import pymysql
import json
import pandas as pd
import re
import streamlit as st
import logging

# Configure logging
logging.basicConfig(level=logging.INFO)  # Set logging level to INFO

# Database connection
def initialize_database():
    try:
        # Database Connection
        db_params = {"host": st.secrets["host"],
                     "user": st.secrets["username"],
                     "password": st.secrets["password"],
                     "port": int(st.secrets["port"]),
                     "database": st.secrets["database"],
                     }
        db = pymysql.connect(**db_params)
        logging.info("Connected to the database successfully!")
        return db
    except pymysql.MySQLError as e:
        logging.error("Error connecting to the database: %s", e)
        raise  # Re-raise the exception to propagate it up the call stack

def execute_query(query):
    print(f"Db initilaizing....")
    db = initialize_database()
    print(f"Db initialized....")
    cursor = db.cursor()
    try:
        cursor.execute(query)
        description = cursor.description
        result = cursor.fetchall()  # Fetch all rows from the result set
        db.commit()
        logging.info("Query executed successfully: %s", query)
        return description, result
    except Exception as e:
        logging.error("Error executing query: %s", e)
        db.rollback()
        return None  # Return None if an error occurs
    finally:
        db.close()


def get_details_mantra_json(query):
    description, data = execute_query(query)
    df = pd.DataFrame(data)
    df.columns = [x[0] for x in description]
    mantra_json = df['mantra_json'].values[0]
    cleaned_data = re.sub('<[^<]+?>', '', mantra_json)
    return json.loads(cleaned_data)