diff --git a/requirements/extras/test_requirements.txt b/requirements/extras/test_requirements.txt
index f44ac76c77..d3b8c129e0 100644
--- a/requirements/extras/test_requirements.txt
+++ b/requirements/extras/test_requirements.txt
@@ -9,7 +9,7 @@ coverage>=5.2, <6.2
 mock==4.0.3
 contextlib2==21.6.0
 awslogs==0.14.0
-black==22.3.0
+black==24.3.0
 stopit==1.1.2
 # Update tox.ini to have correct version of airflow constraints file
 apache-airflow==2.8.4
diff --git a/src/sagemaker/amazon/record_pb2.py b/src/sagemaker/amazon/record_pb2.py
index d06b38663b..9dd6893958 100644
--- a/src/sagemaker/amazon/record_pb2.py
+++ b/src/sagemaker/amazon/record_pb2.py
@@ -31,7 +31,7 @@
     (_message.Message,),
     {
         "DESCRIPTOR": _FLOAT32TENSOR,
-        "__module__": "record_pb2"
+        "__module__": "record_pb2",
         # @@protoc_insertion_point(class_scope:aialgs.data.Float32Tensor)
     },
 )
@@ -42,7 +42,7 @@
     (_message.Message,),
     {
         "DESCRIPTOR": _FLOAT64TENSOR,
-        "__module__": "record_pb2"
+        "__module__": "record_pb2",
         # @@protoc_insertion_point(class_scope:aialgs.data.Float64Tensor)
     },
 )
@@ -53,7 +53,7 @@
     (_message.Message,),
     {
         "DESCRIPTOR": _INT32TENSOR,
-        "__module__": "record_pb2"
+        "__module__": "record_pb2",
         # @@protoc_insertion_point(class_scope:aialgs.data.Int32Tensor)
     },
 )
@@ -64,7 +64,7 @@
     (_message.Message,),
     {
         "DESCRIPTOR": _BYTES,
-        "__module__": "record_pb2"
+        "__module__": "record_pb2",
         # @@protoc_insertion_point(class_scope:aialgs.data.Bytes)
     },
 )
@@ -75,7 +75,7 @@
     (_message.Message,),
     {
         "DESCRIPTOR": _VALUE,
-        "__module__": "record_pb2"
+        "__module__": "record_pb2",
         # @@protoc_insertion_point(class_scope:aialgs.data.Value)
     },
 )
@@ -90,7 +90,7 @@
             (_message.Message,),
             {
                 "DESCRIPTOR": _RECORD_FEATURESENTRY,
-                "__module__": "record_pb2"
+                "__module__": "record_pb2",
                 # @@protoc_insertion_point(class_scope:aialgs.data.Record.FeaturesEntry)
             },
         ),
@@ -99,12 +99,12 @@
             (_message.Message,),
             {
                 "DESCRIPTOR": _RECORD_LABELENTRY,
-                "__module__": "record_pb2"
+                "__module__": "record_pb2",
                 # @@protoc_insertion_point(class_scope:aialgs.data.Record.LabelEntry)
             },
         ),
         "DESCRIPTOR": _RECORD,
-        "__module__": "record_pb2"
+        "__module__": "record_pb2",
         # @@protoc_insertion_point(class_scope:aialgs.data.Record)
     },
 )
diff --git a/src/sagemaker/automl/automl.py b/src/sagemaker/automl/automl.py
index 1413f3aa29..bb4059c03a 100644
--- a/src/sagemaker/automl/automl.py
+++ b/src/sagemaker/automl/automl.py
@@ -930,9 +930,9 @@ def _load_config(cls, inputs, auto_ml, expand_role=True, validate_uri=True):
 
         auto_ml_model_deploy_config = {}
         if auto_ml.auto_generate_endpoint_name is not None:
-            auto_ml_model_deploy_config[
-                "AutoGenerateEndpointName"
-            ] = auto_ml.auto_generate_endpoint_name
+            auto_ml_model_deploy_config["AutoGenerateEndpointName"] = (
+                auto_ml.auto_generate_endpoint_name
+            )
         if not auto_ml.auto_generate_endpoint_name and auto_ml.endpoint_name is not None:
             auto_ml_model_deploy_config["EndpointName"] = auto_ml.endpoint_name
 
@@ -1034,9 +1034,9 @@ def _prepare_auto_ml_stop_condition(
         if max_candidates is not None:
             stopping_condition["MaxCandidates"] = max_candidates
         if max_runtime_per_training_job_in_seconds is not None:
-            stopping_condition[
-                "MaxRuntimePerTrainingJobInSeconds"
-            ] = max_runtime_per_training_job_in_seconds
+            stopping_condition["MaxRuntimePerTrainingJobInSeconds"] = (
+                max_runtime_per_training_job_in_seconds
+            )
         if total_job_runtime_in_seconds is not None:
             stopping_condition["MaxAutoMLJobRuntimeInSeconds"] = total_job_runtime_in_seconds
 
diff --git a/src/sagemaker/automl/automlv2.py b/src/sagemaker/automl/automlv2.py
index 8b34f54a95..0819e5384e 100644
--- a/src/sagemaker/automl/automlv2.py
+++ b/src/sagemaker/automl/automlv2.py
@@ -1446,9 +1446,9 @@ def _load_config(cls, inputs, auto_ml, expand_role=True):
 
         auto_ml_model_deploy_config = {}
         if auto_ml.auto_generate_endpoint_name is not None:
-            auto_ml_model_deploy_config[
-                "AutoGenerateEndpointName"
-            ] = auto_ml.auto_generate_endpoint_name
+            auto_ml_model_deploy_config["AutoGenerateEndpointName"] = (
+                auto_ml.auto_generate_endpoint_name
+            )
         if not auto_ml.auto_generate_endpoint_name and auto_ml.endpoint_name is not None:
             auto_ml_model_deploy_config["EndpointName"] = auto_ml.endpoint_name
 
diff --git a/src/sagemaker/collection.py b/src/sagemaker/collection.py
index 7633085506..653500fee5 100644
--- a/src/sagemaker/collection.py
+++ b/src/sagemaker/collection.py
@@ -377,9 +377,11 @@ def _convert_group_resource_response(
                     {
                         "Name": collection_name,
                         "Arn": collection_arn,
-                        "Type": resource_group["Identifier"]["ResourceType"]
-                        if is_model_group
-                        else "Collection",
+                        "Type": (
+                            resource_group["Identifier"]["ResourceType"]
+                            if is_model_group
+                            else "Collection"
+                        ),
                     }
                 )
         return collection_details
diff --git a/src/sagemaker/debugger/profiler_config.py b/src/sagemaker/debugger/profiler_config.py
index 15766d6936..8ce3b643bf 100644
--- a/src/sagemaker/debugger/profiler_config.py
+++ b/src/sagemaker/debugger/profiler_config.py
@@ -162,19 +162,19 @@ def _to_request_dict(self):
         profiler_config_request["DisableProfiler"] = self.disable_profiler
 
         if self.system_monitor_interval_millis is not None:
-            profiler_config_request[
-                "ProfilingIntervalInMilliseconds"
-            ] = self.system_monitor_interval_millis
+            profiler_config_request["ProfilingIntervalInMilliseconds"] = (
+                self.system_monitor_interval_millis
+            )
 
         if self.framework_profile_params is not None:
-            profiler_config_request[
-                "ProfilingParameters"
-            ] = self.framework_profile_params.profiling_parameters
+            profiler_config_request["ProfilingParameters"] = (
+                self.framework_profile_params.profiling_parameters
+            )
 
         if self.profile_params is not None:
-            profiler_config_request[
-                "ProfilingParameters"
-            ] = self.profile_params.profiling_parameters
+            profiler_config_request["ProfilingParameters"] = (
+                self.profile_params.profiling_parameters
+            )
 
         return profiler_config_request
 
diff --git a/src/sagemaker/djl_inference/model.py b/src/sagemaker/djl_inference/model.py
index 8308215e81..efbb44460c 100644
--- a/src/sagemaker/djl_inference/model.py
+++ b/src/sagemaker/djl_inference/model.py
@@ -213,9 +213,7 @@ def _create_estimator(
     vpc_config: Optional[
         Dict[
             str,
-            List[
-                str,
-            ],
+            List[str],
         ]
     ] = None,
     volume_kms_key=None,
@@ -820,9 +818,9 @@ def _get_container_env(self):
             logger.warning("Ignoring invalid container log level: %s", self.container_log_level)
             return self.env
 
-        self.env[
-            "SERVING_OPTS"
-        ] = f'"-Dai.djl.logging.level={_LOG_LEVEL_MAP[self.container_log_level]}"'
+        self.env["SERVING_OPTS"] = (
+            f'"-Dai.djl.logging.level={_LOG_LEVEL_MAP[self.container_log_level]}"'
+        )
         return self.env
 
 
diff --git a/src/sagemaker/estimator.py b/src/sagemaker/estimator.py
index 8e03cbf132..066846564e 100644
--- a/src/sagemaker/estimator.py
+++ b/src/sagemaker/estimator.py
@@ -2539,9 +2539,9 @@ def _get_train_args(cls, estimator, inputs, experiment_config):
         # which is parsed in execution time
         # This does not check config because the EstimatorBase constuctor already did that check
         if estimator.encrypt_inter_container_traffic:
-            train_args[
-                "encrypt_inter_container_traffic"
-            ] = estimator.encrypt_inter_container_traffic
+            train_args["encrypt_inter_container_traffic"] = (
+                estimator.encrypt_inter_container_traffic
+            )
 
         if isinstance(estimator, sagemaker.algorithm.AlgorithmEstimator):
             train_args["algorithm_arn"] = estimator.algorithm_arn
@@ -2556,9 +2556,9 @@ def _get_train_args(cls, estimator, inputs, experiment_config):
             train_args["debugger_hook_config"] = estimator.debugger_hook_config._to_request_dict()
 
         if estimator.tensorboard_output_config:
-            train_args[
-                "tensorboard_output_config"
-            ] = estimator.tensorboard_output_config._to_request_dict()
+            train_args["tensorboard_output_config"] = (
+                estimator.tensorboard_output_config._to_request_dict()
+            )
 
         cls._add_spot_checkpoint_args(local_mode, estimator, train_args)
 
diff --git a/src/sagemaker/experiments/run.py b/src/sagemaker/experiments/run.py
index 8fbffe3667..33f2f0bbdc 100644
--- a/src/sagemaker/experiments/run.py
+++ b/src/sagemaker/experiments/run.py
@@ -220,9 +220,9 @@ def __init__(
             trial_component_name=self._trial_component.trial_component_name,
             sagemaker_session=sagemaker_session,
             artifact_bucket=artifact_bucket,
-            artifact_prefix=_DEFAULT_ARTIFACT_PREFIX
-            if artifact_prefix is None
-            else artifact_prefix,
+            artifact_prefix=(
+                _DEFAULT_ARTIFACT_PREFIX if artifact_prefix is None else artifact_prefix
+            ),
         )
         self._lineage_artifact_tracker = _LineageArtifactTracker(
             trial_component_arn=self._trial_component.trial_component_arn,
diff --git a/src/sagemaker/explainer/explainer_config.py b/src/sagemaker/explainer/explainer_config.py
index 6a174b27d5..72c226b15d 100644
--- a/src/sagemaker/explainer/explainer_config.py
+++ b/src/sagemaker/explainer/explainer_config.py
@@ -37,8 +37,8 @@ def _to_request_dict(self):
         request_dict = {}
 
         if self.clarify_explainer_config:
-            request_dict[
-                "ClarifyExplainerConfig"
-            ] = self.clarify_explainer_config._to_request_dict()
+            request_dict["ClarifyExplainerConfig"] = (
+                self.clarify_explainer_config._to_request_dict()
+            )
 
         return request_dict
diff --git a/src/sagemaker/feature_store/feature_processor/lineage/_feature_processor_lineage.py b/src/sagemaker/feature_store/feature_processor/lineage/_feature_processor_lineage.py
index 6bba9e5dd6..3801f57be1 100644
--- a/src/sagemaker/feature_store/feature_processor/lineage/_feature_processor_lineage.py
+++ b/src/sagemaker/feature_store/feature_processor/lineage/_feature_processor_lineage.py
@@ -115,19 +115,19 @@ class FeatureProcessorLineageHandler:
 
     def create_lineage(self, tags: Optional[List[Dict[str, str]]] = None) -> None:
         """Create and Update Feature Processor Lineage"""
-        input_feature_group_contexts: List[
-            FeatureGroupContexts
-        ] = self._retrieve_input_feature_group_contexts()
+        input_feature_group_contexts: List[FeatureGroupContexts] = (
+            self._retrieve_input_feature_group_contexts()
+        )
         output_feature_group_contexts: FeatureGroupContexts = (
             self._retrieve_output_feature_group_contexts()
         )
         input_raw_data_artifacts: List[Artifact] = self._retrieve_input_raw_data_artifacts()
-        transformation_code_artifact: Optional[
-            Artifact
-        ] = S3LineageEntityHandler.create_transformation_code_artifact(
-            transformation_code=self.transformation_code,
-            pipeline_last_update_time=self.pipeline[LAST_MODIFIED_TIME].strftime("%s"),
-            sagemaker_session=self.sagemaker_session,
+        transformation_code_artifact: Optional[Artifact] = (
+            S3LineageEntityHandler.create_transformation_code_artifact(
+                transformation_code=self.transformation_code,
+                pipeline_last_update_time=self.pipeline[LAST_MODIFIED_TIME].strftime("%s"),
+                sagemaker_session=self.sagemaker_session,
+            )
         )
         if transformation_code_artifact is not None:
             logger.info("Created Transformation Code Artifact: %s", transformation_code_artifact)
@@ -362,40 +362,40 @@ def _update_pipeline_lineage(
         current_pipeline_version_context: Context = self._get_pipeline_version_context(
             last_update_time=pipeline_context.properties[LAST_UPDATE_TIME]
         )
-        upstream_feature_group_associations: Iterator[
-            AssociationSummary
-        ] = LineageAssociationHandler.list_upstream_associations(
-            # pylint: disable=no-member
-            entity_arn=current_pipeline_version_context.context_arn,
-            source_type=FEATURE_GROUP_PIPELINE_VERSION_CONTEXT_TYPE,
-            sagemaker_session=self.sagemaker_session,
+        upstream_feature_group_associations: Iterator[AssociationSummary] = (
+            LineageAssociationHandler.list_upstream_associations(
+                # pylint: disable=no-member
+                entity_arn=current_pipeline_version_context.context_arn,
+                source_type=FEATURE_GROUP_PIPELINE_VERSION_CONTEXT_TYPE,
+                sagemaker_session=self.sagemaker_session,
+            )
         )
 
-        upstream_raw_data_associations: Iterator[
-            AssociationSummary
-        ] = LineageAssociationHandler.list_upstream_associations(
-            # pylint: disable=no-member
-            entity_arn=current_pipeline_version_context.context_arn,
-            source_type=DATA_SET,
-            sagemaker_session=self.sagemaker_session,
+        upstream_raw_data_associations: Iterator[AssociationSummary] = (
+            LineageAssociationHandler.list_upstream_associations(
+                # pylint: disable=no-member
+                entity_arn=current_pipeline_version_context.context_arn,
+                source_type=DATA_SET,
+                sagemaker_session=self.sagemaker_session,
+            )
         )
 
-        upstream_transformation_code: Iterator[
-            AssociationSummary
-        ] = LineageAssociationHandler.list_upstream_associations(
-            # pylint: disable=no-member
-            entity_arn=current_pipeline_version_context.context_arn,
-            source_type=TRANSFORMATION_CODE,
-            sagemaker_session=self.sagemaker_session,
+        upstream_transformation_code: Iterator[AssociationSummary] = (
+            LineageAssociationHandler.list_upstream_associations(
+                # pylint: disable=no-member
+                entity_arn=current_pipeline_version_context.context_arn,
+                source_type=TRANSFORMATION_CODE,
+                sagemaker_session=self.sagemaker_session,
+            )
         )
 
