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import pandas as pd
import mysql.connector

# Connect to the MariaDB database
cnx = mysql.connector.connect(user='your_username', password='your_password',
                              host='your_host', database='your_database')
cursor = cnx.cursor()

# Execute the primary query
primary_query = "SELECT * FROM tibtcare_ppm_st2.etl_ppm_replication_master"
cursor.execute(primary_query)

# Fetch all rows and construct a pandas DataFrame
rows = cursor.fetchall()
columns = [desc[0] for desc in cursor.description]
df = pd.DataFrame(rows, columns=columns)

# Filter the DataFrame
filtered_df = df[df['eprm_catalog'].isin(['PC', 'RELEASE']) & (df['eprm_anabled_flag'] == 'Y')]

# Perform secondary dynamic queries
for _, row in filtered_df.iterrows():
    eprm_table_name = row['eprm__table_name']
    eprm_join_cols_entity = row['eprm_join_cols_entity']
    eprm_join_cols_reim = row['eprm_join_cols_reim']

    secondary_query = f"SELECT COUNT(*) FROM tibtcare_ppm_st2.{eprm_table_name} WHERE ({eprm_join_cols_entity}) IN (SELECT {eprm_join_cols_reim} FROM gdf_credentials['SOURCE']['DB_SCHEMA'].release_entity_inst_map)"
    cursor.execute(secondary_query)
    result = cursor.fetchone()
    print(f"Count for {eprm_table_name}: {result[0]}")

# Close the database connection
cursor.close()
cnx.close()