Fix import for integration test

pipeline/workflow/cloud_workflow.py

@@ -0,0 +1,77 @@
+# Copyright 2026 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""
+This module contains utilities to help set up and run cloud workflows.
+"""
+import json
+import time
+
+from absl import logging
+from google.cloud.workflows import executions_v1
+
+
+def trigger_workflow_and_wait(project_id: str, location: str, workflow_id: str,
+                              workflow_args: dict):
+    """Triggers a workflow and waits for its completion.
+
+    Args:
+        project_id: ID of the GCP project.
+        location: Region where the workflow is located.
+        workflow_id: ID of the workflow to execute.
+        workflow_args: Arguments to pass to the workflow.
+
+    Returns:
+        The result of the execution if successful.
+
+    Raises:
+        RuntimeError: If the workflow execution fails.
+    """
+    execution_client = executions_v1.ExecutionsClient()
+    parent = execution_client.workflow_path(project_id, location, workflow_id)
+
+    logging.info(
+        f"Triggering workflow: {workflow_id} with args: {workflow_args}")
+
+    try:
+        execution = executions_v1.Execution(argument=json.dumps(workflow_args))
+        response = execution_client.create_execution(parent=parent,
+                                                     execution=execution)
+        execution_name = response.name
+        logging.info(f"Execution started: {execution_name}")
+
+        # Poll for execution completion
+        backoff_delay = 1
+        while True:
+            execution = execution_client.get_execution(
+                request={"name": execution_name})
+            state = execution.state
+
+            if state != executions_v1.Execution.State.ACTIVE:
+                logging.info(f"Execution finished with state: {state}")
+                if state == executions_v1.Execution.State.SUCCEEDED:
+                    logging.info(f"Workflow {workflow_id} succeeded.")
+                    return execution.result
+                else:
+                    logging.error(
+                        f"Workflow {workflow_id} failed: {execution.error}")
+                    raise RuntimeError(
+                        f"Workflow {workflow_id} failed with state {state}")
+
+            time.sleep(backoff_delay)
+            backoff_delay = min(backoff_delay * 2,
+                                60)  # Exponential backoff up to 60s
+
+    except Exception as e:
+        logging.error(f"Error executing workflow {workflow_id}: {e}")
+        raise

pipeline/workflow/spanner_ingestion_test.py

@@ -22,10 +22,8 @@
 from absl import app
 from absl import logging
 
-# Add path for executor modules
-sys.path.append(
-    os.path.abspath(os.path.join(os.path.dirname(__file__), '../executor/app')))
-from executor import cloud_workflow
+sys.path.append(os.path.abspath(os.path.dirname(__file__)))
+import cloud_workflow
 
 from google.cloud import spanner