-        downstream_feature_group_associations: Iterator[
-            AssociationSummary
-        ] = LineageAssociationHandler.list_downstream_associations(
-            # pylint: disable=no-member
-            entity_arn=current_pipeline_version_context.context_arn,
-            destination_type=FEATURE_GROUP_PIPELINE_VERSION_CONTEXT_TYPE,
-            sagemaker_session=self.sagemaker_session,
+        downstream_feature_group_associations: Iterator[AssociationSummary] = (
+            LineageAssociationHandler.list_downstream_associations(
+                # pylint: disable=no-member
+                entity_arn=current_pipeline_version_context.context_arn,
+                destination_type=FEATURE_GROUP_PIPELINE_VERSION_CONTEXT_TYPE,
+                sagemaker_session=self.sagemaker_session,
+            )
         )
 
         is_upstream_feature_group_equal: bool = self._compare_upstream_feature_groups(
@@ -598,9 +598,9 @@ def _update_last_transformation_code(
             last_transformation_code_artifact.properties["state"]
             == TRANSFORMATION_CODE_STATUS_ACTIVE
         ):
-            last_transformation_code_artifact.properties[
-                "state"
-            ] = TRANSFORMATION_CODE_STATUS_INACTIVE
+            last_transformation_code_artifact.properties["state"] = (
+                TRANSFORMATION_CODE_STATUS_INACTIVE
+            )
             last_transformation_code_artifact.properties["exclusive_end_date"] = self.pipeline[
                 LAST_MODIFIED_TIME
             ].strftime("%s")
diff --git a/src/sagemaker/feature_store/feature_processor/lineage/_s3_lineage_entity_handler.py b/src/sagemaker/feature_store/feature_processor/lineage/_s3_lineage_entity_handler.py
index 5c2b59c228..5d8b32adb8 100644
--- a/src/sagemaker/feature_store/feature_processor/lineage/_s3_lineage_entity_handler.py
+++ b/src/sagemaker/feature_store/feature_processor/lineage/_s3_lineage_entity_handler.py
@@ -172,9 +172,9 @@ def retrieve_pipeline_schedule_artifact(
                 sagemaker_session=sagemaker_session,
             )
             pipeline_schedule_artifact.properties["pipeline_name"] = pipeline_schedule.pipeline_name
-            pipeline_schedule_artifact.properties[
-                "schedule_expression"
-            ] = pipeline_schedule.schedule_expression
+            pipeline_schedule_artifact.properties["schedule_expression"] = (
+                pipeline_schedule.schedule_expression
+            )
             pipeline_schedule_artifact.properties["state"] = pipeline_schedule.state
             pipeline_schedule_artifact.properties["start_date"] = pipeline_schedule.start_date
             pipeline_schedule_artifact.save()
diff --git a/src/sagemaker/jumpstart/artifacts/environment_variables.py b/src/sagemaker/jumpstart/artifacts/environment_variables.py
index fa5ae8900b..c28c27ed4e 100644
--- a/src/sagemaker/jumpstart/artifacts/environment_variables.py
+++ b/src/sagemaker/jumpstart/artifacts/environment_variables.py
@@ -112,16 +112,16 @@ def _retrieve_default_environment_variables(
 
             default_environment_variables.update(instance_specific_environment_variables)
 
-            retrieve_gated_env_var_for_instance_type: Callable[
-                [str], Optional[str]
-            ] = lambda instance_type: _retrieve_gated_model_uri_env_var_value(
-                model_id=model_id,
-                model_version=model_version,
-                region=region,
-                tolerate_vulnerable_model=tolerate_vulnerable_model,
-                tolerate_deprecated_model=tolerate_deprecated_model,
-                sagemaker_session=sagemaker_session,
-                instance_type=instance_type,
+            retrieve_gated_env_var_for_instance_type: Callable[[str], Optional[str]] = (
+                lambda instance_type: _retrieve_gated_model_uri_env_var_value(
+                    model_id=model_id,
+                    model_version=model_version,
+                    region=region,
+                    tolerate_vulnerable_model=tolerate_vulnerable_model,
+                    tolerate_deprecated_model=tolerate_deprecated_model,
+                    sagemaker_session=sagemaker_session,
+                    instance_type=instance_type,
+                )
             )
 
             gated_model_env_var: Optional[str] = retrieve_gated_env_var_for_instance_type(
@@ -213,10 +213,10 @@ def _retrieve_gated_model_uri_env_var_value(
         sagemaker_session=sagemaker_session,
     )
 
-    s3_key: Optional[
-        str
-    ] = model_specs.training_instance_type_variants.get_instance_specific_gated_model_key_env_var_value(  # noqa E501  # pylint: disable=c0301
-        instance_type
+    s3_key: Optional[str] = (
+        model_specs.training_instance_type_variants.get_instance_specific_gated_model_key_env_var_value(  # noqa E501  # pylint: disable=c0301
+            instance_type
+        )
     )
     if s3_key is None:
         return None
diff --git a/src/sagemaker/jumpstart/constants.py b/src/sagemaker/jumpstart/constants.py
index 9c1ea79504..242f49658a 100644
--- a/src/sagemaker/jumpstart/constants.py
+++ b/src/sagemaker/jumpstart/constants.py
@@ -243,9 +243,11 @@
         "",
         (logging.StreamHandler,),
         {
-            "emit": lambda self, *args, **kwargs: logging.StreamHandler.emit(self, *args, **kwargs)
-            if not os.environ.get(ENV_VARIABLE_DISABLE_JUMPSTART_LOGGING)
-            else None
+            "emit": lambda self, *args, **kwargs: (
+                logging.StreamHandler.emit(self, *args, **kwargs)
+                if not os.environ.get(ENV_VARIABLE_DISABLE_JUMPSTART_LOGGING)
+                else None
+            )
         },
     )()
 )
diff --git a/src/sagemaker/jumpstart/filters.py b/src/sagemaker/jumpstart/filters.py
index fc5113315d..3490db7b32 100644
--- a/src/sagemaker/jumpstart/filters.py
+++ b/src/sagemaker/jumpstart/filters.py
@@ -71,10 +71,8 @@ class ProprietaryModelFilterIdentifiers(str, Enum):
 }
 
 
-_PAD_ALPHABETIC_OPERATOR = (
-    lambda operator: f" {operator} "
-    if any(character.isalpha() for character in operator)
-    else operator
+_PAD_ALPHABETIC_OPERATOR = lambda operator: (  # noqa E731
+    f" {operator} " if any(character.isalpha() for character in operator) else operator
 )
 
 ACCEPTABLE_OPERATORS_IN_PARSE_ORDER = (
diff --git a/src/sagemaker/jumpstart/notebook_utils.py b/src/sagemaker/jumpstart/notebook_utils.py
index e724bbd1e7..732493ce3b 100644
--- a/src/sagemaker/jumpstart/notebook_utils.py
+++ b/src/sagemaker/jumpstart/notebook_utils.py
@@ -436,19 +436,19 @@ def evaluate_model(model_manifest: JumpStartModelHeader) -> Optional[Tuple[str,
             manifest_specs_cached_values[val] = getattr(model_manifest, val)
 
         if is_task_filter:
-            manifest_specs_cached_values[
-                SpecialSupportedFilterKeys.TASK
-            ] = extract_framework_task_model(model_manifest.model_id)[1]
+            manifest_specs_cached_values[SpecialSupportedFilterKeys.TASK] = (
+                extract_framework_task_model(model_manifest.model_id)[1]
+            )
 
         if is_framework_filter:
-            manifest_specs_cached_values[
-                SpecialSupportedFilterKeys.FRAMEWORK
-            ] = extract_framework_task_model(model_manifest.model_id)[0]
+            manifest_specs_cached_values[SpecialSupportedFilterKeys.FRAMEWORK] = (
+                extract_framework_task_model(model_manifest.model_id)[0]
+            )
 
         if is_model_type_filter:
-            manifest_specs_cached_values[
-                SpecialSupportedFilterKeys.MODEL_TYPE
-            ] = extract_model_type_filter_representation(model_manifest.spec_key)
+            manifest_specs_cached_values[SpecialSupportedFilterKeys.MODEL_TYPE] = (
+                extract_model_type_filter_representation(model_manifest.spec_key)
+            )
 
         if Version(model_manifest.min_version) > Version(get_sagemaker_version()):
             return None
diff --git a/src/sagemaker/jumpstart/utils.py b/src/sagemaker/jumpstart/utils.py
index 02ff39641a..63cfac0939 100644
--- a/src/sagemaker/jumpstart/utils.py
+++ b/src/sagemaker/jumpstart/utils.py
@@ -78,9 +78,9 @@ def get_jumpstart_gated_content_bucket(
             unavailable in that region.
     """
 
-    old_gated_content_bucket: Optional[
-        str
-    ] = accessors.JumpStartModelsAccessor.get_jumpstart_gated_content_bucket()
+    old_gated_content_bucket: Optional[str] = (
+        accessors.JumpStartModelsAccessor.get_jumpstart_gated_content_bucket()
+    )
 
     info_logs: List[str] = []
 
@@ -129,9 +129,9 @@ def get_jumpstart_content_bucket(
         ValueError: If JumpStart is not launched in ``region``.
     """
 
-    old_content_bucket: Optional[
-        str
-    ] = accessors.JumpStartModelsAccessor.get_jumpstart_content_bucket()
+    old_content_bucket: Optional[str] = (
+        accessors.JumpStartModelsAccessor.get_jumpstart_content_bucket()
+    )
 
     info_logs: List[str] = []
 
@@ -175,9 +175,9 @@ def get_formatted_manifest(
     manifest_dict = {}
     for header in manifest:
         header_obj = JumpStartModelHeader(header)
-        manifest_dict[
-            JumpStartVersionedModelId(header_obj.model_id, header_obj.version)
-        ] = header_obj
+        manifest_dict[JumpStartVersionedModelId(header_obj.model_id, header_obj.version)] = (
+            header_obj
+        )
     return manifest_dict
 
 
diff --git a/src/sagemaker/local/entities.py b/src/sagemaker/local/entities.py
index 02ade9bd9a..2ce37f68bd 100644
--- a/src/sagemaker/local/entities.py
+++ b/src/sagemaker/local/entities.py
@@ -832,7 +832,7 @@ def _initialize_and_validate_parameters(self, overridden_parameters):
         merged_parameters = {}
         default_parameters = {parameter.name: parameter for parameter in self.pipeline.parameters}
         if overridden_parameters is not None:
-            for (param_name, param_value) in overridden_parameters.items():
+            for param_name, param_value in overridden_parameters.items():
                 if param_name not in default_parameters:
                     error_msg = self._construct_validation_exception_message(
                         "Unknown parameter '{}'".format(param_name)
diff --git a/src/sagemaker/local/image.py b/src/sagemaker/local/image.py
index 377bdcac85..32437a59c3 100644
--- a/src/sagemaker/local/image.py
+++ b/src/sagemaker/local/image.py
@@ -294,9 +294,9 @@ def train(self, input_data_config, output_data_config, hyperparameters, environm
         }
         training_env_vars.update(environment)
         if self.sagemaker_session.s3_resource is not None:
-            training_env_vars[
-                S3_ENDPOINT_URL_ENV_NAME
-            ] = self.sagemaker_session.s3_resource.meta.client._endpoint.host
+            training_env_vars[S3_ENDPOINT_URL_ENV_NAME] = (
+                self.sagemaker_session.s3_resource.meta.client._endpoint.host
+            )
 
         compose_data = self._generate_compose_file(
             "train", additional_volumes=volumes, additional_env_vars=training_env_vars
diff --git a/src/sagemaker/local/local_session.py b/src/sagemaker/local/local_session.py
index 7d48850077..36a848aa52 100644
--- a/src/sagemaker/local/local_session.py
+++ b/src/sagemaker/local/local_session.py
@@ -472,9 +472,9 @@ def update_pipeline(
             raise ClientError(error_response, "update_pipeline")
         LocalSagemakerClient._pipelines[pipeline.name].pipeline_description = pipeline_description
         LocalSagemakerClient._pipelines[pipeline.name].pipeline = pipeline
-        LocalSagemakerClient._pipelines[
-            pipeline.name
-        ].last_modified_time = datetime.now().timestamp()
+        LocalSagemakerClient._pipelines[pipeline.name].last_modified_time = (
+            datetime.now().timestamp()
+        )
         return {"PipelineArn": pipeline.name}
 
     def describe_pipeline(self, PipelineName):
diff --git a/src/sagemaker/local/pipeline.py b/src/sagemaker/local/pipeline.py
index 9e97dd2059..8d613d6469 100644
--- a/src/sagemaker/local/pipeline.py
+++ b/src/sagemaker/local/pipeline.py
@@ -307,10 +307,10 @@ def execute(self):
                 "ProcessingOutputConfig" in job_describe_response
                 and "Outputs" in job_describe_response["ProcessingOutputConfig"]
             ):
-                job_describe_response["ProcessingOutputConfig"][
-                    "Outputs"
-                ] = self._convert_list_to_dict(
-                    job_describe_response, "ProcessingOutputConfig.Outputs", "OutputName"
+                job_describe_response["ProcessingOutputConfig"]["Outputs"] = (
+                    self._convert_list_to_dict(
+                        job_describe_response, "ProcessingOutputConfig.Outputs", "OutputName"
+                    )
                 )
             if "ProcessingInputs" in job_describe_response:
                 job_describe_response["ProcessingInputs"] = self._convert_list_to_dict(
diff --git a/src/sagemaker/model.py b/src/sagemaker/model.py
index c5f8b86f60..fd21b6342e 100644
--- a/src/sagemaker/model.py
+++ b/src/sagemaker/model.py
@@ -667,9 +667,9 @@ def prepare_container_def(
             self.repacked_model_data or self.model_data,
             deploy_env,
             image_config=self.image_config,
-            accept_eula=accept_eula
-            if accept_eula is not None
-            else getattr(self, "accept_eula", None),
+            accept_eula=(
+                accept_eula if accept_eula is not None else getattr(self, "accept_eula", None)
+            ),
         )
 
     def is_repack(self) -> bool:
@@ -1009,9 +1009,9 @@ def _compilation_job_config(
         """Placeholder Docstring"""
         input_model_config = {
             "S3Uri": self.model_data,
-            "DataInputConfig": json.dumps(input_shape)
-            if isinstance(input_shape, dict)
-            else input_shape,
+            "DataInputConfig": (
+                json.dumps(input_shape) if isinstance(input_shape, dict) else input_shape
+            ),
             "Framework": framework.upper(),
         }
 
@@ -1449,9 +1449,9 @@ def deploy(
         ):
             tags = add_jumpstart_uri_tags(
                 tags=tags,
-                inference_model_uri=self.model_data
-                if isinstance(self.model_data, (str, dict))
-                else None,
+                inference_model_uri=(
+                    self.model_data if isinstance(self.model_data, (str, dict)) else None
+                ),
                 inference_script_uri=self.source_dir,
             )
 
@@ -1566,13 +1566,13 @@ def deploy(
             # [TODO]: Refactor to a module
             startup_parameters = {}
             if model_data_download_timeout:
-                startup_parameters[
-                    "ModelDataDownloadTimeoutInSeconds"
-                ] = model_data_download_timeout
+                startup_parameters["ModelDataDownloadTimeoutInSeconds"] = (
+                    model_data_download_timeout
+                )
             if container_startup_health_check_timeout:
-                startup_parameters[
-                    "ContainerStartupHealthCheckTimeoutInSeconds"
-                ] = container_startup_health_check_timeout
+                startup_parameters["ContainerStartupHealthCheckTimeoutInSeconds"] = (
+                    container_startup_health_check_timeout
+                )
 
             inference_component_spec = {
                 "ModelName": self.name,
diff --git a/src/sagemaker/model_card/model_card.py b/src/sagemaker/model_card/model_card.py
index e6f32eaf8f..33af98723f 100644
--- a/src/sagemaker/model_card/model_card.py
+++ b/src/sagemaker/model_card/model_card.py
@@ -507,9 +507,11 @@ def from_model_package_arn(cls, model_package_arn: str, sagemaker_session: Sessi
                 "SourceAlgorithms"
             ]
             source_algorithms = [
-                SourceAlgorithm(sa["AlgorithmName"], sa["ModelDataUrl"])
-                if "ModelDataUrl" in sa
-                else SourceAlgorithm(sa["AlgorithmName"])
+                (
+                    SourceAlgorithm(sa["AlgorithmName"], sa["ModelDataUrl"])
+                    if "ModelDataUrl" in sa
+                    else SourceAlgorithm(sa["AlgorithmName"])
+                )
                 for sa in source_algorithms_response
             ]
 
