diff --git a/sdk/machinelearning/azure-mgmt-machinelearningcompute/CHANGELOG.md b/sdk/machinelearning/azure-mgmt-machinelearningcompute/CHANGELOG.md new file mode 100644 index 000000000000..578ed6acf479 --- /dev/null +++ b/sdk/machinelearning/azure-mgmt-machinelearningcompute/CHANGELOG.md @@ -0,0 +1,5 @@ +# Release History + +## 0.1.0 (1970-01-01) + +* Initial Release diff --git a/sdk/machinelearning/azure-mgmt-machinelearningcompute/MANIFEST.in b/sdk/machinelearning/azure-mgmt-machinelearningcompute/MANIFEST.in new file mode 100644 index 000000000000..3a9b6517412b --- /dev/null +++ b/sdk/machinelearning/azure-mgmt-machinelearningcompute/MANIFEST.in @@ -0,0 +1,6 @@ +include _meta.json +recursive-include tests *.py *.yaml +include *.md +include azure/__init__.py +include azure/mgmt/__init__.py + diff --git a/sdk/machinelearning/azure-mgmt-machinelearningcompute/README.md b/sdk/machinelearning/azure-mgmt-machinelearningcompute/README.md new file mode 100644 index 000000000000..9526886f62eb --- /dev/null +++ b/sdk/machinelearning/azure-mgmt-machinelearningcompute/README.md @@ -0,0 +1,27 @@ +# Microsoft Azure SDK for Python + +This is the Microsoft Azure MyService Management Client Library. +This package has been tested with Python 2.7, 3.5, 3.6, 3.7 and 3.8. +For a more complete view of Azure libraries, see the [azure sdk python release](https://aka.ms/azsdk/python/all). + + +# Usage + + +To learn how to use this package, see the [quickstart guide](https://aka.ms/azsdk/python/mgmt) + + + +For docs and references, see [Python SDK References](https://docs.microsoft.com/python/api/overview/azure/) +Code samples for this package can be found at [MyService Management](https://docs.microsoft.com/samples/browse/?languages=python&term=Getting%20started%20-%20Managing&terms=Getting%20started%20-%20Managing) on docs.microsoft.com. +Additional code samples for different Azure services are available at [Samples Repo](https://aka.ms/azsdk/python/mgmt/samples) + + +# Provide Feedback + +If you encounter any bugs or have suggestions, please file an issue in the +[Issues](https://github.com/Azure/azure-sdk-for-python/issues) +section of the project. + + +![Impressions](https://azure-sdk-impressions.azurewebsites.net/api/impressions/azure-sdk-for-python%2Fazure-mgmt-machinelearningcompute%2FREADME.png) diff --git a/sdk/machinelearning/azure-mgmt-machinelearningcompute/_meta.json b/sdk/machinelearning/azure-mgmt-machinelearningcompute/_meta.json new file mode 100644 index 000000000000..f095077255d3 --- /dev/null +++ b/sdk/machinelearning/azure-mgmt-machinelearningcompute/_meta.json @@ -0,0 +1,8 @@ +{ + "autorest": "3.4.2", + "use": "@autorest/python@5.6.6", + "commit": "3f1d9a2fd7d79c0e10cca4a4750a00e725ddc541", + "repository_url": "https://github.com/Azure/azure-rest-api-specs", + "autorest_command": "autorest specification/machinelearningcompute/resource-manager/readme.md --multiapi --python --python-mode=update --python-sdks-folder=/home/vsts/work/1/s/azure-sdk-for-python/sdk --track2 --use=@autorest/python@5.6.6 --version=3.4.2", + "readme": "specification/machinelearningcompute/resource-manager/readme.md" +} \ No newline at end of file diff --git a/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/__init__.py b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/__init__.py new file mode 100644 index 000000000000..0260537a02bb --- /dev/null +++ b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/__init__.py @@ -0,0 +1 @@ +__path__ = __import__('pkgutil').extend_path(__path__, __name__) \ No newline at end of file diff --git a/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/__init__.py b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/__init__.py new file mode 100644 index 000000000000..0260537a02bb --- /dev/null +++ b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/__init__.py @@ -0,0 +1 @@ +__path__ = __import__('pkgutil').extend_path(__path__, __name__) \ No newline at end of file diff --git a/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/__init__.py b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/__init__.py new file mode 100644 index 000000000000..bec3f4cbfb1a --- /dev/null +++ b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/__init__.py @@ -0,0 +1,19 @@ +# 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 ._machine_learning_compute_management_client import MachineLearningComputeManagementClient +from ._version import VERSION + +__version__ = VERSION +__all__ = ['MachineLearningComputeManagementClient'] + +try: + from ._patch import patch_sdk # type: ignore + patch_sdk() +except ImportError: + pass diff --git a/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/_configuration.py b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/_configuration.py new file mode 100644 index 000000000000..36b0434fd671 --- /dev/null +++ b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/_configuration.py @@ -0,0 +1,71 @@ +# 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 typing import TYPE_CHECKING + +from azure.core.configuration import Configuration +from azure.core.pipeline import policies +from azure.mgmt.core.policies import ARMHttpLoggingPolicy + +from ._version import VERSION + +if TYPE_CHECKING: + # pylint: disable=unused-import,ungrouped-imports + from typing import Any + + from azure.core.credentials import TokenCredential + + +class MachineLearningComputeManagementClientConfiguration(Configuration): + """Configuration for MachineLearningComputeManagementClient. + + Note that all parameters used to create this instance are saved as instance + attributes. + + :param credential: Credential needed for the client to connect to Azure. + :type credential: ~azure.core.credentials.TokenCredential + :param subscription_id: The Azure subscription ID. + :type subscription_id: str + """ + + def __init__( + self, + credential, # type: "TokenCredential" + subscription_id, # type: str + **kwargs # type: Any + ): + # type: (...) -> None + if credential is None: + raise ValueError("Parameter 'credential' must not be None.") + if subscription_id is None: + raise ValueError("Parameter 'subscription_id' must not be None.") + super(MachineLearningComputeManagementClientConfiguration, self).__init__(**kwargs) + + self.credential = credential + self.subscription_id = subscription_id + self.api_version = "2017-08-01-preview" + self.credential_scopes = kwargs.pop('credential_scopes', ['https://management.azure.com/.default']) + kwargs.setdefault('sdk_moniker', 'mgmt-machinelearningcompute/{}'.format(VERSION)) + self._configure(**kwargs) + + def _configure( + self, + **kwargs # type: Any + ): + # type: (...) -> None + self.user_agent_policy = kwargs.get('user_agent_policy') or policies.UserAgentPolicy(**kwargs) + self.headers_policy = kwargs.get('headers_policy') or policies.HeadersPolicy(**kwargs) + self.proxy_policy = kwargs.get('proxy_policy') or policies.ProxyPolicy(**kwargs) + self.logging_policy = kwargs.get('logging_policy') or policies.NetworkTraceLoggingPolicy(**kwargs) + self.http_logging_policy = kwargs.get('http_logging_policy') or ARMHttpLoggingPolicy(**kwargs) + self.retry_policy = kwargs.get('retry_policy') or policies.RetryPolicy(**kwargs) + self.custom_hook_policy = kwargs.get('custom_hook_policy') or policies.CustomHookPolicy(**kwargs) + self.redirect_policy = kwargs.get('redirect_policy') or policies.RedirectPolicy(**kwargs) + self.authentication_policy = kwargs.get('authentication_policy') + if self.credential and not self.authentication_policy: + self.authentication_policy = policies.BearerTokenCredentialPolicy(self.credential, *self.credential_scopes, **kwargs) diff --git a/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/_machine_learning_compute_management_client.py b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/_machine_learning_compute_management_client.py new file mode 100644 index 000000000000..26ce93371533 --- /dev/null +++ b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/_machine_learning_compute_management_client.py @@ -0,0 +1,94 @@ +# 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 typing import TYPE_CHECKING + +from azure.mgmt.core import ARMPipelineClient +from msrest import Deserializer, Serializer + +if TYPE_CHECKING: + # pylint: disable=unused-import,ungrouped-imports + from typing import Any, Optional + + from azure.core.credentials import TokenCredential + from azure.core.pipeline.transport import HttpRequest, HttpResponse + +from ._configuration import MachineLearningComputeManagementClientConfiguration +from .operations import OperationalizationClustersOperations +from .operations import MachineLearningComputeOperations +from . import models + + +class MachineLearningComputeManagementClient(object): + """These APIs allow end users to operate on Azure Machine Learning Compute resources. They support the following operations::code:``. + + :ivar operationalization_clusters: OperationalizationClustersOperations operations + :vartype operationalization_clusters: azure.mgmt.machinelearningcompute.operations.OperationalizationClustersOperations + :ivar machine_learning_compute: MachineLearningComputeOperations operations + :vartype machine_learning_compute: azure.mgmt.machinelearningcompute.operations.MachineLearningComputeOperations + :param credential: Credential needed for the client to connect to Azure. + :type credential: ~azure.core.credentials.TokenCredential + :param subscription_id: The Azure subscription ID. + :type subscription_id: str + :param str base_url: Service URL + :keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present. + """ + + def __init__( + self, + credential, # type: "TokenCredential" + subscription_id, # type: str + base_url=None, # type: Optional[str] + **kwargs # type: Any + ): + # type: (...) -> None + if not base_url: + base_url = 'https://management.azure.com' + self._config = MachineLearningComputeManagementClientConfiguration(credential, subscription_id, **kwargs) + self._client = ARMPipelineClient(base_url=base_url, config=self._config, **kwargs) + + client_models = {k: v for k, v in models.__dict__.items() if isinstance(v, type)} + self._serialize = Serializer(client_models) + self._serialize.client_side_validation = False + self._deserialize = Deserializer(client_models) + + self.operationalization_clusters = OperationalizationClustersOperations( + self._client, self._config, self._serialize, self._deserialize) + self.machine_learning_compute = MachineLearningComputeOperations( + self._client, self._config, self._serialize, self._deserialize) + + def _send_request(self, http_request, **kwargs): + # type: (HttpRequest, Any) -> HttpResponse + """Runs the network request through the client's chained policies. + + :param http_request: The network request you want to make. Required. + :type http_request: ~azure.core.pipeline.transport.HttpRequest + :keyword bool stream: Whether the response payload will be streamed. Defaults to True. + :return: The response of your network call. Does not do error handling on your response. + :rtype: ~azure.core.pipeline.transport.HttpResponse + """ + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + } + http_request.url = self._client.format_url(http_request.url, **path_format_arguments) + stream = kwargs.pop("stream", True) + pipeline_response = self._client._pipeline.run(http_request, stream=stream, **kwargs) + return pipeline_response.http_response + + def close(self): + # type: () -> None + self._client.close() + + def __enter__(self): + # type: () -> MachineLearningComputeManagementClient + self._client.__enter__() + return self + + def __exit__(self, *exc_details): + # type: (Any) -> None + self._client.__exit__(*exc_details) diff --git a/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/_metadata.json b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/_metadata.json new file mode 100644 index 000000000000..a3f3617969cd --- /dev/null +++ b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/_metadata.json @@ -0,0 +1,104 @@ +{ + "chosen_version": "2017-08-01-preview", + "total_api_version_list": ["2017-08-01-preview"], + "client": { + "name": "MachineLearningComputeManagementClient", + "filename": "_machine_learning_compute_management_client", + "description": "These APIs allow end users to operate on Azure Machine Learning Compute resources. They support the following operations::code:`\u003cul\u003e\u003cli\u003eCreate or update a cluster\u003c/li\u003e\u003cli\u003eGet a cluster\u003c/li\u003e\u003cli\u003ePatch a cluster\u003c/li\u003e\u003cli\u003eDelete a cluster\u003c/li\u003e\u003cli\u003eGet keys for a cluster\u003c/li\u003e\u003cli\u003eCheck if updates are available for system services in a cluster\u003c/li\u003e\u003cli\u003eUpdate system services in a cluster\u003c/li\u003e\u003cli\u003eGet all clusters in a resource group\u003c/li\u003e\u003cli\u003eGet all clusters in a subscription\u003c/li\u003e\u003c/ul\u003e`.", + "base_url": "\u0027https://management.azure.com\u0027", + "custom_base_url": null, + "azure_arm": true, + "has_lro_operations": true, + "client_side_validation": false, + "sync_imports": "{\"typing\": {\"azurecore\": {\"azure.core.credentials\": [\"TokenCredential\"]}}, \"regular\": {\"azurecore\": {\"azure.profiles\": [\"KnownProfiles\", \"ProfileDefinition\"], \"azure.profiles.multiapiclient\": [\"MultiApiClientMixin\"], \"msrest\": [\"Deserializer\", \"Serializer\"], \"azure.mgmt.core\": [\"ARMPipelineClient\"]}, \"local\": {\"._configuration\": [\"MachineLearningComputeManagementClientConfiguration\"]}}, \"conditional\": {\"stdlib\": {\"typing\": [\"Any\", \"Optional\"]}, \"azurecore\": {\"azure.core.pipeline.transport\": [\"HttpRequest\", \"HttpResponse\"]}}}", + "async_imports": "{\"typing\": {\"azurecore\": {\"azure.core.credentials_async\": [\"AsyncTokenCredential\"]}}, \"regular\": {\"azurecore\": {\"azure.profiles\": [\"KnownProfiles\", \"ProfileDefinition\"], \"azure.profiles.multiapiclient\": [\"MultiApiClientMixin\"], \"msrest\": [\"Deserializer\", \"Serializer\"], \"azure.mgmt.core\": [\"AsyncARMPipelineClient\"]}, \"local\": {\"._configuration\": [\"MachineLearningComputeManagementClientConfiguration\"]}}, \"conditional\": {\"stdlib\": {\"typing\": [\"Any\", \"Optional\"]}, \"azurecore\": {\"azure.core.pipeline.transport\": [\"AsyncHttpResponse\", \"HttpRequest\"]}}}" + }, + "global_parameters": { + "sync": { + "credential": { + "signature": "credential, # type: \"TokenCredential\"", + "description": "Credential needed for the client to connect to Azure.", + "docstring_type": "~azure.core.credentials.TokenCredential", + "required": true + }, + "subscription_id": { + "signature": "subscription_id, # type: str", + "description": "The Azure subscription ID.", + "docstring_type": "str", + "required": true + } + }, + "async": { + "credential": { + "signature": "credential: \"AsyncTokenCredential\",", + "description": "Credential needed for the client to connect to Azure.", + "docstring_type": "~azure.core.credentials_async.AsyncTokenCredential", + "required": true + }, + "subscription_id": { + "signature": "subscription_id: str,", + "description": "The Azure subscription ID.", + "docstring_type": "str", + "required": true + } + }, + "constant": { + }, + "call": "credential, subscription_id", + "service_client_specific": { + "sync": { + "api_version": { + "signature": "api_version=None, # type: Optional[str]", + "description": "API version to use if no profile is provided, or if missing in profile.", + "docstring_type": "str", + "required": false + }, + "base_url": { + "signature": "base_url=None, # type: Optional[str]", + "description": "Service URL", + "docstring_type": "str", + "required": false + }, + "profile": { + "signature": "profile=KnownProfiles.default, # type: KnownProfiles", + "description": "A profile definition, from KnownProfiles to dict.", + "docstring_type": "azure.profiles.KnownProfiles", + "required": false + } + }, + "async": { + "api_version": { + "signature": "api_version: Optional[str] = None,", + "description": "API version to use if no profile is provided, or if missing in profile.", + "docstring_type": "str", + "required": false + }, + "base_url": { + "signature": "base_url: Optional[str] = None,", + "description": "Service URL", + "docstring_type": "str", + "required": false + }, + "profile": { + "signature": "profile: KnownProfiles = KnownProfiles.default,", + "description": "A profile definition, from KnownProfiles to dict.", + "docstring_type": "azure.profiles.KnownProfiles", + "required": false + } + } + } + }, + "config": { + "credential": true, + "credential_scopes": ["https://management.azure.com/.default"], + "credential_default_policy_type": "BearerTokenCredentialPolicy", + "credential_default_policy_type_has_async_version": true, + "credential_key_header_name": null, + "sync_imports": "{\"regular\": {\"azurecore\": {\"azure.core.configuration\": [\"Configuration\"], \"azure.core.pipeline\": [\"policies\"], \"azure.mgmt.core.policies\": [\"ARMHttpLoggingPolicy\"]}, \"local\": {\"._version\": [\"VERSION\"]}}, \"conditional\": {\"stdlib\": {\"typing\": [\"Any\"]}}, \"typing\": {\"azurecore\": {\"azure.core.credentials\": [\"TokenCredential\"]}}}", + "async_imports": "{\"regular\": {\"azurecore\": {\"azure.core.configuration\": [\"Configuration\"], \"azure.core.pipeline\": [\"policies\"], \"azure.mgmt.core.policies\": [\"ARMHttpLoggingPolicy\"]}, \"local\": {\".._version\": [\"VERSION\"]}}, \"conditional\": {\"stdlib\": {\"typing\": [\"Any\"]}}, \"typing\": {\"azurecore\": {\"azure.core.credentials_async\": [\"AsyncTokenCredential\"]}}}" + }, + "operation_groups": { + "operationalization_clusters": "OperationalizationClustersOperations", + "machine_learning_compute": "MachineLearningComputeOperations" + } +} \ No newline at end of file diff --git a/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/_version.py b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/_version.py new file mode 100644 index 000000000000..e5754a47ce68 --- /dev/null +++ b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/_version.py @@ -0,0 +1,9 @@ +# 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. +# -------------------------------------------------------------------------- + +VERSION = "1.0.0b1" diff --git a/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/aio/__init__.py b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/aio/__init__.py new file mode 100644 index 000000000000..88188e3f0f13 --- /dev/null +++ b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/aio/__init__.py @@ -0,0 +1,10 @@ +# 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 ._machine_learning_compute_management_client import MachineLearningComputeManagementClient +__all__ = ['MachineLearningComputeManagementClient'] diff --git a/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/aio/_configuration.py b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/aio/_configuration.py new file mode 100644 index 000000000000..daa78697b7e1 --- /dev/null +++ b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/aio/_configuration.py @@ -0,0 +1,67 @@ +# 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 typing import Any, TYPE_CHECKING + +from azure.core.configuration import Configuration +from azure.core.pipeline import policies +from azure.mgmt.core.policies import ARMHttpLoggingPolicy + +from .._version import VERSION + +if TYPE_CHECKING: + # pylint: disable=unused-import,ungrouped-imports + from azure.core.credentials_async import AsyncTokenCredential + + +class MachineLearningComputeManagementClientConfiguration(Configuration): + """Configuration for MachineLearningComputeManagementClient. + + Note that all parameters used to create this instance are saved as instance + attributes. + + :param credential: Credential needed for the client to connect to Azure. + :type credential: ~azure.core.credentials_async.AsyncTokenCredential + :param subscription_id: The Azure subscription ID. + :type subscription_id: str + """ + + def __init__( + self, + credential: "AsyncTokenCredential", + subscription_id: str, + **kwargs: Any + ) -> None: + if credential is None: + raise ValueError("Parameter 'credential' must not be None.") + if subscription_id is None: + raise ValueError("Parameter 'subscription_id' must not be None.") + super(MachineLearningComputeManagementClientConfiguration, self).