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get_azureml_credentials

kedro_azureml_pipeline.client.get_azureml_credentials()

Obtain Azure credentials for Azure ML access.

Tries DefaultAzureCredential first (excluding managed identity on AzureML compute instances). Falls back to InteractiveBrowserCredential on failure.

Returns

Type Description
TokenCredential

Azure credential object.

See Also

AzureMLPipelinesClient : Uses credentials for job submission. AzureMLScheduleClient : Uses credentials for schedule management.

Source Code

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def get_azureml_credentials() -> "TokenCredential":
    """Obtain Azure credentials for Azure ML access.

    Tries ``DefaultAzureCredential`` first (excluding managed identity
    on AzureML compute instances). Falls back to
    ``InteractiveBrowserCredential`` on failure.

    Returns
    -------
    TokenCredential
        Azure credential object.

    See Also
    --------
    [AzureMLPipelinesClient][kedro_azureml_pipeline.client.AzureMLPipelinesClient] : Uses credentials for job submission.
    [AzureMLScheduleClient][kedro_azureml_pipeline.scheduler.AzureMLScheduleClient] : Uses credentials for schedule management.
    """
    try:
        # On a AzureML compute instance, the managed identity will take precedence,
        # while it does not have enough permissions.
        # So, if we are on an AzureML compute instance, we disable the managed identity.
        is_azureml_managed_identity = "MSI_ENDPOINT" in os.environ
        credential = DefaultAzureCredential(exclude_managed_identity_credential=is_azureml_managed_identity)
        # Check if given credential can get token successfully.
        credential.get_token("https://management.azure.com/.default")
    except (ClientAuthenticationError, CredentialUnavailableError):
        # Fall back to InteractiveBrowserCredential in case DefaultAzureCredential not work
        credential = InteractiveBrowserCredential()
    return credential