diff --git a/openfl-tutorials/experimental/Global_DP/Workflow_Interface_Mnist_Implementation_1.py b/openfl-tutorials/experimental/Global_DP/Workflow_Interface_Mnist_Implementation_1.py
index eaa4e1bfc7a..eb9dfd1fc00 100644
--- a/openfl-tutorials/experimental/Global_DP/Workflow_Interface_Mnist_Implementation_1.py
+++ b/openfl-tutorials/experimental/Global_DP/Workflow_Interface_Mnist_Implementation_1.py
@@ -39,7 +39,7 @@
 # Fixing the seed for result repeatation: remove below to stop repeatable runs
 # ----------------------------------
 random_seed = 5495300300540669060
-g_device = torch.Generator(device='cuda')
+g_device = torch.Generator(device="cuda")
 # Uncomment the line below to use g_cpu if not using cuda
 # g_device = torch.Generator() # noqa: E800
 # NOTE: remove below to stop repeatable runs
@@ -601,7 +601,6 @@ def end(self):
 
 
 if __name__ == "__main__":
-
     argparser = argparse.ArgumentParser(description=__doc__)
     argparser.add_argument(
         "--config_path", help="Absolute path to the flow configuration file"
@@ -615,9 +614,7 @@ def end(self):
     args = argparser.parse_args()
 
     if torch.cuda.is_available():
-        device = torch.device(
-            "cuda:0"
-        )
+        device = torch.device("cuda:0")
     else:
         device = torch.device("cpu")
 
@@ -638,8 +635,9 @@ def end(self):
         "Guadalajara",
     ]
 
-    def callable_to_initialize_collaborator_private_attributes(index, n_collaborators,
-            batch_size, train_dataset, test_dataset):
+    def callable_to_initialize_collaborator_private_attributes(
+        index, n_collaborators, batch_size, train_dataset, test_dataset
+    ):
         train = deepcopy(train_dataset)
         test = deepcopy(test_dataset)
         train.data = train_dataset.data[index::n_collaborators]
@@ -648,8 +646,12 @@ def callable_to_initialize_collaborator_private_attributes(index, n_collaborator
         test.targets = test_dataset.targets[index::n_collaborators]
 
         return {
-            "train_loader": torch.utils.data.DataLoader(train, batch_size=batch_size, shuffle=True),
-            "test_loader": torch.utils.data.DataLoader(test, batch_size=batch_size, shuffle=True),
+            "train_loader": torch.utils.data.DataLoader(
+                train, batch_size=batch_size, shuffle=True
+            ),
+            "test_loader": torch.utils.data.DataLoader(
+                test, batch_size=batch_size, shuffle=True
+            ),
         }
 
     collaborators = []
@@ -659,14 +661,19 @@ def callable_to_initialize_collaborator_private_attributes(index, n_collaborator
                 name=collaborator_name,
                 private_attributes_callable=callable_to_initialize_collaborator_private_attributes,
                 # Set `num_gpus=0.1` to `num_gpus=0.0` in order to run this tutorial on CPU
-                num_cpus=0.0, num_gpus=0.1, # Assuming GPU(s) is available in the machine
-                index=idx, n_collaborators=len(collaborator_names),
-                batch_size=batch_size_train, train_dataset=mnist_train,
-                test_dataset=mnist_test
+                num_cpus=0.0,
+                num_gpus=0.1,  # Assuming GPU(s) is available in the machine
+                index=idx,
+                n_collaborators=len(collaborator_names),
+                batch_size=batch_size_train,
+                train_dataset=mnist_train,
+                test_dataset=mnist_test,
             )
         )
 