@@ -948,18 +950,22 @@ def _create_training_details(training_job_data: dict, cls: "TrainingDetails", **
                 "training_environment": Environment(
                     container_image=[training_job_data["AlgorithmSpecification"]["TrainingImage"]]
                 ),
-                "training_metrics": [
-                    TrainingMetric(i["MetricName"], i["Value"])
-                    for i in training_job_data["FinalMetricDataList"]
-                ]
-                if "FinalMetricDataList" in training_job_data
-                else [],
-                "hyper_parameters": [
-                    HyperParameter(key, value)
-                    for key, value in training_job_data["HyperParameters"].items()
-                ]
-                if "HyperParameters" in training_job_data
-                else [],
+                "training_metrics": (
+                    [
+                        TrainingMetric(i["MetricName"], i["Value"])
+                        for i in training_job_data["FinalMetricDataList"]
+                    ]
+                    if "FinalMetricDataList" in training_job_data
+                    else []
+                ),
+                "hyper_parameters": (
+                    [
+                        HyperParameter(key, value)
+                        for key, value in training_job_data["HyperParameters"].items()
+                    ]
+                    if "HyperParameters" in training_job_data
+                    else []
+                ),
             }
             kwargs.update({"training_job_details": TrainingJobDetails(**job)})
             instance = cls(**kwargs)
diff --git a/src/sagemaker/model_monitor/model_monitoring.py b/src/sagemaker/model_monitor/model_monitoring.py
index c313efcf5e..436377fea5 100644
--- a/src/sagemaker/model_monitor/model_monitoring.py
+++ b/src/sagemaker/model_monitor/model_monitoring.py
@@ -2739,9 +2739,9 @@ def _build_create_data_quality_job_definition_request(
 
         app_specification["ImageUri"] = image_uri
         if post_analytics_processor_script_s3_uri:
-            app_specification[
-                "PostAnalyticsProcessorSourceUri"
-            ] = post_analytics_processor_script_s3_uri
+            app_specification["PostAnalyticsProcessorSourceUri"] = (
+                post_analytics_processor_script_s3_uri
+            )
         if record_preprocessor_script_s3_uri:
             app_specification["RecordPreprocessorSourceUri"] = record_preprocessor_script_s3_uri
 
@@ -3519,9 +3519,9 @@ def _build_create_model_quality_job_definition_request(
             )
 
         if post_analytics_processor_script_s3_uri:
-            app_specification[
-                "PostAnalyticsProcessorSourceUri"
-            ] = post_analytics_processor_script_s3_uri
+            app_specification["PostAnalyticsProcessorSourceUri"] = (
+                post_analytics_processor_script_s3_uri
+            )
         if record_preprocessor_script_s3_uri:
             app_specification["RecordPreprocessorSourceUri"] = record_preprocessor_script_s3_uri
 
@@ -4107,9 +4107,9 @@ def _to_request_dict(self):
         if self.probability_attribute is not None:
             batch_transform_input_data["ProbabilityAttribute"] = self.probability_attribute
         if self.probability_threshold_attribute is not None:
-            batch_transform_input_data[
-                "ProbabilityThresholdAttribute"
-            ] = self.probability_threshold_attribute
+            batch_transform_input_data["ProbabilityThresholdAttribute"] = (
+                self.probability_threshold_attribute
+            )
         if self.exclude_features_attribute is not None:
             batch_transform_input_data["ExcludeFeaturesAttribute"] = self.exclude_features_attribute
 
diff --git a/src/sagemaker/network.py b/src/sagemaker/network.py
index 2942e71062..9beb6544a6 100644
--- a/src/sagemaker/network.py
+++ b/src/sagemaker/network.py
@@ -62,9 +62,9 @@ def _to_request_dict(self):
         network_config_request = {"EnableNetworkIsolation": enable_network_isolation}
 
         if self.encrypt_inter_container_traffic is not None:
-            network_config_request[
-                "EnableInterContainerTrafficEncryption"
-            ] = self.encrypt_inter_container_traffic
+            network_config_request["EnableInterContainerTrafficEncryption"] = (
+                self.encrypt_inter_container_traffic
+            )
 
         if self.security_group_ids is not None or self.subnets is not None:
             network_config_request["VpcConfig"] = {}
diff --git a/src/sagemaker/payloads.py b/src/sagemaker/payloads.py
index de33f61b82..06d2ecfcde 100644
--- a/src/sagemaker/payloads.py
+++ b/src/sagemaker/payloads.py
@@ -76,16 +76,16 @@ def retrieve_all_examples(
             "Must specify JumpStart `model_id` and `model_version` when retrieving payloads."
         )
 
-    unserialized_payload_dict: Optional[
-        Dict[str, JumpStartSerializablePayload]
-    ] = artifacts._retrieve_example_payloads(
-        model_id,
-        model_version,
-        region,
-        tolerate_vulnerable_model,
-        tolerate_deprecated_model,
-        sagemaker_session=sagemaker_session,
-        model_type=model_type,
+    unserialized_payload_dict: Optional[Dict[str, JumpStartSerializablePayload]] = (
+        artifacts._retrieve_example_payloads(
+            model_id,
+            model_version,
+            region,
+            tolerate_vulnerable_model,
+            tolerate_deprecated_model,
+            sagemaker_session=sagemaker_session,
+            model_type=model_type,
+        )
     )
 
     if unserialized_payload_dict is None:
diff --git a/src/sagemaker/predictor_async.py b/src/sagemaker/predictor_async.py
index cdf9b141b3..ef70b93599 100644
--- a/src/sagemaker/predictor_async.py
+++ b/src/sagemaker/predictor_async.py
@@ -313,12 +313,14 @@ def check_failure_file():
         failure_object = self.s3_client.get_object(Bucket=failure_bucket, Key=failure_key)
         failure_response = self.predictor._handle_response(response=failure_object)
 
-        raise AsyncInferenceModelError(
-            message=failure_response
-        ) if failure_file_found.is_set() else PollingTimeoutError(
-            message="Inference could still be running",
-            output_path=output_path,
-            seconds=waiter_config.delay * waiter_config.max_attempts,
+        raise (
+            AsyncInferenceModelError(message=failure_response)
+            if failure_file_found.is_set()
+            else PollingTimeoutError(
+                message="Inference could still be running",
+                output_path=output_path,
+                seconds=waiter_config.delay * waiter_config.max_attempts,
+            )
         )
 
     def update_endpoint(
diff --git a/src/sagemaker/remote_function/job.py b/src/sagemaker/remote_function/job.py
index a854de9135..5814ee45ff 100644
--- a/src/sagemaker/remote_function/job.py
+++ b/src/sagemaker/remote_function/job.py
@@ -863,9 +863,9 @@ def compile(
             request_dict["EnableNetworkIsolation"] = job_settings.enable_network_isolation
 
         if job_settings.encrypt_inter_container_traffic is not None:
-            request_dict[
-                "EnableInterContainerTrafficEncryption"
-            ] = job_settings.encrypt_inter_container_traffic
+            request_dict["EnableInterContainerTrafficEncryption"] = (
+                job_settings.encrypt_inter_container_traffic
+            )
 
         if job_settings.vpc_config:
             request_dict["VpcConfig"] = job_settings.vpc_config
@@ -1080,9 +1080,11 @@ def _generate_input_data_config(job_settings: _JobSettings, s3_base_uri: str):
     if user_workspace_s3uri:
         input_data_config.append(
             dict(
-                ChannelName=REMOTE_FUNCTION_WORKSPACE
-                if not step_compilation_context
-                else step_compilation_context.pipeline_build_time,
+                ChannelName=(
+                    REMOTE_FUNCTION_WORKSPACE
+                    if not step_compilation_context
+                    else step_compilation_context.pipeline_build_time
+                ),
                 DataSource={
                     "S3DataSource": {
                         "S3Uri": user_workspace_s3uri,
diff --git a/src/sagemaker/serve/__init__.py b/src/sagemaker/serve/__init__.py
index bb5cafc8dd..886e59d4f1 100644
--- a/src/sagemaker/serve/__init__.py
+++ b/src/sagemaker/serve/__init__.py
@@ -1,4 +1,5 @@
 """Placeholder docstring"""
+
 from __future__ import absolute_import
 import logging
 
diff --git a/src/sagemaker/serve/builder/schema_builder.py b/src/sagemaker/serve/builder/schema_builder.py
index 2a0d4892e4..3fd1816d0e 100644
--- a/src/sagemaker/serve/builder/schema_builder.py
+++ b/src/sagemaker/serve/builder/schema_builder.py
@@ -1,4 +1,5 @@
 """Placeholder docstring"""
+
 from __future__ import absolute_import
 import io
 import logging
@@ -230,18 +231,26 @@ def __repr__(self):
     def generate_marshalling_map(self) -> dict:
         """Generate marshalling map for the schema builder"""
         return {
-            "input_serializer": self.input_serializer.__class__.__name__
-            if hasattr(self, "input_serializer")
-            else None,
-            "output_serializer": self.output_serializer.__class__.__name__
-            if hasattr(self, "output_serializer")
-            else None,
-            "input_deserializer": self._input_deserializer.__class__.__name__
-            if hasattr(self, "_input_deserializer")
-            else None,
-            "output_deserializer": self._output_deserializer.__class__.__name__
-            if hasattr(self, "_output_deserializer")
-            else None,
+            "input_serializer": (
+                self.input_serializer.__class__.__name__
+                if hasattr(self, "input_serializer")
+                else None
+            ),
+            "output_serializer": (
+                self.output_serializer.__class__.__name__
+                if hasattr(self, "output_serializer")
+                else None
+            ),
+            "input_deserializer": (
+                self._input_deserializer.__class__.__name__
+                if hasattr(self, "_input_deserializer")
+                else None
+            ),
+            "output_deserializer": (
+                self._output_deserializer.__class__.__name__
+                if hasattr(self, "_output_deserializer")
+                else None
+            ),
             "custom_input_translator": hasattr(self, "custom_input_translator"),
             "custom_output_translator": hasattr(self, "custom_output_translator"),
         }
diff --git a/src/sagemaker/serve/builder/triton_schema_builder.py b/src/sagemaker/serve/builder/triton_schema_builder.py
index dd51061353..3015dc6e19 100644
--- a/src/sagemaker/serve/builder/triton_schema_builder.py
+++ b/src/sagemaker/serve/builder/triton_schema_builder.py
@@ -1,4 +1,5 @@
 """Placeholder docstring"""
+
 from __future__ import absolute_import
 
 from sagemaker.serve.marshalling.triton_translator import (
diff --git a/src/sagemaker/serve/detector/image_detector.py b/src/sagemaker/serve/detector/image_detector.py
index 15be8eae89..63831f5950 100644
--- a/src/sagemaker/serve/detector/image_detector.py
+++ b/src/sagemaker/serve/detector/image_detector.py
@@ -1,4 +1,5 @@
 """Detects the image to deploy model"""
+
 from __future__ import absolute_import
 from typing import Tuple, List
 import platform
diff --git a/src/sagemaker/serve/detector/pickle_dependencies.py b/src/sagemaker/serve/detector/pickle_dependencies.py
index 8ba95a3cc0..5a1cd43869 100644
--- a/src/sagemaker/serve/detector/pickle_dependencies.py
+++ b/src/sagemaker/serve/detector/pickle_dependencies.py
@@ -1,4 +1,5 @@
 """Load a pickled object to detect the dependencies it requires"""
+
 from __future__ import absolute_import
 from pathlib import Path
 from typing import List
diff --git a/src/sagemaker/serve/detector/pickler.py b/src/sagemaker/serve/detector/pickler.py
index 3adddddc21..8ea2514c73 100644
--- a/src/sagemaker/serve/detector/pickler.py
+++ b/src/sagemaker/serve/detector/pickler.py
@@ -1,4 +1,5 @@
 """Save the object using cloudpickle"""
+
 from __future__ import absolute_import
 from typing import Any
 from pathlib import Path
diff --git a/src/sagemaker/serve/marshalling/custom_payload_translator.py b/src/sagemaker/serve/marshalling/custom_payload_translator.py
index d5562bba51..154d47c80e 100644
--- a/src/sagemaker/serve/marshalling/custom_payload_translator.py
+++ b/src/sagemaker/serve/marshalling/custom_payload_translator.py
@@ -1,4 +1,5 @@
 """Defines CustomPayloadTranslator class that holds custom serialization/deserialization code"""
+
 from __future__ import absolute_import
 import abc
 from typing import IO
diff --git a/src/sagemaker/serve/marshalling/triton_translator.py b/src/sagemaker/serve/marshalling/triton_translator.py
index 034f536fa6..f7a941c2f2 100644
--- a/src/sagemaker/serve/marshalling/triton_translator.py
+++ b/src/sagemaker/serve/marshalling/triton_translator.py
@@ -1,4 +1,5 @@
 """Implements class converts data from and to np.ndarray"""
+
 from __future__ import absolute_import
 
 import logging
diff --git a/src/sagemaker/serve/mode/function_pointers.py b/src/sagemaker/serve/mode/function_pointers.py
index df2f5cc6cd..ba4103eae8 100644
--- a/src/sagemaker/serve/mode/function_pointers.py
+++ b/src/sagemaker/serve/mode/function_pointers.py
@@ -1,4 +1,5 @@
 """Placeholder docstring"""
+
 from __future__ import absolute_import
 from enum import Enum
 
diff --git a/src/sagemaker/serve/mode/local_container_mode.py b/src/sagemaker/serve/mode/local_container_mode.py
index aba6aeb25d..362a3804de 100644
--- a/src/sagemaker/serve/mode/local_container_mode.py
+++ b/src/sagemaker/serve/mode/local_container_mode.py
@@ -1,4 +1,5 @@
 """Module that defines the LocalContainerMode class"""
+
 from __future__ import absolute_import
 from pathlib import Path
 import logging
diff --git a/src/sagemaker/serve/mode/sagemaker_endpoint_mode.py b/src/sagemaker/serve/mode/sagemaker_endpoint_mode.py
index 8f22c4aa1c..0fdc425b31 100644
--- a/src/sagemaker/serve/mode/sagemaker_endpoint_mode.py
+++ b/src/sagemaker/serve/mode/sagemaker_endpoint_mode.py
@@ -1,4 +1,5 @@
 """Placeholder docstring"""
+
 from __future__ import absolute_import
 from pathlib import Path
 
diff --git a/src/sagemaker/serve/model_server/djl_serving/server.py b/src/sagemaker/serve/model_server/djl_serving/server.py
index 3664abf56a..8b152e5b81 100644
--- a/src/sagemaker/serve/model_server/djl_serving/server.py
+++ b/src/sagemaker/serve/model_server/djl_serving/server.py
@@ -1,4 +1,5 @@
 """Module for Local DJL Serving"""
+
 from __future__ import absolute_import
 
 import requests
diff --git a/src/sagemaker/serve/model_server/djl_serving/utils.py b/src/sagemaker/serve/model_server/djl_serving/utils.py
index 1b016a6eae..03719542d2 100644
--- a/src/sagemaker/serve/model_server/djl_serving/utils.py
+++ b/src/sagemaker/serve/model_server/djl_serving/utils.py
@@ -1,4 +1,5 @@
 """DJL ModelBuilder Utils"""
+
 from __future__ import absolute_import
 from urllib.error import HTTPError
 import math
diff --git a/src/sagemaker/serve/model_server/multi_model_server/server.py b/src/sagemaker/serve/model_server/multi_model_server/server.py
index 36e14a56af..b78e01f5c3 100644
--- a/src/sagemaker/serve/model_server/multi_model_server/server.py
+++ b/src/sagemaker/serve/model_server/multi_model_server/server.py
@@ -1,4 +1,5 @@
 """Module for the MultiModel Local and Remote servers"""
+
 from __future__ import absolute_import
 
