Spaces:
Sleeping
Sleeping
File size: 1,770 Bytes
6ec8cbf 16d2e29 6ec8cbf 16d2e29 6ec8cbf 16d2e29 309dfff 16d2e29 6ec8cbf a33dacb 6ec8cbf a33dacb 6ec8cbf 16d2e29 6ec8cbf 16d2e29 6ec8cbf ded07cd 6ec8cbf |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 |
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)
|