-    local_runtime = LocalRuntime(aggregator=aggregator, collaborators=collaborators, backend="ray")
+    local_runtime = LocalRuntime(
+        aggregator=aggregator, collaborators=collaborators, backend="ray"
+    )
     print(f"Local runtime collaborators = {local_runtime.collaborators}")
 
     top_model_accuracy = 0
diff --git a/openfl-tutorials/experimental/Global_DP/Workflow_Interface_Mnist_Implementation_2.py b/openfl-tutorials/experimental/Global_DP/Workflow_Interface_Mnist_Implementation_2.py
index 0a73ee923fd..8d4effa142e 100644
--- a/openfl-tutorials/experimental/Global_DP/Workflow_Interface_Mnist_Implementation_2.py
+++ b/openfl-tutorials/experimental/Global_DP/Workflow_Interface_Mnist_Implementation_2.py
@@ -35,7 +35,7 @@
 
 random_seed = 5495300300540669060
 
-g_device = torch.Generator(device='cuda')
+g_device = torch.Generator(device="cuda")
 # Uncomment the line below to use g_cpu if not using cuda
 # g_device = torch.Generator() # noqa: E800
 # NOTE: remove below to stop repeatable runs
@@ -580,7 +580,6 @@ def end(self):
 
 
 if __name__ == "__main__":
-
     argparser = argparse.ArgumentParser(description=__doc__)
     argparser.add_argument(
         "--config_path", help="Absolute path to the flow configuration file."
@@ -594,9 +593,7 @@ def end(self):
     args = argparser.parse_args()
 
     if torch.cuda.is_available():
-        device = torch.device(
-            "cuda:0"
-        )
+        device = torch.device("cuda:0")
     else:
         device = torch.device("cpu")
 
@@ -617,8 +614,9 @@ def end(self):
         "Guadalajara",
     ]
 
-    def callable_to_initialize_collaborator_private_attributes(index, n_collaborators,
-            batch_size, train_dataset, test_dataset):
+    def callable_to_initialize_collaborator_private_attributes(
+        index, n_collaborators, batch_size, train_dataset, test_dataset
+    ):
         train = deepcopy(train_dataset)
         test = deepcopy(test_dataset)
         train.data = train_dataset.data[index::n_collaborators]
@@ -627,8 +625,12 @@ def callable_to_initialize_collaborator_private_attributes(index, n_collaborator
         test.targets = test_dataset.targets[index::n_collaborators]
 
         return {
-            "train_loader": torch.utils.data.DataLoader(train, batch_size=batch_size, shuffle=True),
-            "test_loader": torch.utils.data.DataLoader(test, batch_size=batch_size, shuffle=True),
+            "train_loader": torch.utils.data.DataLoader(
+                train, batch_size=batch_size, shuffle=True
+            ),
+            "test_loader": torch.utils.data.DataLoader(
+                test, batch_size=batch_size, shuffle=True
+            ),
         }
 
     collaborators = []
@@ -638,14 +640,19 @@ def callable_to_initialize_collaborator_private_attributes(index, n_collaborator
                 name=collaborator_name,
                 private_attributes_callable=callable_to_initialize_collaborator_private_attributes,
                 # Set `num_gpus=0.1` to `num_gpus=0.0` in order to run this tutorial on CPU
-                num_cpus=0.0, num_gpus=0.1, # Assuming GPU(s) is available in the machine
-                index=idx, n_collaborators=len(collaborator_names),
-                batch_size=batch_size_train, train_dataset=mnist_train,
-                test_dataset=mnist_test
+                num_cpus=0.0,
+                num_gpus=0.1,  # Assuming GPU(s) is available in the machine
+                index=idx,
+                n_collaborators=len(collaborator_names),
+                batch_size=batch_size_train,
+                train_dataset=mnist_train,
+                test_dataset=mnist_test,
             )
         )
 