 import requests
diff --git a/src/sagemaker/serve/model_server/tgi/server.py b/src/sagemaker/serve/model_server/tgi/server.py
index d518ccee11..ef39e890c8 100644
--- a/src/sagemaker/serve/model_server/tgi/server.py
+++ b/src/sagemaker/serve/model_server/tgi/server.py
@@ -1,4 +1,5 @@
 """Module for Local TGI Serving"""
+
 from __future__ import absolute_import
 
 import requests
diff --git a/src/sagemaker/serve/model_server/tgi/utils.py b/src/sagemaker/serve/model_server/tgi/utils.py
index ef3a8b7525..05c6f33c5a 100644
--- a/src/sagemaker/serve/model_server/tgi/utils.py
+++ b/src/sagemaker/serve/model_server/tgi/utils.py
@@ -1,4 +1,5 @@
 """TGI ModelBuilder Utils"""
+
 from __future__ import absolute_import
 
 from typing import Dict
diff --git a/src/sagemaker/serve/model_server/torchserve/inference.py b/src/sagemaker/serve/model_server/torchserve/inference.py
index 2161763fc9..2675f6ea6a 100644
--- a/src/sagemaker/serve/model_server/torchserve/inference.py
+++ b/src/sagemaker/serve/model_server/torchserve/inference.py
@@ -1,4 +1,5 @@
 """This module is for SageMaker inference.py."""
+
 from __future__ import absolute_import
 import os
 import io
diff --git a/src/sagemaker/serve/model_server/torchserve/server.py b/src/sagemaker/serve/model_server/torchserve/server.py
index 8d403b8f91..5aef136355 100644
--- a/src/sagemaker/serve/model_server/torchserve/server.py
+++ b/src/sagemaker/serve/model_server/torchserve/server.py
@@ -1,4 +1,5 @@
 """Module for Local Torch Server"""
+
 from __future__ import absolute_import
 
 import requests
diff --git a/src/sagemaker/serve/model_server/torchserve/xgboost_inference.py b/src/sagemaker/serve/model_server/torchserve/xgboost_inference.py
index 1b6f7d0e58..4e82ec66b2 100644
--- a/src/sagemaker/serve/model_server/torchserve/xgboost_inference.py
+++ b/src/sagemaker/serve/model_server/torchserve/xgboost_inference.py
@@ -1,4 +1,5 @@
 """This module is for SageMaker inference.py."""
+
 from __future__ import absolute_import
 import os
 import io
diff --git a/src/sagemaker/serve/model_server/triton/config_template.py b/src/sagemaker/serve/model_server/triton/config_template.py
index 227cd5c7c1..e351049b43 100644
--- a/src/sagemaker/serve/model_server/triton/config_template.py
+++ b/src/sagemaker/serve/model_server/triton/config_template.py
@@ -1,4 +1,5 @@
 """Placeholder docstring"""
+
 from __future__ import absolute_import
 
 CONFIG_TEMPLATE = """name: \"model\"
diff --git a/src/sagemaker/serve/model_server/triton/model.py b/src/sagemaker/serve/model_server/triton/model.py
index 0b8e4a27a5..5d8e9b0a2d 100644
--- a/src/sagemaker/serve/model_server/triton/model.py
+++ b/src/sagemaker/serve/model_server/triton/model.py
@@ -1,4 +1,5 @@
 """This module is for Triton Python backend."""
+
 from __future__ import absolute_import
 import os
 import logging
diff --git a/src/sagemaker/serve/model_server/triton/server.py b/src/sagemaker/serve/model_server/triton/server.py
index 2ebec25406..62dfb4759a 100644
--- a/src/sagemaker/serve/model_server/triton/server.py
+++ b/src/sagemaker/serve/model_server/triton/server.py
@@ -1,4 +1,5 @@
 """Placeholder docerting"""
+
 from __future__ import absolute_import
 import uuid
 import logging
diff --git a/src/sagemaker/serve/model_server/triton/triton_builder.py b/src/sagemaker/serve/model_server/triton/triton_builder.py
index d47d0cc356..ed0ec49204 100644
--- a/src/sagemaker/serve/model_server/triton/triton_builder.py
+++ b/src/sagemaker/serve/model_server/triton/triton_builder.py
@@ -1,4 +1,5 @@
 """Placeholder docstring"""
+
 from __future__ import absolute_import
 import os
 import logging
diff --git a/src/sagemaker/serve/save_retrive/version_1_0_0/save/framework/framework_handler.py b/src/sagemaker/serve/save_retrive/version_1_0_0/save/framework/framework_handler.py
index ac862aa507..1e909ff42b 100644
--- a/src/sagemaker/serve/save_retrive/version_1_0_0/save/framework/framework_handler.py
+++ b/src/sagemaker/serve/save_retrive/version_1_0_0/save/framework/framework_handler.py
@@ -1,4 +1,5 @@
 """Experimental"""
+
 from __future__ import absolute_import
 from abc import ABC, abstractmethod
 from typing import Type
diff --git a/src/sagemaker/serve/save_retrive/version_1_0_0/save/framework/pytorch_handler.py b/src/sagemaker/serve/save_retrive/version_1_0_0/save/framework/pytorch_handler.py
index 0a07e4d93b..7aa00f65b9 100644
--- a/src/sagemaker/serve/save_retrive/version_1_0_0/save/framework/pytorch_handler.py
+++ b/src/sagemaker/serve/save_retrive/version_1_0_0/save/framework/pytorch_handler.py
@@ -1,4 +1,5 @@
 """Experimental"""
+
 from __future__ import absolute_import
 import platform
 import logging
diff --git a/src/sagemaker/serve/save_retrive/version_1_0_0/save/framework/xgboost_handler.py b/src/sagemaker/serve/save_retrive/version_1_0_0/save/framework/xgboost_handler.py
index 6d40c138d9..19e83f58ce 100644
--- a/src/sagemaker/serve/save_retrive/version_1_0_0/save/framework/xgboost_handler.py
+++ b/src/sagemaker/serve/save_retrive/version_1_0_0/save/framework/xgboost_handler.py
@@ -1,4 +1,5 @@
 """Experimental"""
+
 from __future__ import absolute_import
 import platform
 import logging
diff --git a/src/sagemaker/serve/save_retrive/version_1_0_0/save/utils.py b/src/sagemaker/serve/save_retrive/version_1_0_0/save/utils.py
index 305b66fa92..8df442d9f8 100644
--- a/src/sagemaker/serve/save_retrive/version_1_0_0/save/utils.py
+++ b/src/sagemaker/serve/save_retrive/version_1_0_0/save/utils.py
@@ -1,4 +1,5 @@
 """Validates the integrity of pickled file with HMAC signing."""
+
 from __future__ import absolute_import
 import secrets
 import hmac
diff --git a/src/sagemaker/serve/spec/inference_spec.py b/src/sagemaker/serve/spec/inference_spec.py
index 9ecec4fdfe..b61d7d55ea 100644
--- a/src/sagemaker/serve/spec/inference_spec.py
+++ b/src/sagemaker/serve/spec/inference_spec.py
@@ -1,4 +1,5 @@
 """Implements class that holds custom load and invoke function of a model"""
+
 from __future__ import absolute_import
 import abc
 
diff --git a/src/sagemaker/serve/utils/exceptions.py b/src/sagemaker/serve/utils/exceptions.py
index 8132820cc0..72b9083072 100644
--- a/src/sagemaker/serve/utils/exceptions.py
+++ b/src/sagemaker/serve/utils/exceptions.py
@@ -1,4 +1,5 @@
 """Placeholder Docstring"""
+
 from __future__ import absolute_import
 
 
diff --git a/src/sagemaker/serve/utils/logging_agent.py b/src/sagemaker/serve/utils/logging_agent.py
index f140a4c403..196359116e 100644
--- a/src/sagemaker/serve/utils/logging_agent.py
+++ b/src/sagemaker/serve/utils/logging_agent.py
@@ -1,4 +1,5 @@
 """Module for pulling logs from container"""
+
 from __future__ import absolute_import
 import logging
 from threading import Thread
diff --git a/src/sagemaker/serve/utils/predictors.py b/src/sagemaker/serve/utils/predictors.py
index 10fc6bb4aa..e0ff8f8ee1 100644
--- a/src/sagemaker/serve/utils/predictors.py
+++ b/src/sagemaker/serve/utils/predictors.py
@@ -1,4 +1,5 @@
 """Defines the predictors used in local container mode"""
+
 from __future__ import absolute_import
 import io
 from typing import Type
diff --git a/src/sagemaker/serve/utils/tuning.py b/src/sagemaker/serve/utils/tuning.py
index de02708278..22f3c06d47 100644
--- a/src/sagemaker/serve/utils/tuning.py
+++ b/src/sagemaker/serve/utils/tuning.py
@@ -1,4 +1,5 @@
 """Holds mixin logic to support deployment of Model ID"""
+
 from __future__ import absolute_import
 
 import logging
diff --git a/src/sagemaker/serve/utils/types.py b/src/sagemaker/serve/utils/types.py
index 60b7b5cd6f..661093f249 100644
--- a/src/sagemaker/serve/utils/types.py
+++ b/src/sagemaker/serve/utils/types.py
@@ -1,4 +1,5 @@
 """Types used for SageMaker ModelBuilder"""
+
 from __future__ import absolute_import
 
 from enum import Enum
diff --git a/src/sagemaker/serve/utils/uploader.py b/src/sagemaker/serve/utils/uploader.py
index 39459f3513..a6b07f2fa5 100644
--- a/src/sagemaker/serve/utils/uploader.py
+++ b/src/sagemaker/serve/utils/uploader.py
@@ -1,4 +1,5 @@
 """Upload model artifacts to S3"""
+
 from __future__ import absolute_import
 import logging
 import os
diff --git a/src/sagemaker/serve/validations/check_image_and_hardware_type.py b/src/sagemaker/serve/validations/check_image_and_hardware_type.py
index 935d9e185e..0046e47a80 100644
--- a/src/sagemaker/serve/validations/check_image_and_hardware_type.py
+++ b/src/sagemaker/serve/validations/check_image_and_hardware_type.py
@@ -1,4 +1,5 @@
 """Validate if image_uri is compatible with instance_type"""
+
 from __future__ import absolute_import
 import logging
 
diff --git a/src/sagemaker/serve/validations/check_image_uri.py b/src/sagemaker/serve/validations/check_image_uri.py
index 2d559bc2f3..2f50faaeed 100644
--- a/src/sagemaker/serve/validations/check_image_uri.py
+++ b/src/sagemaker/serve/validations/check_image_uri.py
@@ -1,4 +1,5 @@
 """Validates that a given image_uri is not a 1p image."""
+
 from __future__ import absolute_import
 
 # Generated by running the parse_registry_accounts.py script
diff --git a/src/sagemaker/serve/validations/check_integrity.py b/src/sagemaker/serve/validations/check_integrity.py
index ffd4bcfcd6..01b958611c 100644
--- a/src/sagemaker/serve/validations/check_integrity.py
+++ b/src/sagemaker/serve/validations/check_integrity.py
@@ -1,4 +1,5 @@
 """Validates the integrity of pickled file with HMAC signing."""
+
 from __future__ import absolute_import
 import secrets
 import hmac
diff --git a/src/sagemaker/serve/validations/parse_registry_accounts.py b/src/sagemaker/serve/validations/parse_registry_accounts.py
index 14261975b2..04ed6402b3 100644
--- a/src/sagemaker/serve/validations/parse_registry_accounts.py
+++ b/src/sagemaker/serve/validations/parse_registry_accounts.py
@@ -1,4 +1,5 @@
 """Script to scrape account IDs for 1p image URIs defined in src/sagemaker/image_uri_config."""
+
 from __future__ import absolute_import
 import os
 
diff --git a/src/sagemaker/session.py b/src/sagemaker/session.py
index b0ff9bcb86..9e593706c1 100644
--- a/src/sagemaker/session.py
+++ b/src/sagemaker/session.py
@@ -3470,9 +3470,9 @@ def _map_training_config(
             training_job_definition["EnableNetworkIsolation"] = enable_network_isolation
 
         if encrypt_inter_container_traffic:
-            training_job_definition[
-                "EnableInterContainerTrafficEncryption"
-            ] = encrypt_inter_container_traffic
+            training_job_definition["EnableInterContainerTrafficEncryption"] = (
+                encrypt_inter_container_traffic
+            )
 
         if use_spot_instances:
             # use_spot_instances may be a Pipeline ParameterBoolean object
@@ -6405,7 +6405,7 @@ def _intercept_create_request(
         self,
         request: typing.Dict,
         create,
-        func_name: str = None
+        func_name: str = None,
         # pylint: disable=unused-argument
     ):
         """This function intercepts the create job request.
diff --git a/src/sagemaker/spark/processing.py b/src/sagemaker/spark/processing.py
index 82634071cc..5c6c64852d 100644
--- a/src/sagemaker/spark/processing.py
+++ b/src/sagemaker/spark/processing.py
@@ -538,14 +538,14 @@ def _prepare_history_server_env_variables(self, spark_event_logs_s3_uri):
         history_server_env_variables = {}
 
         if spark_event_logs_s3_uri:
-            history_server_env_variables[
-                _HistoryServer.arg_event_logs_s3_uri
-            ] = spark_event_logs_s3_uri
+            history_server_env_variables[_HistoryServer.arg_event_logs_s3_uri] = (
+                spark_event_logs_s3_uri
+            )
         # this variable will be previously set by run() method
         elif self._spark_event_logs_s3_uri is not None:
-            history_server_env_variables[
-                _HistoryServer.arg_event_logs_s3_uri
-            ] = self._spark_event_logs_s3_uri
+            history_server_env_variables[_HistoryServer.arg_event_logs_s3_uri] = (
+                self._spark_event_logs_s3_uri
+            )
         else:
             raise ValueError(
                 "SPARK_EVENT_LOGS_S3_URI not present. You can specify spark_event_logs_s3_uri "
@@ -557,9 +557,9 @@ def _prepare_history_server_env_variables(self, spark_event_logs_s3_uri):
         history_server_env_variables["AWS_REGION"] = region
 
         if self._is_notebook_instance():
-            history_server_env_variables[
-                _HistoryServer.arg_remote_domain_name
-            ] = self._get_notebook_instance_domain()
+            history_server_env_variables[_HistoryServer.arg_remote_domain_name] = (
+                self._get_notebook_instance_domain()
+            )
 
         return history_server_env_variables
 
diff --git a/src/sagemaker/tuner.py b/src/sagemaker/tuner.py
index 967bff1b99..4b0f38f36f 100644
--- a/src/sagemaker/tuner.py
+++ b/src/sagemaker/tuner.py
@@ -568,9 +568,9 @@ def to_input_req(self):
             ] = self.max_number_of_training_jobs_not_improving
 
         if self.target_objective_metric_value is not None:
-            completion_criteria_config[
-                TARGET_OBJECTIVE_METRIC_VALUE
-            ] = self.target_objective_metric_value
+            completion_criteria_config[TARGET_OBJECTIVE_METRIC_VALUE] = (
+                self.target_objective_metric_value
+            )
 
         if self.complete_on_convergence is not None:
             completion_criteria_config[CONVERGENCE_DETECTED] = {}
@@ -867,9 +867,11 @@ def _prepare_static_hyperparameters_for_tuning(self, include_cls_metadata=False)
                 estimator_name: self._prepare_static_hyperparameters(
                     estimator,
                     self._hyperparameter_ranges_dict[estimator_name],
-                    include_cls_metadata.get(estimator_name, False)
-                    if isinstance(include_cls_metadata, dict)
-                    else include_cls_metadata,
+                    (
+                        include_cls_metadata.get(estimator_name, False)
+                        if isinstance(include_cls_metadata, dict)
+                        else include_cls_metadata
+                    ),
                 )
                 for (estimator_name, estimator) in self.estimator_dict.items()
             }
@@ -887,9 +889,11 @@ def _prepare_auto_parameters_for_tuning(self):
             static_auto_parameters_dict = {
                 estimator_name: self._prepare_auto_parameters(
                     self.static_hyperparameters_dict[estimator_name],
-                    self.hyperparameters_to_keep_static_dict.get(estimator_name, None)
-                    if self.hyperparameters_to_keep_static_dict
-                    else None,
+                    (
+                        self.hyperparameters_to_keep_static_dict.get(estimator_name, None)
+                        if self.hyperparameters_to_keep_static_dict
+                        else None
+                    ),
                 )
                 for estimator_name in sorted(self.estimator_dict.keys())
             }
@@ -1268,10 +1272,10 @@ def _attach_with_training_details_list(cls, sagemaker_session, estimator_cls, jo
             objective_metric_name_dict[estimator_name] = training_details["TuningObjective"][
                 "MetricName"
             ]
-            hyperparameter_ranges_dict[
-                estimator_name
-            ] = cls._prepare_parameter_ranges_from_job_description(  # noqa: E501 # pylint: disable=line-too-long
-                training_details["HyperParameterRanges"]
+            hyperparameter_ranges_dict[estimator_name] = (
+                cls._prepare_parameter_ranges_from_job_description(  # noqa: E501 # pylint: disable=line-too-long
+                    training_details["HyperParameterRanges"]
+                )
             )
 
             metric_definitions = training_details["AlgorithmSpecification"].get(
@@ -2111,9 +2115,9 @@ def _add_estimator(
         self.objective_metric_name_dict[estimator_name] = objective_metric_name
         self._hyperparameter_ranges_dict[estimator_name] = hyperparameter_ranges
         if hyperparameters_to_keep_static is not None:
-            self.hyperparameters_to_keep_static_dict[
-                estimator_name
-            ] = hyperparameters_to_keep_static
+            self.hyperparameters_to_keep_static_dict[estimator_name] = (
+                hyperparameters_to_keep_static
+            )
         if metric_definitions is not None:
             self.metric_definitions_dict[estimator_name] = metric_definitions
 
