MAINT Update black to 20.8b1

.circleci/config.yml

@@ -3,7 +3,7 @@ version: 2
 jobs:
   python3:
     docker:
-      - image: circleci/python:3.6.1
+      - image: circleci/python:3.7.6
     steps:
       - checkout
       - run:
@@ -36,7 +36,7 @@ jobs:
 
   lint:
     docker:
-      - image: circleci/python:3.6.1
+      - image: circleci/python:3.7.6
     steps:
       - checkout
       - run:

sklearn_extra/cluster/_k_medoids.py

@@ -41,7 +41,7 @@ class KMedoids(BaseEstimator, ClusterMixin, TransformerMixin):
         with the smallest sum distance to every other point. 'k-medoids++'
         follows an approach based on k-means++_, and in general, gives initial
         medoids which are more separated than those generated by the other methods.
-        
+
         .. _k-means++: https://theory.stanford.edu/~sergei/papers/kMeansPP-soda.pdf
 
     max_iter : int, optional, default : 300
@@ -105,7 +105,7 @@ class KMedoids(BaseEstimator, ClusterMixin, TransformerMixin):
     -----
     Since all pairwise distances are calculated and stored in memory for
     the duration of fit, the space complexity is O(n_samples ** 2).
-    
+
     """
 
     def __init__(

sklearn_extra/kernel_methods/_eigenpro.py

@@ -616,7 +616,7 @@ def __init__(
         )
 
     def fit(self, X, Y):
-        """ Train eigenpro classification model
+        """Train eigenpro classification model
 
         Parameters
         ----------
@@ -629,7 +629,7 @@ def fit(self, X, Y):
         Returns
         -------
         self : returns an instance of self.
-       """
+        """
         X, Y = check_X_y(
             X,
             Y,