:py:mod:`airflow.providers.google.cloud.operators.kubernetes_engine`
====================================================================

.. py:module:: airflow.providers.google.cloud.operators.kubernetes_engine

.. autoapi-nested-parse::

   This module contains Google Kubernetes Engine operators.


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

Classes
~~~~~~~

.. autoapisummary::

   airflow.providers.google.cloud.operators.kubernetes_engine.GKEDeleteClusterOperator
   airflow.providers.google.cloud.operators.kubernetes_engine.GKECreateClusterOperator
   airflow.providers.google.cloud.operators.kubernetes_engine.GKEStartPodOperator


Attributes
~~~~~~~~~~

.. autoapisummary::

   airflow.providers.google.cloud.operators.kubernetes_engine.KUBE_CONFIG_ENV_VAR


.. py:class:: GKEDeleteClusterOperator(*, name, location, project_id = None, gcp_conn_id = 'google_cloud_default', api_version = 'v2', impersonation_chain = None, **kwargs)

   Bases: :py:obj:`airflow.models.BaseOperator`

   Deletes the cluster, including the Kubernetes endpoint and all worker nodes.

   To delete a certain cluster, you must specify the ``project_id``, the ``name``
   of the cluster, the ``location`` that the cluster is in, and the ``task_id``.

   **Operator Creation**: ::

       operator = GKEClusterDeleteOperator(
                   task_id='cluster_delete',
                   project_id='my-project',
                   location='cluster-location'
                   name='cluster-name')

   .. seealso::
       For more detail about deleting clusters have a look at the reference:
       https://google-cloud-python.readthedocs.io/en/latest/container/gapic/v1/api.html#google.cloud.container_v1.ClusterManagerClient.delete_cluster

   .. seealso::
       For more information on how to use this operator, take a look at the guide:
       :ref:`howto/operator:GKEDeleteClusterOperator`

   :param project_id: The Google Developers Console [project ID or project number]
   :param name: The name of the resource to delete, in this case cluster name
   :param location: The name of the Google Kubernetes Engine zone or region in which the cluster
       resides.
   :param gcp_conn_id: The connection ID to use connecting to Google Cloud.
   :param api_version: The api version to use
   :param impersonation_chain: Optional service account to impersonate using short-term
       credentials, or chained list of accounts required to get the access_token
       of the last account in the list, which will be impersonated in the request.
       If set as a string, the account must grant the originating account
       the Service Account Token Creator IAM role.
       If set as a sequence, the identities from the list must grant
       Service Account Token Creator IAM role to the directly preceding identity, with first
       account from the list granting this role to the originating account (templated).

   .. py:attribute:: template_fields
      :annotation: :Sequence[str] = ['project_id', 'gcp_conn_id', 'name', 'location', 'api_version', 'impersonation_chain']

      
   .. py:method:: execute(self, context)

      This is the main method to derive when creating an operator.
      Context is the same dictionary used as when rendering jinja templates.

      Refer to get_template_context for more context.


.. py:class:: GKECreateClusterOperator(*, location, body, project_id = None, gcp_conn_id = 'google_cloud_default', api_version = 'v2', impersonation_chain = None, **kwargs)

   Bases: :py:obj:`airflow.models.BaseOperator`

   Create a Google Kubernetes Engine Cluster of specified dimensions
   The operator will wait until the cluster is created.

   The **minimum** required to define a cluster to create is:

   ``dict()`` ::
       cluster_def = {'name': 'my-cluster-name',
                      'initial_node_count': 1}

   or

   ``Cluster`` proto ::
       from google.cloud.container_v1.types import Cluster

       cluster_def = Cluster(name='my-cluster-name', initial_node_count=1)

   **Operator Creation**: ::

       operator = GKEClusterCreateOperator(
                   task_id='cluster_create',
                   project_id='my-project',
                   location='my-location'
                   body=cluster_def)

   .. seealso::
       For more detail on about creating clusters have a look at the reference:
       :class:`google.cloud.container_v1.types.Cluster`

