AWS: Boto3: AssumeRole example which includes role usage

I'm trying to use the AssumeRole in such a way that i'm traversing multiple accounts and retrieving assets for those accounts. I've made it to this point:

import boto3
stsclient = boto3.client('sts')

assumedRoleObject = sts_client.assume_role(
RoleArn="arn:aws:iam::account-of-role-to-assume:role/name-of-role",
RoleSessionName="AssumeRoleSession1")

Great, i have the assumedRoleObject. But now i want to use that to list things like ELBs or something that isn't a built-in low level resource.

How does one go about doing that? If i may ask - please code out a full example, so that everyone can benefit.

Here's a code snippet from the official AWS documentation where an s3 resource is created for listing all s3 buckets. boto3 resources or clients for other services can be built in a similar fashion.

# create an STS client object that represents a live connection to the 
# STS service
sts_client = boto3.client('sts')

# Call the assume_role method of the STSConnection object and pass the role
# ARN and a role session name.
assumed_role_object=sts_client.assume_role(
    RoleArn="arn:aws:iam::account-of-role-to-assume:role/name-of-role",
    RoleSessionName="AssumeRoleSession1"
)

# From the response that contains the assumed role, get the temporary 
# credentials that can be used to make subsequent API calls
credentials=assumed_role_object['Credentials']

# Use the temporary credentials that AssumeRole returns to make a 
# connection to Amazon S3  
s3_resource=boto3.resource(
    's3',
    aws_access_key_id=credentials['AccessKeyId'],
    aws_secret_access_key=credentials['SecretAccessKey'],
    aws_session_token=credentials['SessionToken'],
)

# Use the Amazon S3 resource object that is now configured with the 
# credentials to access your S3 buckets. 
for bucket in s3_resource.buckets.all():
    print(bucket.name)

You can assume role using STS token, like:

class Boto3STSService(object):
    def __init__(self, arn):
        sess = Session(aws_access_key_id=ARN_ACCESS_KEY,
                       aws_secret_access_key=ARN_SECRET_KEY)
        sts_connection = sess.client('sts')
        assume_role_object = sts_connection.assume_role(
            RoleArn=arn, RoleSessionName=ARN_ROLE_SESSION_NAME,
            DurationSeconds=3600)
        self.credentials = assume_role_object['Credentials']

This will give you temporary access key and secret keys, with session token. With these temporary credentials, you can access any service. For Eg, if you want to access ELB, you can use the below code:

self.tmp_credentials = Boto3STSService(arn).credentials

def get_boto3_session(self):
    tmp_access_key = self.tmp_credentials['AccessKeyId']
    tmp_secret_key = self.tmp_credentials['SecretAccessKey']
    security_token = self.tmp_credentials['SessionToken']

    boto3_session = Session(
        aws_access_key_id=tmp_access_key,
        aws_secret_access_key=tmp_secret_key, aws_session_token=security_token
    )
    return boto3_session

def get_elb_boto3_connection(self, region):
    sess = self.get_boto3_session()
    elb_conn = sess.client(service_name='elb', region_name=region)
    return elb_conn