:
    gr.Markdown("# Stock Log Charts")
    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()