@@ -2190,9 +2194,9 @@ def _get_tuner_args(cls, tuner, inputs):
             tuning_config["auto_parameters"] = tuner.auto_parameters
 
         if tuner.completion_criteria_config is not None:
-            tuning_config[
-                "completion_criteria_config"
-            ] = tuner.completion_criteria_config.to_input_req()
+            tuning_config["completion_criteria_config"] = (
+                tuner.completion_criteria_config.to_input_req()
+            )
 
         tuner_args = {
             "job_name": tuner._current_job_name,
@@ -2222,12 +2226,16 @@ def _get_tuner_args(cls, tuner, inputs):
                     tuner.objective_type,
                     tuner.objective_metric_name_dict[estimator_name],
                     tuner.hyperparameter_ranges_dict()[estimator_name],
-                    tuner.instance_configs_dict.get(estimator_name, None)
-                    if tuner.instance_configs_dict is not None
-                    else None,
-                    tuner.auto_parameters_dict.get(estimator_name, None)
-                    if tuner.auto_parameters_dict is not None
-                    else None,
+                    (
+                        tuner.instance_configs_dict.get(estimator_name, None)
+                        if tuner.instance_configs_dict is not None
+                        else None
+                    ),
+                    (
+                        tuner.auto_parameters_dict.get(estimator_name, None)
+                        if tuner.auto_parameters_dict is not None
+                        else None
+                    ),
                 )
                 for estimator_name in sorted(tuner.estimator_dict.keys())
             ]
@@ -2303,9 +2311,9 @@ def _prepare_training_config(
             training_config["image_uri"] = estimator.training_image_uri()
 
         training_config["enable_network_isolation"] = estimator.enable_network_isolation()
-        training_config[
-            "encrypt_inter_container_traffic"
-        ] = estimator.encrypt_inter_container_traffic
+        training_config["encrypt_inter_container_traffic"] = (
+            estimator.encrypt_inter_container_traffic
+        )
 
         training_config["use_spot_instances"] = estimator.use_spot_instances
         training_config["checkpoint_s3_uri"] = estimator.checkpoint_s3_uri
diff --git a/src/sagemaker/workflow/airflow.py b/src/sagemaker/workflow/airflow.py
index 793849ff93..3678c3d97e 100644
--- a/src/sagemaker/workflow/airflow.py
+++ b/src/sagemaker/workflow/airflow.py
@@ -68,13 +68,13 @@ def prepare_framework(estimator, s3_operations):
         ]
     estimator._hyperparameters[sagemaker.model.DIR_PARAM_NAME] = code_dir
     estimator._hyperparameters[sagemaker.model.SCRIPT_PARAM_NAME] = script
-    estimator._hyperparameters[
-        sagemaker.model.CONTAINER_LOG_LEVEL_PARAM_NAME
-    ] = estimator.container_log_level
+    estimator._hyperparameters[sagemaker.model.CONTAINER_LOG_LEVEL_PARAM_NAME] = (
+        estimator.container_log_level
+    )
     estimator._hyperparameters[sagemaker.model.JOB_NAME_PARAM_NAME] = estimator._current_job_name
-    estimator._hyperparameters[
-        sagemaker.model.SAGEMAKER_REGION_PARAM_NAME
-    ] = estimator.sagemaker_session.boto_region_name
+    estimator._hyperparameters[sagemaker.model.SAGEMAKER_REGION_PARAM_NAME] = (
+        estimator.sagemaker_session.boto_region_name
+    )
 
 
 def prepare_amazon_algorithm_estimator(estimator, inputs, mini_batch_size=None):
@@ -422,7 +422,7 @@ def _extract_training_config_list_from_estimator_dict(
     )
 
     train_config_dict = {}
-    for (estimator_name, estimator) in tuner.estimator_dict.items():
+    for estimator_name, estimator in tuner.estimator_dict.items():
         train_config_dict[estimator_name] = training_base_config(
             estimator=estimator,
             inputs=inputs.get(estimator_name) if inputs else None,
@@ -439,9 +439,9 @@ def _extract_training_config_list_from_estimator_dict(
         train_config.pop("HyperParameters", None)
         train_config["StaticHyperParameters"] = tuner.static_hyperparameters_dict[estimator_name]
 
-        train_config["AlgorithmSpecification"][
-            "MetricDefinitions"
-        ] = tuner.metric_definitions_dict.get(estimator_name)
+        train_config["AlgorithmSpecification"]["MetricDefinitions"] = (
+            tuner.metric_definitions_dict.get(estimator_name)
+        )
 
         train_config["DefinitionName"] = estimator_name
         train_config["TuningObjective"] = {
@@ -461,7 +461,7 @@ def _merge_s3_operations(s3_operations_list):
     """Merge a list of S3 operation dictionaries into one"""
     s3_operations_merged = {}
     for s3_operations in s3_operations_list:
-        for (key, operations) in s3_operations.items():
+        for key, operations in s3_operations.items():
             if key not in s3_operations_merged:
                 s3_operations_merged[key] = []
             for operation in operations:
diff --git a/src/sagemaker/workflow/clarify_check_step.py b/src/sagemaker/workflow/clarify_check_step.py
index c53e7e9666..11fbb2c00b 100644
--- a/src/sagemaker/workflow/clarify_check_step.py
+++ b/src/sagemaker/workflow/clarify_check_step.py
@@ -306,9 +306,9 @@ def to_request(self) -> RequestType:
         if isinstance(
             self.clarify_check_config, (ModelBiasCheckConfig, ModelExplainabilityCheckConfig)
         ):
-            request_dict[
-                "ModelName"
-            ] = self.clarify_check_config.model_config.get_predictor_config()["model_name"]
+            request_dict["ModelName"] = (
+                self.clarify_check_config.model_config.get_predictor_config()["model_name"]
+            )
         return request_dict
 
     def _generate_processing_job_analysis_config(self) -> dict:
@@ -348,9 +348,9 @@ def _generate_processing_job_analysis_config(self) -> dict:
                 predictor_config.update(predicted_label_config)
             else:
                 _set(model_scores, "label", predictor_config)
-            analysis_config[
-                "methods"
-            ] = self.clarify_check_config.explainability_config.get_explainability_config()
+            analysis_config["methods"] = (
+                self.clarify_check_config.explainability_config.get_explainability_config()
+            )
             analysis_config["predictor"] = predictor_config
         return analysis_config
 
diff --git a/src/sagemaker/workflow/functions.py b/src/sagemaker/workflow/functions.py
index 947578d433..3419cb1447 100644
--- a/src/sagemaker/workflow/functions.py
+++ b/src/sagemaker/workflow/functions.py
@@ -144,9 +144,11 @@ def expr(self):
         if self.s3_uri:
             return {
                 "Std:JsonGet": {
-                    "S3Uri": self.s3_uri.expr
-                    if isinstance(self.s3_uri, PipelineVariable)
-                    else self.s3_uri,
+                    "S3Uri": (
+                        self.s3_uri.expr
+                        if isinstance(self.s3_uri, PipelineVariable)
+                        else self.s3_uri
+                    ),
                     "Path": self.json_path,
                 }
             }
diff --git a/src/sagemaker/workflow/pipeline.py b/src/sagemaker/workflow/pipeline.py
index 510ccd76bf..62167b96e7 100644
--- a/src/sagemaker/workflow/pipeline.py
+++ b/src/sagemaker/workflow/pipeline.py
@@ -395,9 +395,11 @@ def definition(self) -> str:
             "Version": self._version,
             "Metadata": self._metadata,
             "Parameters": list_to_request(self.parameters),
-            "PipelineExperimentConfig": self.pipeline_experiment_config.to_request()
-            if self.pipeline_experiment_config is not None
-            else None,
+            "PipelineExperimentConfig": (
+                self.pipeline_experiment_config.to_request()
+                if self.pipeline_experiment_config is not None
+                else None
+            ),
             "Steps": list_to_request(compiled_steps),
         }
 
diff --git a/tests/data/dummy_code_bundle_with_reqs/local_module.py b/tests/data/dummy_code_bundle_with_reqs/local_module.py
index 542ab9f05d..03037550f9 100644
--- a/tests/data/dummy_code_bundle_with_reqs/local_module.py
+++ b/tests/data/dummy_code_bundle_with_reqs/local_module.py
@@ -1,2 +1,3 @@
 """A dummy Python module to check importing local files works OK"""
+
 DUMMY_CONSTANT = 1
diff --git a/tests/data/marketplace/iris/scoring_logic.py b/tests/data/marketplace/iris/scoring_logic.py
index 03a89dc8f2..f9e2f1bb35 100644
--- a/tests/data/marketplace/iris/scoring_logic.py
+++ b/tests/data/marketplace/iris/scoring_logic.py
@@ -63,6 +63,7 @@ def predict(self, x, return_names=True):
 app = Flask(__name__)
 model = IrisModel(model_path="/opt/ml/model/model-artifacts.joblib")
 
+
 # Create a path for health checks
 @app.route("/ping")
 def endpoint_ping():
diff --git a/tests/data/mxnet_mnist/mnist_hosting_with_custom_handlers.py b/tests/data/mxnet_mnist/mnist_hosting_with_custom_handlers.py
index 37f6c4ccb9..5e017766e8 100644
--- a/tests/data/mxnet_mnist/mnist_hosting_with_custom_handlers.py
+++ b/tests/data/mxnet_mnist/mnist_hosting_with_custom_handlers.py
@@ -22,6 +22,7 @@
 
 # --- this example demonstrates how to extend default behavior during model hosting ---
 
+
 # --- Model preparation ---
 # it is possible to specify own code to load the model, otherwise a default model loading takes place
 def model_fn(path_to_model_files):
diff --git a/tests/data/pipeline/test_source_dir/script_1.py b/tests/data/pipeline/test_source_dir/script_1.py
index 4a427b1898..64143395c8 100644
--- a/tests/data/pipeline/test_source_dir/script_1.py
+++ b/tests/data/pipeline/test_source_dir/script_1.py
@@ -1,6 +1,7 @@
 """
 Integ test file script_1.py
 """
+
 import pathlib
 
 if __name__ == "__main__":
diff --git a/tests/data/tensorflow_mnist/mnist_v2.py b/tests/data/tensorflow_mnist/mnist_v2.py
index 6b506fb58d..05467dee49 100644
--- a/tests/data/tensorflow_mnist/mnist_v2.py
+++ b/tests/data/tensorflow_mnist/mnist_v2.py
@@ -26,6 +26,7 @@
 checkpoint manager.
 """
 
+
 # define a model
 class LeNet(tf.keras.Model):
     def __init__(self):
diff --git a/tests/integ/auto_ml_v2_utils.py b/tests/integ/auto_ml_v2_utils.py
index a227235877..65f304f338 100644
--- a/tests/integ/auto_ml_v2_utils.py
+++ b/tests/integ/auto_ml_v2_utils.py
@@ -118,9 +118,12 @@ def create_auto_ml_job_v2_if_not_exist(sagemaker_session, auto_ml_job_name, prob
         inputs = [
             AutoMLDataChannel(
                 s3_data_type="S3Prefix",
-                s3_uri=s3_uri
-                if DATA_CONFIGS[problem_type]["path"] != os.path.join(DATA_DIR, "cifar10_subset")
-                else s3_uri + "/",
+                s3_uri=(
+                    s3_uri
+                    if DATA_CONFIGS[problem_type]["path"]
+                    != os.path.join(DATA_DIR, "cifar10_subset")
+                    else s3_uri + "/"
+                ),
                 channel_type="training",
                 content_type=DATA_CONFIGS[problem_type]["content_type"],
             )
diff --git a/tests/integ/test_feature_store.py b/tests/integ/test_feature_store.py
index c905ff3a48..43db78527a 100644
--- a/tests/integ/test_feature_store.py
+++ b/tests/integ/test_feature_store.py
@@ -2221,9 +2221,9 @@ def test_ingest_in_memory_multi_process_with_collection_types(
             [3.0, 4.0],
             ["a", "b"],
         ]
-        pandas_data_frame_with_collection_type.loc[
-            len(pandas_data_frame_with_collection_type)
-        ] = new_row_data
+        pandas_data_frame_with_collection_type.loc[len(pandas_data_frame_with_collection_type)] = (
+            new_row_data
+        )
         with pytest.raises(IngestionError):
             feature_group.ingest(
                 data_frame=pandas_data_frame_with_collection_type,
@@ -2284,9 +2284,9 @@ def test_ingest_in_memory_single_process_with_collection_types(
             [3.0, 4.0],
             ["a", "b"],
         ]
-        pandas_data_frame_with_collection_type.loc[
-            len(pandas_data_frame_with_collection_type)
-        ] = new_row_data
+        pandas_data_frame_with_collection_type.loc[len(pandas_data_frame_with_collection_type)] = (
+            new_row_data
+        )
         with pytest.raises(IngestionError):
             feature_group.ingest(
                 data_frame=pandas_data_frame_with_collection_type,
@@ -2333,9 +2333,9 @@ def test_ingest_standard_multi_process_with_collection_types(
             [3.0, 4.0],
             ["a", "b"],
         ]
-        pandas_data_frame_with_collection_type.loc[
-            len(pandas_data_frame_with_collection_type)
-        ] = new_row_data
+        pandas_data_frame_with_collection_type.loc[len(pandas_data_frame_with_collection_type)] = (
+            new_row_data
+        )
 
         ingestion_manager = feature_group.ingest(
             data_frame=pandas_data_frame_with_collection_type,
diff --git a/tests/integ/test_serve.py b/tests/integ/test_serve.py
index 951cfc68ca..08ad232b4a 100644
--- a/tests/integ/test_serve.py
+++ b/tests/integ/test_serve.py
@@ -129,6 +129,7 @@ def xgb_happy_infer(fns, model_path, x_test):
 
 # TODO: introduce cleanup option in serve settings so that we can clean up after ourselves
 
+
 # XGB Integ Tests
 @pytest.mark.skipif(
     SKIP_COND_MET, reason="The goal of these test are to test the serving components of our feature"
diff --git a/tests/unit/sagemaker/hyperparameters/jumpstart/test_validate.py b/tests/unit/sagemaker/hyperparameters/jumpstart/test_validate.py
index 07418f8ddb..fdc29b4d90 100644
--- a/tests/unit/sagemaker/hyperparameters/jumpstart/test_validate.py
+++ b/tests/unit/sagemaker/hyperparameters/jumpstart/test_validate.py
@@ -530,9 +530,9 @@ def test_jumpstart_validate_all_hyperparameters(
         )
     assert str(e.value) == "Cannot find hyperparameter for 'sagemaker_submit_directory'."
 
