feat!: migrate to use microgen (#71)

* feat!: migrate to use microgen

* update

* update

* update

* update

dataproc/snippets/create_cluster.py

@@ -38,38 +38,34 @@ def create_cluster(project_id, region, cluster_name):
     """
 
     # Create a client with the endpoint set to the desired cluster region.
-    cluster_client = dataproc.ClusterControllerClient(client_options={
-        'api_endpoint': f'{region}-dataproc.googleapis.com:443',
-    })
+    cluster_client = dataproc.ClusterControllerClient(
+        client_options={"api_endpoint": f"{region}-dataproc.googleapis.com:443"}
+    )
 
     # Create the cluster config.
     cluster = {
-        'project_id': project_id,
-        'cluster_name': cluster_name,
-        'config': {
-            'master_config': {
-                'num_instances': 1,
-                'machine_type_uri': 'n1-standard-1'
-            },
-            'worker_config': {
-                'num_instances': 2,
-                'machine_type_uri': 'n1-standard-1'
-            }
-        }
+        "project_id": project_id,
+        "cluster_name": cluster_name,
+        "config": {
+            "master_config": {"num_instances": 1, "machine_type_uri": "n1-standard-1"},
+            "worker_config": {"num_instances": 2, "machine_type_uri": "n1-standard-1"},
+        },
     }
 
     # Create the cluster.
-    operation = cluster_client.create_cluster(project_id, region, cluster)
+    operation = cluster_client.create_cluster(
+        request={"project_id": project_id, "region": region, "cluster": cluster}
+    )
     result = operation.result()
 
     # Output a success message.
-    print(f'Cluster created successfully: {result.cluster_name}')
+    print(f"Cluster created successfully: {result.cluster_name}")
     # [END dataproc_create_cluster]
 
 
 if __name__ == "__main__":
     if len(sys.argv) < 4:
-        sys.exit('python create_cluster.py project_id region cluster_name')
+        sys.exit("python create_cluster.py project_id region cluster_name")
 
     project_id = sys.argv[1]
     region = sys.argv[2]

dataproc/snippets/create_cluster_test.py

@@ -21,20 +21,26 @@
 import create_cluster
 
 
-PROJECT_ID = os.environ['GOOGLE_CLOUD_PROJECT']
-REGION = 'us-central1'
-CLUSTER_NAME = 'py-cc-test-{}'.format(str(uuid.uuid4()))
+PROJECT_ID = os.environ["GOOGLE_CLOUD_PROJECT"]
+REGION = "us-central1"
+CLUSTER_NAME = "py-cc-test-{}".format(str(uuid.uuid4()))
 
 
 @pytest.fixture(autouse=True)
 def teardown():
     yield
 
-    cluster_client = dataproc.ClusterControllerClient(client_options={
-        'api_endpoint': f'{REGION}-dataproc.googleapis.com:443'
-    })
+    cluster_client = dataproc.ClusterControllerClient(
+        client_options={"api_endpoint": f"{REGION}-dataproc.googleapis.com:443"}
+    )
     # Client library function
-    operation = cluster_client.delete_cluster(PROJECT_ID, REGION, CLUSTER_NAME)
+    operation = cluster_client.delete_cluster(
+        request={
+            "project_id": PROJECT_ID,
+            "region": REGION,
+            "cluster_name": CLUSTER_NAME,
+        }
+    )
     # Wait for cluster to delete
     operation.result()
 

dataproc/snippets/dataproc_e2e_donttest.py

@@ -20,13 +20,12 @@
 
 import submit_job_to_cluster
 
-PROJECT = os.environ['GOOGLE_CLOUD_PROJECT']
-BUCKET = os.environ['CLOUD_STORAGE_BUCKET']
-CLUSTER_NAME = 'testcluster3'
-ZONE = 'us-central1-b'
+PROJECT = os.environ["GOOGLE_CLOUD_PROJECT"]
+BUCKET = os.environ["CLOUD_STORAGE_BUCKET"]
+CLUSTER_NAME = "testcluster3"
+ZONE = "us-central1-b"
 
