AWS Glue create_partition using boto3 successful, but Athena not showing results for query

I have a glue script to create new partitions using create_partition(). The glue script is running successfully, and i could see the partitions in the Athena console when using SHOW PARTITIONS. For glue script create_partitions, I did refer to this sample code here : https://medium.com/@bv_subhash/demystifying-the-ways-of-creating-partitions-in-glue-catalog-on-partitioned-s3-data-for-faster-e25671e65574

When I try to run a Athena query for a given partition which was newly added, I am getting no results.

Is it that I need to trigger the MSCK command, even if I add the partitions using create_partitions. Appreciate any suggestions please .

I have got the solution myself, wanted to share with SO community, so it would be useful someone. The following code when run as a glue job, creates partitions, and can also be queried in Athena for the new partition columns. Please change/add the parameter values db name, table name, partition columns as needed.

import boto3
import urllib.parse
import os
import copy
import sys

# Configure database / table name and emp_id, file_id from workflow params?
DATABASE_NAME = 'my_db'
TABLE_NAME = 'enter_table_name'
emp_id_tmp = ''
file_id_tmp = ''

# # Initialise the Glue client using Boto 3
glue_client = boto3.client('glue')

#get current table schema for the given database name & table name
def get_current_schema(database_name, table_name):
    try:
        response = glue_client.get_table(
            DatabaseName=DATABASE_NAME,
            Name=TABLE_NAME
        )
    except Exception as error:
        print("Exception while fetching table info")
        sys.exit(-1)
    
    # Parsing table info required to create partitions from table
    table_data = {}
    table_data['input_format'] = response['Table']['StorageDescriptor']['InputFormat']
    table_data['output_format'] = response['Table']['StorageDescriptor']['OutputFormat']
    table_data['table_location'] = response['Table']['StorageDescriptor']['Location']
    table_data['serde_info'] = response['Table']['StorageDescriptor']['SerdeInfo']
    table_data['partition_keys'] = response['Table']['PartitionKeys']
    
    return table_data

#prepare partition input list using table_data
def generate_partition_input_list(table_data):
    input_list = []  # Initializing empty list
    part_location = "{}/emp_id={}/file_id={}/".format(table_data['table_location'], emp_id_tmp, file_id_tmp)
    input_dict = {
        'Values': [
            emp_id_tmp, file_id_tmp
        ],
        'StorageDescriptor': {
            'Location': part_location,
            'InputFormat': table_data['input_format'],
            'OutputFormat': table_data['output_format'],
            'SerdeInfo': table_data['serde_info']
        }
    }
    input_list.append(input_dict.copy())
    return input_list

#create partition dynamically using the partition input list
table_data = get_current_schema(DATABASE_NAME, TABLE_NAME)
input_list = generate_partition_input_list(table_data)
try:
    create_partition_response = glue_client.batch_create_partition(
            DatabaseName=DATABASE_NAME,
            TableName=TABLE_NAME,
            PartitionInputList=input_list
        )
    print('Glue partition created successfully.') 
    print(create_partition_response)
except Exception as e:
            # Handle exception as per your business requirements
            print(e)