-    hyperparameter_to_test[
-        "sagemaker_submit_directory"
-    ] = "/opt/ml/input/data/code/sourcedir.tar.gz"
+    hyperparameter_to_test["sagemaker_submit_directory"] = (
+        "/opt/ml/input/data/code/sourcedir.tar.gz"
+    )
     del hyperparameter_to_test["epochs"]
 
     with pytest.raises(JumpStartHyperparametersError) as e:
diff --git a/tests/unit/sagemaker/jumpstart/estimator/test_estimator.py b/tests/unit/sagemaker/jumpstart/estimator/test_estimator.py
index 5a11a5e88d..ce5f15b287 100644
--- a/tests/unit/sagemaker/jumpstart/estimator/test_estimator.py
+++ b/tests/unit/sagemaker/jumpstart/estimator/test_estimator.py
@@ -1090,7 +1090,6 @@ def test_jumpstart_estimator_attach_no_model_id_sad_case(
         mock_attach.assert_not_called()
 
     def test_jumpstart_estimator_kwargs_match_parent_class(self):
-
         """If you add arguments to <Estimator constructor>, this test will fail.
         Please add the new argument to the skip set below,
         and reach out to JumpStart team."""
diff --git a/tests/unit/sagemaker/monitor/test_clarify_model_monitor.py b/tests/unit/sagemaker/monitor/test_clarify_model_monitor.py
index 231f7f2ad7..53119e532a 100644
--- a/tests/unit/sagemaker/monitor/test_clarify_model_monitor.py
+++ b/tests/unit/sagemaker/monitor/test_clarify_model_monitor.py
@@ -1104,9 +1104,9 @@ def _test_model_bias_monitor_update_schedule(model_bias_monitor, sagemaker_sessi
     assert model_bias_monitor.max_runtime_in_seconds == MAX_RUNTIME_IN_SECONDS
     assert model_bias_monitor.env == ENVIRONMENT
     assert model_bias_monitor.network_config == NETWORK_CONFIG
-    expected_arguments[
-        "RoleArn"
-    ] = NEW_ROLE_ARN  # all but role arn are from existing job definition
+    expected_arguments["RoleArn"] = (
+        NEW_ROLE_ARN  # all but role arn are from existing job definition
+    )
     sagemaker_session.sagemaker_client.create_model_bias_job_definition.assert_called_once_with(
         **expected_arguments
     )
@@ -1627,9 +1627,9 @@ def _test_model_explainability_monitor_update_schedule(
     assert model_explainability_monitor.max_runtime_in_seconds == MAX_RUNTIME_IN_SECONDS
     assert model_explainability_monitor.env == ENVIRONMENT
     assert model_explainability_monitor.network_config == NETWORK_CONFIG
-    expected_arguments[
-        "RoleArn"
-    ] = NEW_ROLE_ARN  # all but role arn are from existing job definition
+    expected_arguments["RoleArn"] = (
+        NEW_ROLE_ARN  # all but role arn are from existing job definition
+    )
     sagemaker_session.sagemaker_client.create_model_explainability_job_definition.assert_called_once_with(
         **expected_arguments
     )
diff --git a/tests/unit/sagemaker/monitor/test_model_monitoring.py b/tests/unit/sagemaker/monitor/test_model_monitoring.py
index 2035aa9d3a..d31b9f8527 100644
--- a/tests/unit/sagemaker/monitor/test_model_monitoring.py
+++ b/tests/unit/sagemaker/monitor/test_model_monitoring.py
@@ -1164,9 +1164,9 @@ def _test_data_quality_monitor_update_schedule(data_quality_monitor, sagemaker_s
     assert data_quality_monitor.max_runtime_in_seconds == MAX_RUNTIME_IN_SECONDS
     assert data_quality_monitor.env == ENVIRONMENT
     assert data_quality_monitor.network_config == NETWORK_CONFIG
-    expected_arguments[
-        "RoleArn"
-    ] = NEW_ROLE_ARN  # all but role arn are from existing job definition
+    expected_arguments["RoleArn"] = (
+        NEW_ROLE_ARN  # all but role arn are from existing job definition
+    )
     sagemaker_session.sagemaker_client.create_data_quality_job_definition.assert_called_once_with(
         **expected_arguments
     )
@@ -1786,9 +1786,9 @@ def _test_model_quality_monitor_update_schedule(model_quality_monitor, sagemaker
     assert model_quality_monitor.max_runtime_in_seconds == MAX_RUNTIME_IN_SECONDS
     assert model_quality_monitor.env == ENVIRONMENT
     assert model_quality_monitor.network_config == NETWORK_CONFIG
-    expected_arguments[
-        "RoleArn"
-    ] = NEW_ROLE_ARN  # all but role arn are from existing job definition
+    expected_arguments["RoleArn"] = (
+        NEW_ROLE_ARN  # all but role arn are from existing job definition
+    )
     sagemaker_session.sagemaker_client.create_model_quality_job_definition.assert_called_once_with(
         **expected_arguments
     )
diff --git a/tests/unit/sagemaker/remote_function/core/test_serialization.py b/tests/unit/sagemaker/remote_function/core/test_serialization.py
index 98280af51b..a0742240ea 100644
--- a/tests/unit/sagemaker/remote_function/core/test_serialization.py
+++ b/tests/unit/sagemaker/remote_function/core/test_serialization.py
@@ -439,8 +439,7 @@ def test_serialize_deserialize_service_error():
 def test_serialize_deserialize_exception_with_traceback():
     s3_uri = random_s3_uri()
 
-    class CustomError(Exception):
-        ...
+    class CustomError(Exception): ...  # noqa E701
 
     def func_a():
         raise TypeError
@@ -469,8 +468,7 @@ def func_b():
 def test_serialize_deserialize_custom_exception_with_traceback():
     s3_uri = random_s3_uri()
 
-    class CustomError(Exception):
-        ...
+    class CustomError(Exception): ...  # noqa: E701
 
     def func_a():
         raise TypeError
@@ -500,8 +498,7 @@ def func_b():
 def test_serialize_deserialize_remote_function_error_with_traceback():
     s3_uri = random_s3_uri()
 
-    class CustomError(Exception):
-        ...
+    class CustomError(Exception): ...  # noqa: E701
 
     def func_a():
         raise TypeError
diff --git a/tests/unit/sagemaker/serve/builder/test_model_builder.py b/tests/unit/sagemaker/serve/builder/test_model_builder.py
index eeadd5a495..1d199b7401 100644
--- a/tests/unit/sagemaker/serve/builder/test_model_builder.py
+++ b/tests/unit/sagemaker/serve/builder/test_model_builder.py
@@ -143,8 +143,8 @@ def test_build_happy_path_with_sagemaker_endpoint_mode_and_byoc(
         mock_detect_fw_version,
     ):
         # setup mocks
-        mock_detect_container.side_effect = (
-            lambda model, region, instance_type: mock_image_uri
+        mock_detect_container.side_effect = lambda model, region, instance_type: (
+            mock_image_uri
             if model == mock_fw_model
             and region == mock_session.boto_region_name
             and instance_type == "ml.c5.xlarge"
@@ -154,14 +154,16 @@ def test_build_happy_path_with_sagemaker_endpoint_mode_and_byoc(
         mock_detect_fw_version.return_value = framework, version
 
         mock_prepare_for_torchserve.side_effect = (
-            lambda model_path, shared_libs, dependencies, session, image_uri, inference_spec: mock_secret_key
-            if model_path == MODEL_PATH
-            and shared_libs == []
-            and dependencies == {"auto": False}
-            and session == session
-            and image_uri == mock_image_uri
-            and inference_spec is None
-            else None
+            lambda model_path, shared_libs, dependencies, session, image_uri, inference_spec: (
+                mock_secret_key
+                if model_path == MODEL_PATH
+                and shared_libs == []
+                and dependencies == {"auto": False}
+                and session == session
+                and image_uri == mock_image_uri
+                and inference_spec is None
+                else None
+            )
         )
 
         # Mock _ServeSettings
@@ -172,13 +174,11 @@ def test_build_happy_path_with_sagemaker_endpoint_mode_and_byoc(
         mock_path_exists.side_effect = lambda path: True if path == "test_path" else False
 
         mock_mode = Mock()
-        mock_sageMakerEndpointMode.side_effect = (
-            lambda inference_spec, model_server: mock_mode
-            if inference_spec is None and model_server == ModelServer.TORCHSERVE
-            else None
+        mock_sageMakerEndpointMode.side_effect = lambda inference_spec, model_server: (
+            mock_mode if inference_spec is None and model_server == ModelServer.TORCHSERVE else None
         )
-        mock_mode.prepare.side_effect = (
-            lambda model_path, secret_key, s3_model_data_url, sagemaker_session, image_uri, jumpstart: (
+        mock_mode.prepare.side_effect = lambda model_path, secret_key, s3_model_data_url, sagemaker_session, image_uri, jumpstart: (  # noqa E501
+            (
                 model_data,
                 ENV_VAR_PAIR,
             )
@@ -191,8 +191,8 @@ def test_build_happy_path_with_sagemaker_endpoint_mode_and_byoc(
         )
 
         mock_model_obj = Mock()
-        mock_sdk_model.side_effect = (
-            lambda image_uri, image_config, vpc_config, model_data, role, env, sagemaker_session, predictor_cls: mock_model_obj  # noqa E501
+        mock_sdk_model.side_effect = lambda image_uri, image_config, vpc_config, model_data, role, env, sagemaker_session, predictor_cls: (  # noqa E501
+            mock_model_obj
             if image_uri == mock_image_uri
             and image_config == MOCK_IMAGE_CONFIG
             and vpc_config == MOCK_VPC_CONFIG
@@ -247,8 +247,8 @@ def test_build_happy_path_with_sagemaker_endpoint_mode_and_1p_dlc_as_byoc(
         mock_detect_fw_version,
     ):
         # setup mocks
-        mock_detect_container.side_effect = (
-            lambda model, region, instance_type: mock_1p_dlc_image_uri
+        mock_detect_container.side_effect = lambda model, region, instance_type: (
+            mock_1p_dlc_image_uri
             if model == mock_fw_model
             and region == mock_session.boto_region_name
             and instance_type == "ml.c5.xlarge"
@@ -257,14 +257,16 @@ def test_build_happy_path_with_sagemaker_endpoint_mode_and_1p_dlc_as_byoc(
         mock_detect_fw_version.return_value = framework, version
 
         mock_prepare_for_torchserve.side_effect = (
-            lambda model_path, shared_libs, dependencies, session, image_uri, inference_spec: mock_secret_key
-            if model_path == MODEL_PATH
-            and shared_libs == []
-            and dependencies == {"auto": False}
-            and session == session
-            and image_uri == mock_1p_dlc_image_uri
-            and inference_spec is None
-            else None
+            lambda model_path, shared_libs, dependencies, session, image_uri, inference_spec: (
+                mock_secret_key
+                if model_path == MODEL_PATH
+                and shared_libs == []
+                and dependencies == {"auto": False}
+                and session == session
+                and image_uri == mock_1p_dlc_image_uri
+                and inference_spec is None
+                else None
+            )
         )
 
         # Mock _ServeSettings
@@ -275,13 +277,11 @@ def test_build_happy_path_with_sagemaker_endpoint_mode_and_1p_dlc_as_byoc(
         mock_path_exists.side_effect = lambda path: True if path == "test_path" else False
 
         mock_mode = Mock()
-        mock_sageMakerEndpointMode.side_effect = (
-            lambda inference_spec, model_server: mock_mode
-            if inference_spec is None and model_server == ModelServer.TORCHSERVE
-            else None
+        mock_sageMakerEndpointMode.side_effect = lambda inference_spec, model_server: (
+            mock_mode if inference_spec is None and model_server == ModelServer.TORCHSERVE else None
         )
-        mock_mode.prepare.side_effect = (
-            lambda model_path, secret_key, s3_model_data_url, sagemaker_session, image_uri, jumpstart: (
+        mock_mode.prepare.side_effect = lambda model_path, secret_key, s3_model_data_url, sagemaker_session, image_uri, jumpstart: (  # noqa E501
+            (
                 model_data,
                 ENV_VAR_PAIR,
             )
@@ -294,8 +294,8 @@ def test_build_happy_path_with_sagemaker_endpoint_mode_and_1p_dlc_as_byoc(
         )
 
         mock_model_obj = Mock()
-        mock_sdk_model.side_effect = (
-            lambda image_uri, image_config, vpc_config, model_data, role, env, sagemaker_session, predictor_cls: mock_model_obj  # noqa E501
+        mock_sdk_model.side_effect = lambda image_uri, image_config, vpc_config, model_data, role, env, sagemaker_session, predictor_cls: (  # noqa E501
+            mock_model_obj
             if image_uri == mock_1p_dlc_image_uri
             and model_data == model_data
             and role == mock_role_arn
@@ -347,14 +347,14 @@ def test_build_happy_path_with_sagemaker_endpoint_mode_and_inference_spec(
     ):
         # setup mocks
         mock_native_model = Mock()
-        mock_inference_spec.load = (
-            lambda model_path: mock_native_model if model_path == MODEL_PATH else None
+        mock_inference_spec.load = lambda model_path: (
+            mock_native_model if model_path == MODEL_PATH else None
         )
 
         mock_detect_fw_version.return_value = framework, version
 
-        mock_detect_container.side_effect = (
-            lambda model, region, instance_type: mock_image_uri
+        mock_detect_container.side_effect = lambda model, region, instance_type: (
+            mock_image_uri
             if model == mock_native_model
             and region == mock_session.boto_region_name
             and instance_type == "ml.c5.xlarge"
@@ -362,14 +362,16 @@ def test_build_happy_path_with_sagemaker_endpoint_mode_and_inference_spec(
         )
 
         mock_prepare_for_torchserve.side_effect = (
-            lambda model_path, shared_libs, dependencies, session, image_uri, inference_spec: mock_secret_key
-            if model_path == MODEL_PATH
-            and shared_libs == []
-            and dependencies == {"auto": False}
-            and session == mock_session
-            and image_uri == mock_image_uri
-            and inference_spec == mock_inference_spec
-            else None
+            lambda model_path, shared_libs, dependencies, session, image_uri, inference_spec: (
+                mock_secret_key
+                if model_path == MODEL_PATH
+                and shared_libs == []
+                and dependencies == {"auto": False}
+                and session == mock_session
+                and image_uri == mock_image_uri
+                and inference_spec == mock_inference_spec
+                else None
+            )
         )
 