__init__(**kwargs) + + self.credential = credential + self.subscription_id = subscription_id + self.api_version = "2017-08-01-preview" + self.credential_scopes = kwargs.pop('credential_scopes', ['https://management.azure.com/.default']) + kwargs.setdefault('sdk_moniker', 'mgmt-machinelearningcompute/{}'.format(VERSION)) + self._configure(**kwargs) + + def _configure( + self, + **kwargs: Any + ) -> None: + self.user_agent_policy = kwargs.get('user_agent_policy') or policies.UserAgentPolicy(**kwargs) + self.headers_policy = kwargs.get('headers_policy') or policies.HeadersPolicy(**kwargs) + self.proxy_policy = kwargs.get('proxy_policy') or policies.ProxyPolicy(**kwargs) + self.logging_policy = kwargs.get('logging_policy') or policies.NetworkTraceLoggingPolicy(**kwargs) + self.http_logging_policy = kwargs.get('http_logging_policy') or ARMHttpLoggingPolicy(**kwargs) + self.retry_policy = kwargs.get('retry_policy') or policies.AsyncRetryPolicy(**kwargs) + self.custom_hook_policy = kwargs.get('custom_hook_policy') or policies.CustomHookPolicy(**kwargs) + self.redirect_policy = kwargs.get('redirect_policy') or policies.AsyncRedirectPolicy(**kwargs) + self.authentication_policy = kwargs.get('authentication_policy') + if self.credential and not self.authentication_policy: + self.authentication_policy = policies.AsyncBearerTokenCredentialPolicy(self.credential, *self.credential_scopes, **kwargs) diff --git a/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/aio/_machine_learning_compute_management_client.py b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/aio/_machine_learning_compute_management_client.py new file mode 100644 index 000000000000..23afab1904de --- /dev/null +++ b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/aio/_machine_learning_compute_management_client.py @@ -0,0 +1,87 @@ +# 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 typing import Any, Optional, TYPE_CHECKING + +from azure.core.pipeline.transport import AsyncHttpResponse, HttpRequest +from azure.mgmt.core import AsyncARMPipelineClient +from msrest import Deserializer, Serializer + +if TYPE_CHECKING: + # pylint: disable=unused-import,ungrouped-imports + from azure.core.credentials_async import AsyncTokenCredential + +from ._configuration import MachineLearningComputeManagementClientConfiguration +from .operations import OperationalizationClustersOperations +from .operations import MachineLearningComputeOperations +from .. import models + + +class MachineLearningComputeManagementClient(object): + """These APIs allow end users to operate on Azure Machine Learning Compute resources. They support the following operations::code:``. + + :ivar operationalization_clusters: OperationalizationClustersOperations operations + :vartype operationalization_clusters: azure.mgmt.machinelearningcompute.aio.operations.OperationalizationClustersOperations + :ivar machine_learning_compute: MachineLearningComputeOperations operations + :vartype machine_learning_compute: azure.mgmt.machinelearningcompute.aio.operations.MachineLearningComputeOperations + :param credential: Credential needed for the client to connect to Azure. + :type credential: ~azure.core.credentials_async.AsyncTokenCredential + :param subscription_id: The Azure subscription ID. + :type subscription_id: str + :param str base_url: Service URL + :keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present. + """ + + def __init__( + self, + credential: "AsyncTokenCredential", + subscription_id: str, + base_url: Optional[str] = None, + **kwargs: Any + ) -> None: + if not base_url: + base_url = 'https://management.azure.com' + self._config = MachineLearningComputeManagementClientConfiguration(credential, subscription_id, **kwargs) + self._client = AsyncARMPipelineClient(base_url=base_url, config=self._config, **kwargs) + + client_models = {k: v for k, v in models.__dict__.items() if isinstance(v, type)} + self._serialize = Serializer(client_models) + self._serialize.client_side_validation = False + self._deserialize = Deserializer(client_models) + + self.operationalization_clusters = OperationalizationClustersOperations( + self._client, self._config, self._serialize, self._deserialize) + self.machine_learning_compute = MachineLearningComputeOperations( + self._client, self._config, self._serialize, self._deserialize) + + async def _send_request(self, http_request: HttpRequest, **kwargs: Any) -> AsyncHttpResponse: + """Runs the network request through the client's chained policies. + + :param http_request: The network request you want to make. Required. + :type http_request: ~azure.core.pipeline.transport.HttpRequest + :keyword bool stream: Whether the response payload will be streamed. Defaults to True. + :return: The response of your network call. Does not do error handling on your response. + :rtype: ~azure.core.pipeline.transport.AsyncHttpResponse + """ + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + } + http_request.url = self._client.format_url(http_request.url, **path_format_arguments) + stream = kwargs.pop("stream", True) + pipeline_response = await self._client._pipeline.run(http_request, stream=stream, **kwargs) + return pipeline_response.http_response + + async def close(self) -> None: + await self._client.close() + + async def __aenter__(self) -> "MachineLearningComputeManagementClient": + await self._client.__aenter__() + return self + + async def __aexit__(self, *exc_details) -> None: + await self._client.__aexit__(*exc_details) diff --git a/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/aio/operations/__init__.py b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/aio/operations/__init__.py new file mode 100644 index 000000000000..2dbc2ddbdd04 --- /dev/null +++ b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/aio/operations/__init__.py @@ -0,0 +1,15 @@ +# 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 ._operationalization_clusters_operations import OperationalizationClustersOperations +from ._machine_learning_compute_operations import MachineLearningComputeOperations + +__all__ = [ + 'OperationalizationClustersOperations', + 'MachineLearningComputeOperations', +] diff --git a/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/aio/operations/_machine_learning_compute_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/aio/operations/_machine_learning_compute_operations.py new file mode 100644 index 000000000000..370db471f993 --- /dev/null +++ b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/aio/operations/_machine_learning_compute_operations.py @@ -0,0 +1,87 @@ +# 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 typing import Any, Callable, Dict, Generic, Optional, TypeVar +import warnings + +from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error +from azure.core.pipeline import PipelineResponse +from azure.core.pipeline.transport import AsyncHttpResponse, HttpRequest +from azure.mgmt.core.exceptions import ARMErrorFormat + +from ... import models as _models + +T = TypeVar('T') +ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]] + +class MachineLearningComputeOperations: + """MachineLearningComputeOperations async operations. + + You should not instantiate this class directly. Instead, you should create a Client instance that + instantiates it for you and attaches it as an attribute. + + :ivar models: Alias to model classes used in this operation group. + :type models: ~azure.mgmt.machinelearningcompute.models + :param client: Client for service requests. + :param config: Configuration of service client. + :param serializer: An object model serializer. + :param deserializer: An object model deserializer. + """ + + models = _models + + def __init__(self, client, config, serializer, deserializer) -> None: + self._client = client + self._serialize = serializer + self._deserialize = deserializer + self._config = config + + async def list_available_operations( + self, + **kwargs + ) -> "_models.AvailableOperations": + """Gets all available operations. + + :keyword callable cls: A custom type or function that will be passed the direct response + :return: AvailableOperations, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningcompute.models.AvailableOperations + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.AvailableOperations"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2017-08-01-preview" + accept = "application/json" + + # Construct URL + url = self.list_available_operations.metadata['url'] # type: ignore + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + raise HttpResponseError(response=response, error_format=ARMErrorFormat) + + deserialized = self._deserialize('AvailableOperations', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + list_available_operations.metadata = {'url': '/providers/Microsoft.MachineLearningCompute/operations'} # type: ignore diff --git a/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/aio/operations/_operationalization_clusters_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/aio/operations/_operationalization_clusters_operations.py new file mode 100644 index 000000000000..da70526f4970 --- /dev/null +++ b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/aio/operations/_operationalization_clusters_operations.py @@ -0,0 +1,804 @@ +# 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 typing import Any, AsyncIterable, Callable, Dict, Generic, Optional, TypeVar, Union +import warnings + +from azure.core.async_paging import AsyncItemPaged, AsyncList +from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error +from azure.core.pipeline import PipelineResponse +from azure.core.pipeline.transport import AsyncHttpResponse, HttpRequest +from azure.core.polling import AsyncLROPoller, AsyncNoPolling, AsyncPollingMethod +from azure.mgmt.core.exceptions import ARMErrorFormat +from azure.mgmt.core.polling.async_arm_polling import AsyncARMPolling + +from ... import models as _models + +T = TypeVar('T') +ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]] + +class OperationalizationClustersOperations: + """OperationalizationClustersOperations async operations. + + You should not instantiate this class directly. Instead, you should create a Client instance that + instantiates it for you and attaches it as an attribute. + + :ivar models: Alias to model classes used in this operation group. + :type models: ~azure.mgmt.machinelearningcompute.models + :param client: Client for service requests. + :param config: Configuration of service client. + :param serializer: An object model serializer. + :param deserializer: An object model deserializer. + """ + + models = _models + + def __init__(self, client, config, serializer, deserializer) -> None: + self._client = client + self._serialize = serializer + self._deserialize = deserializer + self._config = config + + async def _create_or_update_initial( + self, + resource_group_name: str, + cluster_name: str, + parameters: "_models.OperationalizationCluster", + **kwargs + ) -> "_models.OperationalizationCluster": + cls = kwargs.pop('cls', None) # type: ClsType["_models.OperationalizationCluster"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2017-08-01-preview" + content_type = kwargs.pop("content_type", "application/json") + accept = "application/json" + + # Construct URL + url = self._create_or_update_initial.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\w\._\(\)]+$'), + 'clusterName': self._serialize.url("cluster_name", cluster_name, 'str', max_length=90, min_length=1, pattern=r'^[a-zA-Z][-\w\._\(\)]+[a-zA-Z0-9]$'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Content-Type'] = self._serialize.header("content_type", content_type, 'str') + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + body_content_kwargs = {} # type: Dict[str, Any] + body_content = self._serialize.body(parameters, 'OperationalizationCluster') + body_content_kwargs['content'] = body_content + request = self._client.put(url, query_parameters, header_parameters, **body_content_kwargs) + pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200, 201]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponseWrapper, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + if response.status_code == 200: + deserialized = self._deserialize('OperationalizationCluster', pipeline_response) + + if response.status_code == 201: + deserialized = self._deserialize('OperationalizationCluster', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + _create_or_update_initial.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningCompute/operationalizationClusters/{clusterName}'} # type: ignore + + async def begin_create_or_update( + self, + resource_group_name: str, + cluster_name: str, + parameters: "_models.OperationalizationCluster", + **kwargs + ) -> AsyncLROPoller["_models.OperationalizationCluster"]: + """Create or update an operationalization cluster. + + :param resource_group_name: Name of the resource group in which the cluster is located. + :type resource_group_name: str + :param cluster_name: The name of the cluster. + :type cluster_name: str + :param parameters: Parameters supplied to create or update an Operationalization cluster. + :type parameters: ~azure.mgmt.machinelearningcompute.models.OperationalizationCluster + :keyword callable cls: A custom type or function that will be passed the direct response + :keyword str continuation_token: A continuation token to restart a poller from a saved state. + :keyword polling: Pass in True if you'd like the AsyncARMPolling polling method, + False for no polling, or your own initialized polling object for a personal polling strategy. + :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod + :keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present. + :return: An instance of AsyncLROPoller that returns either OperationalizationCluster or the result of cls(response) + :rtype: ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningcompute.models.OperationalizationCluster] + :raises ~azure.core.exceptions.HttpResponseError: + """ + polling = kwargs.pop('polling', True) # type: Union[bool, AsyncPollingMethod] + cls = kwargs.pop('cls', None) # type: ClsType["_models.OperationalizationCluster"] + lro_delay = kwargs.pop( + 'polling_interval', + self._config.polling_interval + ) + cont_token = kwargs.pop('continuation_token', None) # type: Optional[str] + if cont_token is None: + raw_result = await self._create_or_update_initial( + resource_group_name=resource_group_name, + cluster_name=cluster_name, + parameters=parameters, + cls=lambda x,y,z: x, + **kwargs + ) + + kwargs.pop('error_map', None) + kwargs.pop('content_type', None) + + def get_long_running_output(pipeline_response): + deserialized = self._deserialize('OperationalizationCluster', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + return deserialized + + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\w\._\(\)]+$'), + 'clusterName': self._serialize.url("cluster_name", cluster_name, 'str', max_length=90, min_length=1, pattern=r'^[a-zA-Z][-\w\._\(\)]+[a-zA-Z0-9]$'), + } + + if polling is True: polling_method = AsyncARMPolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + elif polling is False: polling_method = AsyncNoPolling() + else: polling_method = polling + if cont_token: + return AsyncLROPoller.from_continuation_token( + polling_method=polling_method, + continuation_token=cont_token, + client=self._client, + deserialization_callback=get_long_running_output + ) + else: + return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) + begin_create_or_update.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningCompute/operationalizationClusters/{clusterName}'} # type: ignore + + async def get( + self, + resource_group_name: str, + cluster_name: str, + **kwargs + ) -> "_models.OperationalizationCluster": + """Gets the operationalization cluster resource view. Note that the credentials are not returned + by this call. Call ListKeys to get them. + + :param resource_group_name: Name of the resource group in which the cluster is located. + :type resource_group_name: str + :param cluster_name: The name of the cluster. + :type cluster_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: OperationalizationCluster, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningcompute.models.OperationalizationCluster + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.OperationalizationCluster"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2017-08-01-preview" + accept = "application/json" + + # Construct URL + url = self.get.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\w\._\(\)]+$'), + 'clusterName': self._serialize.url("cluster_name", cluster_name, 'str', max_length=90, min_length=1, pattern=r'^[a-zA-Z][-\w\._\(\)]+[a-zA-Z0-9]$'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponseWrapper, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('OperationalizationCluster', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + get.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningCompute/operationalizationClusters/{clusterName}'} # type: ignore + + async def update( + self, + resource_group_name: str, + cluster_name: str, + parameters: "_models.OperationalizationClusterUpdateParameters", + **kwargs + ) -> "_models.OperationalizationCluster": + """The PATCH operation can be used to update only the tags for a cluster. Use PUT operation to + update other properties. + + :param resource_group_name: Name of the resource group in which the cluster is located. + :type resource_group_name: str + :param cluster_name: The name of the cluster. + :type cluster_name: str + :param parameters: The parameters supplied to patch the cluster. + :type parameters: ~azure.mgmt.machinelearningcompute.models.OperationalizationClusterUpdateParameters + :keyword callable cls: A custom type or function that will be passed the direct response + :return: OperationalizationCluster, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningcompute.models.OperationalizationCluster + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.OperationalizationCluster"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2017-08-01-preview" + content_type = kwargs.pop("content_type", "application/json") + accept = "application/json" + + # Construct URL + url = self.update.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\w\._\(\)]+$'), + 'clusterName': self._serialize.url("cluster_name", cluster_name, 'str', max_length=90, min_length=1, pattern=r'^[a-zA-Z][-\w\._\(\)]+[a-zA-Z0-9]$'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Content-Type'] = self._serialize.header("content_type", content_type, 'str') + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + body_content_kwargs = {} # type: Dict[str, Any] + body_content = self._serialize.body(parameters, 'OperationalizationClusterUpdateParameters') + body_content_kwargs['content'] = body_content + request = self._client.patch(url, query_parameters, header_parameters, **body_content_kwargs) + pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponseWrapper, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('OperationalizationCluster', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + update.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningCompute/operationalizationClusters/{clusterName}'} # type: ignore + + async def _delete_initial( + self, + resource_group_name: str, + cluster_name: str, + delete_all: Optional[bool] = None, + **kwargs + ) -> None: + cls = kwargs.pop('cls', None) # type: ClsType[None] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2017-08-01-preview" + accept = "application/json" + + # Construct URL + url = self._delete_initial.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\w\._\(\)]+$'), + 'clusterName': self._serialize.url("cluster_name", cluster_name, 'str', max_length=90, min_length=1, pattern=r'^[a-zA-Z][-\w\._\(\)]+[a-zA-Z0-9]$'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + if delete_all is not None: + query_parameters['deleteAll'] = self._serialize.query("delete_all", delete_all, 'bool') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.delete(url, query_parameters, header_parameters) + pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [202, 204]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponseWrapper, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + response_headers = {} + if response.status_code == 202: + response_headers['Location']=self._deserialize('str', response.headers.get('Location')) + + if cls: + return cls(pipeline_response, None, response_headers) + + _delete_initial.