diff --git a/python/dune/perftool/sumfact/tabulation.py b/python/dune/perftool/sumfact/tabulation.py
index c4ce095b3adca1fbb42257f42ca42a6d328ae428..0f052c756557271d204cc7362019505aac15c400 100644
--- a/python/dune/perftool/sumfact/tabulation.py
+++ b/python/dune/perftool/sumfact/tabulation.py
@@ -65,12 +65,12 @@ class BasisTabulationMatrix(BasisTabulationMatrixBase, ImmutableRecord):
 
     def __str__(self):
         return "{}{}A{}{}{}" \
-                .format("face{}_".format(self.face) if self.face is not None else "",
-                        "d" if self.derivative else "",
-                        self.basis_size,
-                        "T" if self.transpose else "",
-                        "_slice{}".format(self.slice_index) if self.slice_size is not None else "",
-                        )
+               .format("face{}_".format(self.face) if self.face is not None else "",
+                       "d" if self.derivative else "",
+                       self.basis_size,
+                       "T" if self.transpose else "",
+                       "_slice{}".format(self.slice_index) if self.slice_size is not None else "",
+                       )
 
     @property
     def rows(self):
diff --git a/python/dune/perftool/sumfact/vectorization.py b/python/dune/perftool/sumfact/vectorization.py
index 595fbc839368e455cf6df2b977c2aabfd28f4263..4a9fbd1e88bc507d7bc831845811193a180c1194 100644
--- a/python/dune/perftool/sumfact/vectorization.py
+++ b/python/dune/perftool/sumfact/vectorization.py
@@ -19,7 +19,7 @@ from dune.perftool.sumfact.tabulation import (BasisTabulationMatrixArray,
                                               )
 from dune.perftool.error import PerftoolError
 from dune.perftool.options import get_option
-from dune.perftool.tools import add_to_frozendict,round_to_multiple
+from dune.perftool.tools import add_to_frozendict, round_to_multiple
 
 from pytools import product
 from frozendict import frozendict
@@ -273,7 +273,6 @@ def get_vectorization_dict(sumfacts, vertical, horizontal, qp):
                                                slice_index=i)
             kernels.append(sf.copy(matrix_sequence=tuple(seq)))
 
-
     # Join the new kernels into a sum factorization node
     buffer = get_counted_variable("joined_buffer")
     return {sf: VectorizedSumfactKernel(kernels=tuple(kernels),