app.py

import streamlit as st
import yfinance as yf
import pandas as pd
import cufflinks as cf
import datetime
import plotly.graph_objects as go

# App title
st.markdown('''
# Sovrenn Market Sentiment Indicator App
Shown are the stock price data for the selected company!

**Credits**
- App built by SRL
''')
st.write('---')

# Sidebar
st.sidebar.subheader('Query parameters')
start_date = st.sidebar.date_input("Start date", datetime.date(2023,9, 20))
#start_date = start_date - datetime.timedelta(days=1) 
end_date = start_date + datetime.timedelta(days=14)

# User input for the stock ticker symbol
tickerSymbol = st.sidebar.text_input('Enter Stock Ticker Symbol')

if tickerSymbol:
    tickerData = yf.Ticker(tickerSymbol)  # Get ticker data
    tickerDf = tickerData.history(period='1d', start=start_date, end=end_date)  # Get the historical prices for this ticker

    string_name = tickerData.info.get('longName', 'Company Name Not Available')
    st.header('**%s**' % string_name)

    # Try to get the business summary, handle KeyError if not available
    try:
        string_summary = tickerData.info['longBusinessSummary']
        st.info(string_summary)
    except KeyError:
        st.warning("Business summary not available for this company.")

    # Ticker data
    st.header('**Ticker data**')
    st.write(tickerDf)



    # Create a candlestick chart and volume bar chart
    fig_candlestick = go.Figure(data=[go.Candlestick(x=tickerDf.index,
                                                     open=tickerDf['Open'],
                                                     high=tickerDf['High'],
                                                     low=tickerDf['Low'],
                                                     close=tickerDf['Close'])])

    fig_volume = go.Figure(data=[go.Bar(x=tickerDf.index, y=tickerDf['Volume'])])

    st.header('**Candlestick Chart**')
    st.plotly_chart(fig_candlestick)

    st.header('**Volume Bar Chart**')
    st.plotly_chart(fig_volume)
    
    
    st.write(start_date)
    tickerDf = pd.DataFrame(tickerDf).reset_index()

#    st.write(tickerDf)

    #date = datetime.date(start_date)
    date_str = start_date.strftime("%Y-%m-%d")
    st.write(date_str)
    df = tickerDf[tickerDf["Date"]==date_str]
    st.write(df)

    if (Df["Close"][0] > Df["Open"][0] ):
        st.write("NSE has uptrend on " +date_str )
    if (Df["Close"][0] < Df["Open"][0] ):
        st.write(" NSE has downdtrend on " +date_str )




else:
    st.warning("Please enter a valid Stock Ticker Symbol.")