 
 def test_e2e():
-    output = submit_job_to_cluster.main(
-        PROJECT, ZONE, CLUSTER_NAME, BUCKET)
+    output = submit_job_to_cluster.main(PROJECT, ZONE, CLUSTER_NAME, BUCKET)
     assert b"['Hello,', 'dog', 'elephant', 'panther', 'world!']" in output

dataproc/snippets/instantiate_inline_workflow_template.py

@@ -36,71 +36,61 @@ def instantiate_inline_workflow_template(project_id, region):
 
     # Create a client with the endpoint set to the desired region.
     workflow_template_client = dataproc.WorkflowTemplateServiceClient(
-        client_options={
-            'api_endpoint': f'{region}-dataproc.googleapis.com:443'
-        }
+        client_options={"api_endpoint": f"{region}-dataproc.googleapis.com:443"}
     )
 
-    parent = workflow_template_client.region_path(project_id, region)
+    parent = "projects/{}/regions/{}".format(project_id, region)
 
     template = {
-        'jobs': [
+        "jobs": [
             {
-                'hadoop_job': {
-                    'main_jar_file_uri': 'file:///usr/lib/hadoop-mapreduce/'
-                    'hadoop-mapreduce-examples.jar',
-                    'args': [
-                        'teragen',
-                        '1000',
-                        'hdfs:///gen/'
-                    ]
+                "hadoop_job": {
+                    "main_jar_file_uri": "file:///usr/lib/hadoop-mapreduce/"
+                    "hadoop-mapreduce-examples.jar",
+                    "args": ["teragen", "1000", "hdfs:///gen/"],
                 },
-                'step_id': 'teragen'
+                "step_id": "teragen",
             },
             {
-                'hadoop_job': {
-                    'main_jar_file_uri': 'file:///usr/lib/hadoop-mapreduce/'
-                    'hadoop-mapreduce-examples.jar',
-                    'args': [
-                        'terasort',
-                        'hdfs:///gen/',
-                        'hdfs:///sort/'
-                    ]
+                "hadoop_job": {
+                    "main_jar_file_uri": "file:///usr/lib/hadoop-mapreduce/"
+                    "hadoop-mapreduce-examples.jar",
+                    "args": ["terasort", "hdfs:///gen/", "hdfs:///sort/"],
                 },
-                'step_id': 'terasort',
-                'prerequisite_step_ids': [
-                    'teragen'
-                ]
-            }],
-        'placement': {
-            'managed_cluster': {
-                'cluster_name': 'my-managed-cluster',
-                'config': {
-                    'gce_cluster_config': {
+                "step_id": "terasort",
+                "prerequisite_step_ids": ["teragen"],
+            },
+        ],
+        "placement": {
+            "managed_cluster": {
+                "cluster_name": "my-managed-cluster",
+                "config": {
+                    "gce_cluster_config": {
                         # Leave 'zone_uri' empty for 'Auto Zone Placement'
                         # 'zone_uri': ''
-                        'zone_uri': 'us-central1-a'
+                        "zone_uri": "us-central1-a"
                     }
-                }
+                },
             }
-        }
+        },
     }
 
     # Submit the request to instantiate the workflow from an inline template.
     operation = workflow_template_client.instantiate_inline_workflow_template(
-        parent, template
+        request={"parent": parent, "template": template}
     )
     operation.result()
 