-    local_runtime = LocalRuntime(aggregator=aggregator, collaborators=collaborators, backend="ray")
+    local_runtime = LocalRuntime(
+        aggregator=aggregator, collaborators=collaborators, backend="ray"
+    )
     print(f"Local runtime collaborators = {local_runtime.collaborators}")
 
     best_model = None
diff --git a/openfl-tutorials/experimental/Privacy_Meter/cifar10_PM.py b/openfl-tutorials/experimental/Privacy_Meter/cifar10_PM.py
index cc400182009..f9d9cf3b23a 100644
--- a/openfl-tutorials/experimental/Privacy_Meter/cifar10_PM.py
+++ b/openfl-tutorials/experimental/Privacy_Meter/cifar10_PM.py
@@ -146,7 +146,6 @@ def inference(network, test_loader, device):
 
 
 def optimizer_to_device(optimizer, device):
-
     """
     Sending the "torch.optim.Optimizer" object into the specified device
     for model training and inference
@@ -581,7 +580,6 @@ def end(self):
 
 
 if __name__ == "__main__":
-
     argparser = argparse.ArgumentParser(description=__doc__)
     argparser.add_argument(
         "--audit_dataset_ratio",
@@ -663,9 +661,7 @@ def end(self):
     collaborator_names = ["Portland", "Seattle"]
 
     if torch.cuda.is_available():
-        device = torch.device(
-            "cuda:0"
-        )
+        device = torch.device("cuda:0")
     else:
         device = torch.device("cpu")
 
@@ -693,9 +689,9 @@ def end(self):
     train_dataset.targets = Y[:train_dataset_size]
 
     test_dataset = deepcopy(cifar_test)
-    test_dataset.data = X[train_dataset_size:train_dataset_size + test_dataset_size]
+    test_dataset.data = X[train_dataset_size: train_dataset_size + test_dataset_size]
     test_dataset.targets = Y[
-        train_dataset_size:train_dataset_size + test_dataset_size
+        train_dataset_size: train_dataset_size + test_dataset_size
     ]
 
     population_dataset = deepcopy(cifar_test)
@@ -715,7 +711,8 @@ def end(self):
     # this function will be called before executing collaborator steps
     # which will return private attributes dictionary for each collaborator
     def callable_to_initialize_collaborator_private_attributes(
-            index, n_collaborators, train_ds, test_ds, population_ds, args):
+        index, n_collaborators, train_ds, test_ds, population_ds, args
+    ):
         # construct the training and test and population dataset
         local_train = deepcopy(train_ds)
         local_test = deepcopy(test_ds)
@@ -773,7 +770,6 @@ def callable_to_initialize_collaborator_private_attributes(
             ),
         }
 
-
     collaborators = []
     for idx, collab_name in enumerate(collaborator_names):
         collaborators.append(
@@ -781,16 +777,23 @@ def callable_to_initialize_collaborator_private_attributes(
                 name=collab_name,
                 private_attributes_callable=callable_to_initialize_collaborator_private_attributes,
                 # If 1 GPU is available in the machine
-                # Set `num_gpus=0.0` to `num_gpus=0.5` to run on GPU with ray backend with 2 collaborators
-                num_cpus=0.0, num_gpus=0.0,
-                index=idx, n_collaborators=len(collaborator_names),
-                train_ds=train_dataset, test_ds=test_dataset,
-                population_ds=population_dataset, args=args
+                # Set `num_gpus=0.0` to `num_gpus=0.5` to run on GPU
+                # with ray backend with 2 collaborators
+                num_cpus=0.0,
+                num_gpus=0.0,
+                index=idx,
+                n_collaborators=len(collaborator_names),
+                train_ds=train_dataset,
+                test_ds=test_dataset,
+                population_ds=population_dataset,
+                args=args,
             )
         )
 
