# numerical and statistical utilities
import numpy as np

# visualization requirements
import matplotlib.pyplot as plt
import plotly.graph_objs as go
import plotly.express as ex

# data utitilies
import yfinance as yf
import pandas as pd
import pandas_ta
import datetime as dt

# streamlit artiface 
import streamlit as st

# Observe recent changes
start = dt.datetime(2020, 1, 1).strftime('%Y-%m-%d')
end =  dt.date.today()
#end='2023-2-23'

# set ticker's symbol in yahoo stock
ticker='1303.TW'

# Downloading data

df = yf.download(ticker, start = start, end = end)

# More technic indexes

df['stoch_k'] = pandas_ta.stochrsi(close=df['Adj Close'],length=20).iloc[:,0]
df['stoch_d'] = pandas_ta.stochrsi(close=df['Adj Close'],length=20).iloc[:,1]
df['bb_lower'] = pandas_ta.bbands(close=df['Adj Close'],length=20).iloc[:,0]
df['bb_upper'] = pandas_ta.bbands(close=df['Adj Close'],length=20).iloc[:,2]
df['forward_1d'] = df['Adj Close'].pct_change(1).shift(-1)

fig=ex.line(df, x=df.index, y=['Adj Close','bb_lower','bb_upper'], title='南亞 (1303.TW) Adj Close with Bollinger Bands')
fig.update_layout(title_text=f'南亞 (1303.TW) Adj Close with Bollinger Bands', title_x=0.5);

# Plot!
st.plotly_chart(fig, use_container_width=True)