docs: add generated snippets (#342)

* chore: use gapic-generator-python 0.63.2
docs: add generated snippets

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google/cloud/dataproc_v1/services/autoscaling_policy_service/async_client.py

@@ -227,6 +227,31 @@ async def create_autoscaling_policy(
     ) -> autoscaling_policies.AutoscalingPolicy:
         r"""Creates new autoscaling policy.
 
+        .. code-block::
+
+            from google.cloud import dataproc_v1
+
+            def sample_create_autoscaling_policy():
+                # Create a client
+                client = dataproc_v1.AutoscalingPolicyServiceClient()
+
+                # Initialize request argument(s)
+                policy = dataproc_v1.AutoscalingPolicy()
+                policy.basic_algorithm.yarn_config.scale_up_factor = 0.1578
+                policy.basic_algorithm.yarn_config.scale_down_factor = 0.1789
+                policy.worker_config.max_instances = 1389
+
+                request = dataproc_v1.CreateAutoscalingPolicyRequest(
+                    parent="parent_value",
+                    policy=policy,
+                )
+
+                # Make the request
+                response = client.create_autoscaling_policy(request=request)
+
+                # Handle the response
+                print(response)
+
         Args:
             request (Union[google.cloud.dataproc_v1.types.CreateAutoscalingPolicyRequest, dict]):
                 The request object. A request to create an autoscaling
@@ -323,6 +348,31 @@ async def update_autoscaling_policy(
         Disabled check for update_mask, because all updates will be full
         replacements.
 
+
+        .. code-block::
+
+            from google.cloud import dataproc_v1
+
+            def sample_update_autoscaling_policy():
+                # Create a client
+                client = dataproc_v1.AutoscalingPolicyServiceClient()
+
+                # Initialize request argument(s)
+                policy = dataproc_v1.AutoscalingPolicy()
+                policy.basic_algorithm.yarn_config.scale_up_factor = 0.1578
+                policy.basic_algorithm.yarn_config.scale_down_factor = 0.1789
+                policy.worker_config.max_instances = 1389
+
+                request = dataproc_v1.UpdateAutoscalingPolicyRequest(
+                    policy=policy,
+                )
+
+                # Make the request
+                response = client.update_autoscaling_policy(request=request)
+
+                # Handle the response
+                print(response)
+
         Args:
             request (Union[google.cloud.dataproc_v1.types.UpdateAutoscalingPolicyRequest, dict]):
                 The request object. A request to update an autoscaling
@@ -406,6 +456,25 @@ async def get_autoscaling_policy(
     ) -> autoscaling_policies.AutoscalingPolicy:
         r"""Retrieves autoscaling policy.
 
+        .. code-block::
+
+            from google.cloud import dataproc_v1
+
+            def sample_get_autoscaling_policy():
+                # Create a client
+                client = dataproc_v1.AutoscalingPolicyServiceClient()
+
+                # Initialize request argument(s)
+                request = dataproc_v1.GetAutoscalingPolicyRequest(
+                    name="name_value",
+                )
+
+                # Make the request
+                response = client.get_autoscaling_policy(request=request)
+
+                # Handle the response
+                print(response)
+
         Args:
             request (Union[google.cloud.dataproc_v1.types.GetAutoscalingPolicyRequest, dict]):
                 The request object. A request to fetch an autoscaling
@@ -499,6 +568,26 @@ async def list_autoscaling_policies(
     ) -> pagers.ListAutoscalingPoliciesAsyncPager:
         r"""Lists autoscaling policies in the project.
 
+        .. code-block::
+
+            from google.cloud import dataproc_v1
+
+            def sample_list_autoscaling_policies():
+                # Create a client
+                client = dataproc_v1.AutoscalingPolicyServiceClient()
+
+                # Initialize request argument(s)
+                request = dataproc_v1.ListAutoscalingPoliciesRequest(
+                    parent="parent_value",
+                )
+
+                # Make the request
+                page_result = client.list_autoscaling_policies(request=request)
+
+                # Handle the response
+                for response in page_result:
+                    print(response)
+
         Args:
             request (Union[google.cloud.dataproc_v1.types.ListAutoscalingPoliciesRequest, dict]):
                 The request object. A request to list autoscaling
@@ -603,6 +692,23 @@ async def delete_autoscaling_policy(
         delete an autoscaling policy that is in use by one or
         more clusters.
 
