fix visualizer for pipeline processing job steps

Author: danabens

src/sagemaker/lineage/visualizer.py

@@ -105,7 +105,7 @@ def _get_start_arn_from_pipeline_execution_step(self, pipeline_execution_step):
             return None
 
         metadata = pipeline_execution_step["Metadata"]
-        jobs = ["TrainingJob", "ProccessingJob", "TransformJob"]
+        jobs = ["TrainingJob", "ProcessingJob", "TransformJob"]
         for job in jobs:
             if job in metadata and metadata[job]:
                 job_arn = metadata[job]["Arn"]

tests/unit/sagemaker/lineage/conftest.py

@@ -0,0 +1,27 @@
+# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License"). You
+# may not use this file except in compliance with the License. A copy of
+# the License is located at
+#
+#     http://aws.amazon.com/apache2.0/
+#
+# or in the "license" file accompanying this file. This file 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.
+from __future__ import absolute_import
+
+import pytest
+from sagemaker.lineage import visualizer
+import unittest.mock
+
+
+@pytest.fixture
+def sagemaker_session():
+    return unittest.mock.Mock()
+
+
+@pytest.fixture
+def viz(sagemaker_session):
+    return visualizer.LineageTableVisualizer(sagemaker_session)

tests/unit/sagemaker/lineage/test_action.py

@@ -15,15 +15,9 @@
 import datetime
 import unittest.mock
 
-import pytest
 from sagemaker.lineage import action, _api_types
 
 
-@pytest.fixture
-def sagemaker_session():
-    return unittest.mock.Mock()
-
-
 def test_create(sagemaker_session):
     sagemaker_session.sagemaker_client.create_action.return_value = {
         "ActionArn": "bazz",

tests/unit/sagemaker/lineage/test_artifact.py

@@ -15,15 +15,9 @@
 import datetime
 import unittest.mock
 
-import pytest
 from sagemaker.lineage import artifact, _api_types
 
 
-@pytest.fixture
-def sagemaker_session():
-    return unittest.mock.Mock()
-
-
 def test_create(sagemaker_session):
     sagemaker_session.sagemaker_client.create_artifact.return_value = {
         "ArtifactArn": "bazz",

tests/unit/sagemaker/lineage/test_association.py

@@ -15,15 +15,9 @@
 import datetime
 import unittest.mock
 
-import pytest
 from sagemaker.lineage import association, _api_types
 
 
-@pytest.fixture
-def sagemaker_session():
-    return unittest.mock.Mock()
-
-
 def test_create(sagemaker_session):
     sagemaker_session.sagemaker_client.add_association.return_value = {
         "AssociationArn": "bazz",

tests/unit/sagemaker/lineage/test_endpoint_context.py

@@ -14,15 +14,9 @@
 
 import unittest.mock
 
-import pytest
 from sagemaker.lineage import context, _api_types
 
 
-@pytest.fixture
-def sagemaker_session():
-    return unittest.mock.Mock()
-
-
 def test_models(sagemaker_session):
     obj = context.EndpointContext(sagemaker_session, context_name="foo", context_arn="bazz")
 

tests/unit/sagemaker/lineage/test_model_artifact.py

@@ -14,15 +14,9 @@
 
 import unittest.mock
 
-import pytest
 from sagemaker.lineage import artifact, _api_types
 
 
-@pytest.fixture
-def sagemaker_session():
-    return unittest.mock.Mock()
-
-
 def test_trained_models(sagemaker_session):
     model_artifact_obj = artifact.ModelArtifact(
         sagemaker_session, artifact_arn="model-artifact-arn"

tests/unit/sagemaker/lineage/test_visualizer.py

@@ -14,33 +14,21 @@
 
 import unittest.mock
 
-import pytest
-from sagemaker.lineage import visualizer
 import pandas as pd
 from collections import OrderedDict
 
 
-@pytest.fixture
-def sagemaker_session():
-    return unittest.mock.Mock()
-
-
-@pytest.fixture
-def vizualizer(sagemaker_session):
-    return visualizer.LineageTableVisualizer(sagemaker_session)
-
-
-def test_friendly_name_short_uri(vizualizer, sagemaker_session):
+def test_friendly_name_short_uri(viz, sagemaker_session):
     uri = "s3://f-069083975568/train.txt"
     arn = "test_arn"
     sagemaker_session.sagemaker_client.describe_artifact.return_value = {
         "Source": {"SourceUri": uri, "SourceTypes": ""}
     }
-    actual_name = vizualizer._get_friendly_name(name=None, arn=arn, entity_type="artifact")
+    actual_name = viz._get_friendly_name(name=None, arn=arn, entity_type="artifact")
     assert uri == actual_name
 
