azure_ml_sdk.services.connection.authenticate
=============================================

.. py:module:: azure_ml_sdk.services.connection.authenticate


Classes
-------

.. autoapisummary::

   azure_ml_sdk.services.connection.authenticate.Authenticator


Module Contents
---------------

.. py:class:: Authenticator(subscription_id: str, resource_group: str, workspace_name: str)

   Class for setting up authentication for Azure Machine Learning resources and workflows.

   Different methods can be used in authentication: Local authentication, interactive authentication,
   and Service Principal.

   .. attribute:: subscription_id

      Azure Subscription ID.

      :type: str

   .. attribute:: resource_group

      Azure resource group name.

      :type: str

   .. attribute:: workspace_name

      Azure ML workspace name.

      :type: str


   .. py:attribute:: subscription_id


   .. py:attribute:: resource_group


   .. py:attribute:: workspace_name


   .. py:method:: default_connection() -> Optional[azure.ai.ml.MLClient]

      Authenticate locally with DefaultAzureCredential.

      This method is used in experimentation and iterative developments.

      :returns: MLClient instance if success.
      :rtype: MLClient



   .. py:method:: interactive_connection() -> Optional[azure.ai.ml.MLClient]

      Authenticate interactively with InteractiveBrowserCredential.

      This method opens an interactive browser for connection.

      :returns: MLClient instance if success.
      :rtype: MLClient



   .. py:method:: service_principal_connection(tenant_id, client_id, client_secret) -> Optional[azure.ai.ml.MLClient]

      Authenticate using a Service principal with ClientSecrterCredential.

      This method is best suited for automated process without user interaction.

      :param tenant_id: Tenant ID of the Service principal application.
      :type tenant_id: str
      :param client_id: ID of the Service principal application.
      :type client_id: str
      :param client_secret: Secret ID of the Service principal application.
      :type client_secret: str

      :returns: MLClient instance if success.
      :rtype: MLClient



   .. py:method:: managed_identity_connection(client_id: Optional[str] = None) -> Optional[azure.ai.ml.MLClient]

      Authenticate using Managed Identity.

      This method supports both system-assigned and user-assigned managed identities.
      For system-assigned managed identity, leave client_id as None.
      For user-assigned managed identity, provide the client_id.

      :param client_id: The client ID of the user-assigned managed identity.
                        Leave as None for system-assigned managed identity.
      :type client_id: Optional[str]

      :returns: MLClient instance if success.
      :rtype: MLClient



   .. py:method:: workload_identity_connection(tenant_id: Optional[str] = None, client_id: Optional[str] = None) -> Optional[azure.ai.ml.MLClient]

      Authenticate using Workload Identity Federation.

      This method is designed for Azure DevOps pipelines that use Workload Identity Federation.
      If running in Azure DevOps with properly configured federation, the tenant_id and client_id parameters
      are optional as they will be automatically detected.

      :param tenant_id: The Azure AD tenant ID. Optional if running in Azure DevOps.
      :type tenant_id: Optional[str]
      :param client_id: The client ID of the federated application. Optional if running in Azure DevOps.
      :type client_id: Optional[str]

      :returns: MLClient instance if success.
      :rtype: MLClient