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningCompute/operationalizationClusters/{clusterName}'} # type: ignore + + async def begin_delete( + self, + resource_group_name: str, + cluster_name: str, + delete_all: Optional[bool] = None, + **kwargs + ) -> AsyncLROPoller[None]: + """Deletes the specified cluster. + + :param resource_group_name: Name of the resource group in which the cluster is located. + :type resource_group_name: str + :param cluster_name: The name of the cluster. + :type cluster_name: str + :param delete_all: If true, deletes all resources associated with this cluster. + :type delete_all: bool + :keyword callable cls: A custom type or function that will be passed the direct response + :keyword str continuation_token: A continuation token to restart a poller from a saved state. + :keyword polling: Pass in True if you'd like the AsyncARMPolling polling method, + False for no polling, or your own initialized polling object for a personal polling strategy. + :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod + :keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present. + :return: An instance of AsyncLROPoller that returns either None or the result of cls(response) + :rtype: ~azure.core.polling.AsyncLROPoller[None] + :raises ~azure.core.exceptions.HttpResponseError: + """ + polling = kwargs.pop('polling', True) # type: Union[bool, AsyncPollingMethod] + cls = kwargs.pop('cls', None) # type: ClsType[None] + lro_delay = kwargs.pop( + 'polling_interval', + self._config.polling_interval + ) + cont_token = kwargs.pop('continuation_token', None) # type: Optional[str] + if cont_token is None: + raw_result = await self._delete_initial( + resource_group_name=resource_group_name, + cluster_name=cluster_name, + delete_all=delete_all, + cls=lambda x,y,z: x, + **kwargs + ) + + kwargs.pop('error_map', None) + kwargs.pop('content_type', None) + + def get_long_running_output(pipeline_response): + if cls: + return cls(pipeline_response, None, {}) + + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\w\._\(\)]+$'), + 'clusterName': self._serialize.url("cluster_name", cluster_name, 'str', max_length=90, min_length=1, pattern=r'^[a-zA-Z][-\w\._\(\)]+[a-zA-Z0-9]$'), + } + + if polling is True: polling_method = AsyncARMPolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + elif polling is False: polling_method = AsyncNoPolling() + else: polling_method = polling + if cont_token: + return AsyncLROPoller.from_continuation_token( + polling_method=polling_method, + continuation_token=cont_token, + client=self._client, + deserialization_callback=get_long_running_output + ) + else: + return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) + begin_delete.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningCompute/operationalizationClusters/{clusterName}'} # type: ignore + + async def list_keys( + self, + resource_group_name: str, + cluster_name: str, + **kwargs + ) -> "_models.OperationalizationClusterCredentials": + """Gets the credentials for the specified cluster such as Storage, ACR and ACS credentials. This + is a long running operation because it fetches keys from dependencies. + + :param resource_group_name: Name of the resource group in which the cluster is located. + :type resource_group_name: str + :param cluster_name: The name of the cluster. + :type cluster_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: OperationalizationClusterCredentials, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningcompute.models.OperationalizationClusterCredentials + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.OperationalizationClusterCredentials"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2017-08-01-preview" + accept = "application/json" + + # Construct URL + url = self.list_keys.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\w\._\(\)]+$'), + 'clusterName': self._serialize.url("cluster_name", cluster_name, 'str', max_length=90, min_length=1, pattern=r'^[a-zA-Z][-\w\._\(\)]+[a-zA-Z0-9]$'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.post(url, query_parameters, header_parameters) + pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + raise HttpResponseError(response=response, error_format=ARMErrorFormat) + + deserialized = self._deserialize('OperationalizationClusterCredentials', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + list_keys.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningCompute/operationalizationClusters/{clusterName}/listKeys'} # type: ignore + + async def check_system_services_updates_available( + self, + resource_group_name: str, + cluster_name: str, + **kwargs + ) -> "_models.CheckSystemServicesUpdatesAvailableResponse": + """Checks if updates are available for system services in the cluster. + + :param resource_group_name: Name of the resource group in which the cluster is located. + :type resource_group_name: str + :param cluster_name: The name of the cluster. + :type cluster_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: CheckSystemServicesUpdatesAvailableResponse, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningcompute.models.CheckSystemServicesUpdatesAvailableResponse + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.CheckSystemServicesUpdatesAvailableResponse"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2017-08-01-preview" + accept = "application/json" + + # Construct URL + url = self.check_system_services_updates_available.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\w\._\(\)]+$'), + 'clusterName': self._serialize.url("cluster_name", cluster_name, 'str', max_length=90, min_length=1, pattern=r'^[a-zA-Z][-\w\._\(\)]+[a-zA-Z0-9]$'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.post(url, query_parameters, header_parameters) + pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + raise HttpResponseError(response=response, error_format=ARMErrorFormat) + + deserialized = self._deserialize('CheckSystemServicesUpdatesAvailableResponse', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + check_system_services_updates_available.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningCompute/operationalizationClusters/{clusterName}/checkSystemServicesUpdatesAvailable'} # type: ignore + + async def _update_system_services_initial( + self, + resource_group_name: str, + cluster_name: str, + **kwargs + ) -> Optional["_models.UpdateSystemServicesResponse"]: + cls = kwargs.pop('cls', None) # type: ClsType[Optional["_models.UpdateSystemServicesResponse"]] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2017-08-01-preview" + accept = "application/json" + + # Construct URL + url = self._update_system_services_initial.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\w\._\(\)]+$'), + 'clusterName': self._serialize.url("cluster_name", cluster_name, 'str', max_length=90, min_length=1, pattern=r'^[a-zA-Z][-\w\._\(\)]+[a-zA-Z0-9]$'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.post(url, query_parameters, header_parameters) + pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200, 202]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + raise HttpResponseError(response=response, error_format=ARMErrorFormat) + + response_headers = {} + deserialized = None + if response.status_code == 200: + deserialized = self._deserialize('UpdateSystemServicesResponse', pipeline_response) + + if response.status_code == 202: + response_headers['Location']=self._deserialize('str', response.headers.get('Location')) + + if cls: + return cls(pipeline_response, deserialized, response_headers) + + return deserialized + _update_system_services_initial.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningCompute/operationalizationClusters/{clusterName}/updateSystemServices'} # type: ignore + + async def begin_update_system_services( + self, + resource_group_name: str, + cluster_name: str, + **kwargs + ) -> AsyncLROPoller["_models.UpdateSystemServicesResponse"]: + """Updates system services in a cluster. + + :param resource_group_name: Name of the resource group in which the cluster is located. + :type resource_group_name: str + :param cluster_name: The name of the cluster. + :type cluster_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :keyword str continuation_token: A continuation token to restart a poller from a saved state. + :keyword polling: Pass in True if you'd like the AsyncARMPolling polling method, + False for no polling, or your own initialized polling object for a personal polling strategy. + :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod + :keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present. + :return: An instance of AsyncLROPoller that returns either UpdateSystemServicesResponse or the result of cls(response) + :rtype: ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningcompute.models.UpdateSystemServicesResponse] + :raises ~azure.core.exceptions.HttpResponseError: + """ + polling = kwargs.pop('polling', True) # type: Union[bool, AsyncPollingMethod] + cls = kwargs.pop('cls', None) # type: ClsType["_models.UpdateSystemServicesResponse"] + lro_delay = kwargs.pop( + 'polling_interval', + self._config.polling_interval + ) + cont_token = kwargs.pop('continuation_token', None) # type: Optional[str] + if cont_token is None: + raw_result = await self._update_system_services_initial( + resource_group_name=resource_group_name, + cluster_name=cluster_name, + cls=lambda x,y,z: x, + **kwargs + ) + + kwargs.pop('error_map', None) + kwargs.pop('content_type', None) + + def get_long_running_output(pipeline_response): + deserialized = self._deserialize('UpdateSystemServicesResponse', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + return deserialized + + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\w\._\(\)]+$'), + 'clusterName': self._serialize.url("cluster_name", cluster_name, 'str', max_length=90, min_length=1, pattern=r'^[a-zA-Z][-\w\._\(\)]+[a-zA-Z0-9]$'), + } + + if polling is True: polling_method = AsyncARMPolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + elif polling is False: polling_method = AsyncNoPolling() + else: polling_method = polling + if cont_token: + return AsyncLROPoller.from_continuation_token( + polling_method=polling_method, + continuation_token=cont_token, + client=self._client, + deserialization_callback=get_long_running_output + ) + else: + return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) + begin_update_system_services.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningCompute/operationalizationClusters/{clusterName}/updateSystemServices'} # type: ignore + + def list_by_resource_group( + self, + resource_group_name: str, + skiptoken: Optional[str] = None, + **kwargs + ) -> AsyncIterable["_models.PaginatedOperationalizationClustersList"]: + """Gets the clusters in the specified resource group. + + :param resource_group_name: Name of the resource group in which the cluster is located. + :type resource_group_name: str + :param skiptoken: Continuation token for pagination. + :type skiptoken: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either PaginatedOperationalizationClustersList or the result of cls(response) + :rtype: ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.machinelearningcompute.models.PaginatedOperationalizationClustersList] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.PaginatedOperationalizationClustersList"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2017-08-01-preview" + accept = "application/json" + + def prepare_request(next_link=None): + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + if not next_link: + # Construct URL + url = self.list_by_resource_group.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\w\._\(\)]+$'), + } + url = self._client.format_url(url, **path_format_arguments) + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + if skiptoken is not None: + query_parameters['$skiptoken'] = self._serialize.query("skiptoken", skiptoken, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + else: + url = next_link + query_parameters = {} # type: Dict[str, Any] + request = self._client.get(url, query_parameters, header_parameters) + return request + + async def extract_data(pipeline_response): + deserialized = self._deserialize('PaginatedOperationalizationClustersList', pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, AsyncList(list_of_elem) + + async def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + raise HttpResponseError(response=response, error_format=ARMErrorFormat) + + return pipeline_response + + return AsyncItemPaged( + get_next, extract_data + ) + list_by_resource_group.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningCompute/operationalizationClusters'} # type: ignore + + def list_by_subscription_id( + self, + skiptoken: Optional[str] = None, + **kwargs + ) -> AsyncIterable["_models.PaginatedOperationalizationClustersList"]: + """Gets the operationalization clusters in the specified subscription. + + :param skiptoken: Continuation token for pagination. + :type skiptoken: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either PaginatedOperationalizationClustersList or the result of cls(response) + :rtype: ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.machinelearningcompute.models.PaginatedOperationalizationClustersList] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.PaginatedOperationalizationClustersList"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2017-08-01-preview" + accept = "application/json" + + def prepare_request(next_link=None): + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + if not next_link: + # Construct URL + url = self.list_by_subscription_id.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + if skiptoken is not None: + query_parameters['$skiptoken'] = self._serialize.query("skiptoken", skiptoken, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + else: + url = next_link + query_parameters = {} # type: Dict[str, Any] + request = self._client.get(url, query_parameters, header_parameters) + return request + + async def extract_data(pipeline_response): + deserialized = self._deserialize('PaginatedOperationalizationClustersList', pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, AsyncList(list_of_elem) + + async def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + raise HttpResponseError(response=response, error_format=ARMErrorFormat) + + return pipeline_response + + return AsyncItemPaged( + get_next, extract_data + ) + list_by_subscription_id.metadata = {'url': '/subscriptions/{subscriptionId}/providers/Microsoft.MachineLearningCompute/operationalizationClusters'} # type: ignore diff --git a/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/models/__init__.py b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/models/__init__.py new file mode 100644 index 000000000000..73ceb102b5be --- /dev/null +++ b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/models/__init__.py @@ -0,0 +1,114 @@ +# 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. +# -------------------------------------------------------------------------- + +try: + from ._models_py3 import AcsClusterProperties + from ._models_py3 import AppInsightsCredentials + from ._models_py3 import AppInsightsProperties + from ._models_py3 import AutoScaleConfiguration + from ._models_py3 import AvailableOperations + from ._models_py3 import CheckSystemServicesUpdatesAvailableResponse + from ._models_py3 import ContainerRegistryCredentials + from ._models_py3 import ContainerRegistryProperties + from ._models_py3 import ContainerServiceCredentials + from ._models_py3 import ErrorDetail + from ._models_py3 import ErrorResponse + from ._models_py3 import ErrorResponseWrapper + from ._models_py3 import GlobalServiceConfiguration + from ._models_py3 import KubernetesClusterProperties + from ._models_py3 import OperationalizationCluster + from ._models_py3 import OperationalizationClusterCredentials + from ._models_py3 import OperationalizationClusterUpdateParameters + from ._models_py3 import PaginatedOperationalizationClustersList + from ._models_py3 import Resource + from ._models_py3 import ResourceOperation + from ._models_py3 import ResourceOperationDisplay + from ._models_py3 import ServiceAuthConfiguration + from ._models_py3 import ServicePrincipalProperties + from ._models_py3 import SslConfiguration + from ._models_py3 import StorageAccountCredentials + from ._models_py3 import StorageAccountProperties + from ._models_py3 import SystemService + from ._models_py3 import UpdateSystemServicesResponse +except (SyntaxError, ImportError): + from ._models import AcsClusterProperties # type: ignore + from ._models import AppInsightsCredentials # type: ignore + from ._models import AppInsightsProperties # type: ignore + from ._models import AutoScaleConfiguration # type: ignore + from ._models import AvailableOperations # type: ignore + from ._models import CheckSystemServicesUpdatesAvailableResponse # type: ignore + from ._models import ContainerRegistryCredentials # type: ignore + from ._models import ContainerRegistryProperties # type: ignore + from ._models import ContainerServiceCredentials # type: ignore + from ._models import ErrorDetail # type: ignore + from ._models import ErrorResponse # type: ignore + from ._models import ErrorResponseWrapper # type: ignore + from ._models import GlobalServiceConfiguration # type: ignore + from ._models import KubernetesClusterProperties # type: ignore + from ._models import OperationalizationCluster # type: ignore + from ._models import OperationalizationClusterCredentials # type: ignore + from ._models import OperationalizationClusterUpdateParameters # type: ignore + from ._models import PaginatedOperationalizationClustersList # type: ignore + from ._models import Resource # type: ignore + from ._models import ResourceOperation # type: ignore + from ._models import ResourceOperationDisplay # type: ignore + from ._models import ServiceAuthConfiguration # type: ignore + from ._models import ServicePrincipalProperties # type: ignore + from ._models import SslConfiguration # type: ignore + from ._models import StorageAccountCredentials # type: ignore + from ._models import StorageAccountProperties # type: ignore + from ._models import SystemService # type: ignore + from ._models import UpdateSystemServicesResponse # type: ignore + +from ._machine_learning_compute_management_client_enums import ( + AgentVMSizeTypes, + ClusterType, + OperationStatus, + OrchestratorType, + Status, + SystemServiceType, + UpdatesAvailable, +) + +__all__ = [ + 'AcsClusterProperties', + 'AppInsightsCredentials', + 'AppInsightsProperties', + 'AutoScaleConfiguration', + 'AvailableOperations', + 'CheckSystemServicesUpdatesAvailableResponse', + 'ContainerRegistryCredentials', + 'ContainerRegistryProperties', + 'ContainerServiceCredentials', + 'ErrorDetail', + 'ErrorResponse', + 'ErrorResponseWrapper', + 'GlobalServiceConfiguration', + 'KubernetesClusterProperties', + 'OperationalizationCluster', + 'OperationalizationClusterCredentials', + 'OperationalizationClusterUpdateParameters', + 'PaginatedOperationalizationClustersList', + 'Resource', + 'ResourceOperation', + 'ResourceOperationDisplay', + 'ServiceAuthConfiguration', + 'ServicePrincipalProperties', + 'SslConfiguration', + 'StorageAccountCredentials', + 'StorageAccountProperties', + 'SystemService', + 'UpdateSystemServicesResponse', + 'AgentVMSizeTypes', + 'ClusterType', + 'OperationStatus', + 'OrchestratorType', + 'Status', + 'SystemServiceType', + 'UpdatesAvailable', +] diff --git a/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/models/_machine_learning_compute_management_client_enums.py b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/models/_machine_learning_compute_management_client_enums.py new file mode 100644 index 000000000000..f07194326483 --- /dev/null +++ b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/models/_machine_learning_compute_management_client_enums.py @@ -0,0 +1,131 @@ +# 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 enum import Enum, EnumMeta +from six import with_metaclass + +class _CaseInsensitiveEnumMeta(EnumMeta): + def __getitem__(self, name): + return super().