diff --git a/examples/splitlearning_titanic/client/backward.py b/examples/splitlearning_titanic/client/backward.py
index ec7f7d983..63de493d1 100644
--- a/examples/splitlearning_titanic/client/backward.py
+++ b/examples/splitlearning_titanic/client/backward.py
@@ -17,10 +17,10 @@
 
 
 def backward_pass(gradient_path, client_id):
-    """Load gradients from in_gradients_path, load the embeddings, and perform a backward pass to update 
+    """Load gradients from in_gradients_path, load the embeddings, and perform a backward pass to update
     the parameters of the client model. Save the updated model to out_model_path.
     """
-    # load client model with parameters 
+    # load client model with parameters
     client_model = load_client_model(client_id)
     logger.info(f"Client model loaded from {client_id}")
 
diff --git a/fedn/network/combiner/aggregators/splitlearningagg.py b/fedn/network/combiner/aggregators/splitlearningagg.py
index eced9030e..68f58eaee 100644
--- a/fedn/network/combiner/aggregators/splitlearningagg.py
+++ b/fedn/network/combiner/aggregators/splitlearningagg.py
@@ -54,7 +54,7 @@ def __init__(self, update_handler):
     def combine_models(self, helper=None, delete_models=True):
         """Concatenates client embeddings in the queue by aggregating them.
 
-        After all embeddings are received, the embeddings need to be sorted 
+        After all embeddings are received, the embeddings need to be sorted
         (consistently) by client ID.
 
         :param helper: An instance of :class: `fedn.utils.helpers.helpers.HelperBase`, ML framework specific helper, defaults to None
diff --git a/fedn/network/controller/control.py b/fedn/network/controller/control.py
index 990bccd2f..de65d3363 100644
--- a/fedn/network/controller/control.py
+++ b/fedn/network/controller/control.py
@@ -296,7 +296,7 @@ def splitlearning_session(self, config: RoundConfig) -> None:
 
         if self.get_session_status(config["session_id"]) == "Started":
             self.set_session_status(config["session_id"], "Finished")
-        self._state = ReducerState.idle 
+        self._state = ReducerState.idle
 
     def round(self, session_config: RoundConfig, round_id: str):
         """Execute one global round.