     # Set backend='ray' to use ray-backend
-    local_runtime = LocalRuntime(aggregator=aggregator, collaborators=collaborators, backend="single_process")
+    local_runtime = LocalRuntime(
+        aggregator=aggregator, collaborators=collaborators, backend="single_process"
+    )
 
     print(f"Local runtime collaborators = {local_runtime.collaborators}")
 
diff --git a/openfl/experimental/interface/fl_spec.py b/openfl/experimental/interface/fl_spec.py
index a342a2111f4..c87ce68cae3 100644
--- a/openfl/experimental/interface/fl_spec.py
+++ b/openfl/experimental/interface/fl_spec.py
@@ -84,7 +84,8 @@ def run(self) -> None:
                         "\nLocalRuntime(...,backend='single_process')\n"
                         "\n or for more information about the original error,"
                         "\nPlease see the official Ray documentation"
-                        "\nhttps://docs.ray.io/en/releases-2.2.0/ray-core/objects/serialization.html"
+                        "\nhttps://docs.ray.io/en/releases-2.2.0/ray-core/\
+                        objects/serialization.html"
                     )
                     raise SerializationError(str(e) + msg)
                 else:
diff --git a/openfl/experimental/interface/participants.py b/openfl/experimental/interface/participants.py
index bcedfb96364..5c17c7f76d8 100644
--- a/openfl/experimental/interface/participants.py
+++ b/openfl/experimental/interface/participants.py
@@ -45,20 +45,20 @@ class Collaborator(Participant):
     def __init__(self, name: str = "", private_attributes_callable: Callable = None,
                  num_cpus: int = 0, num_gpus: int = 0.0, **kwargs):
         """
-        Create collaborator object with custom resources and a callable 
+        Create collaborator object with custom resources and a callable
         function to assign private attributes
 
         Parameters:
         name (str): Name of the collaborator. default=""
 
         private_attributes_callable (Callable): A function which returns collaborator
-        private attributes for each collaborator. In case private_attributes are not 
+        private attributes for each collaborator. In case private_attributes are not
         required this can be omitted. default=None
 
         num_cpus (int): Specifies how many cores to use for the collaborator step exection.
         This will only be used if backend is set to ray. default=0
 
-        num_gpus (float): Specifies how many GPUs to use to accerlerate the collaborator 
+        num_gpus (float): Specifies how many GPUs to use to accerlerate the collaborator
         step exection. This will only be used if backend is set to ray. default=0
 
         kwargs (dict): Parameters required to call private_attributes_callable function.
@@ -84,7 +84,7 @@ def get_name(self) -> str:
 
     def initialize_private_attributes(self) -> None:
         """
-        initialize private attributes of Collaborator object by invoking 
+        initialize private attributes of Collaborator object by invoking
         the callable specified by user
         """
         if self.private_attributes_callable is not None:
@@ -92,7 +92,7 @@ def initialize_private_attributes(self) -> None:
 
     def __set_collaborator_attrs_to_clone(self, clone: Any) -> None:
         """
-        Set collaborator private attributes to FLSpec clone before transitioning 
+        Set collaborator private attributes to FLSpec clone before transitioning
         from Aggregator step to collaborator steps
         """
         # set collaborator private attributes as
@@ -102,10 +102,10 @@ def __set_collaborator_attrs_to_clone(self, clone: Any) -> None:
 
     def __delete_collab_attrs_from_clone(self, clone: Any) -> None:
         """
-        Remove collaborator private attributes from FLSpec clone before 
+        Remove collaborator private attributes from FLSpec clone before
         transitioning from Collaborator step to Aggregator step
         """
-        # Update collaborator private attributes by taking latest 
+        # Update collaborator private attributes by taking latest
         # parameters from clone, then delete attributes from clone.
         for attr_name in self.private_attributes:
             if hasattr(clone, attr_name):
@@ -146,9 +146,8 @@ def __init__(self, name: str = "", private_attributes_callable: Callable = None,
 
     def initialize_private_attributes(self) -> None:
         """
-        initialize private attributes of Aggregator object by invoking 
+        initialize private attributes of Aggregator object by invoking
         the callable specified by user
         """
         if self.private_attributes_callable is not None:
             self.private_attributes = self.private_attributes_callable(**self.kwargs)
-
diff --git a/openfl/experimental/runtime/local_runtime.py b/openfl/experimental/runtime/local_runtime.py
index a8790942cca..d64510b9b88 100644
--- a/openfl/experimental/runtime/local_runtime.py
+++ b/openfl/experimental/runtime/local_runtime.py
@@ -9,9 +9,9 @@
 import ray
 import os
 import gc
-import numpy as np
 from openfl.experimental.runtime import Runtime
 from typing import TYPE_CHECKING
+
 if TYPE_CHECKING:
     from openfl.experimental.interface import Aggregator, Collaborator, FLSpec
 