+
+        .. code-block::
+
+            from google.cloud import dataproc_v1
+
+            def sample_delete_autoscaling_policy():
+                # Create a client
+                client = dataproc_v1.AutoscalingPolicyServiceClient()
+
+                # Initialize request argument(s)
+                request = dataproc_v1.DeleteAutoscalingPolicyRequest(
+                    name="name_value",
+                )
+
+                # Make the request
+                client.delete_autoscaling_policy(request=request)
+
         Args:
             request (Union[google.cloud.dataproc_v1.types.DeleteAutoscalingPolicyRequest, dict]):
                 The request object. A request to delete an autoscaling

google/cloud/dataproc_v1/services/autoscaling_policy_service/client.py

@@ -419,6 +419,32 @@ def create_autoscaling_policy(
     ) -> autoscaling_policies.AutoscalingPolicy:
         r"""Creates new autoscaling policy.
 
+
+        .. code-block::
+
+            from google.cloud import dataproc_v1
+
+            def sample_create_autoscaling_policy():
+                # Create a client
+                client = dataproc_v1.AutoscalingPolicyServiceClient()
+
+                # Initialize request argument(s)
+                policy = dataproc_v1.AutoscalingPolicy()
+                policy.basic_algorithm.yarn_config.scale_up_factor = 0.1578
+                policy.basic_algorithm.yarn_config.scale_down_factor = 0.1789
+                policy.worker_config.max_instances = 1389
+
+                request = dataproc_v1.CreateAutoscalingPolicyRequest(
+                    parent="parent_value",
+                    policy=policy,
+                )
+
+                # Make the request
+                response = client.create_autoscaling_policy(request=request)
+
+                # Handle the response
+                print(response)
+
         Args:
             request (Union[google.cloud.dataproc_v1.types.CreateAutoscalingPolicyRequest, dict]):
                 The request object. A request to create an autoscaling
@@ -517,6 +543,32 @@ def update_autoscaling_policy(
         Disabled check for update_mask, because all updates will be full
         replacements.
 
+
+
+        .. code-block::
+
+            from google.cloud import dataproc_v1
+
+            def sample_update_autoscaling_policy():
+                # Create a client
+                client = dataproc_v1.AutoscalingPolicyServiceClient()
+
+                # Initialize request argument(s)
+                policy = dataproc_v1.AutoscalingPolicy()
+                policy.basic_algorithm.yarn_config.scale_up_factor = 0.1578
+                policy.basic_algorithm.yarn_config.scale_down_factor = 0.1789
+                policy.worker_config.max_instances = 1389
+
+                request = dataproc_v1.UpdateAutoscalingPolicyRequest(
+                    policy=policy,
+                )
+
+                # Make the request
+                response = client.update_autoscaling_policy(request=request)
+
+                # Handle the response
+                print(response)
+
         Args:
             request (Union[google.cloud.dataproc_v1.types.UpdateAutoscalingPolicyRequest, dict]):
                 The request object. A request to update an autoscaling
@@ -592,6 +644,26 @@ def get_autoscaling_policy(
     ) -> autoscaling_policies.AutoscalingPolicy:
         r"""Retrieves autoscaling policy.
 
+
+        .. code-block::
+
+            from google.cloud import dataproc_v1
+
+            def sample_get_autoscaling_policy():
+                # Create a client
+                client = dataproc_v1.AutoscalingPolicyServiceClient()
+
+                # Initialize request argument(s)
+                request = dataproc_v1.GetAutoscalingPolicyRequest(
+                    name="name_value",
+                )
+
+                # Make the request
+                response = client.get_autoscaling_policy(request=request)
+
+                # Handle the response
+                print(response)
+
         Args:
             request (Union[google.cloud.dataproc_v1.types.GetAutoscalingPolicyRequest, dict]):
                 The request object. A request to fetch an autoscaling
@@ -675,6 +747,27 @@ def list_autoscaling_policies(
     ) -> pagers.ListAutoscalingPoliciesPager:
         r"""Lists autoscaling policies in the project.
 