__getitem__(name.upper()) + + def __getattr__(cls, name): + """Return the enum member matching `name` + We use __getattr__ instead of descriptors or inserting into the enum + class' __dict__ in order to support `name` and `value` being both + properties for enum members (which live in the class' __dict__) and + enum members themselves. + """ + try: + return cls._member_map_[name.upper()] + except KeyError: + raise AttributeError(name) + + +class AgentVMSizeTypes(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)): + """The Azure VM size of the agent VM nodes. This cannot be changed once the cluster is created. + This list is non exhaustive; refer to + https://docs.microsoft.com/en-us/azure/virtual-machines/windows/sizes for the possible VM + sizes. + """ + + STANDARD_A0 = "Standard_A0" + STANDARD_A1 = "Standard_A1" + STANDARD_A2 = "Standard_A2" + STANDARD_A3 = "Standard_A3" + STANDARD_A4 = "Standard_A4" + STANDARD_A5 = "Standard_A5" + STANDARD_A6 = "Standard_A6" + STANDARD_A7 = "Standard_A7" + STANDARD_A8 = "Standard_A8" + STANDARD_A9 = "Standard_A9" + STANDARD_A10 = "Standard_A10" + STANDARD_A11 = "Standard_A11" + STANDARD_D1 = "Standard_D1" + STANDARD_D2 = "Standard_D2" + STANDARD_D3 = "Standard_D3" + STANDARD_D4 = "Standard_D4" + STANDARD_D11 = "Standard_D11" + STANDARD_D12 = "Standard_D12" + STANDARD_D13 = "Standard_D13" + STANDARD_D14 = "Standard_D14" + STANDARD_D1_V2 = "Standard_D1_v2" + STANDARD_D2_V2 = "Standard_D2_v2" + STANDARD_D3_V2 = "Standard_D3_v2" + STANDARD_D4_V2 = "Standard_D4_v2" + STANDARD_D5_V2 = "Standard_D5_v2" + STANDARD_D11_V2 = "Standard_D11_v2" + STANDARD_D12_V2 = "Standard_D12_v2" + STANDARD_D13_V2 = "Standard_D13_v2" + STANDARD_D14_V2 = "Standard_D14_v2" + STANDARD_G1 = "Standard_G1" + STANDARD_G2 = "Standard_G2" + STANDARD_G3 = "Standard_G3" + STANDARD_G4 = "Standard_G4" + STANDARD_G5 = "Standard_G5" + STANDARD_DS1 = "Standard_DS1" + STANDARD_DS2 = "Standard_DS2" + STANDARD_DS3 = "Standard_DS3" + STANDARD_DS4 = "Standard_DS4" + STANDARD_DS11 = "Standard_DS11" + STANDARD_DS12 = "Standard_DS12" + STANDARD_DS13 = "Standard_DS13" + STANDARD_DS14 = "Standard_DS14" + STANDARD_GS1 = "Standard_GS1" + STANDARD_GS2 = "Standard_GS2" + STANDARD_GS3 = "Standard_GS3" + STANDARD_GS4 = "Standard_GS4" + STANDARD_GS5 = "Standard_GS5" + +class ClusterType(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)): + """The cluster type. + """ + + ACS = "ACS" + LOCAL = "Local" + +class OperationStatus(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)): + """The provision state of the cluster. Valid values are Unknown, Updating, Provisioning, + Succeeded, and Failed. + """ + + UNKNOWN = "Unknown" + UPDATING = "Updating" + CREATING = "Creating" + DELETING = "Deleting" + SUCCEEDED = "Succeeded" + FAILED = "Failed" + CANCELED = "Canceled" + +class OrchestratorType(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)): + """Type of orchestrator. It cannot be changed once the cluster is created. + """ + + KUBERNETES = "Kubernetes" + NONE = "None" + +class Status(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)): + """SSL status. Allowed values are Enabled and Disabled. + """ + + ENABLED = "Enabled" + DISABLED = "Disabled" + +class SystemServiceType(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)): + """The system service type + """ + + NONE = "None" + SCORING_FRONT_END = "ScoringFrontEnd" + BATCH_FRONT_END = "BatchFrontEnd" + +class UpdatesAvailable(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)): + """Yes if updates are available for the system services, No if not. + """ + + YES = "Yes" + NO = "No" diff --git a/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/models/_models.py b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/models/_models.py new file mode 100644 index 000000000000..f6ed840f0cc4 --- /dev/null +++ b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/models/_models.py @@ -0,0 +1,954 @@ +# 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 azure.core.exceptions import HttpResponseError +import msrest.serialization + + +class AcsClusterProperties(msrest.serialization.Model): + """Information about the container service backing the cluster. + + Variables are only populated by the server, and will be ignored when sending a request. + + All required parameters must be populated in order to send to Azure. + + :ivar cluster_fqdn: The FQDN of the cluster. + :vartype cluster_fqdn: str + :param orchestrator_type: Required. Type of orchestrator. It cannot be changed once the cluster + is created. Possible values include: "Kubernetes", "None". + :type orchestrator_type: str or ~azure.mgmt.machinelearningcompute.models.OrchestratorType + :param orchestrator_properties: Orchestrator specific properties. + :type orchestrator_properties: + ~azure.mgmt.machinelearningcompute.models.KubernetesClusterProperties + :param system_services: The system services deployed to the cluster. + :type system_services: list[~azure.mgmt.machinelearningcompute.models.SystemService] + :param master_count: The number of master nodes in the container service. + :type master_count: int + :param agent_count: The number of agent nodes in the Container Service. This can be changed to + scale the cluster. + :type agent_count: int + :param agent_vm_size: The Azure VM size of the agent VM nodes. This cannot be changed once the + cluster is created. This list is non exhaustive; refer to + https://docs.microsoft.com/en-us/azure/virtual-machines/windows/sizes for the possible VM + sizes. Possible values include: "Standard_A0", "Standard_A1", "Standard_A2", "Standard_A3", + "Standard_A4", "Standard_A5", "Standard_A6", "Standard_A7", "Standard_A8", "Standard_A9", + "Standard_A10", "Standard_A11", "Standard_D1", "Standard_D2", "Standard_D3", "Standard_D4", + "Standard_D11", "Standard_D12", "Standard_D13", "Standard_D14", "Standard_D1_v2", + "Standard_D2_v2", "Standard_D3_v2", "Standard_D4_v2", "Standard_D5_v2", "Standard_D11_v2", + "Standard_D12_v2", "Standard_D13_v2", "Standard_D14_v2", "Standard_G1", "Standard_G2", + "Standard_G3", "Standard_G4", "Standard_G5", "Standard_DS1", "Standard_DS2", "Standard_DS3", + "Standard_DS4", "Standard_DS11", "Standard_DS12", "Standard_DS13", "Standard_DS14", + "Standard_GS1", "Standard_GS2", "Standard_GS3", "Standard_GS4", "Standard_GS5". Default value: + "Standard_D3_v2". + :type agent_vm_size: str or ~azure.mgmt.machinelearningcompute.models.AgentVMSizeTypes + """ + + _validation = { + 'cluster_fqdn': {'readonly': True}, + 'orchestrator_type': {'required': True}, + 'master_count': {'maximum': 5, 'minimum': 1}, + 'agent_count': {'maximum': 100, 'minimum': 1}, + } + + _attribute_map = { + 'cluster_fqdn': {'key': 'clusterFqdn', 'type': 'str'}, + 'orchestrator_type': {'key': 'orchestratorType', 'type': 'str'}, + 'orchestrator_properties': {'key': 'orchestratorProperties', 'type': 'KubernetesClusterProperties'}, + 'system_services': {'key': 'systemServices', 'type': '[SystemService]'}, + 'master_count': {'key': 'masterCount', 'type': 'int'}, + 'agent_count': {'key': 'agentCount', 'type': 'int'}, + 'agent_vm_size': {'key': 'agentVmSize', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(AcsClusterProperties, self).__init__(**kwargs) + self.cluster_fqdn = None + self.orchestrator_type = kwargs['orchestrator_type'] + self.orchestrator_properties = kwargs.get('orchestrator_properties', None) + self.system_services = kwargs.get('system_services', None) + self.master_count = kwargs.get('master_count', 1) + self.agent_count = kwargs.get('agent_count', 2) + self.agent_vm_size = kwargs.get('agent_vm_size', "Standard_D3_v2") + + +class AppInsightsCredentials(msrest.serialization.Model): + """AppInsights credentials. + + :param app_id: The AppInsights application ID. + :type app_id: str + :param instrumentation_key: The AppInsights instrumentation key. This is not returned in + response of GET/PUT on the resource. To see this please call listKeys API. + :type instrumentation_key: str + """ + + _attribute_map = { + 'app_id': {'key': 'appId', 'type': 'str'}, + 'instrumentation_key': {'key': 'instrumentationKey', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(AppInsightsCredentials, self).__init__(**kwargs) + self.app_id = kwargs.get('app_id', None) + self.instrumentation_key = kwargs.get('instrumentation_key', None) + + +class AppInsightsProperties(msrest.serialization.Model): + """Properties of App Insights. + + :param resource_id: ARM resource ID of the App Insights. + :type resource_id: str + """ + + _attribute_map = { + 'resource_id': {'key': 'resourceId', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(AppInsightsProperties, self).__init__(**kwargs) + self.resource_id = kwargs.get('resource_id', None) + + +class AutoScaleConfiguration(msrest.serialization.Model): + """AutoScale configuration properties. + + :param status: If auto-scale is enabled for all services. Each service can turn it off + individually. Possible values include: "Enabled", "Disabled". + :type status: str or ~azure.mgmt.machinelearningcompute.models.Status + :param min_replicas: The minimum number of replicas for each service. + :type min_replicas: int + :param max_replicas: The maximum number of replicas for each service. + :type max_replicas: int + :param target_utilization: The target utilization. + :type target_utilization: float + :param refresh_period_in_seconds: Refresh period in seconds. + :type refresh_period_in_seconds: int + """ + + _validation = { + 'min_replicas': {'minimum': 1}, + 'max_replicas': {'minimum': 1}, + } + + _attribute_map = { + 'status': {'key': 'status', 'type': 'str'}, + 'min_replicas': {'key': 'minReplicas', 'type': 'int'}, + 'max_replicas': {'key': 'maxReplicas', 'type': 'int'}, + 'target_utilization': {'key': 'targetUtilization', 'type': 'float'}, + 'refresh_period_in_seconds': {'key': 'refreshPeriodInSeconds', 'type': 'int'}, + } + + def __init__( + self, + **kwargs + ): + super(AutoScaleConfiguration, self).__init__(**kwargs) + self.status = kwargs.get('status', None) + self.min_replicas = kwargs.get('min_replicas', 1) + self.max_replicas = kwargs.get('max_replicas', 100) + self.target_utilization = kwargs.get('target_utilization', None) + self.refresh_period_in_seconds = kwargs.get('refresh_period_in_seconds', None) + + +class AvailableOperations(msrest.serialization.Model): + """Available operation list. + + :param value: An array of available operations. + :type value: list[~azure.mgmt.machinelearningcompute.models.ResourceOperation] + """ + + _attribute_map = { + 'value': {'key': 'value', 'type': '[ResourceOperation]'}, + } + + def __init__( + self, + **kwargs + ): + super(AvailableOperations, self).__init__(**kwargs) + self.value = kwargs.get('value', None) + + +class CheckSystemServicesUpdatesAvailableResponse(msrest.serialization.Model): + """Information about updates available for system services in a cluster. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar updates_available: Yes if updates are available for the system services, No if not. + Possible values include: "Yes", "No". + :vartype updates_available: str or ~azure.mgmt.machinelearningcompute.models.UpdatesAvailable + """ + + _validation = { + 'updates_available': {'readonly': True}, + } + + _attribute_map = { + 'updates_available': {'key': 'updatesAvailable', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(CheckSystemServicesUpdatesAvailableResponse, self).__init__(**kwargs) + self.updates_available = None + + +class ContainerRegistryCredentials(msrest.serialization.Model): + """Information about the Azure Container Registry which contains the images deployed to the cluster. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar login_server: The ACR login server name. User name is the first part of the FQDN. + :vartype login_server: str + :ivar password: The ACR primary password. + :vartype password: str + :ivar password2: The ACR secondary password. + :vartype password2: str + :ivar username: The ACR login username. + :vartype username: str + """ + + _validation = { + 'login_server': {'readonly': True}, + 'password': {'readonly': True}, + 'password2': {'readonly': True}, + 'username': {'readonly': True}, + } + + _attribute_map = { + 'login_server': {'key': 'loginServer', 'type': 'str'}, + 'password': {'key': 'password', 'type': 'str'}, + 'password2': {'key': 'password2', 'type': 'str'}, + 'username': {'key': 'username', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(ContainerRegistryCredentials, self).__init__(**kwargs) + self.login_server = None + self.password = None + self.password2 = None + self.username = None + + +class ContainerRegistryProperties(msrest.serialization.Model): + """Properties of Azure Container Registry. + + :param resource_id: ARM resource ID of the Azure Container Registry used to store Docker images + for web services in the cluster. If not provided one will be created. This cannot be changed + once the cluster is created. + :type resource_id: str + """ + + _attribute_map = { + 'resource_id': {'key': 'resourceId', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(ContainerRegistryProperties, self).__init__(**kwargs) + self.resource_id = kwargs.get('resource_id', None) + + +class ContainerServiceCredentials(msrest.serialization.Model): + """Information about the Azure Container Registry which contains the images deployed to the cluster. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar acs_kube_config: The ACS kube config file. + :vartype acs_kube_config: str + :ivar service_principal_configuration: Service principal configuration used by Kubernetes. + :vartype service_principal_configuration: + ~azure.mgmt.machinelearningcompute.models.ServicePrincipalProperties + :ivar image_pull_secret_name: The ACR image pull secret name which was created in Kubernetes. + :vartype image_pull_secret_name: str + """ + + _validation = { + 'acs_kube_config': {'readonly': True}, + 'service_principal_configuration': {'readonly': True}, + 'image_pull_secret_name': {'readonly': True}, + } + + _attribute_map = { + 'acs_kube_config': {'key': 'acsKubeConfig', 'type': 'str'}, + 'service_principal_configuration': {'key': 'servicePrincipalConfiguration', 'type': 'ServicePrincipalProperties'}, + 'image_pull_secret_name': {'key': 'imagePullSecretName', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(ContainerServiceCredentials, self).__init__(**kwargs) + self.acs_kube_config = None + self.service_principal_configuration = None + self.image_pull_secret_name = None + + +class ErrorDetail(msrest.serialization.Model): + """Error detail information. + + All required parameters must be populated in order to send to Azure. + + :param code: Required. Error code. + :type code: str + :param message: Required. Error message. + :type message: str + """ + + _validation = { + 'code': {'required': True}, + 'message': {'required': True}, + } + + _attribute_map = { + 'code': {'key': 'code', 'type': 'str'}, + 'message': {'key': 'message', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(ErrorDetail, self).__init__(**kwargs) + self.code = kwargs['code'] + self.message = kwargs['message'] + + +class ErrorResponse(msrest.serialization.Model): + """Error response information. + + All required parameters must be populated in order to send to Azure. + + :param code: Required. Error code. + :type code: str + :param message: Required. Error message. + :type message: str + :param details: An array of error detail objects. + :type details: list[~azure.mgmt.machinelearningcompute.models.ErrorDetail] + """ + + _validation = { + 'code': {'required': True}, + 'message': {'required': True}, + } + + _attribute_map = { + 'code': {'key': 'code', 'type': 'str'}, + 'message': {'key': 'message', 'type': 'str'}, + 'details': {'key': 'details', 'type': '[ErrorDetail]'}, + } + + def __init__( + self, + **kwargs + ): + super(ErrorResponse, self).__init__(**kwargs) + self.code = kwargs['code'] + self.message = kwargs['message'] + self.details = kwargs.get('details', None) + + +class ErrorResponseWrapper(msrest.serialization.Model): + """Wrapper for error response to follow ARM guidelines. + + :param error: The error response. + :type error: ~azure.mgmt.machinelearningcompute.models.ErrorResponse + """ + + _attribute_map = { + 'error': {'key': 'error', 'type': 'ErrorResponse'}, + } + + def __init__( + self, + **kwargs + ): + super(ErrorResponseWrapper, self).__init__(**kwargs) + self.error = kwargs.get('error', None) + + +class GlobalServiceConfiguration(msrest.serialization.Model): + """Global configuration for services in the cluster. + + :param additional_properties: Unmatched properties from the message are deserialized to this + collection. + :type additional_properties: dict[str, str] + :param etag: The configuration ETag for updates. + :type etag: str + :param ssl: The SSL configuration properties. + :type ssl: ~azure.mgmt.machinelearningcompute.models.SslConfiguration + :param service_auth: Optional global authorization keys for all user services deployed in + cluster. These are used if the service does not have auth keys. + :type service_auth: ~azure.mgmt.machinelearningcompute.models.ServiceAuthConfiguration + :param auto_scale: The auto-scale configuration. + :type auto_scale: ~azure.mgmt.machinelearningcompute.models.AutoScaleConfiguration + """ + + _attribute_map = { + 'additional_properties': {'key': '', 'type': '{str}'}, + 'etag': {'key': 'etag', 'type': 'str'}, + 'ssl': {'key': 'ssl', 'type': 'SslConfiguration'}, + 'service_auth': {'key': 'serviceAuth', 'type': 'ServiceAuthConfiguration'}, + 'auto_scale': {'key': 'autoScale', 'type': 'AutoScaleConfiguration'}, + } + + def __init__( + self, + **kwargs + ): + super(GlobalServiceConfiguration, self).__init__(**kwargs) + self.additional_properties = kwargs.get('additional_properties', None) + self.etag = kwargs.get('etag', None) + self.ssl = kwargs.get('ssl', None) + self.service_auth = kwargs.get('service_auth', None) + self.auto_scale = kwargs.get('auto_scale', None) + + +class KubernetesClusterProperties(msrest.serialization.Model): + """Kubernetes cluster specific properties. + + :param service_principal: The Azure Service Principal used by Kubernetes. + :type service_principal: ~azure.mgmt.machinelearningcompute.models.ServicePrincipalProperties + """ + + _attribute_map = { + 'service_principal': {'key': 'servicePrincipal', 'type': 'ServicePrincipalProperties'}, + } + + def __init__( + self, + **kwargs + ): + super(KubernetesClusterProperties, self).__init__(**kwargs) + self.service_principal = kwargs.get('service_principal', None) + + +class Resource(msrest.serialization.Model): + """Azure resource. + + Variables are only populated by the server, and will be ignored when sending a request. + + All required parameters must be populated in order to send to Azure. + + :ivar id: Specifies the resource ID. + :vartype id: str + :ivar name: Specifies the name of the resource. + :vartype name: str + :param location: Required. Specifies the location of the resource. + :type location: str + :ivar type: Specifies the type of the resource. + :vartype type: str + :param tags: A set of tags. Contains resource tags defined as key/value pairs. + :type tags: dict[str, str] + """ + + _validation = { + 'id': {'readonly': True}, + 'name': {'readonly': True}, + 'location': {'required': True}, + 'type': {'readonly': True}, + } + + _attribute_map = { + 'id': {'key': 'id', 'type': 'str'}, + 'name': {'key': 'name', 'type': 'str'}, + 'location': {'key': 'location', 'type': 'str'}, + 'type': {'key': 'type', 'type': 'str'}, + 'tags': {'key': 'tags', 'type': '{str}'}, + } + + def __init__( + self, + **kwargs + ): + super(Resource, self).__init__(**kwargs) + self.id = None + self.name = None + self.location = kwargs['location'] + self.type = None + self.tags = kwargs.get('tags', None) + + +class OperationalizationCluster(Resource): + """Instance of an Azure ML Operationalization Cluster resource. + + Variables are only populated by the server, and will be ignored when sending a request. + + All required parameters must be populated in order to send to Azure. + + :ivar id: Specifies the resource ID. + :vartype id: str + :ivar name: Specifies the name of the resource. + :vartype name: str + :param location: Required. Specifies the location of the resource. + :type location: str + :ivar type: Specifies the type of the resource. + :vartype type: str + :param tags: A set of tags. Contains resource tags defined as key/value pairs. + :type tags: dict[str, str] + :param description: The description of the cluster. + :type description: str + :ivar created_on: The date and time when the cluster was created. + :vartype created_on: ~datetime.datetime + :ivar modified_on: The date and time when the cluster was last modified. + :vartype modified_on: ~datetime.datetime + :ivar provisioning_state: The provision state of the cluster. Valid values are Unknown, + Updating, Provisioning, Succeeded, and Failed. Possible values include: "Unknown", "Updating", + "Creating", "Deleting", "Succeeded", "Failed", "Canceled". + :vartype provisioning_state: str or ~azure.mgmt.machinelearningcompute.models.OperationStatus + :ivar provisioning_errors: List of provisioning errors reported by the resource provider. + :vartype provisioning_errors: + list[~azure.mgmt.machinelearningcompute.models.ErrorResponseWrapper] + :param cluster_type: The cluster type. Possible values include: "ACS", "Local". + :type cluster_type: str or ~azure.mgmt.machinelearningcompute.models.ClusterType + :param storage_account: Storage Account properties. + :type storage_account: ~azure.mgmt.machinelearningcompute.models.StorageAccountProperties + :param container_registry: Container Registry properties. + :type container_registry: ~azure.mgmt.machinelearningcompute.models.ContainerRegistryProperties + :param container_service: Parameters for the Azure Container Service cluster. + :type container_service: ~azure.mgmt.machinelearningcompute.models.AcsClusterProperties + :param app_insights: AppInsights configuration. + :type app_insights: ~azure.mgmt.machinelearningcompute.models.AppInsightsProperties + :param global_service_configuration: Contains global configuration for the web services in the + cluster. + :type global_service_configuration: + ~azure.mgmt.machinelearningcompute.models.GlobalServiceConfiguration + """ + + _validation = { + 'id': {'readonly': True}, + 'name': {'readonly': True}, + 'location': {'required': True}, + 'type': {'readonly': True}, + 'created_on': {'readonly': True}, + 'modified_on': {'readonly': True}, + 'provisioning_state': {'readonly': True}, + 'provisioning_errors': {'readonly': True}, + } + + _attribute_map = { + 'id': {'key': 'id', 'type': 'str'}, + 'name': {'key': 'name', 'type': 'str'}, + 'location': {'key': 'location', 'type': 'str'}, + 'type': {'key': 'type', 'type': 'str'}, + 'tags': {'key': 'tags', 'type': '{str}'}, + 'description': {'key': 'properties.description', 'type': 'str'}, + 'created_on': {'key': 'properties.createdOn', 'type': 'iso-8601'}, + 'modified_on': {'key': 'properties.modifiedOn', 'type': 'iso-8601'}, + 'provisioning_state': {'key': 'properties.provisioningState', 'type': 'str'}, + 'provisioning_errors': {'key': 'properties.provisioningErrors', 'type': '[ErrorResponseWrapper]'}, + 'cluster_type': {'key': 'properties.clusterType', 'type': 'str'}, + 'storage_account': {'key': 'properties.storageAccount', 'type': 'StorageAccountProperties'}, + 'container_registry': {'key': 'properties.containerRegistry', 'type': 'ContainerRegistryProperties'}, + 'container_service': {'key': 'properties.containerService', 'type': 'AcsClusterProperties'}, + 'app_insights': {'key': 'properties.appInsights', 'type': 'AppInsightsProperties'}, + 'global_service_configuration': {'key': 'properties.globalServiceConfiguration', 'type': 'GlobalServiceConfiguration'}, + } + + def __init__( + self, + **kwargs + ): + super(OperationalizationCluster, self).