feat(sdk): add experiment_id parameter to create run methods (#9004)

Co-authored-by: alenawang <alena.n.wang@gmail.com>
Co-authored-by: andreafehrman <andrea.k.fehrman@vanderbilt.edu>
Co-authored-by: owmasch <owenmaschal0598@gmail.com>
Co-authored-by: ryanrusson <ryan.russon@gmail.com>

sdk/python/kfp/client/client.py

@@ -507,7 +507,7 @@ class Client:
             return result.pipelines[0].id
         elif len(result.pipelines) > 1:
             raise ValueError(
-                f'Multiple pipelines with the name: {name} found, the name needs to be unique'
+                f'Multiple pipelines with the name: {name} found, the name needs to be unique.'
             )
         return None
 
@@ -572,7 +572,7 @@ class Client:
         namespace = namespace or self.get_user_namespace()
         if experiment_id is None and experiment_name is None:
             raise ValueError(
-                'Either experiment_id or experiment_name is required')
+                'Either experiment_id or experiment_name is required.')
         if experiment_id is not None:
             return self._experiment_api.get_experiment(id=experiment_id)
         experiment_filter = json.dumps({
@@ -916,7 +916,7 @@ class Client:
         if all([interval_second, cron_expression
                ]) or not any([interval_second, cron_expression]):
             raise ValueError(
-                'Either interval_second or cron_expression is required')
+                'Either interval_second or cron_expression is required.')
         if interval_second is not None:
             trigger = kfp_server_api.ApiTrigger(
                 periodic_schedule=kfp_server_api.ApiPeriodicSchedule(
@@ -1025,6 +1025,7 @@ class Client:
         pipeline_root: Optional[str] = None,
         enable_caching: Optional[bool] = None,
         service_account: Optional[str] = None,
+        experiment_id: Optional[str] = None,
     ) -> RunPipelineResult:
         """Runs pipeline on KFP-enabled Kubernetes cluster.
 
@@ -1035,7 +1036,7 @@ class Client:
             pipeline_func: Pipeline function constructed with ``@kfp.dsl.pipeline`` decorator.
             arguments: Arguments to the pipeline function provided as a dict.
             run_name: Name of the run to be shown in the UI.
-            experiment_name: Name of the experiment to add the run to.
+            experiment_name: Name of the experiment to add the run to. You cannot specify both experiment_name and experiment_id.
             namespace: Kubernetes namespace to use. Used for multi-user deployments. For single-user deployments, this should be left as ``None``.
             pipeline_root: Root path of the pipeline outputs.
             enable_caching: Whether or not to enable caching for the
@@ -1046,6 +1047,7 @@ class Client:
                 compile time settings).
             service_account: Specifies which Kubernetes service
                 account to use for this run.
+            experiment_id: ID of the experiment to add the run to. You cannot specify both experiment_id and experiment_name.
 
         Returns:
             ``RunPipelineResult`` object containing information about the pipeline run.
@@ -1066,6 +1068,7 @@ class Client:
                 pipeline_file=pipeline_package_path,
                 arguments=arguments,
                 run_name=run_name,
+                experiment_id=experiment_id,
                 experiment_name=experiment_name,
                 namespace=namespace,
                 pipeline_root=pipeline_root,
@@ -1083,6 +1086,7 @@ class Client:
         pipeline_root: Optional[str] = None,
         enable_caching: Optional[bool] = None,
         service_account: Optional[str] = None,
+        experiment_id: Optional[str] = None,
     ) -> RunPipelineResult:
         """Runs pipeline on KFP-enabled Kubernetes cluster.
 
@@ -1093,7 +1097,7 @@ class Client:
             pipeline_file: A compiled pipeline package file.
             arguments: Arguments to the pipeline function provided as a dict.
             run_name:  Name of the run to be shown in the UI.
-            experiment_name: Name of the experiment to add the run to.
+            experiment_name: Name of the experiment to add the run to. You cannot specify both experiment_name and experiment_id.
             namespace: Kubernetes namespace to use. Used for multi-user deployments. For single-user deployments, this should be left as ``None``.
             pipeline_root: Root path of the pipeline outputs.
             enable_caching: Whether or not to enable caching for the
@@ -1104,6 +1108,7 @@ class Client:
                 compile time settings).
             service_account: Specifies which Kubernetes service
                 account to use for this run.
+            experiment_id: ID of the experiment to add the run to. You cannot specify both experiment_id and experiment_name.
 
         Returns:
             ``RunPipelineResult`` object containing information about the pipeline run.
@@ -1111,22 +1116,31 @@ class Client:
 
         #TODO: Check arguments against the pipeline function
         pipeline_name = os.path.basename(pipeline_file)
-        experiment_name = experiment_name or os.environ.get(
-            KF_PIPELINES_DEFAULT_EXPERIMENT_NAME, None)
-        overridden_experiment_name = os.environ.get(
-            KF_PIPELINES_OVERRIDE_EXPERIMENT_NAME, experiment_name)
-        if overridden_experiment_name != experiment_name:
-            warnings.warn(
-                f'Changing experiment name from "{experiment_name}" to "{overridden_experiment_name}".'
-            )
-        experiment_name = overridden_experiment_name or 'Default'
+
+        if (experiment_name is not None) and (experiment_id is not None):
+            raise ValueError(
+                'You cannot specify both experiment_name and experiment_id.')
+
+        if not experiment_id:
+            experiment_name = experiment_name or os.environ.get(
+                KF_PIPELINES_DEFAULT_EXPERIMENT_NAME, None)
+            overridden_experiment_name = os.environ.get(
+                KF_PIPELINES_OVERRIDE_EXPERIMENT_NAME, experiment_name)
+            if overridden_experiment_name != experiment_name:
+                warnings.warn(
+                    f'Changing experiment name from "{experiment_name}" to "{overridden_experiment_name}".'
+                )
+            experiment_name = overridden_experiment_name or 'Default'
+            experiment = self.create_experiment(
+                name=experiment_name, namespace=namespace)
+            experiment_id = experiment.id
+
         run_name = run_name or (
             pipeline_name + ' ' +
             datetime.datetime.now().strftime('%Y-%m-%d %H-%M-%S'))
-        experiment = self.create_experiment(
-            name=experiment_name, namespace=namespace)
+
         run_info = self.run_pipeline(
-            experiment_id=experiment.id,
+            experiment_id=experiment_id,
             job_name=run_name,
             pipeline_package_path=pipeline_file,
             params=arguments,
@@ -1411,7 +1425,7 @@ class Client:
 
         if all([pipeline_id, pipeline_name
                ]) or not any([pipeline_id, pipeline_name]):
-            raise ValueError('Either pipeline_id or pipeline_name is required')
+            raise ValueError('Either pipeline_id or pipeline_name is required.')
 
         if pipeline_name:
             pipeline_id = self.get_pipeline_id(pipeline_name)