@@ -33,10 +33,11 @@ def __init__(self):
         """Create RayExecutor object"""
         self.__remote_contexts = []
 
-    def ray_call_put(self, collaborator: Collaborator, ctx: Any,
-                     f_name: str, callback: Callable) -> None:
+    def ray_call_put(
+        self, collaborator: Collaborator, ctx: Any, f_name: str, callback: Callable
+    ) -> None:
         """
-        Execute f_name from inside collaborator class with the context 
+        Execute f_name from inside collaborator class with the context
         of clone (ctx)
         """
         self.__remote_contexts.append(
@@ -116,19 +117,27 @@ def __get_collaborator_object(self, collaborators: List) -> Any:
         total_available_cpus = os.cpu_count()
         total_available_gpus = get_number_of_gpus()
 
-        total_required_gpus = sum([collaborator.num_gpus for collaborator in collaborators])
-        total_required_cpus = sum([collaborator.num_cpus for collaborator in collaborators])
+        total_required_gpus = sum(
+            [collaborator.num_gpus for collaborator in collaborators]
+        )
+        total_required_cpus = sum(
+            [collaborator.num_cpus for collaborator in collaborators]
+        )
         if total_required_gpus > 0:
-            check_resource_allocation(total_available_gpus, {collab.get_name(): collab.num_gpus 
-                                                             for collab in collaborators})
+            check_resource_allocation(
+                total_available_gpus,
+                {collab.get_name(): collab.num_gpus for collab in collaborators},
+            )
 
         if total_available_gpus < total_required_gpus:
             raise ResourcesNotAvailableError(
-                    f"cannot assign more than available GPUs ({total_required_gpus} < {total_available_gpus})."
-                )
+                f"cannot assign more than available GPUs \
+                    ({total_required_gpus} < {total_available_gpus})."
+            )
         if total_available_cpus < total_required_cpus:
             raise ResourcesNotAvailableError(
-                    f"cannot assign more than available CPUs ({total_required_cpus} < {total_available_cpus})."
+                f"cannot assign more than available CPUs \
+                    ({total_required_cpus} < {total_available_cpus})."
             )
         interface_module = importlib.import_module("openfl.experimental.interface")
         collaborator_class = getattr(interface_module, "Collaborator")
@@ -139,13 +148,16 @@ def __get_collaborator_object(self, collaborators: List) -> Any:
             num_gpus = collaborator.num_gpus
 
             collaborator_actor = ray.remote(collaborator_class).options(
-                num_cpus=num_cpus, num_gpus=num_gpus)
+                num_cpus=num_cpus, num_gpus=num_gpus
+            )
 
-            collaborator_ray_refs.append(collaborator_actor.remote(
-                name=collaborator.get_name(),
-                private_attributes_callable=collaborator.private_attributes_callable,
-                **collaborator.kwargs
-            ))
+            collaborator_ray_refs.append(
+                collaborator_actor.remote(
+                    name=collaborator.get_name(),
+                    private_attributes_callable=collaborator.private_attributes_callable,
+                    **collaborator.kwargs,
+                )
+            )
         return collaborator_ray_refs
 
