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Aggiornare la gestione dell'area di lavoro all'SDK v2

L'area di lavoro rimane invariata a livello funzionale con la piattaforma di sviluppo V2. Tuttavia, esistono modifiche correlate alla rete da tenere presenti. Per informazioni dettagliate, vedere Modifica dell'isolamento della rete con la nuova piattaforma API in Azure Resource Manager

Questo articolo offre un confronto tra scenari in SDK v1 e SDK v2.

Creare un'area di lavoro

  • 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)
    

Caricare/connettersi all'area di lavoro usando i parametri

  • 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'
    )
    

Caricare/connettersi all'area di lavoro usando il file di configurazione

  • 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()
    )
    

Mapping delle funzionalità chiave in SDK v1 e SDK v2

Funzionalità nell'SDK v1 Mapping approssimativo in SDK v2
Metodo/API in SDK v1 (usare i collegamenti alla documentazione di riferimento) Metodo/API in SDK v2 (usare i collegamenti alla documentazione di riferimento)

Per altre informazioni, vedi: