Refactor teardown handling into a separate helper

Author: Val Brodsky

libs/labelbox/tests/conftest.py

@@ -7,6 +7,7 @@
 import re
 import uuid
 import time
+from labelbox.schema.project import Project
 import requests
 import pytest
 from types import SimpleNamespace
@@ -768,7 +769,7 @@ def configured_batch_project_with_label(client, dataset, data_row,
 @pytest.fixture
 def configured_batch_project_with_multiple_datarows(client, dataset, data_rows,
                                                     wait_for_label_processing,
-                                                    rand_gen):
+                                                    rand_gen, teardown_helpers):
     """Project with a batch having multiple datarows
     Project contains an ontology with 1 bbox tool
     Additionally includes a create_label method for any needed extra labels
@@ -787,18 +788,7 @@ def configured_batch_project_with_multiple_datarows(client, dataset, data_rows,
 
     yield [project, dataset, data_rows]
 
-    featureSchemaIds = [tool.feature_schema_id for tool in ontology.tools]
-    ontology = project.ontology()
-    ontology_id = ontology.uid
-    client = project.client
-
-    for label in project.labels():
-        label.delete()
-
-    project.delete()
-    client.delete_unused_ontology(ontology_id)
-    for featureSchemaId in featureSchemaIds:
-        project.client.delete_unused_feature_schema(featureSchemaId)
+    teardown_helpers.teardown_project_labels_ontology_feature_schemas(project)
 
 
 @pytest.fixture
@@ -1181,3 +1171,37 @@ def requested_labeling_service(
     labeling_service.request()
 
     yield project, project.get_labeling_service()
+
+
+class TearDownHelpers:
+
+    @staticmethod
+    def teardown_project_labels_ontology_feature_schemas(project: Project):
+        """
+        Call this function to release project, labels, ontology and feature schemas in fixture teardown
+
+        NOTE: exception handling is not required as this is a fixture teardown
+        """
+        ontology = project.ontology()
+        ontology_id = ontology.uid
+        client = project.client
+
+        # featureSchemaIds = [tool.feature_schema_id for tool in ontology_builder.tools]
+        featureSchemaIds = [
+            feature["featureSchemaId"]
+            for feature in ontology.normalized["classifications"]
+        ]
+
+        labels = list(project.labels())
+        for label in labels:
+            label.delete()
+
+        project.delete()
+        client.delete_unused_ontology(ontology_id)
+        for featureSchemaId in featureSchemaIds:
+            project.client.delete_unused_feature_schema(featureSchemaId)
+
+
+@pytest.fixture
+def teardown_helpers():
+    return TearDownHelpers()

libs/labelbox/tests/data/annotation_import/conftest.py

@@ -1,4 +1,3 @@
-import itertools
 import uuid
 
 from labelbox.schema.model_run import ModelRun
@@ -14,8 +13,6 @@
 from typing import Tuple, Type
 from labelbox.schema.annotation_import import LabelImport, AnnotationImportState
 from pytest import FixtureRequest
-from contextlib import suppress
-
 """
 The main fixtures of this library are configured_project and configured_project_by_global_key. Both fixtures generate data rows with a parametrize media type. They create the amount of data rows equal to the DATA_ROW_COUNT variable below. The data rows are generated with a factory fixture that returns a function that allows you to pass a global key. The ontologies are generated normalized and based on the MediaType given (i.e. only features supported by MediaType are created). This ontology is later used to obtain the correct annotations with the prediction_id_mapping and corresponding inferences. Each data row will have all possible annotations attached supported for the MediaType. 
 """