@@ -390,7 +390,7 @@ class IntegratorLearner(BaseLearner):

     def tell(self, point, value):

         if point not in self.x_mapping:

-            raise ValueError("Point {} doesn't belong to any interval".format(point))

+            raise ValueError(f"Point {point} doesn't belong to any interval")

         self.done_points[point] = value

         self.pending_points.discard(point)

@@ -751,4 +751,4 @@ def _get_ncores(ex):

         ex.bootup()  # wait until all workers are up and running

         return ex._pool.size  # not public API!

     else:

-        raise TypeError("Cannot get number of cores for {}".format(ex.__class__))

+        raise TypeError(f"Cannot get number of cores for {ex.__class__}")

@@ -75,7 +75,7 @@ def generate_random_parametrization(f):

     _, *params = inspect.signature(f).parameters.items()

     if any(not callable(v.annotation) for (p, v) in params):

         raise TypeError(

-            "All parameters to {} must be annotated with functions.".format(f.__name__)

+            f"All parameters to {f.__name__} must be annotated with functions."

         )

     realization = {p: v.annotation() for (p, v) in params}

     return ft.partial(f, **realization)