I was able to mock AWS-Batch with python, moto, so I will leave it

Introduction

I mocked AWS-Batch using moto, and I was able to register the job, so I will leave it as a memorandum.

mock target resource

• IAM Role --AWS-Batch computing environment --AWS-Batch Job Queue --AWS-Batch job definition

code

test_aws_batch.py

#!/usr/bin/env python
# -*- coding: utf-8 -*-
import unittest
import boto3
from moto import mock_batch, mock_iam


class MyTestCase(unittest.TestCase):
    @mock_iam
    @mock_batch
    def test_aws_batch(self):
        client = boto3.client('batch')
        iam = boto3.client('iam')

        #mock iam role
        iams = iam.create_role(
            RoleName='test_matsu_iam',
            AssumeRolePolicyDocument='string',

        )
        iam_arn = iams.get('Role').get('Arn')
        print("iamRoleArn: " + iam_arn)

        # aws-batch computing environment mock
        batch = client.create_compute_environment(
            computeEnvironmentName='test_matsu_batch',
            type='UNMANAGED',
            serviceRole=iam_arn
        )
        compute_environment_arn = batch.get('computeEnvironmentArn')
        print("computeEnvironmentArn: " + compute_environment_arn)

        # aws-batch job queue mock
        job_qs = client.create_job_queue(
            jobQueueName='test_matsu_job_q',
            state='ENABLED',
            priority=1,
            computeEnvironmentOrder=[
                {
                    'order': 1,
                    'computeEnvironment': compute_environment_arn
                },
            ]
        )
        job_q_arn = job_qs.get('jobQueueArn')
        print("jobQueueArn: " + job_q_arn)

        # aws-batch job definition mock
        job_definition = client.register_job_definition(
            jobDefinitionName='test_matsu_job_definition',
            type='container',
            containerProperties={
                'image': 'string',
                'vcpus': 123,
                'memory': 123
            },
        )
        job_definition_arn = job_definition.get('jobDefinitionArn')
        print("jobDefinitionArn: " + job_definition_arn)

        #Add job
        client.submit_job(
            jobName='string',
            jobQueue=job_q_arn,
            jobDefinition=job_definition_arn
        )

        #Get job list
        jobs = client.list_jobs(
            jobQueue=job_q_arn
        )

        #Output job list
        print("jobSummaryList: " + str(jobs.get('jobSummaryList')))


if __name__ == '__main__':
    unittest.main()

Execution result

$ python -m unittest test.test_aws_batch -v
test_aws_batch (test.test_aws_batch.MyTestCase) ... iamRoleArn: arn:aws:iam::123456789012:role/test_matsu_iam
computeEnvironmentArn: arn:aws:batch:ap-northeast-1:123456789012:compute-environment/test_matsu_batch
jobQueueArn: arn:aws:batch:ap-northeast-1:123456789012:job-queue/test_matsu_job_q
jobDefinitionArn: arn:aws:batch:ap-northeast-1:123456789012:job-definition/test_matsu_job_definition:1
jobSummaryList: [{'jobId': 'ee3a3206-fdfe-404f-a1c1-9c444b41b546', 'jobName': 'string'}]
ok

----------------------------------------------------------------------
Ran 1 test in 0.167s

OK

Various resources were mocked and the job was successfully submitted.

At the end

With this mock, it is possible to test submitting jobs to AWS-Batch without using actual AWS resources. Unfortunately, the content of the submitted job is only jobId and jobName. It is unlikely to be available for tests related to job creation time or status. The conclusion is that it seems better to use mock of ʻunit test` for tests that use the submitted jobs.