mirror of
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325 lines
10 KiB
Python
325 lines
10 KiB
Python
#!/usr/bin/python
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# Copyright (c) 2017 Jon Meran <jonathan.meran@sonos.com>
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# GNU General Public License v3.0+ (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt)
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ANSIBLE_METADATA = {'metadata_version': '1.1',
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'status': ['preview'],
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'supported_by': 'community'}
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DOCUMENTATION = '''
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---
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module: aws_batch_job_queue
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short_description: Manage AWS Batch Job Queues
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description:
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- This module allows the management of AWS Batch Job Queues.
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It is idempotent and supports "Check" mode. Use module M(aws_batch_compute_environment) to manage the compute
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environment, M(aws_batch_job_queue) to manage job queues, M(aws_batch_job_definition) to manage job definitions.
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version_added: "2.5"
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author: Jon Meran (@jonmer85)
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options:
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job_queue_name:
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description:
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- The name for the job queue
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required: true
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state:
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description:
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- Describes the desired state.
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required: true
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default: "present"
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choices: ["present", "absent"]
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job_queue_state:
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description:
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- The state of the job queue. If the job queue state is ENABLED , it is able to accept jobs.
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default: "ENABLED"
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choices: ["ENABLED", "DISABLED"]
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priority:
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description:
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- The priority of the job queue. Job queues with a higher priority (or a lower integer value for the priority
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parameter) are evaluated first when associated with same compute environment. Priority is determined in
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ascending order, for example, a job queue with a priority value of 1 is given scheduling preference over a job
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queue with a priority value of 10.
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required: true
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compute_environment_order:
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description:
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- The set of compute environments mapped to a job queue and their order relative to each other. The job
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scheduler uses this parameter to determine which compute environment should execute a given job. Compute
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environments must be in the VALID state before you can associate them with a job queue. You can associate up to
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3 compute environments with a job queue.
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required: true
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requirements:
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- boto3
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extends_documentation_fragment:
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- aws
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- ec2
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'''
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EXAMPLES = '''
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---
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- hosts: localhost
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gather_facts: no
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vars:
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state: present
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tasks:
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- name: My Batch Job Queue
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batch_job_queue:
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job_queue_name: jobQueueName
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state: present
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region: us-east-1
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job_queue_state: ENABLED
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priority: 1
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compute_environment_order:
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- order: 1
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compute_environment: my_compute_env1
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- order: 2
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compute_environment: my_compute_env2
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- name: show results
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debug: var=batch_job_queue_action
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'''
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RETURN = '''
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---
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output:
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description: "returns what action was taken, whether something was changed, invocation and response"
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returned: always
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sample:
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batch_job_queue_action: updated
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changed: false
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response:
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job_queue_arn: "arn:aws:batch:...."
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job_queue_name: <name>
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priority: 1
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state: DISABLED
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status: UPDATING
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status_reason: "JobQueue Healthy"
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type: dict
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'''
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from ansible.module_utils._text import to_native
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from ansible.module_utils.aws.batch import AWSConnection, cc, set_api_params
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from ansible.module_utils.basic import AnsibleModule
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from ansible.module_utils.ec2 import ec2_argument_spec, get_aws_connection_info, boto3_conn, HAS_BOTO3
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from ansible.module_utils.ec2 import camel_dict_to_snake_dict
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import re
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import traceback
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try:
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from botocore.exceptions import ClientError, ParamValidationError, MissingParametersError
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except ImportError:
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pass # Handled by HAS_BOTO3
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# ---------------------------------------------------------------------------------------------------
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#
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# Helper Functions & classes
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#
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# ---------------------------------------------------------------------------------------------------
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def validate_params(module, aws):
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"""
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Performs basic parameter validation.