 
-def test_friendly_name_long_uri(vizualizer, sagemaker_session):
+def test_friendly_name_long_uri(viz, sagemaker_session):
     uri = (
         "s3://flintstone-end-to-end-tests-gamma-us-west-2-069083975568/results/canary-auto-1608761252626/"
         "preprocessed-data/tuning_data/train.txt"
@@ -49,12 +37,12 @@ def test_friendly_name_long_uri(vizualizer, sagemaker_session):
     sagemaker_session.sagemaker_client.describe_artifact.return_value = {
         "Source": {"SourceUri": uri, "SourceTypes": ""}
     }
-    actual_name = vizualizer._get_friendly_name(name=None, arn=arn, entity_type="artifact")
+    actual_name = viz._get_friendly_name(name=None, arn=arn, entity_type="artifact")
     expected_name = "s3://.../preprocessed-data/tuning_data/train.txt"
     assert expected_name == actual_name
 
 
-def test_trial_component_name(sagemaker_session, vizualizer):
+def test_trial_component_name(viz, sagemaker_session):
     name = "tc-name"
 
     sagemaker_session.sagemaker_client.describe_trial_component.return_value = {
@@ -90,7 +78,7 @@ def test_trial_component_name(sagemaker_session, vizualizer):
         },
     ]
 
-    df = vizualizer.show(trial_component_name=name)
+    df = viz.show(trial_component_name=name)
 
     sagemaker_session.sagemaker_client.describe_trial_component.assert_called_with(
         TrialComponentName=name,
@@ -119,3 +107,71 @@ def test_trial_component_name(sagemaker_session, vizualizer):
     )
 
     pd.testing.assert_frame_equal(expected_dataframe, df)
+
+
+def test_processing_job_pipeline_execution_step(viz, sagemaker_session):
+
+    sagemaker_session.sagemaker_client.list_trial_components.return_value = {
+        "TrialComponentSummaries": [{"TrialComponentArn": "tc-arn"}]
+    }
+
+    sagemaker_session.sagemaker_client.list_associations.side_effect = [
+        {
+            "AssociationSummaries": [
+                {
+                    "SourceArn": "a:b:c:d:e:artifact/src-arn-1",
+                    "SourceName": "source-name-1",
+                    "SourceType": "source-type-1",
+                    "DestinationArn": "a:b:c:d:e:artifact/dest-arn-1",
+                    "DestinationName": "dest-name-1",
+                    "DestinationType": "dest-type-1",
+                    "AssociationType": "type-1",
+                }
+            ]
+        },
+        {
+            "AssociationSummaries": [
+                {
+                    "SourceArn": "a:b:c:d:e:artifact/src-arn-2",
+                    "SourceName": "source-name-2",
+                    "SourceType": "source-type-2",
+                    "DestinationArn": "a:b:c:d:e:artifact/dest-arn-2",
+                    "DestinationName": "dest-name-2",
+                    "DestinationType": "dest-type-2",
+                    "AssociationType": "type-2",
+                }
+            ]
+        },
+    ]
+
+    step = {"Metadata": {"ProcessingJob": {"Arn": "proc-job-arn"}}}
+
+    df = viz.show(pipeline_execution_step=step)
+
+    sagemaker_session.sagemaker_client.list_trial_components.assert_called_with(
+        SourceArn="proc-job-arn",
+    )
+
+    expected_calls = [
+        unittest.mock.call(
+            DestinationArn="tc-arn",
+        ),
+        unittest.mock.call(
+            SourceArn="tc-arn",
+        ),
+    ]
+    assert expected_calls == sagemaker_session.sagemaker_client.list_associations.mock_calls
+
+    expected_dataframe = pd.DataFrame.from_dict(
+        OrderedDict(
+            [
+                ("Name/Source", ["source-name-1", "dest-name-2"]),
+                ("Direction", ["Input", "Output"]),
+                ("Type", ["source-type-1", "dest-type-2"]),
+                ("Association Type", ["type-1", "type-2"]),
+                ("Lineage Type", ["artifact", "artifact"]),
+            ]
+        )
+    )
+
+    pd.testing.assert_frame_equal(expected_dataframe, df)