     @property
@@ -169,9 +181,14 @@ def collaborators(self) -> List[str]:
     def collaborators(self, collaborators: List[Type[Collaborator]]):
         """Set LocalRuntime collaborators"""
         if self.backend == "single_process":
-            get_collab_name = lambda collab: collab.get_name()
+
+            def get_collab_name(collab):
+                return collab.get_name()
+
         else:
-            get_collab_name = lambda collab: ray.get(collab.get_name.remote())
+
+            def get_collab_name(collab):
+                return ray.get(collab.get_name.remote())
 
         self.__collaborators = {
             get_collab_name(collaborator): collaborator
@@ -185,17 +202,20 @@ def initialize_aggregator(self):
     def initialize_collaborators(self):
         """initialize collaborator private attributes"""
         if self.backend == "single_process":
-            init_private_attrs = lambda collab: collab.initialize_private_attributes()
+
+            def init_private_attrs(collab):
+                return collab.initialize_private_attributes()
+
         else:
-            init_private_attrs = lambda collab: collab.initialize_private_attributes.remote()
+
+            def init_private_attrs(collab):
+                return collab.initialize_private_attributes.remote()
 
         for collaborator in self.__collaborators.values():
             init_private_attrs(collaborator)
 
     def restore_instance_snapshot(
-            self,
-            ctx: Type[FLSpec],
-            instance_snapshot: List[Type[FLSpec]]
+        self, ctx: Type[FLSpec], instance_snapshot: List[Type[FLSpec]]
     ):
         """Restores attributes from backup (in instance snapshot) to ctx"""
         for backup in instance_snapshot:
@@ -206,7 +226,7 @@ def restore_instance_snapshot(
 
     def execute_collaborator_steps(self, ctx: Any, f_name: str):
         """
-        Execute collaborator steps for each 
+        Execute collaborator steps for each
         collaborator until at transition point
         """
         not_at_transition_point = True
@@ -279,8 +299,11 @@ def execute_end_task(self, flspec_obj, f):
             list: updated arguments to be executed
         """
 
-        interface_module = importlib.import_module("openfl.experimental.interface")
-        final_attributes = getattr(interface_module, "final_attributes")
+        from openfl.experimental.interface import (
+            final_attributes,
+        )
+
+        global final_attributes
 
         to_exec = getattr(flspec_obj, f.__name__)
         to_exec()
@@ -325,9 +348,7 @@ def execute_foreach_task(
             clone = FLSpec._clones[col]
             if aggregator_to_collaborator(f, parent_func):
                 for attr in self._aggregator.private_attributes:
-                    self._aggregator.private_attributes[attr] = getattr(
-                        clone, attr
-                    )
+                    self._aggregator.private_attributes[attr] = getattr(clone, attr)
                     if hasattr(clone, attr):
                         delattr(clone, attr)
 
@@ -350,9 +371,13 @@ def execute_foreach_task(
             collaborator = self.__collaborators[collab_name]
 
             if self.backend == "ray":
-                ray_executor.ray_call_put(collaborator, clone, f.__name__, self.execute_collaborator_steps)
+                ray_executor.ray_call_put(
+                    collaborator, clone, f.__name__, self.execute_collaborator_steps
+                )
             else:
-                collaborator.execute_func(clone, f.__name__, self.execute_collaborator_steps)
+                collaborator.execute_func(
+                    clone, f.__name__, self.execute_collaborator_steps
+                )
 
         if self.backend == "ray":
             clones = ray_executor.get_remote_clones()
diff --git a/openfl/experimental/utilities/__init__.py b/openfl/experimental/utilities/__init__.py
index e0b4d119c80..2272d1459a4 100644
--- a/openfl/experimental/utilities/__init__.py
+++ b/openfl/experimental/utilities/__init__.py
@@ -10,10 +10,10 @@
     collaborator_to_aggregator,
 )
 from .exceptions import (
-        SerializationError,
-        ResourcesNotAvailableError,
-        ResourcesAllocationError,
-    )
+    SerializationError,
+    ResourcesNotAvailableError,
+    ResourcesAllocationError,
+)
 from .stream_redirect import (
     RedirectStdStreamBuffer,
     RedirectStdStream,
diff --git a/openfl/experimental/utilities/exceptions.py b/openfl/experimental/utilities/exceptions.py
index e89773e09a6..12a307d271e 100644
--- a/openfl/experimental/utilities/exceptions.py
+++ b/openfl/experimental/utilities/exceptions.py
@@ -12,6 +12,7 @@ def __init__(self, *args: object) -> None:
         super().__init__(*args)
         pass
 