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:param module:
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:param aws:
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:return:
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"""
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return
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# ---------------------------------------------------------------------------------------------------
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#
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# Batch Job Queue functions
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#
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# ---------------------------------------------------------------------------------------------------
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def get_current_job_queue(module, connection):
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try:
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environments = connection.client().describe_job_queues(
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jobQueues=[module.params['job_queue_name']]
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)
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return environments['jobQueues'][0] if len(environments['jobQueues']) > 0 else None
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except ClientError:
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return None
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def create_job_queue(module, aws):
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"""
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Adds a Batch job queue
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:param module:
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:param aws:
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:return:
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"""
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client = aws.client('batch')
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changed = False
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# set API parameters
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params = ('job_queue_name', 'priority')
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api_params = set_api_params(module, params)
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if module.params['job_queue_state'] is not None:
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api_params['state'] = module.params['job_queue_state']
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api_params['computeEnvironmentOrder'] = get_compute_environment_order_list(module)
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try:
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if not module.check_mode:
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client.create_job_queue(**api_params)
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changed = True
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except (ClientError, ParamValidationError, MissingParametersError) as e:
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module.fail_json(msg='Error creating compute environment: {0}'.format(to_native(e)),
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exception=traceback.format_exc())
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return changed
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def get_compute_environment_order_list(module):
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compute_environment_order_list = []
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for ceo in module.params['compute_environment_order']:
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compute_environment_order_list.append(dict(order=ceo['order'], computeEnvironment=ceo['compute_environment']))
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return compute_environment_order_list
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def remove_job_queue(module, aws):
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"""
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Remove a Batch job queue
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:param module:
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:param aws:
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:return:
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"""
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client = aws.client('batch')
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changed = False
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# set API parameters
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api_params = {'jobQueue': module.params['job_queue_name']}
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try:
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if not module.check_mode:
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client.delete_job_queue(**api_params)
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changed = True
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except (ClientError, ParamValidationError, MissingParametersError) as e:
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module.fail_json(msg='Error removing job queue: {0}'.format(to_native(e)),
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exception=traceback.format_exc())
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return changed
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def manage_state(module, aws):
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changed = False
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current_state = 'absent'
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state = module.params['state']
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job_queue_state = module.params['job_queue_state']
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job_queue_name = module.params['job_queue_name']
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priority = module.params['priority']
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action_taken = 'none'
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response = None
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check_mode = module.check_mode
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# check if the job queue exists
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current_job_queue = get_current_job_queue(module, aws)
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if current_job_queue:
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current_state = 'present'
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if state == 'present':
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if current_state == 'present':
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updates = False
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# Update Batch Job Queuet configuration
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job_kwargs = {'jobQueue': job_queue_name}
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# Update configuration if needed
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if job_queue_state and current_job_queue['state'] != job_queue_state:
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job_kwargs.update({'state': job_queue_state})
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updates = True
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if priority is not None and current_job_queue['priority'] != priority:
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job_kwargs.update({'priority': priority})
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updates = True
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new_compute_environment_order_list = get_compute_environment_order_list(module)
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if new_compute_environment_order_list != current_job_queue['computeEnvironmentOrder']:
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job_kwargs['computeEnvironmentOrder'] = new_compute_environment_order_list
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updates = True
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if updates:
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try:
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if not check_mode:
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aws.client().update_job_queue(**job_kwargs)
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changed = True
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action_taken = "updated"
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except (ParamValidationError, ClientError) as e:
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module.fail_json(msg="Unable to update job queue: {0}".format(to_native(e)),
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exception=traceback.format_exc())
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else:
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# Create Job Queue
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changed = create_job_queue(module, aws)
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action_taken = 'added'
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# Describe job queue
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response = get_current_job_queue(module, aws)
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if not response:
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module.fail_json(msg='Unable to get job queue information after creating/updating')
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else:
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if current_state == 'present':
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# remove the Job Queue
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changed = remove_job_queue(module, aws)
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action_taken = 'deleted'
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return dict(changed=changed, batch_job_queue_action=action_taken, response=response)
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# ---------------------------------------------------------------------------------------------------
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#
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# MAIN
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#
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# ---------------------------------------------------------------------------------------------------
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def main():
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"""
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Main entry point.
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:return dict: changed, batch_job_queue_action, response
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"""
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argument_spec = ec2_argument_spec()
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argument_spec.update(
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dict(
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state=dict(required=False, default='present', choices=['present', 'absent']),
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job_queue_name=dict(required=True),
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job_queue_state=dict(required=False, default='ENABLED', choices=['ENABLED', 'DISABLED']),
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priority=dict(type='int', required=True),
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compute_environment_order=dict(type='list', required=True),
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region=dict(aliases=['aws_region', 'ec2_region'])
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)
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)
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module = AnsibleModule(
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argument_spec=argument_spec,
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supports_check_mode=True
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)
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# validate dependencies
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if not HAS_BOTO3:
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module.fail_json(msg='boto3 is required for this module.')
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aws = AWSConnection(module, ['batch'])
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validate_params(module, aws)
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results = manage_state(module, aws)
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module.exit_json(**camel_dict_to_snake_dict(results))
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if __name__ == '__main__':
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main()
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