Teilen über


Upgrade der Arbeitsbereichsverwaltung auf SDK v2

Die Funktionalität zur Arbeitsbereichsverwaltung bleibt auf der Entwicklungsplattform von v2 unverändert. Es sind jedoch netzwerkbezogene Änderungen zu beachten. Einzelheiten finden Sie unter Netzwerkisolationsänderung mit unserer neuen API-Plattform für Azure Resource Manager.

Dieser Artikel enthält einen Vergleich der Szenarien in SDK v1 und SDK v2.

Erstellen eines Arbeitsbereichs

  • SDK v1

    from azureml.core import Workspace
    
    ws = Workspace.create(
        name='my_workspace',
        location='eastus',
        subscription_id = '<SUBSCRIPTION_ID>'
        resource_group = '<RESOURCE_GROUP>'
    )
    
  • SDK v2

    from azure.ai.ml import MLClient
    from azure.ai.ml.entities import Workspace
    from azure.identity import DefaultAzureCredential
    
    # specify the details of your subscription
    subscription_id = "<SUBSCRIPTION_ID>"
    resource_group = "<RESOURCE_GROUP>"
    
    # get a handle to the subscription
    ml_client = MLClient(DefaultAzureCredential(), subscription_id, resource_group)
    
    # specify the workspace details
    ws = Workspace(
        name="my_workspace",
        location="eastus",
        display_name="My workspace",
        description="This example shows how to create a workspace",
        tags=dict(purpose="demo"),
    )
    
    ml_client.workspaces.begin_create(ws)
    
  • SDK v1

    from azureml.core import Workspace
    
    ws = Workspace.create(
        name='my_workspace',
        location='eastus',
        subscription_id = '<SUBSCRIPTION_ID>'
        resource_group = '<RESOURCE_GROUP>'
    )
    
    ple = PrivateEndPointConfig(
        name='my_private_link_endpoint',
        vnet_name='<VNET_NAME>',
        vnet_subnet_name='<VNET_SUBNET_NAME>',
        vnet_subscription_id='<SUBSCRIPTION_ID>', 
        vnet_resource_group='<RESOURCE_GROUP>'
    )
    
    ws.add_private_endpoint(ple, private_endpoint_auto_approval=True)
    
  • SDK v2

    from azure.ai.ml import MLClient
    from azure.ai.ml.entities import Workspace
    from azure.identity import DefaultAzureCredential
    
    # specify the details of your subscription
    subscription_id = "<SUBSCRIPTION_ID>"
    resource_group = "<RESOURCE_GROUP>"
    
    # get a handle to the subscription
    ml_client = MLClient(DefaultAzureCredential(), subscription_id, resource_group)
    
    ws = Workspace(
        name="private_link_endpoint_workspace,
        location="eastus",
        display_name="Private Link endpoint workspace",
        description="When using private link, you must set the image_build_compute property to a cluster name to use for Docker image environment building. You can also specify whether the workspace should be accessible over the internet.",
        image_build_compute="cpu-compute",
        public_network_access="Disabled",
        tags=dict(purpose="demonstration"),
    )
    
    ml_client.workspaces.begin_create(ws)
    

Laden von bzw. Verbinden mit dem Arbeitsbereich über Parameter

  • SDK v1

    from azureml.core import Workspace
    ws = Workspace.from_config()
    
    # specify the details of your subscription
    subscription_id = "<SUBSCRIPTION_ID>"
    resource_group = "<RESOURCE_GROUP>"
    
    # get handle on the workspace
    ws = Workspace.get(
        subscription_id='<SUBSCRIPTION_ID>',
        resource_group='<RESOURCE_GROUP>',
        name='my_workspace',
    )
    
  • SDK v2

    from azure.ai.ml import MLClient
    from azure.ai.ml.entities import Workspace
    from azure.identity import DefaultAzureCredential
    
    # specify the details of your subscription
    subscription_id = "<SUBSCRIPTION_ID>"
    resource_group = "<RESOURCE_GROUP>"
    
    # get handle on the workspace
    ws = MLClient(
        DefaultAzureCredential(),
        subscription_id='<SUBSCRIPTION_ID>',
        resource_group_name='<RESOURCE_GROUP>',
        workspace_name='my_workspace'
    )
    

Laden von bzw. Verbinden mit dem Arbeitsbereich über eine Konfigurationsdatei

  • SDK v1

    from azureml.core import Workspace
    
    ws = Workspace.from_config()
    ws.get_details()
    
  • SDK v2

    from azure.ai.ml import MLClient
    from azure.ai.ml.entities import Workspace
    from azure.identity import DefaultAzureCredential
    
    ws = MLClient.from_config(
        DefaultAzureCredential()
    )
    

Zuordnung der wichtigsten Funktionen in SDK v1 und SDK v2

Funktionalität im SDK v1 Grobe Zuordnung in SDK v2
Methode/API im SDK v1 (mit Links zur Referenzdokumentation) Methode/API im SDK v2 (mit Links zur Referenzdokumentation)

Weitere Informationen finden Sie unter