__init__(**kwargs) + self.description = kwargs.get('description', None) + self.created_on = None + self.modified_on = None + self.provisioning_state = None + self.provisioning_errors = None + self.cluster_type = kwargs.get('cluster_type', None) + self.storage_account = kwargs.get('storage_account', None) + self.container_registry = kwargs.get('container_registry', None) + self.container_service = kwargs.get('container_service', None) + self.app_insights = kwargs.get('app_insights', None) + self.global_service_configuration = kwargs.get('global_service_configuration', None) + + +class OperationalizationClusterCredentials(msrest.serialization.Model): + """Credentials to resources in the cluster. + + :param storage_account: Credentials for the Storage Account. + :type storage_account: ~azure.mgmt.machinelearningcompute.models.StorageAccountCredentials + :param container_registry: Credentials for Azure Container Registry. + :type container_registry: + ~azure.mgmt.machinelearningcompute.models.ContainerRegistryCredentials + :param container_service: Credentials for Azure Container Service. + :type container_service: ~azure.mgmt.machinelearningcompute.models.ContainerServiceCredentials + :param app_insights: Credentials for Azure AppInsights. + :type app_insights: ~azure.mgmt.machinelearningcompute.models.AppInsightsCredentials + :param service_auth_configuration: Global authorization keys for all user services deployed in + cluster. These are used if the service does not have auth keys. + :type service_auth_configuration: + ~azure.mgmt.machinelearningcompute.models.ServiceAuthConfiguration + :param ssl_configuration: The SSL configuration for the services. + :type ssl_configuration: ~azure.mgmt.machinelearningcompute.models.SslConfiguration + """ + + _attribute_map = { + 'storage_account': {'key': 'storageAccount', 'type': 'StorageAccountCredentials'}, + 'container_registry': {'key': 'containerRegistry', 'type': 'ContainerRegistryCredentials'}, + 'container_service': {'key': 'containerService', 'type': 'ContainerServiceCredentials'}, + 'app_insights': {'key': 'appInsights', 'type': 'AppInsightsCredentials'}, + 'service_auth_configuration': {'key': 'serviceAuthConfiguration', 'type': 'ServiceAuthConfiguration'}, + 'ssl_configuration': {'key': 'sslConfiguration', 'type': 'SslConfiguration'}, + } + + def __init__( + self, + **kwargs + ): + super(OperationalizationClusterCredentials, self).__init__(**kwargs) + self.storage_account = kwargs.get('storage_account', None) + self.container_registry = kwargs.get('container_registry', None) + self.container_service = kwargs.get('container_service', None) + self.app_insights = kwargs.get('app_insights', None) + self.service_auth_configuration = kwargs.get('service_auth_configuration', None) + self.ssl_configuration = kwargs.get('ssl_configuration', None) + + +class OperationalizationClusterUpdateParameters(msrest.serialization.Model): + """Parameters for PATCH operation on an operationalization cluster. + + :param tags: A set of tags. Gets or sets a list of key value pairs that describe the resource. + These tags can be used in viewing and grouping this resource (across resource groups). A + maximum of 15 tags can be provided for a resource. Each tag must have a key no greater in + length than 128 characters and a value no greater in length than 256 characters. + :type tags: dict[str, str] + """ + + _attribute_map = { + 'tags': {'key': 'tags', 'type': '{str}'}, + } + + def __init__( + self, + **kwargs + ): + super(OperationalizationClusterUpdateParameters, self).__init__(**kwargs) + self.tags = kwargs.get('tags', None) + + +class PaginatedOperationalizationClustersList(msrest.serialization.Model): + """Paginated list of operationalization clusters. + + :param value: An array of cluster objects. + :type value: list[~azure.mgmt.machinelearningcompute.models.OperationalizationCluster] + :param next_link: A continuation link (absolute URI) to the next page of results in the list. + :type next_link: str + """ + + _attribute_map = { + 'value': {'key': 'value', 'type': '[OperationalizationCluster]'}, + 'next_link': {'key': 'nextLink', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(PaginatedOperationalizationClustersList, self).__init__(**kwargs) + self.value = kwargs.get('value', None) + self.next_link = kwargs.get('next_link', None) + + +class ResourceOperation(msrest.serialization.Model): + """Resource operation. + + :param name: Name of this operation. + :type name: str + :param display: Display of the operation. + :type display: ~azure.mgmt.machinelearningcompute.models.ResourceOperationDisplay + :param origin: The operation origin. + :type origin: str + """ + + _attribute_map = { + 'name': {'key': 'name', 'type': 'str'}, + 'display': {'key': 'display', 'type': 'ResourceOperationDisplay'}, + 'origin': {'key': 'origin', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(ResourceOperation, self).__init__(**kwargs) + self.name = kwargs.get('name', None) + self.display = kwargs.get('display', None) + self.origin = kwargs.get('origin', None) + + +class ResourceOperationDisplay(msrest.serialization.Model): + """Display of the operation. + + :param provider: The resource provider name. + :type provider: str + :param resource: The resource name. + :type resource: str + :param operation: The operation. + :type operation: str + :param description: The description of the operation. + :type description: str + """ + + _attribute_map = { + 'provider': {'key': 'provider', 'type': 'str'}, + 'resource': {'key': 'resource', 'type': 'str'}, + 'operation': {'key': 'operation', 'type': 'str'}, + 'description': {'key': 'description', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(ResourceOperationDisplay, self).__init__(**kwargs) + self.provider = kwargs.get('provider', None) + self.resource = kwargs.get('resource', None) + self.operation = kwargs.get('operation', None) + self.description = kwargs.get('description', None) + + +class ServiceAuthConfiguration(msrest.serialization.Model): + """Global service auth configuration properties. These are the data-plane authorization keys and are used if a service doesn't define it's own. + + All required parameters must be populated in order to send to Azure. + + :param primary_auth_key_hash: Required. The primary auth key hash. This is not returned in + response of GET/PUT on the resource.. To see this please call listKeys API. + :type primary_auth_key_hash: str + :param secondary_auth_key_hash: Required. The secondary auth key hash. This is not returned in + response of GET/PUT on the resource.. To see this please call listKeys API. + :type secondary_auth_key_hash: str + """ + + _validation = { + 'primary_auth_key_hash': {'required': True}, + 'secondary_auth_key_hash': {'required': True}, + } + + _attribute_map = { + 'primary_auth_key_hash': {'key': 'primaryAuthKeyHash', 'type': 'str'}, + 'secondary_auth_key_hash': {'key': 'secondaryAuthKeyHash', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(ServiceAuthConfiguration, self).__init__(**kwargs) + self.primary_auth_key_hash = kwargs['primary_auth_key_hash'] + self.secondary_auth_key_hash = kwargs['secondary_auth_key_hash'] + + +class ServicePrincipalProperties(msrest.serialization.Model): + """The Azure service principal used by Kubernetes for configuring load balancers. + + All required parameters must be populated in order to send to Azure. + + :param client_id: Required. The service principal client ID. + :type client_id: str + :param secret: Required. The service principal secret. This is not returned in response of + GET/PUT on the resource. To see this please call listKeys. + :type secret: str + """ + + _validation = { + 'client_id': {'required': True}, + 'secret': {'required': True}, + } + + _attribute_map = { + 'client_id': {'key': 'clientId', 'type': 'str'}, + 'secret': {'key': 'secret', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(ServicePrincipalProperties, self).__init__(**kwargs) + self.client_id = kwargs['client_id'] + self.secret = kwargs['secret'] + + +class SslConfiguration(msrest.serialization.Model): + """SSL configuration. If configured data-plane calls to user services will be exposed over SSL only. + + :param status: SSL status. Allowed values are Enabled and Disabled. Possible values include: + "Enabled", "Disabled". + :type status: str or ~azure.mgmt.machinelearningcompute.models.Status + :param cert: The SSL cert data in PEM format. + :type cert: str + :param key: The SSL key data in PEM format. This is not returned in response of GET/PUT on the + resource. To see this please call listKeys API. + :type key: str + :param cname: The CName of the certificate. + :type cname: str + """ + + _attribute_map = { + 'status': {'key': 'status', 'type': 'str'}, + 'cert': {'key': 'cert', 'type': 'str'}, + 'key': {'key': 'key', 'type': 'str'}, + 'cname': {'key': 'cname', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(SslConfiguration, self).__init__(**kwargs) + self.status = kwargs.get('status', None) + self.cert = kwargs.get('cert', None) + self.key = kwargs.get('key', None) + self.cname = kwargs.get('cname', None) + + +class StorageAccountCredentials(msrest.serialization.Model): + """Access information for the storage account. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar resource_id: The ARM resource ID of the storage account. + :vartype resource_id: str + :ivar primary_key: The primary key of the storage account. + :vartype primary_key: str + :ivar secondary_key: The secondary key of the storage account. + :vartype secondary_key: str + """ + + _validation = { + 'resource_id': {'readonly': True}, + 'primary_key': {'readonly': True}, + 'secondary_key': {'readonly': True}, + } + + _attribute_map = { + 'resource_id': {'key': 'resourceId', 'type': 'str'}, + 'primary_key': {'key': 'primaryKey', 'type': 'str'}, + 'secondary_key': {'key': 'secondaryKey', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(StorageAccountCredentials, self).__init__(**kwargs) + self.resource_id = None + self.primary_key = None + self.secondary_key = None + + +class StorageAccountProperties(msrest.serialization.Model): + """Properties of Storage Account. + + :param resource_id: ARM resource ID of the Azure Storage Account to store CLI specific files. + If not provided one will be created. This cannot be changed once the cluster is created. + :type resource_id: str + """ + + _attribute_map = { + 'resource_id': {'key': 'resourceId', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(StorageAccountProperties, self).__init__(**kwargs) + self.resource_id = kwargs.get('resource_id', None) + + +class SystemService(msrest.serialization.Model): + """Information about a system service deployed in the cluster. + + Variables are only populated by the server, and will be ignored when sending a request. + + All required parameters must be populated in order to send to Azure. + + :param system_service_type: Required. The system service type. Possible values include: "None", + "ScoringFrontEnd", "BatchFrontEnd". + :type system_service_type: str or ~azure.mgmt.machinelearningcompute.models.SystemServiceType + :ivar public_ip_address: The public IP address of the system service. + :vartype public_ip_address: str + :ivar version: The state of the system service. + :vartype version: str + """ + + _validation = { + 'system_service_type': {'required': True}, + 'public_ip_address': {'readonly': True}, + 'version': {'readonly': True}, + } + + _attribute_map = { + 'system_service_type': {'key': 'systemServiceType', 'type': 'str'}, + 'public_ip_address': {'key': 'publicIpAddress', 'type': 'str'}, + 'version': {'key': 'version', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(SystemService, self).__init__(**kwargs) + self.system_service_type = kwargs['system_service_type'] + self.public_ip_address = None + self.version = None + + +class UpdateSystemServicesResponse(msrest.serialization.Model): + """Response of the update system services API. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar update_status: Update status. Possible values include: "Unknown", "Updating", "Creating", + "Deleting", "Succeeded", "Failed", "Canceled". + :vartype update_status: str or ~azure.mgmt.machinelearningcompute.models.OperationStatus + :ivar update_started_on: The date and time when the last system services update was started. + :vartype update_started_on: ~datetime.datetime + :ivar update_completed_on: The date and time when the last system services update completed. + :vartype update_completed_on: ~datetime.datetime + """ + + _validation = { + 'update_status': {'readonly': True}, + 'update_started_on': {'readonly': True}, + 'update_completed_on': {'readonly': True}, + } + + _attribute_map = { + 'update_status': {'key': 'updateStatus', 'type': 'str'}, + 'update_started_on': {'key': 'updateStartedOn', 'type': 'iso-8601'}, + 'update_completed_on': {'key': 'updateCompletedOn', 'type': 'iso-8601'}, + } + + def __init__( + self, + **kwargs + ): + super(UpdateSystemServicesResponse, self).__init__(**kwargs) + self.update_status = None + self.update_started_on = None + self.update_completed_on = None diff --git a/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/models/_models_py3.py b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/models/_models_py3.py new file mode 100644 index 000000000000..ce6fe4b0b556 --- /dev/null +++ b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/models/_models_py3.py @@ -0,0 +1,1046 @@ +# 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 typing import Dict, List, Optional, Union + +from azure.core.exceptions import HttpResponseError +import msrest.serialization + +from ._machine_learning_compute_management_client_enums import * + + +class AcsClusterProperties(msrest.serialization.Model): + """Information about the container service backing the cluster. + + Variables are only populated by the server, and will be ignored when sending a request. + + All required parameters must be populated in order to send to Azure. + + :ivar cluster_fqdn: The FQDN of the cluster. + :vartype cluster_fqdn: str + :param orchestrator_type: Required. Type of orchestrator. It cannot be changed once the cluster + is created. Possible values include: "Kubernetes", "None". + :type orchestrator_type: str or ~azure.mgmt.machinelearningcompute.models.OrchestratorType + :param orchestrator_properties: Orchestrator specific properties. + :type orchestrator_properties: + ~azure.mgmt.machinelearningcompute.models.KubernetesClusterProperties + :param system_services: The system services deployed to the cluster. + :type system_services: list[~azure.mgmt.machinelearningcompute.models.SystemService] + :param master_count: The number of master nodes in the container service. + :type master_count: int + :param agent_count: The number of agent nodes in the Container Service. This can be changed to + scale the cluster. + :type agent_count: int + :param agent_vm_size: The Azure VM size of the agent VM nodes. This cannot be changed once the + cluster is created. This list is non exhaustive; refer to + https://docs.microsoft.com/en-us/azure/virtual-machines/windows/sizes for the possible VM + sizes. Possible values include: "Standard_A0", "Standard_A1", "Standard_A2", "Standard_A3", + "Standard_A4", "Standard_A5", "Standard_A6", "Standard_A7", "Standard_A8", "Standard_A9", + "Standard_A10", "Standard_A11", "Standard_D1", "Standard_D2", "Standard_D3", "Standard_D4", + "Standard_D11", "Standard_D12", "Standard_D13", "Standard_D14", "Standard_D1_v2", + "Standard_D2_v2", "Standard_D3_v2", "Standard_D4_v2", "Standard_D5_v2", "Standard_D11_v2", + "Standard_D12_v2", "Standard_D13_v2", "Standard_D14_v2", "Standard_G1", "Standard_G2", + "Standard_G3", "Standard_G4", "Standard_G5", "Standard_DS1", "Standard_DS2", "Standard_DS3", + "Standard_DS4", "Standard_DS11", "Standard_DS12", "Standard_DS13", "Standard_DS14", + "Standard_GS1", "Standard_GS2", "Standard_GS3", "Standard_GS4", "Standard_GS5". Default value: + "Standard_D3_v2". + :type agent_vm_size: str or ~azure.mgmt.machinelearningcompute.models.AgentVMSizeTypes + """ + + _validation = { + 'cluster_fqdn': {'readonly': True}, + 'orchestrator_type': {'required': True}, + 'master_count': {'maximum': 5, 'minimum': 1}, + 'agent_count': {'maximum': 100, 'minimum': 1}, + } + + _attribute_map = { + 'cluster_fqdn': {'key': 'clusterFqdn', 'type': 'str'}, + 'orchestrator_type': {'key': 'orchestratorType', 'type': 'str'}, + 'orchestrator_properties': {'key': 'orchestratorProperties', 'type': 'KubernetesClusterProperties'}, + 'system_services': {'key': 'systemServices', 'type': '[SystemService]'}, + 'master_count': {'key': 'masterCount', 'type': 'int'}, + 'agent_count': {'key': 'agentCount', 'type': 'int'}, + 'agent_vm_size': {'key': 'agentVmSize', 'type': 'str'}, + } + + def __init__( + self, + *, + orchestrator_type: Union[str, "OrchestratorType"], + orchestrator_properties: Optional["KubernetesClusterProperties"] = None, + system_services: Optional[List["SystemService"]] = None, + master_count: Optional[int] = 1, + agent_count: Optional[int] = 2, + agent_vm_size: Optional[Union[str, "AgentVMSizeTypes"]] = "Standard_D3_v2", + **kwargs + ): + super(AcsClusterProperties, self).__init__(**kwargs) + self.cluster_fqdn = None + self.orchestrator_type = orchestrator_type + self.orchestrator_properties = orchestrator_properties + self.system_services = system_services + self.master_count = master_count + self.agent_count = agent_count + self.agent_vm_size = agent_vm_size + + +class AppInsightsCredentials(msrest.serialization.Model): + """AppInsights credentials. + + :param app_id: The AppInsights application ID. + :type app_id: str + :param instrumentation_key: The AppInsights instrumentation key. This is not returned in + response of GET/PUT on the resource. To see this please call listKeys API. + :type instrumentation_key: str + """ + + _attribute_map = { + 'app_id': {'key': 'appId', 'type': 'str'}, + 'instrumentation_key': {'key': 'instrumentationKey', 'type': 'str'}, + } + + def __init__( + self, + *, + app_id: Optional[str] = None, + instrumentation_key: Optional[str] = None, + **kwargs + ): + super(AppInsightsCredentials, self).__init__(**kwargs) + self.app_id = app_id + self.instrumentation_key = instrumentation_key + + +class AppInsightsProperties(msrest.serialization.Model): + """Properties of App Insights. + + :param resource_id: ARM resource ID of the App Insights. + :type resource_id: str + """ + + _attribute_map = { + 'resource_id': {'key': 'resourceId', 'type': 'str'}, + } + + def __init__( + self, + *, + resource_id: Optional[str] = None, + **kwargs + ): + super(AppInsightsProperties, self).__init__(**kwargs) + self.resource_id = resource_id + + +class AutoScaleConfiguration(msrest.serialization.Model): + """AutoScale configuration properties. + + :param status: If auto-scale is enabled for all services. Each service can turn it off + individually. Possible values include: "Enabled", "Disabled". + :type status: str or ~azure.mgmt.machinelearningcompute.models.Status + :param min_replicas: The minimum number of replicas for each service. + :type min_replicas: int + :param max_replicas: The maximum number of replicas for each service. + :type max_replicas: int + :param target_utilization: The target utilization. + :type target_utilization: float + :param refresh_period_in_seconds: Refresh period in seconds. + :type refresh_period_in_seconds: int + """ + + _validation = { + 'min_replicas': {'minimum': 1}, + 'max_replicas': {'minimum': 1}, + } + + _attribute_map = { + 'status': {'key': 'status', 'type': 'str'}, + 'min_replicas': {'key': 'minReplicas', 'type': 'int'}, + 'max_replicas': {'key': 'maxReplicas', 'type': 'int'}, + 'target_utilization': {'key': 'targetUtilization', 'type': 'float'}, + 'refresh_period_in_seconds': {'key': 'refreshPeriodInSeconds', 'type': 'int'}, + } + + def __init__( + self, + *, + status: Optional[Union[str, "Status"]] = None, + min_replicas: Optional[int] = 1, + max_replicas: Optional[int] = 100, + target_utilization: Optional[float] = None, + refresh_period_in_seconds: Optional[int] = None, + **kwargs + ): + super(AutoScaleConfiguration, self).