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): db = initialize_database() 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)