diff --git a/src/fairlens/metrics/unified.py b/src/fairlens/metrics/unified.py
index ce49c459..0c3f7d0b 100644
--- a/src/fairlens/metrics/unified.py
+++ b/src/fairlens/metrics/unified.py
@@ -177,7 +177,6 @@ def _correlation_matrix_helper(
     cat_num_metric: Callable[[pd.Series, pd.Series], float] = kruskal_wallis,
     cat_cat_metric: Callable[[pd.Series, pd.Series], float] = cramers_v,
 ) -> float:
-
     a_type = utils.infer_distr_type(sr_a)
     b_type = utils.infer_distr_type(sr_b)
 
diff --git a/src/fairlens/scorer.py b/src/fairlens/scorer.py
index ca978b3a..7ec020f7 100644
--- a/src/fairlens/scorer.py
+++ b/src/fairlens/scorer.py
@@ -323,7 +323,6 @@ def _calculate_distance(
     method: str = "dist_to_all",
     p_value: bool = False,
 ) -> pd.DataFrame:
-
     unique = df[sensitive_attrs].drop_duplicates()
 
     dist = []
diff --git a/src/fairlens/sensitive/detection.py b/src/fairlens/sensitive/detection.py
index 70c1681b..4ce95490 100644
--- a/src/fairlens/sensitive/detection.py
+++ b/src/fairlens/sensitive/detection.py
@@ -81,7 +81,6 @@ def detect_names_df(
     sensitive_dict = _detect_names_dict(cols, threshold, str_distance, attr_synonym_dict)
 
     if deep_search:
-
         for col in cols:
             # Series containing only the unique values of the analyzed column.
             uniques = pd.Series(df[col].unique())