__init__(**kwargs) + self.status = status + self.min_replicas = min_replicas + self.max_replicas = max_replicas + self.target_utilization = target_utilization + self.refresh_period_in_seconds = refresh_period_in_seconds + + +class AvailableOperations(msrest.serialization.Model): + """Available operation list. + + :param value: An array of available operations. + :type value: list[~azure.mgmt.machinelearningcompute.models.ResourceOperation] + """ + + _attribute_map = { + 'value': {'key': 'value', 'type': '[ResourceOperation]'}, + } + + def __init__( + self, + *, + value: Optional[List["ResourceOperation"]] = None, + **kwargs + ): + super(AvailableOperations, self).__init__(**kwargs) + self.value = value + + +class CheckSystemServicesUpdatesAvailableResponse(msrest.serialization.Model): + """Information about updates available for system services in a cluster. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar updates_available: Yes if updates are available for the system services, No if not. + Possible values include: "Yes", "No". + :vartype updates_available: str or ~azure.mgmt.machinelearningcompute.models.UpdatesAvailable + """ + + _validation = { + 'updates_available': {'readonly': True}, + } + + _attribute_map = { + 'updates_available': {'key': 'updatesAvailable', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(CheckSystemServicesUpdatesAvailableResponse, self).__init__(**kwargs) + self.updates_available = None + + +class ContainerRegistryCredentials(msrest.serialization.Model): + """Information about the Azure Container Registry which contains the images deployed to the cluster. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar login_server: The ACR login server name. User name is the first part of the FQDN. + :vartype login_server: str + :ivar password: The ACR primary password. + :vartype password: str + :ivar password2: The ACR secondary password. + :vartype password2: str + :ivar username: The ACR login username. + :vartype username: str + """ + + _validation = { + 'login_server': {'readonly': True}, + 'password': {'readonly': True}, + 'password2': {'readonly': True}, + 'username': {'readonly': True}, + } + + _attribute_map = { + 'login_server': {'key': 'loginServer', 'type': 'str'}, + 'password': {'key': 'password', 'type': 'str'}, + 'password2': {'key': 'password2', 'type': 'str'}, + 'username': {'key': 'username', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(ContainerRegistryCredentials, self).__init__(**kwargs) + self.login_server = None + self.password = None + self.password2 = None + self.username = None + + +class ContainerRegistryProperties(msrest.serialization.Model): + """Properties of Azure Container Registry. + + :param resource_id: ARM resource ID of the Azure Container Registry used to store Docker images + for web services in the cluster. If not provided one will be created. This cannot be changed + once the cluster is created. + :type resource_id: str + """ + + _attribute_map = { + 'resource_id': {'key': 'resourceId', 'type': 'str'}, + } + + def __init__( + self, + *, + resource_id: Optional[str] = None, + **kwargs + ): + super(ContainerRegistryProperties, self).__init__(**kwargs) + self.resource_id = resource_id + + +class ContainerServiceCredentials(msrest.serialization.Model): + """Information about the Azure Container Registry which contains the images deployed to the cluster. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar acs_kube_config: The ACS kube config file. + :vartype acs_kube_config: str + :ivar service_principal_configuration: Service principal configuration used by Kubernetes. + :vartype service_principal_configuration: + ~azure.mgmt.machinelearningcompute.models.ServicePrincipalProperties + :ivar image_pull_secret_name: The ACR image pull secret name which was created in Kubernetes. + :vartype image_pull_secret_name: str + """ + + _validation = { + 'acs_kube_config': {'readonly': True}, + 'service_principal_configuration': {'readonly': True}, + 'image_pull_secret_name': {'readonly': True}, + } + + _attribute_map = { + 'acs_kube_config': {'key': 'acsKubeConfig', 'type': 'str'}, + 'service_principal_configuration': {'key': 'servicePrincipalConfiguration', 'type': 'ServicePrincipalProperties'}, + 'image_pull_secret_name': {'key': 'imagePullSecretName', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(ContainerServiceCredentials, self).__init__(**kwargs) + self.acs_kube_config = None + self.service_principal_configuration = None + self.image_pull_secret_name = None + + +class ErrorDetail(msrest.serialization.Model): + """Error detail information. + + All required parameters must be populated in order to send to Azure. + + :param code: Required. Error code. + :type code: str + :param message: Required. Error message. + :type message: str + """ + + _validation = { + 'code': {'required': True}, + 'message': {'required': True}, + } + + _attribute_map = { + 'code': {'key': 'code', 'type': 'str'}, + 'message': {'key': 'message', 'type': 'str'}, + } + + def __init__( + self, + *, + code: str, + message: str, + **kwargs + ): + super(ErrorDetail, self).__init__(**kwargs) + self.code = code + self.message = message + + +class ErrorResponse(msrest.serialization.Model): + """Error response information. + + All required parameters must be populated in order to send to Azure. + + :param code: Required. Error code. + :type code: str + :param message: Required. Error message. + :type message: str + :param details: An array of error detail objects. + :type details: list[~azure.mgmt.machinelearningcompute.models.ErrorDetail] + """ + + _validation = { + 'code': {'required': True}, + 'message': {'required': True}, + } + + _attribute_map = { + 'code': {'key': 'code', 'type': 'str'}, + 'message': {'key': 'message', 'type': 'str'}, + 'details': {'key': 'details', 'type': '[ErrorDetail]'}, + } + + def __init__( + self, + *, + code: str, + message: str, + details: Optional[List["ErrorDetail"]] = None, + **kwargs + ): + super(ErrorResponse, self).__init__(**kwargs) + self.code = code + self.message = message + self.details = details + + +class ErrorResponseWrapper(msrest.serialization.Model): + """Wrapper for error response to follow ARM guidelines. + + :param error: The error response. + :type error: ~azure.mgmt.machinelearningcompute.models.ErrorResponse + """ + + _attribute_map = { + 'error': {'key': 'error', 'type': 'ErrorResponse'}, + } + + def __init__( + self, + *, + error: Optional["ErrorResponse"] = None, + **kwargs + ): + super(ErrorResponseWrapper, self).__init__(**kwargs) + self.error = error + + +class GlobalServiceConfiguration(msrest.serialization.Model): + """Global configuration for services in the cluster. + + :param additional_properties: Unmatched properties from the message are deserialized to this + collection. + :type additional_properties: dict[str, str] + :param etag: The configuration ETag for updates. + :type etag: str + :param ssl: The SSL configuration properties. + :type ssl: ~azure.mgmt.machinelearningcompute.models.SslConfiguration + :param service_auth: Optional global authorization keys for all user services deployed in + cluster. These are used if the service does not have auth keys. + :type service_auth: ~azure.mgmt.machinelearningcompute.models.ServiceAuthConfiguration + :param auto_scale: The auto-scale configuration. + :type auto_scale: ~azure.mgmt.machinelearningcompute.models.AutoScaleConfiguration + """ + + _attribute_map = { + 'additional_properties': {'key': '', 'type': '{str}'}, + 'etag': {'key': 'etag', 'type': 'str'}, + 'ssl': {'key': 'ssl', 'type': 'SslConfiguration'}, + 'service_auth': {'key': 'serviceAuth', 'type': 'ServiceAuthConfiguration'}, + 'auto_scale': {'key': 'autoScale', 'type': 'AutoScaleConfiguration'}, + } + + def __init__( + self, + *, + additional_properties: Optional[Dict[str, str]] = None, + etag: Optional[str] = None, + ssl: Optional["SslConfiguration"] = None, + service_auth: Optional["ServiceAuthConfiguration"] = None, + auto_scale: Optional["AutoScaleConfiguration"] = None, + **kwargs + ): + super(GlobalServiceConfiguration, self).__init__(**kwargs) + self.additional_properties = additional_properties + self.etag = etag + self.ssl = ssl + self.service_auth = service_auth + self.auto_scale = auto_scale + + +class KubernetesClusterProperties(msrest.serialization.Model): + """Kubernetes cluster specific properties. + + :param service_principal: The Azure Service Principal used by Kubernetes. + :type service_principal: ~azure.mgmt.machinelearningcompute.models.ServicePrincipalProperties + """ + + _attribute_map = { + 'service_principal': {'key': 'servicePrincipal', 'type': 'ServicePrincipalProperties'}, + } + + def __init__( + self, + *, + service_principal: Optional["ServicePrincipalProperties"] = None, + **kwargs + ): + super(KubernetesClusterProperties, self).__init__(**kwargs) + self.service_principal = service_principal + + +class Resource(msrest.serialization.Model): + """Azure resource. + + Variables are only populated by the server, and will be ignored when sending a request. + + All required parameters must be populated in order to send to Azure. + + :ivar id: Specifies the resource ID. + :vartype id: str + :ivar name: Specifies the name of the resource. + :vartype name: str + :param location: Required. Specifies the location of the resource. + :type location: str + :ivar type: Specifies the type of the resource. + :vartype type: str + :param tags: A set of tags. Contains resource tags defined as key/value pairs. + :type tags: dict[str, str] + """ + + _validation = { + 'id': {'readonly': True}, + 'name': {'readonly': True}, + 'location': {'required': True}, + 'type': {'readonly': True}, + } + + _attribute_map = { + 'id': {'key': 'id', 'type': 'str'}, + 'name': {'key': 'name', 'type': 'str'}, + 'location': {'key': 'location', 'type': 'str'}, + 'type': {'key': 'type', 'type': 'str'}, + 'tags': {'key': 'tags', 'type': '{str}'}, + } + + def __init__( + self, + *, + location: str, + tags: Optional[Dict[str, str]] = None, + **kwargs + ): + super(Resource, self).__init__(**kwargs) + self.id = None + self.name = None + self.location = location + self.type = None + self.tags = tags + + +class OperationalizationCluster(Resource): + """Instance of an Azure ML Operationalization Cluster resource. + + Variables are only populated by the server, and will be ignored when sending a request. + + All required parameters must be populated in order to send to Azure. + + :ivar id: Specifies the resource ID. + :vartype id: str + :ivar name: Specifies the name of the resource. + :vartype name: str + :param location: Required. Specifies the location of the resource. + :type location: str + :ivar type: Specifies the type of the resource. + :vartype type: str + :param tags: A set of tags. Contains resource tags defined as key/value pairs. + :type tags: dict[str, str] + :param description: The description of the cluster. + :type description: str + :ivar created_on: The date and time when the cluster was created. + :vartype created_on: ~datetime.datetime + :ivar modified_on: The date and time when the cluster was last modified. + :vartype modified_on: ~datetime.datetime + :ivar provisioning_state: The provision state of the cluster. Valid values are Unknown, + Updating, Provisioning, Succeeded, and Failed. Possible values include: "Unknown", "Updating", + "Creating", "Deleting", "Succeeded", "Failed", "Canceled". + :vartype provisioning_state: str or ~azure.mgmt.machinelearningcompute.models.OperationStatus + :ivar provisioning_errors: List of provisioning errors reported by the resource provider. + :vartype provisioning_errors: + list[~azure.mgmt.machinelearningcompute.models.ErrorResponseWrapper] + :param cluster_type: The cluster type. Possible values include: "ACS", "Local". + :type cluster_type: str or ~azure.mgmt.machinelearningcompute.models.ClusterType + :param storage_account: Storage Account properties. + :type storage_account: ~azure.mgmt.machinelearningcompute.models.StorageAccountProperties + :param container_registry: Container Registry properties. + :type container_registry: ~azure.mgmt.machinelearningcompute.models.ContainerRegistryProperties + :param container_service: Parameters for the Azure Container Service cluster. + :type container_service: ~azure.mgmt.machinelearningcompute.models.AcsClusterProperties + :param app_insights: AppInsights configuration. + :type app_insights: ~azure.mgmt.machinelearningcompute.models.AppInsightsProperties + :param global_service_configuration: Contains global configuration for the web services in the + cluster. + :type global_service_configuration: + ~azure.mgmt.machinelearningcompute.models.GlobalServiceConfiguration + """ + + _validation = { + 'id': {'readonly': True}, + 'name': {'readonly': True}, + 'location': {'required': True}, + 'type': {'readonly': True}, + 'created_on': {'readonly': True}, + 'modified_on': {'readonly': True}, + 'provisioning_state': {'readonly': True}, + 'provisioning_errors': {'readonly': True}, + } + + _attribute_map = { + 'id': {'key': 'id', 'type': 'str'}, + 'name': {'key': 'name', 'type': 'str'}, + 'location': {'key': 'location', 'type': 'str'}, + 'type': {'key': 'type', 'type': 'str'}, + 'tags': {'key': 'tags', 'type': '{str}'}, + 'description': {'key': 'properties.description', 'type': 'str'}, + 'created_on': {'key': 'properties.createdOn', 'type': 'iso-8601'}, + 'modified_on': {'key': 'properties.modifiedOn', 'type': 'iso-8601'}, + 'provisioning_state': {'key': 'properties.provisioningState', 'type': 'str'}, + 'provisioning_errors': {'key': 'properties.provisioningErrors', 'type': '[ErrorResponseWrapper]'}, + 'cluster_type': {'key': 'properties.clusterType', 'type': 'str'}, + 'storage_account': {'key': 'properties.storageAccount', 'type': 'StorageAccountProperties'}, + 'container_registry': {'key': 'properties.containerRegistry', 'type': 'ContainerRegistryProperties'}, + 'container_service': {'key': 'properties.containerService', 'type': 'AcsClusterProperties'}, + 'app_insights': {'key': 'properties.appInsights', 'type': 'AppInsightsProperties'}, + 'global_service_configuration': {'key': 'properties.globalServiceConfiguration', 'type': 'GlobalServiceConfiguration'}, + } + + def __init__( + self, + *, + location: str, + tags: Optional[Dict[str, str]] = None, + description: Optional[str] = None, + cluster_type: Optional[Union[str, "ClusterType"]] = None, + storage_account: Optional["StorageAccountProperties"] = None, + container_registry: Optional["ContainerRegistryProperties"] = None, + container_service: Optional["AcsClusterProperties"] = None, + app_insights: Optional["AppInsightsProperties"] = None, + global_service_configuration: Optional["GlobalServiceConfiguration"] = None, + **kwargs + ): + super(OperationalizationCluster, self).__init__(location=location, tags=tags, **kwargs) + self.description = description + self.created_on = None + self.modified_on = None + self.provisioning_state = None + self.provisioning_errors = None + self.cluster_type = cluster_type + self.storage_account = storage_account + self.container_registry = container_registry + self.container_service = container_service + self.app_insights = app_insights + self.global_service_configuration = global_service_configuration + + +class OperationalizationClusterCredentials(msrest.serialization.Model): + """Credentials to resources in the cluster. + + :param storage_account: Credentials for the Storage Account. + :type storage_account: ~azure.mgmt.machinelearningcompute.models.StorageAccountCredentials + :param container_registry: Credentials for Azure Container Registry. + :type container_registry: + ~azure.mgmt.machinelearningcompute.models.ContainerRegistryCredentials + :param container_service: Credentials for Azure Container Service. + :type container_service: ~azure.mgmt.machinelearningcompute.models.ContainerServiceCredentials + :param app_insights: Credentials for Azure AppInsights. + :type app_insights: ~azure.mgmt.machinelearningcompute.models.AppInsightsCredentials + :param service_auth_configuration: Global authorization keys for all user services deployed in + cluster. These are used if the service does not have auth keys. + :type service_auth_configuration: + ~azure.mgmt.machinelearningcompute.models.ServiceAuthConfiguration + :param ssl_configuration: The SSL configuration for the services. + :type ssl_configuration: ~azure.mgmt.machinelearningcompute.models.SslConfiguration + """ + + _attribute_map = { + 'storage_account': {'key': 'storageAccount', 'type': 'StorageAccountCredentials'}, + 'container_registry': {'key': 'containerRegistry', 'type': 'ContainerRegistryCredentials'}, + 'container_service': {'key': 'containerService', 'type': 'ContainerServiceCredentials'}, + 'app_insights': {'key': 'appInsights', 'type': 'AppInsightsCredentials'}, + 'service_auth_configuration': {'key': 'serviceAuthConfiguration', 'type': 'ServiceAuthConfiguration'}, + 'ssl_configuration': {'key': 'sslConfiguration', 'type': 'SslConfiguration'}, + } + + def __init__( + self, + *, + storage_account: Optional["StorageAccountCredentials"] = None, + container_registry: Optional["ContainerRegistryCredentials"] = None, + container_service: Optional["ContainerServiceCredentials"] = None, + app_insights: Optional["AppInsightsCredentials"] = None, + service_auth_configuration: Optional["ServiceAuthConfiguration"] = None, + ssl_configuration: Optional["SslConfiguration"] = None, + **kwargs + ): + super(OperationalizationClusterCredentials, self).__init__(**kwargs) + self.storage_account = storage_account + self.container_registry = container_registry + self.container_service = container_service + self.app_insights = app_insights + self.service_auth_configuration = service_auth_configuration + self.ssl_configuration = ssl_configuration + + +class OperationalizationClusterUpdateParameters(msrest.serialization.Model): + """Parameters for PATCH operation on an operationalization cluster. + + :param tags: A set of tags. Gets or sets a list of key value pairs that describe the resource. + These tags can be used in viewing and grouping this resource (across resource groups). A + maximum of 15 tags can be provided for a resource. Each tag must have a key no greater in + length than 128 characters and a value no greater in length than 256 characters. + :type tags: dict[str, str] + """ + + _attribute_map = { + 'tags': {'key': 'tags', 'type': '{str}'}, + } + + def __init__( + self, + *, + tags: Optional[Dict[str, str]] = None, + **kwargs + ): + super(OperationalizationClusterUpdateParameters, self).__init__(**kwargs) + self.tags = tags + + +class PaginatedOperationalizationClustersList(msrest.serialization.Model): + """Paginated list of operationalization clusters. + + :param value: An array of cluster objects. + :type value: list[~azure.mgmt.machinelearningcompute.models.OperationalizationCluster] + :param next_link: A continuation link (absolute URI) to the next page of results in the list. + :type next_link: str + """ + + _attribute_map = { + 'value': {'key': 'value', 'type': '[OperationalizationCluster]'}, + 'next_link': {'key': 'nextLink', 'type': 'str'}, + } + + def __init__( + self, + *, + value: Optional[List["OperationalizationCluster"]] = None, + next_link: Optional[str] = None, + **kwargs + ): + super(PaginatedOperationalizationClustersList, self).__init__(**kwargs) + self.value = value + self.next_link = next_link + + +class ResourceOperation(msrest.serialization.Model): + """Resource operation. + + :param name: Name of this operation. + :type name: str + :param display: Display of the operation. + :type display: ~azure.mgmt.machinelearningcompute.models.ResourceOperationDisplay + :param origin: The operation origin. + :type origin: str + """ + + _attribute_map = { + 'name': {'key': 'name', 'type': 'str'}, + 'display': {'key': 'display', 'type': 'ResourceOperationDisplay'}, + 'origin': {'key': 'origin', 'type': 'str'}, + } + + def __init__( + self, + *, + name: Optional[str] = None, + display: Optional["ResourceOperationDisplay"] = None, + origin: Optional[str] = None, + **kwargs + ): + super(ResourceOperation, self).__init__(**kwargs) + self.name = name + self.display = display + self.origin = origin + + +class ResourceOperationDisplay(msrest.serialization.Model): + """Display of the operation. + + :param provider: The resource provider name. + :type provider: str + :param resource: The resource name. + :type resource: str + :param operation: The operation. + :type operation: str + :param description: The description of the operation. + :type description: str + """ + + _attribute_map = { + 'provider': {'key': 'provider', 'type': 'str'}, + 'resource': {'key': 'resource', 'type': 'str'}, + 'operation': {'key': 'operation', 'type': 'str'}, + 'description': {'key': 'description', 'type': 'str'}, + } + + def __init__( + self, + *, + provider: Optional[str] = None, + resource: Optional[str] = None, + operation: Optional[str] = None, + description: Optional[str] = None, + **kwargs + ): + super(ResourceOperationDisplay, self).