+
 class ResourcesAllocationError(Exception):
     def __init__(self, *args: object) -> None:
         super().__init__(*args)
diff --git a/openfl/experimental/utilities/metaflow_utils.py b/openfl/experimental/utilities/metaflow_utils.py
index 126a86ef0df..ba142ddd811 100644
--- a/openfl/experimental/utilities/metaflow_utils.py
+++ b/openfl/experimental/utilities/metaflow_utils.py
@@ -201,7 +201,8 @@ def __init__(self, flow):
         self._postprocess()
 
     def _create_nodes(self, flow):
-        tree = ast.parse(getsource(flow)).body
+        module = __import__(flow.__module__)
+        tree = ast.parse(getsource(module)).body
         root = [
             n
             for n in tree
diff --git a/openfl/experimental/utilities/resources.py b/openfl/experimental/utilities/resources.py
index 125a2dbd9e4..126c6b0e175 100644
--- a/openfl/experimental/utilities/resources.py
+++ b/openfl/experimental/utilities/resources.py
@@ -9,4 +9,3 @@
 def get_number_of_gpus():
     # TODO remove pytorch dependency
     return device_count()
-
diff --git a/openfl/experimental/utilities/runtime_utils.py b/openfl/experimental/utilities/runtime_utils.py
index 9ac420c4a9c..fa4ae989027 100644
--- a/openfl/experimental/utilities/runtime_utils.py
+++ b/openfl/experimental/utilities/runtime_utils.py
@@ -96,16 +96,17 @@ def checkpoint(ctx, parent_func, chkpnt_reserved_words=["next", "runtime"]):
         )
         print(f"Saved data artifacts for {parent_func.__name__}")
 
+
 def check_resource_allocation(num_gpus, each_collab_gpu_usage):
     remaining_gpu_memory = {}
     for gpu in np.ones(num_gpus, dtype=int):
         for i, (collab_name, collab_gpu_usage) in enumerate(each_collab_gpu_usage.items()):
             if gpu == 0:
                 break
-            if gpu < collab_gpu_usage: # and collab_gpu_usage > 0:
+            if gpu < collab_gpu_usage:  # and collab_gpu_usage > 0:
                 remaining_gpu_memory.update({collab_name: gpu})
-                print (f"each_collab_gpu_usage: {each_collab_gpu_usage}")
-                print (f"i: {i}")
+                print(f"each_collab_gpu_usage: {each_collab_gpu_usage}")
+                print(f"i: {i}")
                 each_collab_gpu_usage = dict(itertools.islice(each_collab_gpu_usage.items(), i))
             else:
                 gpu -= collab_gpu_usage
diff --git a/tests/github/experimental/testflow_privateattributes.py b/tests/github/experimental/testflow_privateattributes.py
index 3b0d653523a..ae320f56f0c 100644
--- a/tests/github/experimental/testflow_privateattributes.py
+++ b/tests/github/experimental/testflow_privateattributes.py
@@ -105,6 +105,7 @@ def join(self, inputs):
             )
 
         for input in enumerate(inputs):
+            collab = input[1].input
             if (
                 hasattr(input, "train_loader") is True
                 or hasattr(input, "test_loader") is True
@@ -114,7 +115,7 @@ def join(self, inputs):
                     "join_collaborator_attributes_found"
                 )
                 print(
-                    f"{bcolors.FAIL} ... Attribute test failed in Join - COllaborator: {collab}"
+                    f"{bcolors.FAIL} ... Attribute test failed in Join - Collaborator: {collab}"
                     + f" private attributes accessible {bcolors.ENDC}"
                 )
 