         # Mock _ServeSettings
@@ -380,13 +382,13 @@ def test_build_happy_path_with_sagemaker_endpoint_mode_and_inference_spec(
         mock_path_exists.side_effect = lambda path: True if path == "test_path" else False
 
         mock_mode = Mock()
-        mock_sageMakerEndpointMode.side_effect = (
-            lambda inference_spec, model_server: mock_mode
+        mock_sageMakerEndpointMode.side_effect = lambda inference_spec, model_server: (
+            mock_mode
             if inference_spec == mock_inference_spec and model_server == ModelServer.TORCHSERVE
             else None
         )
-        mock_mode.prepare.side_effect = (
-            lambda model_path, secret_key, s3_model_data_url, sagemaker_session, image_uri, jumpstart: (
+        mock_mode.prepare.side_effect = lambda model_path, secret_key, s3_model_data_url, sagemaker_session, image_uri, jumpstart: (  # noqa E501
+            (
                 model_data,
                 ENV_VAR_PAIR,
             )
@@ -399,8 +401,8 @@ def test_build_happy_path_with_sagemaker_endpoint_mode_and_inference_spec(
         )
 
         mock_model_obj = Mock()
-        mock_sdk_model.side_effect = (
-            lambda image_uri, image_config, vpc_config, model_data, role, env, sagemaker_session, predictor_cls: mock_model_obj  # noqa E501
+        mock_sdk_model.side_effect = lambda image_uri, image_config, vpc_config, model_data, role, env, sagemaker_session, predictor_cls: (  # noqa E501
+            mock_model_obj
             if image_uri == mock_image_uri
             and model_data == model_data
             and role == mock_role_arn
@@ -447,8 +449,8 @@ def test_build_happy_path_with_sagemakerEndpoint_mode_and_model(
         mock_detect_fw_version,
     ):
         # setup mocks
-        mock_detect_container.side_effect = (
-            lambda model, region, instance_type: mock_image_uri
+        mock_detect_container.side_effect = lambda model, region, instance_type: (
+            mock_image_uri
             if model == mock_fw_model
             and region == mock_session.boto_region_name
             and instance_type == "ml.c5.xlarge"
@@ -458,14 +460,16 @@ def test_build_happy_path_with_sagemakerEndpoint_mode_and_model(
         mock_detect_fw_version.return_value = framework, version
 
         mock_prepare_for_torchserve.side_effect = (
-            lambda model_path, shared_libs, dependencies, session, image_uri, inference_spec: mock_secret_key
-            if model_path == MODEL_PATH
-            and shared_libs == []
-            and dependencies == {"auto": False}
-            and session == session
-            and image_uri == mock_image_uri
-            and inference_spec is None
-            else None
+            lambda model_path, shared_libs, dependencies, session, image_uri, inference_spec: (
+                mock_secret_key
+                if model_path == MODEL_PATH
+                and shared_libs == []
+                and dependencies == {"auto": False}
+                and session == session
+                and image_uri == mock_image_uri
+                and inference_spec is None
+                else None
+            )
         )
 
         # Mock _ServeSettings
@@ -476,13 +480,11 @@ def test_build_happy_path_with_sagemakerEndpoint_mode_and_model(
         mock_path_exists.side_effect = lambda path: True if path == "test_path" else False
 
         mock_mode = Mock()
-        mock_sageMakerEndpointMode.side_effect = (
-            lambda inference_spec, model_server: mock_mode
-            if inference_spec is None and model_server == ModelServer.TORCHSERVE
-            else None
+        mock_sageMakerEndpointMode.side_effect = lambda inference_spec, model_server: (
+            mock_mode if inference_spec is None and model_server == ModelServer.TORCHSERVE else None
         )
-        mock_mode.prepare.side_effect = (
-            lambda model_path, secret_key, s3_model_data_url, sagemaker_session, image_uri, jumpstart: (
+        mock_mode.prepare.side_effect = lambda model_path, secret_key, s3_model_data_url, sagemaker_session, image_uri, jumpstart: (  # noqa E501
+            (
                 model_data,
                 ENV_VAR_PAIR,
             )
@@ -495,8 +497,8 @@ def test_build_happy_path_with_sagemakerEndpoint_mode_and_model(
         )
 
         mock_model_obj = Mock()
-        mock_sdk_model.side_effect = (
-            lambda image_uri, image_config, vpc_config, model_data, role, env, sagemaker_session, predictor_cls: mock_model_obj  # noqa E501
+        mock_sdk_model.side_effect = lambda image_uri, image_config, vpc_config, model_data, role, env, sagemaker_session, predictor_cls: (  # noqa E501
+            mock_model_obj
             if image_uri == mock_image_uri
             and model_data == model_data
             and role == mock_role_arn
@@ -551,8 +553,8 @@ def test_build_happy_path_with_sagemakerEndpoint_mode_and_xgboost_model(
         mock_save_xgb,
     ):
         # setup mocks
-        mock_detect_container.side_effect = (
-            lambda model, region, instance_type: mock_image_uri
+        mock_detect_container.side_effect = lambda model, region, instance_type: (
+            mock_image_uri
             if model == mock_fw_model
             and region == mock_session.boto_region_name
             and instance_type == "ml.c5.xlarge"
@@ -562,14 +564,16 @@ def test_build_happy_path_with_sagemakerEndpoint_mode_and_xgboost_model(
         mock_detect_fw_version.return_value = "xgboost", version
 
         mock_prepare_for_torchserve.side_effect = (
-            lambda model_path, shared_libs, dependencies, session, image_uri, inference_spec: mock_secret_key
-            if model_path == MODEL_PATH
-            and shared_libs == []
-            and dependencies == {"auto": False}
-            and session == session
-            and image_uri == mock_image_uri
-            and inference_spec is None
-            else None
+            lambda model_path, shared_libs, dependencies, session, image_uri, inference_spec: (
+                mock_secret_key
+                if model_path == MODEL_PATH
+                and shared_libs == []
+                and dependencies == {"auto": False}
+                and session == session
+                and image_uri == mock_image_uri
+                and inference_spec is None
+                else None
+            )
         )
 
         # Mock _ServeSettings
@@ -580,13 +584,11 @@ def test_build_happy_path_with_sagemakerEndpoint_mode_and_xgboost_model(
         mock_path_exists.side_effect = lambda path: True if path == "test_path" else False
 
         mock_mode = Mock()
-        mock_sageMakerEndpointMode.side_effect = (
-            lambda inference_spec, model_server: mock_mode
-            if inference_spec is None and model_server == ModelServer.TORCHSERVE
-            else None
+        mock_sageMakerEndpointMode.side_effect = lambda inference_spec, model_server: (
+            mock_mode if inference_spec is None and model_server == ModelServer.TORCHSERVE else None
         )
-        mock_mode.prepare.side_effect = (
-            lambda model_path, secret_key, s3_model_data_url, sagemaker_session, image_uri, jumpstart: (
+        mock_mode.prepare.side_effect = lambda model_path, secret_key, s3_model_data_url, sagemaker_session, image_uri, jumpstart: (  # noqa E501
+            (
                 model_data,
                 ENV_VAR_PAIR,
             )
@@ -599,8 +601,8 @@ def test_build_happy_path_with_sagemakerEndpoint_mode_and_xgboost_model(
         )
 
         mock_model_obj = Mock()
-        mock_sdk_model.side_effect = (
-            lambda image_uri, image_config, vpc_config, model_data, role, env, sagemaker_session, predictor_cls: mock_model_obj  # noqa E501
+        mock_sdk_model.side_effect = lambda image_uri, image_config, vpc_config, model_data, role, env, sagemaker_session, predictor_cls: (  # noqa E501
+            mock_model_obj
             if image_uri == mock_image_uri
             and model_data == model_data
             and role == mock_role_arn
@@ -655,12 +657,12 @@ def test_build_happy_path_with_local_container_mode(
     ):
         # setup mocks
         mock_native_model = Mock()
-        mock_inference_spec.load = (
-            lambda model_path: mock_native_model if model_path == MODEL_PATH else None
+        mock_inference_spec.load = lambda model_path: (
+            mock_native_model if model_path == MODEL_PATH else None
         )
 
-        mock_detect_container.side_effect = (
-            lambda model, region, instance_type: mock_image_uri
+        mock_detect_container.side_effect = lambda model, region, instance_type: (
+            mock_image_uri
             if model == mock_native_model
             and region == mock_session.boto_region_name
             and instance_type == "ml.c5.xlarge"
@@ -668,14 +670,16 @@ def test_build_happy_path_with_local_container_mode(
         )
 
         mock_prepare_for_torchserve.side_effect = (
-            lambda model_path, shared_libs, dependencies, session, image_uri, inference_spec: mock_secret_key
-            if model_path == MODEL_PATH
-            and shared_libs == []
-            and dependencies == {"auto": False}
-            and session == mock_session
-            and image_uri == mock_image_uri
-            and inference_spec == mock_inference_spec
-            else None
+            lambda model_path, shared_libs, dependencies, session, image_uri, inference_spec: (
+                mock_secret_key
+                if model_path == MODEL_PATH
+                and shared_libs == []
+                and dependencies == {"auto": False}
+                and session == mock_session
+                and image_uri == mock_image_uri
+                and inference_spec == mock_inference_spec
+                else None
+            )
         )
 
         # Mock _ServeSettings
@@ -687,21 +691,23 @@ def test_build_happy_path_with_local_container_mode(
 
         mock_mode = Mock()
         mock_localContainerMode.side_effect = (
-            lambda inference_spec, schema_builder, session, model_path, env_vars, model_server: mock_mode
-            if inference_spec == mock_inference_spec
-            and schema_builder == schema_builder
-            and model_server == ModelServer.TORCHSERVE
-            and session == mock_session
-            and model_path == MODEL_PATH
-            and env_vars == {}
-            and model_server == ModelServer.TORCHSERVE
-            else None
+            lambda inference_spec, schema_builder, session, model_path, env_vars, model_server: (
+                mock_mode
+                if inference_spec == mock_inference_spec
+                and schema_builder == schema_builder
+                and model_server == ModelServer.TORCHSERVE
+                and session == mock_session
+                and model_path == MODEL_PATH
+                and env_vars == {}
+                and model_server == ModelServer.TORCHSERVE
+                else None
+            )
         )
         mock_mode.prepare.side_effect = lambda: None
 
         mock_model_obj = Mock()
-        mock_sdk_model.side_effect = (
-            lambda image_uri, image_config, vpc_config, model_data, role, env, sagemaker_session, predictor_cls: mock_model_obj  # noqa E501
+        mock_sdk_model.side_effect = lambda image_uri, image_config, vpc_config, model_data, role, env, sagemaker_session, predictor_cls: (  # noqa E501
+            mock_model_obj
             if image_uri == mock_image_uri
             and model_data is None
             and role == mock_role_arn
@@ -751,14 +757,14 @@ def test_build_happy_path_with_localContainer_mode_overwritten_with_sagemaker_mo
     ):
         # setup mocks
         mock_native_model = Mock()
-        mock_inference_spec.load = (
-            lambda model_path: mock_native_model if model_path == MODEL_PATH else None
+        mock_inference_spec.load = lambda model_path: (
+            mock_native_model if model_path == MODEL_PATH else None
         )
 
         mock_detect_fw_version.return_value = framework, version
 
-        mock_detect_container.side_effect = (
-            lambda model, region, instance_type: mock_image_uri
+        mock_detect_container.side_effect = lambda model, region, instance_type: (
+            mock_image_uri
             if model == mock_native_model
             and region == mock_session.boto_region_name
             and instance_type == "ml.c5.xlarge"
@@ -766,14 +772,16 @@ def test_build_happy_path_with_localContainer_mode_overwritten_with_sagemaker_mo
         )
 
         mock_prepare_for_torchserve.side_effect = (
-            lambda model_path, shared_libs, dependencies, session, image_uri, inference_spec: mock_secret_key
-            if model_path == MODEL_PATH
-            and shared_libs == []
-            and dependencies == {"auto": False}
-            and session == mock_session
-            and image_uri == mock_image_uri
-            and inference_spec == mock_inference_spec
-            else None
+            lambda model_path, shared_libs, dependencies, session, image_uri, inference_spec: (
+                mock_secret_key
+                if model_path == MODEL_PATH
+                and shared_libs == []
+                and dependencies == {"auto": False}
+                and session == mock_session
+                and image_uri == mock_image_uri
+                and inference_spec == mock_inference_spec
+                else None
+            )
         )
 
         # Mock _ServeSettings
@@ -785,26 +793,28 @@ def test_build_happy_path_with_localContainer_mode_overwritten_with_sagemaker_mo
 
         mock_lc_mode = Mock()
         mock_localContainerMode.side_effect = (
-            lambda inference_spec, schema_builder, session, model_path, env_vars, model_server: mock_lc_mode
-            if inference_spec == mock_inference_spec
-            and schema_builder == schema_builder
-            and model_server == ModelServer.TORCHSERVE
-            and session == mock_session
-            and model_path == MODEL_PATH
-            and env_vars == {}
-            and model_server == ModelServer.TORCHSERVE
-            else None
+            lambda inference_spec, schema_builder, session, model_path, env_vars, model_server: (
+                mock_lc_mode
+                if inference_spec == mock_inference_spec
+                and schema_builder == schema_builder
+                and model_server == ModelServer.TORCHSERVE
+                and session == mock_session
+                and model_path == MODEL_PATH
+                and env_vars == {}
+                and model_server == ModelServer.TORCHSERVE
+                else None
+            )
         )
         mock_lc_mode.prepare.side_effect = lambda: None
 
         mock_sagemaker_endpoint_mode = Mock()
-        mock_sageMakerEndpointMode.side_effect = (
-            lambda inference_spec, model_server: mock_sagemaker_endpoint_mode
+        mock_sageMakerEndpointMode.side_effect = lambda inference_spec, model_server: (
+            mock_sagemaker_endpoint_mode
             if inference_spec == mock_inference_spec and model_server == ModelServer.TORCHSERVE
             else None
         )
-        mock_sagemaker_endpoint_mode.prepare.side_effect = (
-            lambda model_path, secret_key, s3_model_data_url, sagemaker_session, image_uri, jumpstart: (
+        mock_sagemaker_endpoint_mode.prepare.side_effect = lambda model_path, secret_key, s3_model_data_url, sagemaker_session, image_uri, jumpstart: (  # noqa E501
+            (
                 model_data,
                 ENV_VAR_PAIR,
             )
@@ -817,8 +827,8 @@ def test_build_happy_path_with_localContainer_mode_overwritten_with_sagemaker_mo
         )
 
         mock_model_obj = Mock()
-        mock_sdk_model.side_effect = (
-            lambda image_uri, image_config, vpc_config, model_data, role, env, sagemaker_session, predictor_cls: mock_model_obj  # noqa E501
+        mock_sdk_model.side_effect = lambda image_uri, image_config, vpc_config, model_data, role, env, sagemaker_session, predictor_cls: (  # noqa E501
+            mock_model_obj
             if image_uri == mock_image_uri
             and model_data is None
             and role == mock_role_arn
@@ -848,8 +858,8 @@ def test_build_happy_path_with_localContainer_mode_overwritten_with_sagemaker_mo
         mock_predictor = Mock()
 
         builder._original_deploy = Mock()
-        builder._original_deploy.side_effect = (
-            lambda *args, **kwargs: mock_predictor
+        builder._original_deploy.side_effect = lambda *args, **kwargs: (
+            mock_predictor
             if kwargs.get("initial_instance_count") == 1
             and kwargs.get("instance_type") == mock_instance_type
             else None
@@ -893,8 +903,8 @@ def test_build_happy_path_with_sagemaker_endpoint_mode_overwritten_with_local_co
         # setup mocks
         mock_detect_fw_version.return_value = framework, version
 
-        mock_detect_container.side_effect = (
-            lambda model, region, instance_type: mock_image_uri
+        mock_detect_container.side_effect = lambda model, region, instance_type: (
+            mock_image_uri
             if model == mock_fw_model
             and region == mock_session.boto_region_name
             and instance_type == "ml.c5.xlarge"
@@ -902,14 +912,16 @@ def test_build_happy_path_with_sagemaker_endpoint_mode_overwritten_with_local_co
         )
 
         mock_prepare_for_torchserve.side_effect = (
-            lambda model_path, shared_libs, dependencies, image_uri, session, inference_spec: mock_secret_key
-            if model_path == MODEL_PATH
-            and shared_libs == []
-            and dependencies == {"auto": False}
-            and session == mock_session
-            and inference_spec is None
-            and image_uri == mock_image_uri
-            else None
+            lambda model_path, shared_libs, dependencies, image_uri, session, inference_spec: (
+                mock_secret_key
+                if model_path == MODEL_PATH
+                and shared_libs == []
+                and dependencies == {"auto": False}
+                and session == mock_session
+                and inference_spec is None
+                and image_uri == mock_image_uri
+                else None
+            )
         )
 