__init__(**kwargs) + self.provider = provider + self.resource = resource + self.operation = operation + self.description = description + + +class ServiceAuthConfiguration(msrest.serialization.Model): + """Global service auth configuration properties. These are the data-plane authorization keys and are used if a service doesn't define it's own. + + All required parameters must be populated in order to send to Azure. + + :param primary_auth_key_hash: Required. The primary auth key hash. This is not returned in + response of GET/PUT on the resource.. To see this please call listKeys API. + :type primary_auth_key_hash: str + :param secondary_auth_key_hash: Required. The secondary auth key hash. This is not returned in + response of GET/PUT on the resource.. To see this please call listKeys API. + :type secondary_auth_key_hash: str + """ + + _validation = { + 'primary_auth_key_hash': {'required': True}, + 'secondary_auth_key_hash': {'required': True}, + } + + _attribute_map = { + 'primary_auth_key_hash': {'key': 'primaryAuthKeyHash', 'type': 'str'}, + 'secondary_auth_key_hash': {'key': 'secondaryAuthKeyHash', 'type': 'str'}, + } + + def __init__( + self, + *, + primary_auth_key_hash: str, + secondary_auth_key_hash: str, + **kwargs + ): + super(ServiceAuthConfiguration, self).__init__(**kwargs) + self.primary_auth_key_hash = primary_auth_key_hash + self.secondary_auth_key_hash = secondary_auth_key_hash + + +class ServicePrincipalProperties(msrest.serialization.Model): + """The Azure service principal used by Kubernetes for configuring load balancers. + + All required parameters must be populated in order to send to Azure. + + :param client_id: Required. The service principal client ID. + :type client_id: str + :param secret: Required. The service principal secret. This is not returned in response of + GET/PUT on the resource. To see this please call listKeys. + :type secret: str + """ + + _validation = { + 'client_id': {'required': True}, + 'secret': {'required': True}, + } + + _attribute_map = { + 'client_id': {'key': 'clientId', 'type': 'str'}, + 'secret': {'key': 'secret', 'type': 'str'}, + } + + def __init__( + self, + *, + client_id: str, + secret: str, + **kwargs + ): + super(ServicePrincipalProperties, self).__init__(**kwargs) + self.client_id = client_id + self.secret = secret + + +class SslConfiguration(msrest.serialization.Model): + """SSL configuration. If configured data-plane calls to user services will be exposed over SSL only. + + :param status: SSL status. Allowed values are Enabled and Disabled. Possible values include: + "Enabled", "Disabled". + :type status: str or ~azure.mgmt.machinelearningcompute.models.Status + :param cert: The SSL cert data in PEM format. + :type cert: str + :param key: The SSL key data in PEM format. This is not returned in response of GET/PUT on the + resource. To see this please call listKeys API. + :type key: str + :param cname: The CName of the certificate. + :type cname: str + """ + + _attribute_map = { + 'status': {'key': 'status', 'type': 'str'}, + 'cert': {'key': 'cert', 'type': 'str'}, + 'key': {'key': 'key', 'type': 'str'}, + 'cname': {'key': 'cname', 'type': 'str'}, + } + + def __init__( + self, + *, + status: Optional[Union[str, "Status"]] = None, + cert: Optional[str] = None, + key: Optional[str] = None, + cname: Optional[str] = None, + **kwargs + ): + super(SslConfiguration, self).__init__(**kwargs) + self.status = status + self.cert = cert + self.key = key + self.cname = cname + + +class StorageAccountCredentials(msrest.serialization.Model): + """Access information for the storage account. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar resource_id: The ARM resource ID of the storage account. + :vartype resource_id: str + :ivar primary_key: The primary key of the storage account. + :vartype primary_key: str + :ivar secondary_key: The secondary key of the storage account. + :vartype secondary_key: str + """ + + _validation = { + 'resource_id': {'readonly': True}, + 'primary_key': {'readonly': True}, + 'secondary_key': {'readonly': True}, + } + + _attribute_map = { + 'resource_id': {'key': 'resourceId', 'type': 'str'}, + 'primary_key': {'key': 'primaryKey', 'type': 'str'}, + 'secondary_key': {'key': 'secondaryKey', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(StorageAccountCredentials, self).__init__(**kwargs) + self.resource_id = None + self.primary_key = None + self.secondary_key = None + + +class StorageAccountProperties(msrest.serialization.Model): + """Properties of Storage Account. + + :param resource_id: ARM resource ID of the Azure Storage Account to store CLI specific files. + If not provided one will be created. This cannot be changed once the cluster is created. + :type resource_id: str + """ + + _attribute_map = { + 'resource_id': {'key': 'resourceId', 'type': 'str'}, + } + + def __init__( + self, + *, + resource_id: Optional[str] = None, + **kwargs + ): + super(StorageAccountProperties, self).__init__(**kwargs) + self.resource_id = resource_id + + +class SystemService(msrest.serialization.Model): + """Information about a system service deployed in the cluster. + + Variables are only populated by the server, and will be ignored when sending a request. + + All required parameters must be populated in order to send to Azure. + + :param system_service_type: Required. The system service type. Possible values include: "None", + "ScoringFrontEnd", "BatchFrontEnd". + :type system_service_type: str or ~azure.mgmt.machinelearningcompute.models.SystemServiceType + :ivar public_ip_address: The public IP address of the system service. + :vartype public_ip_address: str + :ivar version: The state of the system service. + :vartype version: str + """ + + _validation = { + 'system_service_type': {'required': True}, + 'public_ip_address': {'readonly': True}, + 'version': {'readonly': True}, + } + + _attribute_map = { + 'system_service_type': {'key': 'systemServiceType', 'type': 'str'}, + 'public_ip_address': {'key': 'publicIpAddress', 'type': 'str'}, + 'version': {'key': 'version', 'type': 'str'}, + } + + def __init__( + self, + *, + system_service_type: Union[str, "SystemServiceType"], + **kwargs + ): + super(SystemService, self).__init__(**kwargs) + self.system_service_type = system_service_type + self.public_ip_address = None + self.version = None + + +class UpdateSystemServicesResponse(msrest.serialization.Model): + """Response of the update system services API. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar update_status: Update status. Possible values include: "Unknown", "Updating", "Creating", + "Deleting", "Succeeded", "Failed", "Canceled". + :vartype update_status: str or ~azure.mgmt.machinelearningcompute.models.OperationStatus + :ivar update_started_on: The date and time when the last system services update was started. + :vartype update_started_on: ~datetime.datetime + :ivar update_completed_on: The date and time when the last system services update completed. + :vartype update_completed_on: ~datetime.datetime + """ + + _validation = { + 'update_status': {'readonly': True}, + 'update_started_on': {'readonly': True}, + 'update_completed_on': {'readonly': True}, + } + + _attribute_map = { + 'update_status': {'key': 'updateStatus', 'type': 'str'}, + 'update_started_on': {'key': 'updateStartedOn', 'type': 'iso-8601'}, + 'update_completed_on': {'key': 'updateCompletedOn', 'type': 'iso-8601'}, + } + + def __init__( + self, + **kwargs + ): + super(UpdateSystemServicesResponse, self).__init__(**kwargs) + self.update_status = None + self.update_started_on = None + self.update_completed_on = None diff --git a/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/operations/__init__.py b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/operations/__init__.py new file mode 100644 index 000000000000..2dbc2ddbdd04 --- /dev/null +++ b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/operations/__init__.py @@ -0,0 +1,15 @@ +# 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 ._operationalization_clusters_operations import OperationalizationClustersOperations +from ._machine_learning_compute_operations import MachineLearningComputeOperations + +__all__ = [ + 'OperationalizationClustersOperations', + 'MachineLearningComputeOperations', +] diff --git a/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/operations/_machine_learning_compute_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/operations/_machine_learning_compute_operations.py new file mode 100644 index 000000000000..b6bbe129c8ce --- /dev/null +++ b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/operations/_machine_learning_compute_operations.py @@ -0,0 +1,92 @@ +# 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 typing import TYPE_CHECKING +import warnings + +from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error +from azure.core.pipeline import PipelineResponse +from azure.core.pipeline.transport import HttpRequest, HttpResponse +from azure.mgmt.core.exceptions import ARMErrorFormat + +from .. import models as _models + +if TYPE_CHECKING: + # pylint: disable=unused-import,ungrouped-imports + from typing import Any, Callable, Dict, Generic, Optional, TypeVar + + T = TypeVar('T') + ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]] + +class MachineLearningComputeOperations(object): + """MachineLearningComputeOperations operations. + + You should not instantiate this class directly. Instead, you should create a Client instance that + instantiates it for you and attaches it as an attribute. + + :ivar models: Alias to model classes used in this operation group. + :type models: ~azure.mgmt.machinelearningcompute.models + :param client: Client for service requests. + :param config: Configuration of service client. + :param serializer: An object model serializer. + :param deserializer: An object model deserializer. + """ + + models = _models + + def __init__(self, client, config, serializer, deserializer): + self._client = client + self._serialize = serializer + self._deserialize = deserializer + self._config = config + + def list_available_operations( + self, + **kwargs # type: Any + ): + # type: (...) -> "_models.AvailableOperations" + """Gets all available operations. + + :keyword callable cls: A custom type or function that will be passed the direct response + :return: AvailableOperations, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningcompute.models.AvailableOperations + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.AvailableOperations"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2017-08-01-preview" + accept = "application/json" + + # Construct URL + url = self.list_available_operations.metadata['url'] # type: ignore + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + raise HttpResponseError(response=response, error_format=ARMErrorFormat) + + deserialized = self._deserialize('AvailableOperations', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + list_available_operations.metadata = {'url': '/providers/Microsoft.MachineLearningCompute/operations'} # type: ignore diff --git a/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/operations/_operationalization_clusters_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/operations/_operationalization_clusters_operations.py new file mode 100644 index 000000000000..8851e706db7a --- /dev/null +++ b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/operations/_operationalization_clusters_operations.py @@ -0,0 +1,820 @@ +# 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 typing import TYPE_CHECKING +import warnings + +from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error +from azure.core.paging import ItemPaged +from azure.core.pipeline import PipelineResponse +from azure.core.pipeline.transport import HttpRequest, HttpResponse +from azure.core.polling import LROPoller, NoPolling, PollingMethod +from azure.mgmt.core.exceptions import ARMErrorFormat +from azure.mgmt.core.polling.arm_polling import ARMPolling + +from .. import models as _models + +if TYPE_CHECKING: + # pylint: disable=unused-import,ungrouped-imports + from typing import Any, Callable, Dict, Generic, Iterable, Optional, TypeVar, Union + + T = TypeVar('T') + ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]] + +class OperationalizationClustersOperations(object): + """OperationalizationClustersOperations operations. + + You should not instantiate this class directly. Instead, you should create a Client instance that + instantiates it for you and attaches it as an attribute. + + :ivar models: Alias to model classes used in this operation group. + :type models: ~azure.mgmt.machinelearningcompute.models + :param client: Client for service requests. + :param config: Configuration of service client. + :param serializer: An object model serializer. + :param deserializer: An object model deserializer. + """ + + models = _models + + def __init__(self, client, config, serializer, deserializer): + self._client = client + self._serialize = serializer + self._deserialize = deserializer + self._config = config + + def _create_or_update_initial( + self, + resource_group_name, # type: str + cluster_name, # type: str + parameters, # type: "_models.OperationalizationCluster" + **kwargs # type: Any + ): + # type: (...) -> "_models.OperationalizationCluster" + cls = kwargs.pop('cls', None) # type: ClsType["_models.OperationalizationCluster"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2017-08-01-preview" + content_type = kwargs.pop("content_type", "application/json") + accept = "application/json" + + # Construct URL + url = self._create_or_update_initial.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\w\._\(\)]+$'), + 'clusterName': self._serialize.url("cluster_name", cluster_name, 'str', max_length=90, min_length=1, pattern=r'^[a-zA-Z][-\w\._\(\)]+[a-zA-Z0-9]$'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Content-Type'] = self._serialize.header("content_type", content_type, 'str') + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + body_content_kwargs = {} # type: Dict[str, Any] + body_content = self._serialize.body(parameters, 'OperationalizationCluster') + body_content_kwargs['content'] = body_content + request = self._client.put(url, query_parameters, header_parameters, **body_content_kwargs) + pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200, 201]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponseWrapper, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + if response.status_code == 200: + deserialized = self._deserialize('OperationalizationCluster', pipeline_response) + + if response.status_code == 201: + deserialized = self._deserialize('OperationalizationCluster', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + _create_or_update_initial.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningCompute/operationalizationClusters/{clusterName}'} # type: ignore + + def begin_create_or_update( + self, + resource_group_name, # type: str + cluster_name, # type: str + parameters, # type: "_models.OperationalizationCluster" + **kwargs # type: Any + ): + # type: (...) -> LROPoller["_models.OperationalizationCluster"] + """Create or update an operationalization cluster. + + :param resource_group_name: Name of the resource group in which the cluster is located. + :type resource_group_name: str + :param cluster_name: The name of the cluster. + :type cluster_name: str + :param parameters: Parameters supplied to create or update an Operationalization cluster. + :type parameters: ~azure.mgmt.machinelearningcompute.models.OperationalizationCluster + :keyword callable cls: A custom type or function that will be passed the direct response + :keyword str continuation_token: A continuation token to restart a poller from a saved state. + :keyword polling: Pass in True if you'd like the ARMPolling polling method, + False for no polling, or your own initialized polling object for a personal polling strategy. + :paramtype polling: bool or ~azure.core.polling.PollingMethod + :keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present. + :return: An instance of LROPoller that returns either OperationalizationCluster or the result of cls(response) + :rtype: ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningcompute.models.OperationalizationCluster] + :raises ~azure.core.exceptions.HttpResponseError: + """ + polling = kwargs.pop('polling', True) # type: Union[bool, PollingMethod] + cls = kwargs.pop('cls', None) # type: ClsType["_models.OperationalizationCluster"] + lro_delay = kwargs.pop( + 'polling_interval', + self._config.polling_interval + ) + cont_token = kwargs.pop('continuation_token', None) # type: Optional[str] + if cont_token is None: + raw_result = self._create_or_update_initial( + resource_group_name=resource_group_name, + cluster_name=cluster_name, + parameters=parameters, + cls=lambda x,y,z: x, + **kwargs + ) + + kwargs.pop('error_map', None) + kwargs.pop('content_type', None) + + def get_long_running_output(pipeline_response): + deserialized = self._deserialize('OperationalizationCluster', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + return deserialized + + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\w\._\(\)]+$'), + 'clusterName': self._serialize.url("cluster_name", cluster_name, 'str', max_length=90, min_length=1, pattern=r'^[a-zA-Z][-\w\._\(\)]+[a-zA-Z0-9]$'), + } + + if polling is True: polling_method = ARMPolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + elif polling is False: polling_method = NoPolling() + else: polling_method = polling + if cont_token: + return LROPoller.from_continuation_token( + polling_method=polling_method, + continuation_token=cont_token, + client=self._client, + deserialization_callback=get_long_running_output + ) + else: + return LROPoller(self._client, raw_result, get_long_running_output, polling_method) + begin_create_or_update.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningCompute/operationalizationClusters/{clusterName}'} # type: ignore + + def get( + self, + resource_group_name, # type: str + cluster_name, # type: str + **kwargs # type: Any + ): + # type: (...) -> "_models.OperationalizationCluster" + """Gets the operationalization cluster resource view. Note that the credentials are not returned + by this call. Call ListKeys to get them. + + :param resource_group_name: Name of the resource group in which the cluster is located. + :type resource_group_name: str + :param cluster_name: The name of the cluster. + :type cluster_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: OperationalizationCluster, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningcompute.models.OperationalizationCluster + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.OperationalizationCluster"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2017-08-01-preview" + accept = "application/json" + + # Construct URL + url = self.get.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\w\._\(\)]+$'), + 'clusterName': self._serialize.url("cluster_name", cluster_name, 'str', max_length=90, min_length=1, pattern=r'^[a-zA-Z][-\w\._\(\)]+[a-zA-Z0-9]$'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponseWrapper, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('OperationalizationCluster', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + get.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningCompute/operationalizationClusters/{clusterName}'} # type: ignore + + def update( + self, + resource_group_name, # type: str + cluster_name, # type: str + parameters, # type: "_models.OperationalizationClusterUpdateParameters" + **kwargs # type: Any + ): + # type: (...) -> "_models.OperationalizationCluster" + """The PATCH operation can be used to update only the tags for a cluster. Use PUT operation to + update other properties. + + :param resource_group_name: Name of the resource group in which the cluster is located. + :type resource_group_name: str + :param cluster_name: The name of the cluster. + :type cluster_name: str + :param parameters: The parameters supplied to patch the cluster. + :type parameters: ~azure.mgmt.machinelearningcompute.models.OperationalizationClusterUpdateParameters + :keyword callable cls: A custom type or function that will be passed the direct response + :return: OperationalizationCluster, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningcompute.models.OperationalizationCluster + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.OperationalizationCluster"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2017-08-01-preview" + content_type = kwargs.pop("content_type", "application/json") + accept = "application/json" + + # Construct URL + url = self.update.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\w\._\(\)]+$'), + 'clusterName': self._serialize.url("cluster_name", cluster_name, 'str', max_length=90, min_length=1, pattern=r'^[a-zA-Z][-\w\._\(\)]+[a-zA-Z0-9]$'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Content-Type'] = self._serialize.header("content_type", content_type, 'str') + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + body_content_kwargs = {} # type: Dict[str, Any] + body_content = self._serialize.body(parameters, 'OperationalizationClusterUpdateParameters') + body_content_kwargs['content'] = body_content + request = self._client.patch(url, query_parameters, header_parameters, **body_content_kwargs) + pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponseWrapper, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('OperationalizationCluster', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + update.