+
+        .. code-block::
+
+            from google.cloud import dataproc_v1
+
+            def sample_list_autoscaling_policies():
+                # Create a client
+                client = dataproc_v1.AutoscalingPolicyServiceClient()
+
+                # Initialize request argument(s)
+                request = dataproc_v1.ListAutoscalingPoliciesRequest(
+                    parent="parent_value",
+                )
+
+                # Make the request
+                page_result = client.list_autoscaling_policies(request=request)
+
+                # Handle the response
+                for response in page_result:
+                    print(response)
+
         Args:
             request (Union[google.cloud.dataproc_v1.types.ListAutoscalingPoliciesRequest, dict]):
                 The request object. A request to list autoscaling
@@ -771,6 +864,24 @@ def delete_autoscaling_policy(
         delete an autoscaling policy that is in use by one or
         more clusters.
 
+
+
+        .. code-block::
+
+            from google.cloud import dataproc_v1
+
+            def sample_delete_autoscaling_policy():
+                # Create a client
+                client = dataproc_v1.AutoscalingPolicyServiceClient()
+
+                # Initialize request argument(s)
+                request = dataproc_v1.DeleteAutoscalingPolicyRequest(
+                    name="name_value",
+                )
+
+                # Make the request
+                client.delete_autoscaling_policy(request=request)
+
         Args:
             request (Union[google.cloud.dataproc_v1.types.DeleteAutoscalingPolicyRequest, dict]):
                 The request object. A request to delete an autoscaling

google/cloud/dataproc_v1/services/batch_controller/async_client.py

@@ -223,6 +223,34 @@ async def create_batch(
         r"""Creates a batch workload that executes
         asynchronously.
 
+
+        .. code-block::
+
+            from google.cloud import dataproc_v1
+
+            def sample_create_batch():
+                # Create a client
+                client = dataproc_v1.BatchControllerClient()
+
+                # Initialize request argument(s)
+                batch = dataproc_v1.Batch()
+                batch.pyspark_batch.main_python_file_uri = "main_python_file_uri_value"
+
+                request = dataproc_v1.CreateBatchRequest(
+                    parent="parent_value",
+                    batch=batch,
+                )
+
+                # Make the request
+                operation = client.create_batch(request=request)
+
+                print("Waiting for operation to complete...")
+
+                response = operation.result()
+
+                # Handle the response
+                print(response)
+
         Args:
             request (Union[google.cloud.dataproc_v1.types.CreateBatchRequest, dict]):
                 The request object. A request to create a batch
@@ -324,6 +352,25 @@ async def get_batch(
     ) -> batches.Batch:
         r"""Gets the batch workload resource representation.
 
+        .. code-block::
+
+            from google.cloud import dataproc_v1
+
+            def sample_get_batch():
+                # Create a client
+                client = dataproc_v1.BatchControllerClient()
+
+                # Initialize request argument(s)
+                request = dataproc_v1.GetBatchRequest(
+                    name="name_value",
+                )
+
+                # Make the request
+                response = client.get_batch(request=request)
+
+                # Handle the response
+                print(response)
+
         Args:
             request (Union[google.cloud.dataproc_v1.types.GetBatchRequest, dict]):
                 The request object. A request to get the resource
@@ -395,6 +442,26 @@ async def list_batches(
     ) -> pagers.ListBatchesAsyncPager:
         r"""Lists batch workloads.
 
+        .. code-block::
+
+            from google.cloud import dataproc_v1
+
+            def sample_list_batches():
+                # Create a client
+                client = dataproc_v1.BatchControllerClient()
+
+                # Initialize request argument(s)
+                request = dataproc_v1.ListBatchesRequest(
+                    parent="parent_value",
+                )
+
+                # Make the request
+                page_result = client.list_batches(request=request)
+
+                # Handle the response
+                for response in page_result:
+                    print(response)
+
         Args:
             request (Union[google.cloud.dataproc_v1.types.ListBatchesRequest, dict]):
                 The request object. A request to list batch workloads in
@@ -476,6 +543,23 @@ async def delete_batch(
         terminal state, the delete fails and the response returns
         ``FAILED_PRECONDITION``.
 
+
+        .. code-block::
+
+            from google.cloud import dataproc_v1
+
+            def sample_delete_batch():
+                # Create a client
+                client = dataproc_v1.BatchControllerClient()
+
+                # Initialize request argument(s)
+                request = dataproc_v1.DeleteBatchRequest(
+                    name="name_value",
+                )
+
+                # Make the request
+                client.delete_batch(request=request)
+
         Args:
             request (Union[google.cloud.dataproc_v1.types.DeleteBatchRequest, dict]):
                 The request object. A request to delete a batch