     # Output a success message.
-    print('Workflow ran successfully.')
+    print("Workflow ran successfully.")
     # [END dataproc_instantiate_inline_workflow_template]
 
 
 if __name__ == "__main__":
     if len(sys.argv) < 3:
-        sys.exit('python instantiate_inline_workflow_template.py '
-                 + 'project_id region')
+        sys.exit(
+            "python instantiate_inline_workflow_template.py " + "project_id region"
+        )
 
     project_id = sys.argv[1]
     region = sys.argv[2]

dataproc/snippets/instantiate_inline_workflow_template_test.py

@@ -17,8 +17,8 @@
 import instantiate_inline_workflow_template
 
 
-PROJECT_ID = os.environ['GOOGLE_CLOUD_PROJECT']
-REGION = 'us-central1'
+PROJECT_ID = os.environ["GOOGLE_CLOUD_PROJECT"]
+REGION = "us-central1"
 
 
 def test_workflows(capsys):

dataproc/snippets/list_clusters.py

@@ -19,45 +19,50 @@
 import argparse
 
 from google.cloud import dataproc_v1
-from google.cloud.dataproc_v1.gapic.transports import (
-    cluster_controller_grpc_transport)
+from google.cloud.dataproc_v1.gapic.transports import cluster_controller_grpc_transport
 
 
 # [START dataproc_list_clusters]
 def list_clusters(dataproc, project, region):
     """List the details of clusters in the region."""
-    for cluster in dataproc.list_clusters(project, region):
-        print(('{} - {}'.format(cluster.cluster_name,
-                                cluster.status.State.Name(
-                                    cluster.status.state))))
+    for cluster in dataproc.list_clusters(
+        request={"project_id": project, "region": region}
+    ):
+        print(
+            (
+                "{} - {}".format(
+                    cluster.cluster_name,
+                    cluster.status.State.Name(cluster.status.state),
+                )
+            )
+        )
+
+
 # [END dataproc_list_clusters]
 
 
 def main(project_id, region):
 
-    if region == 'global':
+    if region == "global":
         # Use the default gRPC global endpoints.
         dataproc_cluster_client = dataproc_v1.ClusterControllerClient()
     else:
         # Use a regional gRPC endpoint. See:
         # https://cloud.google.com/dataproc/docs/concepts/regional-endpoints
-        client_transport = (
-            cluster_controller_grpc_transport.ClusterControllerGrpcTransport(
-                address='{}-dataproc.googleapis.com:443'.format(region)))
-        dataproc_cluster_client = dataproc_v1.ClusterControllerClient(
-            client_transport)
+        client_transport = cluster_controller_grpc_transport.ClusterControllerGrpcTransport(
+            address="{}-dataproc.googleapis.com:443".format(region)
+        )
+        dataproc_cluster_client = dataproc_v1.ClusterControllerClient(client_transport)
 
     list_clusters(dataproc_cluster_client, project_id, region)
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     parser = argparse.ArgumentParser(
-        description=__doc__, formatter_class=(
-            argparse.RawDescriptionHelpFormatter))
-    parser.add_argument(
-        '--project_id', help='Project ID to access.', required=True)
-    parser.add_argument(
-        '--region', help='Region of clusters to list.', required=True)
+        description=__doc__, formatter_class=(argparse.RawDescriptionHelpFormatter)
+    )
+    parser.add_argument("--project_id", help="Project ID to access.", required=True)
+    parser.add_argument("--region", help="Region of clusters to list.", required=True)
 
     args = parser.parse_args()
     main(args.project_id, args.region)

dataproc/snippets/pyspark_sort.py

@@ -22,7 +22,7 @@
 import pyspark
 
 sc = pyspark.SparkContext()
-rdd = sc.parallelize(['Hello,', 'world!', 'dog', 'elephant', 'panther'])
+rdd = sc.parallelize(["Hello,", "world!", "dog", "elephant", "panther"])
 words = sorted(rdd.collect())
 print(words)
 # [END dataproc_pyspark_sort]

dataproc/snippets/pyspark_sort_gcs.py

@@ -25,6 +25,6 @@
 import pyspark
 
 sc = pyspark.SparkContext()
-rdd = sc.textFile('gs://path-to-your-GCS-file')
+rdd = sc.textFile("gs://path-to-your-GCS-file")
 print(sorted(rdd.collect()))
 # [END dataproc_pyspark_sort_gcs]