@@ -239,7 +240,9 @@ def callable_to_initialize_collaborator_private_attributes(index):
     if len(sys.argv) > 1 and sys.argv[1] == "ray":
         backend = "ray"
 
-    local_runtime = LocalRuntime(aggregator=aggregator, collaborators=collaborators, backend=backend)
+    local_runtime = LocalRuntime(
+        aggregator=aggregator, collaborators=collaborators, backend=backend
+    )
     print(f"Local runtime collaborators = {local_runtime.collaborators}")
 
     flflow = TestFlowPrivateAttributes(checkpoint=True)
diff --git a/tests/github/experimental/testflow_reference.py b/tests/github/experimental/testflow_reference.py
index c6ff2493122..16dc38914f8 100644
--- a/tests/github/experimental/testflow_reference.py
+++ b/tests/github/experimental/testflow_reference.py
@@ -242,7 +242,7 @@ def find_matched_references(collab_attr_list, all_collaborators):
     for attr_name in collab_attr_list:
         for i, curr_collab in enumerate(all_collaborators):
             # Compare the current collaborator with the collaborator(s) that come(s) after it.
-            for next_collab in all_collaborators[i + 1 :]:
+            for next_collab in all_collaborators[i + 1:]:
                 # Check if both collaborators have the current attribute
                 if hasattr(curr_collab, attr_name) and hasattr(next_collab, attr_name):
                     # Check if both collaborators are sharing same reference
@@ -336,13 +336,13 @@ def validate_agg_collab_references(all_collborators, agg_obj, agg_attrs):
 if __name__ == "__main__":
     # Setup participants
     aggregator = Aggregator()
-    
+
     # Setup collaborators private attributes via callable function
     collaborator_names = ["Portland", "Seattle", "Chandler", "Bangalore"]
 
     def callable_to_initialize_collaborator_private_attributes(index):
         return {"index": index + 1}
-    
+
     collaborators = []
     for idx, collaborator_name in enumerate(collaborator_names):
         collaborators.append(
diff --git a/tests/github/experimental/testflow_reference_with_exclude.py b/tests/github/experimental/testflow_reference_with_exclude.py
index 04295c27599..0b5ffa93b75 100644
--- a/tests/github/experimental/testflow_reference_with_exclude.py
+++ b/tests/github/experimental/testflow_reference_with_exclude.py
@@ -206,7 +206,7 @@ def find_matched_references(collab_attr_list, all_collaborators):
     for attr_name in collab_attr_list:
         for i, curr_collab in enumerate(all_collaborators):
             # Compare the current collaborator with the collaborator(s) that come(s) after it.
-            for next_collab in all_collaborators[i + 1 :]:
+            for next_collab in all_collaborators[i + 1:]:
                 # Check if both collaborators have the current attribute
                 if hasattr(curr_collab, attr_name) and hasattr(next_collab, attr_name):
                     # Check if both collaborators are sharing same reference
diff --git a/tests/github/experimental/testflow_reference_with_include.py b/tests/github/experimental/testflow_reference_with_include.py
index 5003c6752fd..954b20ae5a5 100644
--- a/tests/github/experimental/testflow_reference_with_include.py
+++ b/tests/github/experimental/testflow_reference_with_include.py
@@ -203,7 +203,7 @@ def find_matched_references(collab_attr_list, all_collaborators):
     for attr_name in collab_attr_list:
         for i, curr_collab in enumerate(all_collaborators):
             # Compare the current collaborator with the collaborator(s) that come(s) after it.
-            for next_collab in all_collaborators[i + 1 :]:
+            for next_collab in all_collaborators[i + 1:]:
                 # Check if both collaborators have the current attribute
                 if hasattr(curr_collab, attr_name) and hasattr(next_collab, attr_name):
                     # Check if both collaborators are sharing same reference