         # Mock _ServeSettings
@@ -920,13 +932,11 @@ def test_build_happy_path_with_sagemaker_endpoint_mode_overwritten_with_local_co
         mock_path_exists.side_effect = lambda path: True if path == "test_path" else False
 
         mock_mode = Mock()
-        mock_sageMakerEndpointMode.side_effect = (
-            lambda inference_spec, model_server: mock_mode
-            if inference_spec is None and model_server == ModelServer.TORCHSERVE
-            else None
+        mock_sageMakerEndpointMode.side_effect = lambda inference_spec, model_server: (
+            mock_mode if inference_spec is None and model_server == ModelServer.TORCHSERVE else None
         )
-        mock_mode.prepare.side_effect = (
-            lambda model_path, secret_key, s3_model_data_url, sagemaker_session, image_uri, jumpstart: (
+        mock_mode.prepare.side_effect = lambda model_path, secret_key, s3_model_data_url, sagemaker_session, image_uri, jumpstart: (  # noqa E501
+            (
                 model_data,
                 ENV_VAR_PAIR,
             )
@@ -940,27 +950,31 @@ def test_build_happy_path_with_sagemaker_endpoint_mode_overwritten_with_local_co
 
         mock_lc_mode = Mock()
         mock_localContainerMode.side_effect = (
-            lambda inference_spec, schema_builder, session, model_path, env_vars, model_server: mock_lc_mode
-            if inference_spec is None
-            and schema_builder == schema_builder
-            and model_server == ModelServer.TORCHSERVE
-            and session == mock_session
-            and model_path == MODEL_PATH
-            and env_vars == ENV_VARS
-            else None
+            lambda inference_spec, schema_builder, session, model_path, env_vars, model_server: (
+                mock_lc_mode
+                if inference_spec is None
+                and schema_builder == schema_builder
+                and model_server == ModelServer.TORCHSERVE
+                and session == mock_session
+                and model_path == MODEL_PATH
+                and env_vars == ENV_VARS
+                else None
+            )
         )
         mock_lc_mode.prepare.side_effect = lambda: None
         mock_lc_mode.create_server.side_effect = (
-            lambda image_uri, container_timeout_seconds, secret_key, predictor: None
-            if image_uri == mock_image_uri
-            and secret_key == mock_secret_key
-            and container_timeout_seconds == 60
-            else None
+            lambda image_uri, container_timeout_seconds, secret_key, predictor: (
+                None
+                if image_uri == mock_image_uri
+                and secret_key == mock_secret_key
+                and container_timeout_seconds == 60
+                else None
+            )
         )
 
         mock_model_obj = Mock()
-        mock_sdk_model.side_effect = (
-            lambda image_uri, image_config, vpc_config, model_data, role, env, sagemaker_session, predictor_cls: mock_model_obj  # noqa E501
+        mock_sdk_model.side_effect = lambda image_uri, image_config, vpc_config, model_data, role, env, sagemaker_session, predictor_cls: (  # noqa E501
+            mock_model_obj
             if image_uri == mock_image_uri
             and model_data == model_data
             and role == mock_role_arn
@@ -1708,10 +1722,8 @@ def test_build_mlflow_model_local_input_happy(
         mock_path_exists.side_effect = lambda path: True if path == "test_path" else False
 
         mock_mode = Mock()
-        mock_sageMakerEndpointMode.side_effect = (
-            lambda inference_spec, model_server: mock_mode
-            if inference_spec is None and model_server == ModelServer.TORCHSERVE
-            else None
+        mock_sageMakerEndpointMode.side_effect = lambda inference_spec, model_server: (
+            mock_mode if inference_spec is None and model_server == ModelServer.TORCHSERVE else None
         )
         mock_mode.prepare.return_value = (
             model_data,
@@ -1785,10 +1797,8 @@ def test_build_mlflow_model_s3_input_happy(
         mock_path_exists.side_effect = lambda path: True if path == "test_path" else False
 
         mock_mode = Mock()
-        mock_sageMakerEndpointMode.side_effect = (
-            lambda inference_spec, model_server: mock_mode
-            if inference_spec is None and model_server == ModelServer.TORCHSERVE
-            else None
+        mock_sageMakerEndpointMode.side_effect = lambda inference_spec, model_server: (
+            mock_mode if inference_spec is None and model_server == ModelServer.TORCHSERVE else None
         )
         mock_mode.prepare.return_value = (
             model_data,
@@ -1861,10 +1871,8 @@ def test_build_mlflow_model_s3_input_non_mlflow_case(
         mock_path_exists.side_effect = lambda path: True if path == "test_path" else False
 
         mock_mode = Mock()
-        mock_sageMakerEndpointMode.side_effect = (
-            lambda inference_spec, model_server: mock_mode
-            if inference_spec is None and model_server == ModelServer.TORCHSERVE
-            else None
+        mock_sageMakerEndpointMode.side_effect = lambda inference_spec, model_server: (
+            mock_mode if inference_spec is None and model_server == ModelServer.TORCHSERVE else None
         )
         mock_mode.prepare.return_value = (
             model_data,
diff --git a/tests/unit/sagemaker/serve/model_server/triton/test_server.py b/tests/unit/sagemaker/serve/model_server/triton/test_server.py
index 0e6ea624d7..c80c4296e7 100644
--- a/tests/unit/sagemaker/serve/model_server/triton/test_server.py
+++ b/tests/unit/sagemaker/serve/model_server/triton/test_server.py
@@ -40,8 +40,8 @@ class TritonServerTests(TestCase):
     @patch("sagemaker.serve.model_server.triton.server.importlib")
     def test_start_invoke_destroy_local_triton_server_gpu(self, mock_importlib):
         mock_triton_client = Mock()
-        mock_importlib.import_module.side_effect = (
-            lambda module_name: mock_triton_client if module_name == "tritonclient.http" else None
+        mock_importlib.import_module.side_effect = lambda module_name: (
+            mock_triton_client if module_name == "tritonclient.http" else None
         )
 
         mock_container = Mock()
@@ -99,8 +99,8 @@ def test_start_invoke_destroy_local_triton_server_gpu(self, mock_importlib):
     @patch("sagemaker.serve.model_server.triton.server.importlib")
     def test_start_invoke_destroy_local_triton_server_cpu(self, mock_importlib):
         mock_triton_client = Mock()
-        mock_importlib.import_module.side_effect = (
-            lambda module_name: mock_triton_client if module_name == "tritonclient.http" else None
+        mock_importlib.import_module.side_effect = lambda module_name: (
+            mock_triton_client if module_name == "tritonclient.http" else None
         )
 
         mock_container = Mock()
@@ -158,8 +158,8 @@ def test_start_invoke_destroy_local_triton_server_cpu(self, mock_importlib):
     def test_upload_artifacts_sagemaker_triton_server(self, mock_upload, mock_platform):
         mock_session = Mock()
         mock_platform.python_version.return_value = "3.8"
-        mock_upload.side_effect = (
-            lambda session, repo, bucket, prefix: S3_URI
+        mock_upload.side_effect = lambda session, repo, bucket, prefix: (
+            S3_URI
             if session == mock_session
             and repo == MODEL_PATH + "/model_repository"
             and bucket == "mock_model_data_uri"
diff --git a/tests/unit/sagemaker/tensorflow/test_estimator.py b/tests/unit/sagemaker/tensorflow/test_estimator.py
index 475639bd1d..de91703d63 100644
--- a/tests/unit/sagemaker/tensorflow/test_estimator.py
+++ b/tests/unit/sagemaker/tensorflow/test_estimator.py
@@ -554,9 +554,9 @@ def test_fit_mwms(
 
     expected_train_args = _create_train_job(framework_version, py_version=py_version)
     expected_train_args["input_config"][0]["DataSource"]["S3DataSource"]["S3Uri"] = inputs
-    expected_train_args[
-        "image_uri"
-    ] = f"763104351884.dkr.ecr.{REGION}.amazonaws.com/tensorflow-training:{framework_version}-cpu-{py_version}"
+    expected_train_args["image_uri"] = (
+        f"763104351884.dkr.ecr.{REGION}.amazonaws.com/tensorflow-training:{framework_version}-cpu-{py_version}"
+    )
     expected_train_args["job_name"] = f"tensorflow-training-{TIMESTAMP}"
     expected_train_args["hyperparameters"][TensorFlow.LAUNCH_MWMS_ENV_NAME] = json.dumps(True)
     expected_train_args["hyperparameters"]["sagemaker_job_name"] = json.dumps(
diff --git a/tests/unit/sagemaker/training_compiler/test_tensorflow_compiler.py b/tests/unit/sagemaker/training_compiler/test_tensorflow_compiler.py
index a165fa523e..ac42bb53ab 100644
--- a/tests/unit/sagemaker/training_compiler/test_tensorflow_compiler.py
+++ b/tests/unit/sagemaker/training_compiler/test_tensorflow_compiler.py
@@ -299,9 +299,9 @@ def test_default(
         )
         expected_train_args["input_config"][0]["DataSource"]["S3DataSource"]["S3Uri"] = inputs
         expected_train_args["enable_sagemaker_metrics"] = False
-        expected_train_args["hyperparameters"][
-            TrainingCompilerConfig.HP_ENABLE_COMPILER
-        ] = json.dumps(True)
+        expected_train_args["hyperparameters"][TrainingCompilerConfig.HP_ENABLE_COMPILER] = (
+            json.dumps(True)
+        )
         expected_train_args["hyperparameters"][TrainingCompilerConfig.HP_ENABLE_DEBUG] = json.dumps(
             False
         )
@@ -358,9 +358,9 @@ def test_byoc(
         )
         expected_train_args["input_config"][0]["DataSource"]["S3DataSource"]["S3Uri"] = inputs
         expected_train_args["enable_sagemaker_metrics"] = False
-        expected_train_args["hyperparameters"][
-            TrainingCompilerConfig.HP_ENABLE_COMPILER
-        ] = json.dumps(True)
+        expected_train_args["hyperparameters"][TrainingCompilerConfig.HP_ENABLE_COMPILER] = (
+            json.dumps(True)
+        )
         expected_train_args["hyperparameters"][TrainingCompilerConfig.HP_ENABLE_DEBUG] = json.dumps(
             False
         )
@@ -409,9 +409,9 @@ def test_debug_compiler_config(
         )
         expected_train_args["input_config"][0]["DataSource"]["S3DataSource"]["S3Uri"] = inputs
         expected_train_args["enable_sagemaker_metrics"] = False
-        expected_train_args["hyperparameters"][
-            TrainingCompilerConfig.HP_ENABLE_COMPILER
-        ] = json.dumps(True)
+        expected_train_args["hyperparameters"][TrainingCompilerConfig.HP_ENABLE_COMPILER] = (
+            json.dumps(True)
+        )
         expected_train_args["hyperparameters"][TrainingCompilerConfig.HP_ENABLE_DEBUG] = json.dumps(
             True
         )
@@ -460,9 +460,9 @@ def test_disable_compiler_config(
         )
         expected_train_args["input_config"][0]["DataSource"]["S3DataSource"]["S3Uri"] = inputs
         expected_train_args["enable_sagemaker_metrics"] = False
-        expected_train_args["hyperparameters"][
-            TrainingCompilerConfig.HP_ENABLE_COMPILER
-        ] = json.dumps(False)
+        expected_train_args["hyperparameters"][TrainingCompilerConfig.HP_ENABLE_COMPILER] = (
+            json.dumps(False)
+        )
         expected_train_args["hyperparameters"][TrainingCompilerConfig.HP_ENABLE_DEBUG] = json.dumps(
             False
         )
diff --git a/tests/unit/sagemaker/workflow/test_retry.py b/tests/unit/sagemaker/workflow/test_retry.py
index cf58d615e4..9d871317a1 100644
--- a/tests/unit/sagemaker/workflow/test_retry.py
+++ b/tests/unit/sagemaker/workflow/test_retry.py
@@ -115,7 +115,7 @@ def test_invalid_retry_policy():
         (5, 2.0, 10, 30),
     ]
 
-    for (interval_sec, backoff_rate, max_attempts, expire_after) in retry_policies:
+    for interval_sec, backoff_rate, max_attempts, expire_after in retry_policies:
         try:
             RetryPolicy(
                 interval_seconds=interval_sec,
diff --git a/tests/unit/test_clarify.py b/tests/unit/test_clarify.py
index 82ac2cd8bc..43d52e521d 100644
--- a/tests/unit/test_clarify.py
+++ b/tests/unit/test_clarify.py
@@ -846,9 +846,7 @@ def test_valid_model_config(content_type, accept_type):
     content_template = (
         '{"instances":$features}'
         if content_type == "application/jsonlines"
-        else "$records"
-        if content_type == "application/json"
-        else None
+        else "$records" if content_type == "application/json" else None
     )
     record_template = "$features_kvp" if content_type == "application/json" else None
     model_config = ModelConfig(
@@ -1071,9 +1069,7 @@ def test_model_config_with_time_series(self, content_type, accept_type):
         content_template = (
             '{"instances":$features}'
             if content_type == "application/jsonlines"
-            else "$records"
-            if content_type == "application/json"
-            else None
+            else "$records" if content_type == "application/json" else None
         )
         record_template = "$features_kvp" if content_type == "application/json" else None
         # create mock config for TimeSeriesModelConfig
diff --git a/tests/unit/test_default_bucket.py b/tests/unit/test_default_bucket.py
index 8790f158a8..9f0d68f01d 100644
--- a/tests/unit/test_default_bucket.py
+++ b/tests/unit/test_default_bucket.py
@@ -97,9 +97,9 @@ def test_default_bucket_s3_custom_bucket_input(sagemaker_session, datetime_obj,
     )
     sagemaker_session.boto_session.resource("s3").meta.client.head_bucket.side_effect = error
     # bucket exists
-    sagemaker_session.boto_session.resource("s3").Bucket(
-        name=DEFAULT_BUCKET_NAME
-    ).creation_date = datetime_obj
+    sagemaker_session.boto_session.resource("s3").Bucket(name=DEFAULT_BUCKET_NAME).creation_date = (
+        datetime_obj
+    )
     # This should not raise ClientError as no head_bucket call is expected for custom bucket
     sagemaker_session.default_bucket()
     assert sagemaker_session._default_bucket == "custom-bucket-override"
diff --git a/tests/unit/test_session.py b/tests/unit/test_session.py
index 0b9d62ca83..19f9d0ae3d 100644
--- a/tests/unit/test_session.py
+++ b/tests/unit/test_session.py
@@ -2460,9 +2460,9 @@ def boto_session_complete():
     boto_mock.client("logs").describe_log_streams.return_value = DEFAULT_LOG_STREAMS
     boto_mock.client("logs").get_log_events.side_effect = DEFAULT_LOG_EVENTS
     boto_mock.client("sagemaker").describe_training_job.return_value = COMPLETED_DESCRIBE_JOB_RESULT
-    boto_mock.client(
-        "sagemaker"
-    ).describe_transform_job.return_value = COMPLETED_DESCRIBE_TRANSFORM_JOB_RESULT
+    boto_mock.client("sagemaker").describe_transform_job.return_value = (
+        COMPLETED_DESCRIBE_TRANSFORM_JOB_RESULT
+    )
     return boto_mock
 
 
@@ -2482,9 +2482,9 @@ def boto_session_stopped():
     boto_mock.client("logs").describe_log_streams.return_value = DEFAULT_LOG_STREAMS
     boto_mock.client("logs").get_log_events.side_effect = DEFAULT_LOG_EVENTS
     boto_mock.client("sagemaker").describe_training_job.return_value = STOPPED_DESCRIBE_JOB_RESULT
-    boto_mock.client(
-        "sagemaker"
-    ).describe_transform_job.return_value = STOPPED_DESCRIBE_TRANSFORM_JOB_RESULT
+    boto_mock.client("sagemaker").describe_transform_job.return_value = (
+        STOPPED_DESCRIBE_TRANSFORM_JOB_RESULT
+    )
     return boto_mock
 
 
diff --git a/tests/unit/test_tuner.py b/tests/unit/test_tuner.py
index ff39535adf..f0325b79e9 100644
--- a/tests/unit/test_tuner.py
+++ b/tests/unit/test_tuner.py
@@ -830,7 +830,7 @@ def _assert_parameter_ranges(expected, actual, is_framework_estimator):
     continuous_ranges = []
     integer_ranges = []
     categorical_ranges = []
-    for (name, param_range) in expected.items():
+    for name, param_range in expected.items():
         if isinstance(param_range, ContinuousParameter):
             continuous_ranges.append(param_range.as_tuning_range(name))
         elif isinstance(param_range, IntegerParameter):