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_stock_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."

        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)}"

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")
            ])
        )
    )

    return fig

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")
            ])
        )
    )

    return fig

# Get the current date
current_date = datetime.now().strftime("%Y-%m-%d")

# Custom CSS for button and input hover effects, and to style the header image
custom_css = """
.center-text {
    text-align: center;
}

#generate-button:hover, #ticker-input input:hover, #start-date-input input:hover, #end-date-input input:hover {
    background-color: #FFB3BA !important;  /* Pastel red */
}

#header-image {
    display: block;
    margin: 0 auto;
    max-width: 100%;
    height: auto;
}
"""

# Create Gradio interface with custom Seafoam theme
with gr.Blocks(theme=seafoam, title="Log Stock Charts", css=custom_css) as iface:
    # Use the custom header image
    gr.Image("header.png", elem_id="header-image", show_label=False)
    
    gr.Markdown("Enter a stock ticker and date range to generate a chart.", elem_classes=["center-text"])
    
    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():
        stock_chart = gr.Plot(label="Stock Chart")
    
    submit_button.click(
        plot_interactive_stock_chart,
        inputs=[ticker, start_date, end_date, chart_type],
        outputs=[stock_chart]
    )

# Launch the app
iface.launch(show_api=False, show_error=False)