:py:mod:`airflow.providers.grpc.operators.grpc`
===============================================

.. py:module:: airflow.providers.grpc.operators.grpc


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

Classes
~~~~~~~

.. autoapisummary::

   airflow.providers.grpc.operators.grpc.GrpcOperator


.. py:class:: GrpcOperator(*, stub_class, call_func, grpc_conn_id = 'grpc_default', data = None, interceptors = None, custom_connection_func = None, streaming = False, response_callback = None, log_response = False, **kwargs)

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

   Calls a gRPC endpoint to execute an action

   :param stub_class: The stub client to use for this gRPC call
   :param call_func: The client function name to call the gRPC endpoint
   :param grpc_conn_id: The connection to run the operator against
   :param data: The data to pass to the rpc call
   :param interceptors: A list of gRPC interceptor objects to be used on the channel
   :param custom_connection_func: The customized connection function to return channel object.
       A callable that accepts the connection as its only arg.
   :param streaming: A flag to indicate if the call is a streaming call
   :param response_callback: The callback function to process the response from gRPC call,
       takes in response object and context object, context object can be used to perform
       push xcom or other after task actions
   :param log_response: A flag to indicate if we need to log the response

   .. py:attribute:: template_fields
      :annotation: :Sequence[str] = ['stub_class', 'call_func', 'data']

      
   .. py:attribute:: template_fields_renderers
      

   .. 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.