import streamlit as st
import sqlite3
import pandas as pd
import streamlit as st
import pygwalker as pyg
import streamlit.components.v1 as components


st.set_page_config(
    page_title="Financial Data",
    page_icon="📈",
    layout="wide",
    initial_sidebar_state="expanded",
)


st.title('Financial Data')
st.subheader('This is a BI tool to analyze news sentiment data')

conn = sqlite3.connect('fin_data.db')
c = conn.cursor()
c.execute("""
       select * from company_news
""")

rows = c.fetchall()

# Extract column names from the cursor
column_names = [description[0] for description in c.description]

conn.commit()
conn.close()

# Create a DataFrame
df = pd.DataFrame(rows, columns=column_names)

# setup pygwalker configuration: https://github.com/Kanaries/pygwalker, https://docs.kanaries.net/pygwalker/use-pygwalker-with-streamlit.en
pyg_html = pyg.walk(df, dark = 'dark', return_html=True)

components.html(pyg_html, height=1000, scrolling=True)