Dynamic bucket name for Tekton test

ods_ci/libs/DataSciencePipelinesKfpTekton.py

@@ -67,6 +67,16 @@ def get_secret(self, api, project, name):
         )
         return json.loads(secret_json)
 
+    def get_bucket_name(self, api, project):
+        bucket_name, _ = api.run_oc(
+            f"oc get dspa -n {project} pipelines-definition -o json"
+        )
+        objectStorage = json.loads(bucket_name)['spec']['objectStorage']
+        if 'minio' in objectStorage:
+            return objectStorage['minio']['bucket']
+        else:
+            return objectStorage['externalStorage']['bucket']
+
     def import_souce_code(self, path):
         module_name = os.path.basename(path).replace("-", "_")
         spec = importlib.util.spec_from_loader(
@@ -83,6 +93,7 @@ def kfp_tekton_create_run_from_pipeline_func(
     ):
         client, api = self.get_client(user, pwd, project, route_name)
         mlpipeline_minio_artifact_secret = self.get_secret(api, project, 'mlpipeline-minio-artifact')
+        bucket_name = self.get_bucket_name(api, project)
         # the current path is from where you are running the script
         # sh ods_ci/run_robot_test.sh
         # the current_path will be ods-ci
@@ -97,7 +108,8 @@ def kfp_tekton_create_run_from_pipeline_func(
         # if you need to see the yaml, for debugging purpose, call: TektonCompiler().compile(pipeline, f'{fn}.yaml')
         result = client.create_run_from_pipeline_func(
             pipeline_func=pipeline, arguments={
-                'mlpipeline_minio_artifact_secret': mlpipeline_minio_artifact_secret["data"]
+                'mlpipeline_minio_artifact_secret': mlpipeline_minio_artifact_secret["data"],
+                'bucket_name': bucket_name
             }
         )
         # easy to debug and double check failures

ods_ci/tests/Resources/Files/pipeline-samples/upload_download.py

@@ -49,7 +49,7 @@ def receive_file(
     shutil.copyfile(incomingfile, saveartifact)
 
 
-def test_uploaded_artifact(previous_step: kfp.components.InputPath(), file_size_bytes: int, mlpipeline_minio_artifact_secret: str):
+def test_uploaded_artifact(previous_step: kfp.components.InputPath(), file_size_bytes: int, mlpipeline_minio_artifact_secret: str, bucket_name: str):
     from minio import Minio
     import base64
     import json
@@ -76,7 +76,7 @@ def inner_decode(my_str):
         secure=secure
     )
 
-    data = client.get_object('mlpipeline', object_name)
+    data = client.get_object(bucket_name, object_name)
     with open('my-testfile', 'wb') as file_data:
         for d in data.stream(32 * 1024):
             file_data.write(d)
@@ -113,7 +113,7 @@ def inner_decode(my_str):
 @kfp.dsl.pipeline(
     name="Test Data Passing Pipeline 1",
 )
-def wire_up_pipeline(mlpipeline_minio_artifact_secret):
+def wire_up_pipeline(mlpipeline_minio_artifact_secret, bucket_name):
     import json
 
     file_size_mb = 20
@@ -125,6 +125,6 @@ def wire_up_pipeline(mlpipeline_minio_artifact_secret):
         send_file_task.output,
     ).add_pod_annotation(name='artifact_outputs', value=json.dumps(['saveartifact']))
 
-    test_uploaded_artifact_op(receive_file_task.output, file_size_bytes, mlpipeline_minio_artifact_secret)
+    test_uploaded_artifact_op(receive_file_task.output, file_size_bytes, mlpipeline_minio_artifact_secret, bucket_name)