app.py

import yfinance as yf
import pandas as pd
from bokeh.io import curdoc
from bokeh.layouts import column, row
from bokeh.models import ColumnDataSource, Select, CheckboxGroup, Div
from bokeh.plotting import figure
from bokeh.models.tools import HoverTool

# Available stocks and indicators
stocks = ['AAPL', 'GOOGL', 'MSFT', 'TSLA', 'AMZN']
indicators = ['SMA_20', 'EMA_20', 'RSI']

# Widgets
stock_select = Select(title="Select Stock:", value=stocks[0], options=stocks)
indicator_check = CheckboxGroup(labels=indicators, active=[0, 1])  # SMA and EMA selected by default
status_div = Div(text='')

# Data source
source = ColumnDataSource(data=dict(date=[], close=[], SMA_20=[], EMA_20=[], RSI=[]))

# Plot setup
p = figure(title="Stock Price", x_axis_type='datetime', width=1000, height=400)
p.line('date', 'close', source=source, line_width=2, color='navy', legend_label='Close Price')
p.add_tools(HoverTool(tooltips=[("Date", "@date{%F}"), ("Close", "@close")],
                      formatters={'@date': 'datetime'}, mode='vline'))

# Indicator lines
sma_line = p.line('date', 'SMA_20', source=source, line_width=2, color='green', legend_label='SMA 20')
ema_line = p.line('date', 'EMA_20', source=source, line_width=2, color='orange', legend_label='EMA 20')
rsi_plot = figure(title="RSI", x_axis_type='datetime', width=1000, height=200)
rsi_line = rsi_plot.line('date', 'RSI', source=source, line_width=2, color='purple', legend_label='RSI')

def fetch_data():
    try:
        ticker = stock_select.value
        df = yf.download(ticker, period='6mo', interval='1d')
        df.reset_index(inplace=True)
        df['SMA_20'] = df['Close'].rolling(window=20).mean()
        df['EMA_20'] = df['Close'].ewm(span=20, adjust=False).mean()
        delta = df['Close'].diff()
        gain = (delta.where(delta > 0, 0)).rolling(window=14).mean()
        loss = (-delta.where(delta < 0, 0)).rolling(window=14).mean()
        rs = gain / loss
        df['RSI'] = 100 - (100 / (1 + rs))
        df.fillna(method='bfill', inplace=True)
        source.data = {
            'date': df['Date'],
            'close': df['Close'],
            'SMA_20': df['SMA_20'],
            'EMA_20': df['EMA_20'],
            'RSI': df['RSI']
        }
        status_div.text = f"<b>Data fetched successfully for {ticker}</b>"
    except Exception as e:
        status_div.text = f"<b>Error fetching data: {e}</b>"

def update_plot(attr, old, new):
    active = indicator_check.active
    sma_line.visible = 0 in active
    ema_line.visible = 1 in active
    rsi_plot.visible = 2 in active

stock_select.on_change('value', lambda attr, old, new: fetch_data())
indicator_check.on_change('active', update_plot)

# Initial load
fetch_data()
update_plot(None, None, None)

# Layout
layout = column(status_div, row(stock_select, indicator_check), p, rsi_plot)
curdoc().add_root(layout)
curdoc().title = "Real-Time Stock Dashboard"