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# coding=utf-8
# --------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
#
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is
# regenerated.
# --------------------------------------------------------------------------
from msrest.serialization import Model
class StartTask(Model):
"""A task which is run when a compute node joins a pool in the Azure Batch
service, or when the compute node is rebooted or reimaged.
Batch will retry tasks when a recovery operation is triggered on a compute
node. Examples of recovery operations include (but are not limited to) when
an unhealthy compute node is rebooted or a compute node disappeared due to
host failure. Retries due to recovery operations are independent of and are
not counted against the maxTaskRetryCount. Even if the maxTaskRetryCount is
0, an internal retry due to a recovery operation may occur. Because of
this, all tasks should be idempotent. This means tasks need to tolerate
being interrupted and restarted without causing any corruption or duplicate
data. The best practice for long running tasks is to use some form of
checkpointing.
All required parameters must be populated in order to send to Azure.
:param command_line: Required. The command line of the start task. The
command line does not run under a shell, and therefore cannot take
advantage of shell features such as environment variable expansion. If you
want to take advantage of such features, you should invoke the shell in
the command line, for example using "cmd /c MyCommand" in Windows or
"/bin/sh -c MyCommand" in Linux. If the command line refers to file paths,
it should use a relative path (relative to the task working directory), or
use the Batch provided environment variable
(https://docs.microsoft.com/en-us/azure/batch/batch-compute-node-environment-variables).
:type command_line: str
:param container_settings: The settings for the container under which the
start task runs. When this is specified, all directories recursively below
the AZ_BATCH_NODE_ROOT_DIR (the root of Azure Batch directories on the
node) are mapped into the container, all task environment variables are
mapped into the container, and the task command line is executed in the
container.
:type container_settings: ~azure.batch.models.TaskContainerSettings
:param resource_files: A list of files that the Batch service will
download to the compute node before running the command line. There is a
maximum size for the list of resource files. When the max size is
exceeded, the request will fail and the response error code will be
RequestEntityTooLarge. If this occurs, the collection of ResourceFiles
must be reduced in size. This can be achieved using .zip files,
Application Packages, or Docker Containers. Files listed under this
element are located in the task's working directory.
:type resource_files: list[~azure.batch.models.ResourceFile]
:param environment_settings: A list of environment variable settings for
the start task.
:type environment_settings: list[~azure.batch.models.EnvironmentSetting]
:param user_identity: The user identity under which the start task runs.
If omitted, the task runs as a non-administrative user unique to the task.
:type user_identity: ~azure.batch.models.UserIdentity
:param max_task_retry_count: The maximum number of times the task may be
retried. The Batch service retries a task if its exit code is nonzero.
Note that this value specifically controls the number of retries. The
Batch service will try the task once, and may then retry up to this limit.
For example, if the maximum retry count is 3, Batch tries the task up to 4
times (one initial try and 3 retries). If the maximum retry count is 0,
the Batch service does not retry the task. If the maximum retry count is
-1, the Batch service retries the task without limit.
:type max_task_retry_count: int
:param wait_for_success: Whether the Batch service should wait for the
start task to complete successfully (that is, to exit with exit code 0)
before scheduling any tasks on the compute node. If true and the start
task fails on a compute node, the Batch service retries the start task up
to its maximum retry count (maxTaskRetryCount). If the task has still not
completed successfully after all retries, then the Batch service marks the
compute node unusable, and will not schedule tasks to it. This condition
can be detected via the node state and failure info details. If false, the
Batch service will not wait for the start task to complete. In this case,
other tasks can start executing on the compute node while the start task
is still running; and even if the start task fails, new tasks will
continue to be scheduled on the node. The default is false.
:type wait_for_success: bool
"""
_validation = {
'command_line': {'required': True},
}
_attribute_map = {
'command_line': {'key': 'commandLine', 'type': 'str'},
'container_settings': {'key': 'containerSettings', 'type': 'TaskContainerSettings'},
'resource_files': {'key': 'resourceFiles', 'type': '[ResourceFile]'},
'environment_settings': {'key': 'environmentSettings', 'type': '[EnvironmentSetting]'},
'user_identity': {'key': 'userIdentity', 'type': 'UserIdentity'},
'max_task_retry_count': {'key': 'maxTaskRetryCount', 'type': 'int'},
'wait_for_success': {'key': 'waitForSuccess', 'type': 'bool'},
}
def __init__(self, **kwargs):
super(StartTask, self).__init__(**kwargs)
self.command_line = kwargs.get('command_line', None)
self.container_settings = kwargs.get('container_settings', None)
self.resource_files = kwargs.get('resource_files', None)
self.environment_settings = kwargs.get('environment_settings', None)
self.user_identity = kwargs.get('user_identity', None)
self.max_task_retry_count = kwargs.get('max_task_retry_count', None)
self.wait_for_success = kwargs.get('wait_for_success', None)
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