diff --git a/python/tempo/interpol.py b/python/tempo/interpol.py
index eccfdb26..e5b93e2d 100644
--- a/python/tempo/interpol.py
+++ b/python/tempo/interpol.py
@@ -193,7 +193,10 @@ def __generate_time_series_fill(
         :param partition_cols: partition column names
         :param ts_col: timestamp column name
         """
-        return df.withColumn("previous_timestamp", col(ts_col),).withColumn(
+        return df.withColumn(
+            "previous_timestamp",
+            col(ts_col),
+        ).withColumn(
             "next_timestamp",
             lead(df[ts_col]).over(Window.partitionBy(*partition_cols).orderBy(ts_col)),
         )
diff --git a/python/tempo/intervals.py b/python/tempo/intervals.py
index 12f7fe66..1cf7a7a6 100644
--- a/python/tempo/intervals.py
+++ b/python/tempo/intervals.py
@@ -346,14 +346,12 @@ def __merge_adjacent_overlaps(
         """
 
         if how == "left":
-
             # new boundary for interval end will become the start of the next
             # interval
             new_boundary_col = self.end_ts
             new_boundary_val = f"_lead_1_{self.start_ts}"
 
         else:
-
             # new boundary for interval start will become the end of the
             # previous interval
             new_boundary_col = self.start_ts
@@ -386,7 +384,6 @@ def __merge_adjacent_overlaps(
         )
 
         if how == "left":
-
             for c in self.metric_columns:
                 df = df.withColumn(
                     c,
@@ -599,7 +596,6 @@ def toDF(self, stack: bool = False) -> DataFrame:
         """
 
         if stack:
-
             n_cols = len(self.metric_columns)
             metric_cols_expr = ",".join(
                 tuple(f"'{col}', {col}" for col in self.metric_columns)
diff --git a/python/tempo/tsdf.py b/python/tempo/tsdf.py
index 778ec3ca..bc16455b 100644
--- a/python/tempo/tsdf.py
+++ b/python/tempo/tsdf.py
@@ -1236,7 +1236,6 @@ def interpolate(
         return TSDF(interpolated_df, ts_col=ts_col, partition_cols=partition_cols)
 
     def calc_bars(tsdf, freq, func=None, metricCols=None, fill=None):
-
         resample_open = tsdf.resample(
             freq=freq, func="floor", metricCols=metricCols, prefix="open", fill=fill
         )