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import pandas as pd
import mysql.connector

cnx = mysql.connector.connect(user='tibtcare_ppm_st2', password='tibtcare_ppm_st2',
                              host='10.16.16.128', port='3308')
cursor = cnx.cursor()

primary_query = "SELECT * FROM tibtcare_ppm_st2.etl_ppm_replication_master"
cursor.execute(primary_query)

rows = cursor.fetchall()
columns = [desc[0] for desc in cursor.description]
df = pd.DataFrame(rows, columns=columns)

filtered_df = df[df['eprm_catalog'].isin(['PC']) & (df['eprm_enabled_flg'] == 'Y')]

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']
    eprm_table_alias = row['eprm_table_alias']

    # Replace 'AND' with ',' in eprm_join_cols_reim
    eprm_join_cols_reim = eprm_join_cols_reim.replace('AND', ',')
    # Split the string by ',' to get individual column assignments
    columns_reim = eprm_join_cols_reim.split(',')

    # Construct the modified assignment string
    assignment_string = ''
    for col_reim in columns_reim:
        # Extract the column name after '='
        col_name = col_reim.split('=')[0].strip()
        # Append the modified assignment to the string
        assignment_string += f"{col_reim.replace(col_name, eprm_table_alias + '.' + col_name)}, "

    # remove the trailing comma and whitespace
    assignment_string = assignment_string.rstrip(', ')
    assignment_string = assignment_string.replace("AND", ",")

    secondary_query = f"SELECT COUNT(*) FROM tibtcare_ppm_st2.{eprm_table_name} WHERE ({eprm_join_cols_entity}) IN (SELECT {eprm_join_cols_entity} FROM tibtcare_ppm_st2.release_entity_inst_map)"

    # extract only the column names after "=" and "."
    column_names = [col.split('=')[1].split('.')[-1].strip() for col in columns_reim]
    # Create a string of the extracted column names separated by commas
    column_names_string = ', '.join(column_names)

    # replace the column fields in the secondary query with the extracted column names
    secondary_query = secondary_query.replace(assignment_string, column_names_string)
    cursor.execute(secondary_query)
    result = cursor.fetchone()
    print(secondary_query)
    print(f"Count for {eprm_table_name}: {result[0]}")

cursor.close()
cnx.close()