Using Boto3 to interact with amazon Aurora on RDS

When using Amazon RDS offerings (including Aurora), you don't connect to the database via any AWS API (including Boto). Instead you would use the native client of your chosen database. In the case of Aurora, you would connect using the MySQL Command Line client. From there, you can query it just like any other MySQL database.

There's a brief section of the "Getting Started" documentation that talks about connecting to your Aurora database:

Connecting to an Amazon Aurora DB Cluster

Here are a couple examples:

INSERT example:

import boto3

sql = """
        INSERT INTO YOUR_TABLE_NAME_HERE
        (
            your_column_name_1
            ,your_column_name_2
            ,your_column_name_3)
        VALUES(
            :your_param_1_name
            ,:your_param_2_name)
            ,:your_param_3_name
        """

param1 = {'name':'your_param_1_name', 'value':{'longValue': 5}}
param2 = {'name':'your_param_2_name', 'value':{'longValue': 63}}
param3 = {'name':'your_param_3_name', 'value':{'stringValue': 'para bailar la bamba'}}

param_set = [param1, param2, param3]

db_clust_arn = 'your_db_cluster_arn_here'

db_secret_arn = 'your_db_secret_arn_here'

rds_data = boto3.client('rds-data')

response = rds_data.execute_statement(
    resourceArn = db_clust_arn, 
    secretArn = db_secret_arn, 
    database = 'your_database_name_here', 
    sql = sql,
    parameters = param_set)

print(str(response))

READ example:

import boto3

rds_data = boto3.client('rds-data')

db_clust_arn = 'your_db_cluster_arn_here'

db_secret_arn = 'your_db_secret_arn_here'


employee_id = 35853

get_vacation_days_sql = f"""
    select vacation_days_remaining
    from employees_tbl
    where employee_id = {employee_id}    
        """


response1 = rds_data.execute_statement(
        resourceArn = db_clust_arn, 
        secretArn = db_secret_arn, 
        database = 'your_database_name_here', 
        sql = get_vacation_days_sql)

#recs is a list (of rows returned from Db)
recs = response1['records']

print(f"recs === {recs}")
#recs === [[{'longValue': 57}]]

#single_row is a list of dictionaries, where each dictionary represents a 
#column from that single row
for single_row in recs:
    print(f"single_row === {single_row}")
    #single_row === [{'longValue': 57}]
    
    #one_dict is a dictionary with one key value pair
    #where the key is the data type of the column and the 
    #value is the value of the column
    #each additional column is another dictionary
    for single_column_dict in single_row:
        print(f"one_dict === {single_column_dict}")
        # one_dict === {'longValue': 57}

        vacation_days_remaining = single_column_dict['longValue']
        
        print(f'vacation days remaining === {vacation_days_remaining}')

Source Link: https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/data-api.html#data-api.calling.python