diff --git a/examples/tutorials/self-paced-training/part-1_federated_learning_introduction/chapter-2_develop_federated_learning_applications/02.4_convert_machine_learning_to_federated_learning/02.3.1_convert_logistic_regression_to_federated_learning/code/src/newton_raphson_workflow.py b/examples/tutorials/self-paced-training/part-1_federated_learning_introduction/chapter-2_develop_federated_learning_applications/02.4_convert_machine_learning_to_federated_learning/02.3.1_convert_logistic_regression_to_federated_learning/code/src/newton_raphson_workflow.py
index 83cf87d4ee..52c9083f98 100644
--- a/examples/tutorials/self-paced-training/part-1_federated_learning_introduction/chapter-2_develop_federated_learning_applications/02.4_convert_machine_learning_to_federated_learning/02.3.1_convert_logistic_regression_to_federated_learning/code/src/newton_raphson_workflow.py
+++ b/examples/tutorials/self-paced-training/part-1_federated_learning_introduction/chapter-2_develop_federated_learning_applications/02.4_convert_machine_learning_to_federated_learning/02.3.1_convert_logistic_regression_to_federated_learning/code/src/newton_raphson_workflow.py
@@ -26,7 +26,7 @@
 class FedAvgNewtonRaphson(BaseFedAvg):
     def __init__(self, damping_factor, epsilon=1.0, *args, **kwargs):
         super().__init__(*args, **kwargs)
-        
+
         """
         Init function for FedAvgNewtonRaphson.
 
@@ -167,4 +167,4 @@ def update_model(self, model, model_update, replace_meta=True) -> FLModel:
 
         model.metrics = model_update.metrics
         # model.params[NPConstants.NUMPY_KEY] += model_update.params["newton_raphson_updates"]
-        model.params["weights"] += model_update.params["newton_raphson_updates"]
\ No newline at end of file
+        model.params["weights"] += model_update.params["newton_raphson_updates"]
diff --git a/nvflare/app_common/statistics/numeric_stats.py b/nvflare/app_common/statistics/numeric_stats.py
index 8e2c1f3324..a8bccc8b70 100644
--- a/nvflare/app_common/statistics/numeric_stats.py
+++ b/nvflare/app_common/statistics/numeric_stats.py
@@ -19,7 +19,6 @@
 from nvflare.app_common.app_constant import StatisticsConstants as StC
 from nvflare.app_opt.statistics.quantile_stats import get_quantiles
 from nvflare.fuel.utils.log_utils import get_module_logger
- 
 
 T = TypeVar("T")
 
@@ -49,7 +48,6 @@ def get_global_stats(
     ordered_target_metrics = StC.ordered_statistics[metric_task]
     ordered_metrics = [metric for metric in ordered_target_metrics if metric in client_metrics]
 
-
     for metric in ordered_metrics:
         if metric not in global_metrics:
             global_metrics[metric] = {}
diff --git a/nvflare/app_opt/statistics/df/df_core_statistics.py b/nvflare/app_opt/statistics/df/df_core_statistics.py
index 3da031b8c7..ad0c0ae4d0 100644
--- a/nvflare/app_opt/statistics/df/df_core_statistics.py
+++ b/nvflare/app_opt/statistics/df/df_core_statistics.py
@@ -100,7 +100,7 @@ def quantiles(self, dataset_name: str, feature_name: str, percents: List) -> Dic
         if not flag:
             results[StatisticsConstants.STATS_QUANTILE] = {}
             return results
-        
+
         df = self.data[dataset_name]
         data = df[feature_name]
         max_bin = self.max_bin if self.max_bin else round(sqrt(len(data)))
@@ -116,4 +116,3 @@ def quantiles(self, dataset_name: str, feature_name: str, percents: List) -> Dic
         # Extract the Q-Digest into a dictionary
         results[StatisticsConstants.STATS_DIGEST_COORD] = digest.to_dict()
         return results
-    
\ No newline at end of file
diff --git a/nvflare/app_opt/statistics/quantile_stats.py b/nvflare/app_opt/statistics/quantile_stats.py
index 4ffa2c17e6..1daef0e6b7 100644
--- a/nvflare/app_opt/statistics/quantile_stats.py
+++ b/nvflare/app_opt/statistics/quantile_stats.py
@@ -13,12 +13,13 @@
 # limitations under the License.
 
 from typing import Dict
+
 from nvflare.app_common.app_constant import StatisticsConstants as StC
 from nvflare.fuel.utils.log_utils import get_module_logger
 
-
 try:
     from fastdigest import TDigest
+
     TDIGEST_AVAILABLE = True
 except ImportError:
     TDIGEST_AVAILABLE = False
@@ -28,7 +29,7 @@
 
 
 def get_quantiles(stats: Dict, statistic_configs: Dict, precision: int):
-    
+
     logger.info(f"get_quantiles: stats: {TDIGEST_AVAILABLE=}")
 
     if not TDIGEST_AVAILABLE:
@@ -36,7 +37,7 @@ def get_quantiles(stats: Dict, statistic_configs: Dict, precision: int):
 
     global_digest = {}
     for client_name in stats:
-        global_digest = merge_quantiles(stats[client_name],global_digest)
+        global_digest = merge_quantiles(stats[client_name], global_digest)
 
     quantile_config = statistic_configs.get(StC.STATS_QUANTILE)
     return compute_quantiles(global_digest, quantile_config, precision)
@@ -87,7 +88,7 @@ def compute_quantiles(g_digest: dict, quantile_config: Dict, precision: int) ->
         feature_metrics = g_digest[ds_name]
         for feature_name in feature_metrics:
             digest = feature_metrics[feature_name]
-            percentiles = get_target_quantiles(quantile_config,feature_name)
+            percentiles = get_target_quantiles(quantile_config, feature_name)
             quantile_values = {}
             for percentile in percentiles:
                 quantile_values[percentile] = round(digest.quantile(percentile), precision)
@@ -95,4 +96,3 @@ def compute_quantiles(g_digest: dict, quantile_config: Dict, precision: int) ->
             g_ds_metrics[ds_name][feature_name] = quantile_values
 
     return g_ds_metrics
-
diff --git a/tests/unit_test/app_common/statistics/quantile_test.py b/tests/unit_test/app_common/statistics/quantile_test.py
index 8ae125f942..38a85fe964 100644
--- a/tests/unit_test/app_common/statistics/quantile_test.py
+++ b/tests/unit_test/app_common/statistics/quantile_test.py
@@ -25,6 +25,7 @@
 
 try:
     from fastdigest import TDigest
+
     TDIGEST_AVAILABLE = True
 except ImportError:
     TDIGEST_AVAILABLE = False