   .. seealso::
       For more information on how to use this operator, take a look at the guide:
       :ref:`howto/operator:GKECreateClusterOperator`

   :param project_id: The Google Developers Console [project ID or project number]
   :param location: The name of the Google Kubernetes Engine zone or region in which the cluster
       resides.
   :param body: The Cluster definition to create, can be protobuf or python dict, if
       dict it must match protobuf message Cluster
   :param gcp_conn_id: The connection ID to use connecting to Google Cloud.
   :param api_version: The api version to use
   :param impersonation_chain: Optional service account to impersonate using short-term
       credentials, or chained list of accounts required to get the access_token
       of the last account in the list, which will be impersonated in the request.
       If set as a string, the account must grant the originating account
       the Service Account Token Creator IAM role.
       If set as a sequence, the identities from the list must grant
       Service Account Token Creator IAM role to the directly preceding identity, with first
       account from the list granting this role to the originating account (templated).

   .. py:attribute:: template_fields
      :annotation: :Sequence[str] = ['project_id', 'gcp_conn_id', 'location', 'api_version', 'body', 'impersonation_chain']

      
   .. py:method:: execute(self, context)

      This is the main method to derive when creating an operator.
      Context is the same dictionary used as when rendering jinja templates.

      Refer to get_template_context for more context.


.. py:data:: KUBE_CONFIG_ENV_VAR
   :annotation: = KUBECONFIG

   
.. py:class:: GKEStartPodOperator(*, location, cluster_name, use_internal_ip = False, project_id = None, gcp_conn_id = 'google_cloud_default', impersonation_chain = None, regional = False, is_delete_operator_pod = None, **kwargs)

   Bases: :py:obj:`airflow.providers.cncf.kubernetes.operators.kubernetes_pod.KubernetesPodOperator`

   Executes a task in a Kubernetes pod in the specified Google Kubernetes
   Engine cluster

   This Operator assumes that the system has gcloud installed and has configured a
   connection id with a service account.

   The **minimum** required to define a cluster to create are the variables
   ``task_id``, ``project_id``, ``location``, ``cluster_name``, ``name``,
   ``namespace``, and ``image``

   .. seealso::
       For more detail about Kubernetes Engine authentication have a look at the reference:
       https://cloud.google.com/kubernetes-engine/docs/how-to/cluster-access-for-kubectl#internal_ip

   .. seealso::
       For more information on how to use this operator, take a look at the guide:
       :ref:`howto/operator:GKEStartPodOperator`

   :param location: The name of the Google Kubernetes Engine zone or region in which the
       cluster resides, e.g. 'us-central1-a'
   :param cluster_name: The name of the Google Kubernetes Engine cluster the pod
       should be spawned in
   :param use_internal_ip: Use the internal IP address as the endpoint.
   :param project_id: The Google Developers Console project id
   :param gcp_conn_id: The google cloud connection id to use. This allows for
       users to specify a service account.
   :param impersonation_chain: Optional service account to impersonate using short-term
       credentials, or list of accounts required to get the access_token
       of the last account in the list, which will be impersonated in the request.
       If set as a string, the account must grant the originating account
       the Service Account Token Creator IAM role.
       If set as a sequence, the identities from the list must grant
       Service Account Token Creator IAM role to the directly preceding identity, with first
       account from the list granting this role to the originating account (templated).
   :param regional: The location param is region name.
   :param is_delete_operator_pod: What to do when the pod reaches its final
       state, or the execution is interrupted. If True, delete the
       pod; if False, leave the pod.  Current default is False, but this will be
       changed in the next major release of this provider.

   .. py:attribute:: template_fields
      :annotation: :Sequence[str]

      
   .. py:method:: get_gke_config_file(gcp_conn_id, project_id, cluster_name, impersonation_chain, regional, location, use_internal_ip)
      :staticmethod:


   .. py:method:: execute(self, context)

      This is the main method to derive when creating an operator.
      Context is the same dictionary used as when rendering jinja templates.

      Refer to get_template_context for more context.