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningCompute/operationalizationClusters/{clusterName}'} # type: ignore + + def _delete_initial( + self, + resource_group_name, # type: str + cluster_name, # type: str + delete_all=None, # type: Optional[bool] + **kwargs # type: Any + ): + # type: (...) -> None + cls = kwargs.pop('cls', None) # type: ClsType[None] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2017-08-01-preview" + accept = "application/json" + + # Construct URL + url = self._delete_initial.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\w\._\(\)]+$'), + 'clusterName': self._serialize.url("cluster_name", cluster_name, 'str', max_length=90, min_length=1, pattern=r'^[a-zA-Z][-\w\._\(\)]+[a-zA-Z0-9]$'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + if delete_all is not None: + query_parameters['deleteAll'] = self._serialize.query("delete_all", delete_all, 'bool') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.delete(url, query_parameters, header_parameters) + pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [202, 204]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponseWrapper, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + response_headers = {} + if response.status_code == 202: + response_headers['Location']=self._deserialize('str', response.headers.get('Location')) + + if cls: + return cls(pipeline_response, None, response_headers) + + _delete_initial.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningCompute/operationalizationClusters/{clusterName}'} # type: ignore + + def begin_delete( + self, + resource_group_name, # type: str + cluster_name, # type: str + delete_all=None, # type: Optional[bool] + **kwargs # type: Any + ): + # type: (...) -> LROPoller[None] + """Deletes the specified cluster. + + :param resource_group_name: Name of the resource group in which the cluster is located. + :type resource_group_name: str + :param cluster_name: The name of the cluster. + :type cluster_name: str + :param delete_all: If true, deletes all resources associated with this cluster. + :type delete_all: bool + :keyword callable cls: A custom type or function that will be passed the direct response + :keyword str continuation_token: A continuation token to restart a poller from a saved state. + :keyword polling: Pass in True if you'd like the ARMPolling polling method, + False for no polling, or your own initialized polling object for a personal polling strategy. + :paramtype polling: bool or ~azure.core.polling.PollingMethod + :keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present. + :return: An instance of LROPoller that returns either None or the result of cls(response) + :rtype: ~azure.core.polling.LROPoller[None] + :raises ~azure.core.exceptions.HttpResponseError: + """ + polling = kwargs.pop('polling', True) # type: Union[bool, PollingMethod] + cls = kwargs.pop('cls', None) # type: ClsType[None] + lro_delay = kwargs.pop( + 'polling_interval', + self._config.polling_interval + ) + cont_token = kwargs.pop('continuation_token', None) # type: Optional[str] + if cont_token is None: + raw_result = self._delete_initial( + resource_group_name=resource_group_name, + cluster_name=cluster_name, + delete_all=delete_all, + cls=lambda x,y,z: x, + **kwargs + ) + + kwargs.pop('error_map', None) + kwargs.pop('content_type', None) + + def get_long_running_output(pipeline_response): + if cls: + return cls(pipeline_response, None, {}) + + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\w\._\(\)]+$'), + 'clusterName': self._serialize.url("cluster_name", cluster_name, 'str', max_length=90, min_length=1, pattern=r'^[a-zA-Z][-\w\._\(\)]+[a-zA-Z0-9]$'), + } + + if polling is True: polling_method = ARMPolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + elif polling is False: polling_method = NoPolling() + else: polling_method = polling + if cont_token: + return LROPoller.from_continuation_token( + polling_method=polling_method, + continuation_token=cont_token, + client=self._client, + deserialization_callback=get_long_running_output + ) + else: + return LROPoller(self._client, raw_result, get_long_running_output, polling_method) + begin_delete.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningCompute/operationalizationClusters/{clusterName}'} # type: ignore + + def list_keys( + self, + resource_group_name, # type: str + cluster_name, # type: str + **kwargs # type: Any + ): + # type: (...) -> "_models.OperationalizationClusterCredentials" + """Gets the credentials for the specified cluster such as Storage, ACR and ACS credentials. This + is a long running operation because it fetches keys from dependencies. + + :param resource_group_name: Name of the resource group in which the cluster is located. + :type resource_group_name: str + :param cluster_name: The name of the cluster. + :type cluster_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: OperationalizationClusterCredentials, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningcompute.models.OperationalizationClusterCredentials + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.OperationalizationClusterCredentials"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2017-08-01-preview" + accept = "application/json" + + # Construct URL + url = self.list_keys.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\w\._\(\)]+$'), + 'clusterName': self._serialize.url("cluster_name", cluster_name, 'str', max_length=90, min_length=1, pattern=r'^[a-zA-Z][-\w\._\(\)]+[a-zA-Z0-9]$'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.post(url, query_parameters, header_parameters) + pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + raise HttpResponseError(response=response, error_format=ARMErrorFormat) + + deserialized = self._deserialize('OperationalizationClusterCredentials', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + list_keys.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningCompute/operationalizationClusters/{clusterName}/listKeys'} # type: ignore + + def check_system_services_updates_available( + self, + resource_group_name, # type: str + cluster_name, # type: str + **kwargs # type: Any + ): + # type: (...) -> "_models.CheckSystemServicesUpdatesAvailableResponse" + """Checks if updates are available for system services in the cluster. + + :param resource_group_name: Name of the resource group in which the cluster is located. + :type resource_group_name: str + :param cluster_name: The name of the cluster. + :type cluster_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: CheckSystemServicesUpdatesAvailableResponse, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningcompute.models.CheckSystemServicesUpdatesAvailableResponse + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.CheckSystemServicesUpdatesAvailableResponse"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2017-08-01-preview" + accept = "application/json" + + # Construct URL + url = self.check_system_services_updates_available.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\w\._\(\)]+$'), + 'clusterName': self._serialize.url("cluster_name", cluster_name, 'str', max_length=90, min_length=1, pattern=r'^[a-zA-Z][-\w\._\(\)]+[a-zA-Z0-9]$'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.post(url, query_parameters, header_parameters) + pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + raise HttpResponseError(response=response, error_format=ARMErrorFormat) + + deserialized = self._deserialize('CheckSystemServicesUpdatesAvailableResponse', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + check_system_services_updates_available.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningCompute/operationalizationClusters/{clusterName}/checkSystemServicesUpdatesAvailable'} # type: ignore + + def _update_system_services_initial( + self, + resource_group_name, # type: str + cluster_name, # type: str + **kwargs # type: Any + ): + # type: (...) -> Optional["_models.UpdateSystemServicesResponse"] + cls = kwargs.pop('cls', None) # type: ClsType[Optional["_models.UpdateSystemServicesResponse"]] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2017-08-01-preview" + accept = "application/json" + + # Construct URL + url = self._update_system_services_initial.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\w\._\(\)]+$'), + 'clusterName': self._serialize.url("cluster_name", cluster_name, 'str', max_length=90, min_length=1, pattern=r'^[a-zA-Z][-\w\._\(\)]+[a-zA-Z0-9]$'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.post(url, query_parameters, header_parameters) + pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200, 202]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + raise HttpResponseError(response=response, error_format=ARMErrorFormat) + + response_headers = {} + deserialized = None + if response.status_code == 200: + deserialized = self._deserialize('UpdateSystemServicesResponse', pipeline_response) + + if response.status_code == 202: + response_headers['Location']=self._deserialize('str', response.headers.get('Location')) + + if cls: + return cls(pipeline_response, deserialized, response_headers) + + return deserialized + _update_system_services_initial.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningCompute/operationalizationClusters/{clusterName}/updateSystemServices'} # type: ignore + + def begin_update_system_services( + self, + resource_group_name, # type: str + cluster_name, # type: str + **kwargs # type: Any + ): + # type: (...) -> LROPoller["_models.UpdateSystemServicesResponse"] + """Updates system services in a cluster. + + :param resource_group_name: Name of the resource group in which the cluster is located. + :type resource_group_name: str + :param cluster_name: The name of the cluster. + :type cluster_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :keyword str continuation_token: A continuation token to restart a poller from a saved state. + :keyword polling: Pass in True if you'd like the ARMPolling polling method, + False for no polling, or your own initialized polling object for a personal polling strategy. + :paramtype polling: bool or ~azure.core.polling.PollingMethod + :keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present. + :return: An instance of LROPoller that returns either UpdateSystemServicesResponse or the result of cls(response) + :rtype: ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningcompute.models.UpdateSystemServicesResponse] + :raises ~azure.core.exceptions.HttpResponseError: + """ + polling = kwargs.pop('polling', True) # type: Union[bool, PollingMethod] + cls = kwargs.pop('cls', None) # type: ClsType["_models.UpdateSystemServicesResponse"] + lro_delay = kwargs.pop( + 'polling_interval', + self._config.polling_interval + ) + cont_token = kwargs.pop('continuation_token', None) # type: Optional[str] + if cont_token is None: + raw_result = self._update_system_services_initial( + resource_group_name=resource_group_name, + cluster_name=cluster_name, + cls=lambda x,y,z: x, + **kwargs + ) + + kwargs.pop('error_map', None) + kwargs.pop('content_type', None) + + def get_long_running_output(pipeline_response): + deserialized = self._deserialize('UpdateSystemServicesResponse', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + return deserialized + + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\w\._\(\)]+$'), + 'clusterName': self._serialize.url("cluster_name", cluster_name, 'str', max_length=90, min_length=1, pattern=r'^[a-zA-Z][-\w\._\(\)]+[a-zA-Z0-9]$'), + } + + if polling is True: polling_method = ARMPolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + elif polling is False: polling_method = NoPolling() + else: polling_method = polling + if cont_token: + return LROPoller.from_continuation_token( + polling_method=polling_method, + continuation_token=cont_token, + client=self._client, + deserialization_callback=get_long_running_output + ) + else: + return LROPoller(self._client, raw_result, get_long_running_output, polling_method) + begin_update_system_services.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningCompute/operationalizationClusters/{clusterName}/updateSystemServices'} # type: ignore + + def list_by_resource_group( + self, + resource_group_name, # type: str + skiptoken=None, # type: Optional[str] + **kwargs # type: Any + ): + # type: (...) -> Iterable["_models.PaginatedOperationalizationClustersList"] + """Gets the clusters in the specified resource group. + + :param resource_group_name: Name of the resource group in which the cluster is located. + :type resource_group_name: str + :param skiptoken: Continuation token for pagination. + :type skiptoken: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either PaginatedOperationalizationClustersList or the result of cls(response) + :rtype: ~azure.core.paging.ItemPaged[~azure.mgmt.machinelearningcompute.models.PaginatedOperationalizationClustersList] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.PaginatedOperationalizationClustersList"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2017-08-01-preview" + accept = "application/json" + + def prepare_request(next_link=None): + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + if not next_link: + # Construct URL + url = self.list_by_resource_group.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\w\._\(\)]+$'), + } + url = self._client.format_url(url, **path_format_arguments) + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + if skiptoken is not None: + query_parameters['$skiptoken'] = self._serialize.query("skiptoken", skiptoken, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + else: + url = next_link + query_parameters = {} # type: Dict[str, Any] + request = self._client.get(url, query_parameters, header_parameters) + return request + + def extract_data(pipeline_response): + deserialized = self._deserialize('PaginatedOperationalizationClustersList', pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, iter(list_of_elem) + + def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + raise HttpResponseError(response=response, error_format=ARMErrorFormat) + + return pipeline_response + + return ItemPaged( + get_next, extract_data + ) + list_by_resource_group.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningCompute/operationalizationClusters'} # type: ignore + + def list_by_subscription_id( + self, + skiptoken=None, # type: Optional[str] + **kwargs # type: Any + ): + # type: (...) -> Iterable["_models.PaginatedOperationalizationClustersList"] + """Gets the operationalization clusters in the specified subscription. + + :param skiptoken: Continuation token for pagination. + :type skiptoken: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either PaginatedOperationalizationClustersList or the result of cls(response) + :rtype: ~azure.core.paging.ItemPaged[~azure.mgmt.machinelearningcompute.models.PaginatedOperationalizationClustersList] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.PaginatedOperationalizationClustersList"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2017-08-01-preview" + accept = "application/json" + + def prepare_request(next_link=None): + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + if not next_link: + # Construct URL + url = self.list_by_subscription_id.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + if skiptoken is not None: + query_parameters['$skiptoken'] = self._serialize.query("skiptoken", skiptoken, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + else: + url = next_link + query_parameters = {} # type: Dict[str, Any] + request = self._client.get(url, query_parameters, header_parameters) + return request + + def extract_data(pipeline_response): + deserialized = self._deserialize('PaginatedOperationalizationClustersList', pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, iter(list_of_elem) + + def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + raise HttpResponseError(response=response, error_format=ARMErrorFormat) + + return pipeline_response + + return ItemPaged( + get_next, extract_data + ) + list_by_subscription_id.metadata = {'url': '/subscriptions/{subscriptionId}/providers/Microsoft.MachineLearningCompute/operationalizationClusters'} # type: ignore diff --git a/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/py.typed b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/py.typed new file mode 100644 index 000000000000..e5aff4f83af8 --- /dev/null +++ b/sdk/machinelearning/azure-mgmt-machinelearningcompute/azure/mgmt/machinelearningcompute/py.typed @@ -0,0 +1 @@ +# Marker file for PEP 561. \ No newline at end of file diff --git a/sdk/machinelearning/azure-mgmt-machinelearningcompute/sdk_packaging.toml b/sdk/machinelearning/azure-mgmt-machinelearningcompute/sdk_packaging.toml new file mode 100644 index 000000000000..d3102976019a --- /dev/null +++ b/sdk/machinelearning/azure-mgmt-machinelearningcompute/sdk_packaging.toml @@ -0,0 +1,9 @@ +[packaging] +package_name = "azure-mgmt-machinelearningcompute" +package_nspkg = "azure-mgmt-nspkg" +package_pprint_name = "MyService Management" +package_doc_id = "" +is_stable = false +is_arm = true +need_msrestazure = false +need_azuremgmtcore = true diff --git a/sdk/machinelearning/azure-mgmt-machinelearningcompute/setup.cfg b/sdk/machinelearning/azure-mgmt-machinelearningcompute/setup.cfg new file mode 100644 index 000000000000..3c6e79cf31da --- /dev/null +++ b/sdk/machinelearning/azure-mgmt-machinelearningcompute/setup.cfg @@ -0,0 +1,2 @@ +[bdist_wheel] +universal=1 diff --git a/sdk/machinelearning/azure-mgmt-machinelearningcompute/setup.py b/sdk/machinelearning/azure-mgmt-machinelearningcompute/setup.py new file mode 100644 index 000000000000..fae61476e8f4 --- /dev/null +++ b/sdk/machinelearning/azure-mgmt-machinelearningcompute/setup.py @@ -0,0 +1,91 @@ +#!/usr/bin/env python + +#------------------------------------------------------------------------- +# Copyright (c) Microsoft Corporation. All rights reserved. +# Licensed under the MIT License. See License.txt in the project root for +# license information. +#-------------------------------------------------------------------------- + +import re +import os.path +from io import open +from setuptools import find_packages, setup + +# Change the PACKAGE_NAME only to change folder and different name +PACKAGE_NAME = "azure-mgmt-machinelearningcompute" +PACKAGE_PPRINT_NAME = "MyService Management" + +# a-b-c => a/b/c +package_folder_path = PACKAGE_NAME.replace('-', '/') +# a-b-c => a.b.c +namespace_name = PACKAGE_NAME.replace('-', '.') + +# azure v0.x is not compatible with this package +# azure v0.x used to have a __version__ attribute (newer versions don't) +try: + import azure + try: + ver = azure.__version__ + raise Exception( + 'This package is incompatible with azure=={}. '.format(ver) + + 'Uninstall it with "pip uninstall azure".' + ) + except AttributeError: + pass +except ImportError: + pass + +# Version extraction inspired from 'requests' +with open(os.path.join(package_folder_path, 'version.py') + if os.path.exists(os.path.join(package_folder_path, 'version.py')) + else os.path.join(package_folder_path, '_version.py'), 'r') as fd: + version = re.search(r'^VERSION\s*=\s*[\'"]([^\'"]*)[\'"]', + fd.read(), re.MULTILINE).group(1) + +if not version: + raise RuntimeError('Cannot find version information') + +with open('README.md', encoding='utf-8') as f: + readme = f.read() +with open('CHANGELOG.md', encoding='utf-8') as f: + changelog = f.read() + +setup( + name=PACKAGE_NAME, + version=version, + description='Microsoft Azure {} Client Library for Python'.format(PACKAGE_PPRINT_NAME), + long_description=readme + '\n\n' + changelog, + long_description_content_type='text/markdown', + license='MIT License', + author='Microsoft Corporation', + author_email='azpysdkhelp@microsoft.com', + url='https://github.com/Azure/azure-sdk-for-python', + classifiers=[ + 'Development Status :: 4 - Beta', + 'Programming Language :: Python', + 'Programming Language :: Python :: 2', + 'Programming Language :: Python :: 2.7', + 'Programming Language :: Python :: 3', + 'Programming Language :: Python :: 3.5', + 'Programming Language :: Python :: 3.6', + 'Programming Language :: Python :: 3.7', + 'Programming Language :: Python :: 3.8', + 'Programming Language :: Python :: 3.9', + 'License :: OSI Approved :: MIT License', + ], + zip_safe=False, + packages=find_packages(exclude=[ + 'tests', + # Exclude packages that will be covered by PEP420 or nspkg + 'azure', + 'azure.mgmt', + ]), + install_requires=[ + 'msrest>=0.6.21', + 'azure-common~=1.1', + 'azure-mgmt-core>=1.2.0,<2.0.0', + ], + extras_require={ + ":python_version<'3.0'": ['azure-mgmt-nspkg'], + } +)