Quick fixes

5 files changed, 13 insertions, 13 deletions

diff --git a/networkx/algorithms/approximation/tests/test_kcomponents.py b/networkx/algorithms/approximation/tests/test_kcomponents.py
index 8e17a36c..d97743dc 100644
--- a/networkx/algorithms/approximation/tests/test_kcomponents.py
+++ b/networkx/algorithms/approximation/tests/test_kcomponents.py
@@ -259,9 +259,9 @@ class TestAntiGraph:
             node = list(G.nodes())[0]
             nodes = list(G.nodes())[1:4]
             assert_equal(G.degree(node), A.degree(node))
-            assert_equal(sum(dict(G.degree()).values()), sum(dict(A.degree()).values()))
+            assert_equal(sum(d for n, d in G.degree()), sum(d for n, d in A.degree()))
             # AntiGraph is a ThinGraph, so all the weights are 1
-            assert_equal(sum(dict(A.degree()).values()), 
-                         sum(dict(A.degree(weight='weight')).values()))
-            assert_equal(sum(dict(G.degree(nodes)).values()), 
-                         sum(dict(A.degree(nodes)).values()))
+            assert_equal(sum(d for n, d in A.degree()),
+                         sum(d for n, d in A.degree(weight='weight')))
+            assert_equal(sum(d for n, d in G.degree(nodes)),
+                         sum(d for n, d in A.degree(nodes)))
diff --git a/networkx/algorithms/assortativity/connectivity.py b/networkx/algorithms/assortativity/connectivity.py
index e596f974..67eb4871 100644
--- a/networkx/algorithms/assortativity/connectivity.py
+++ b/networkx/algorithms/assortativity/connectivity.py
@@ -23,7 +23,7 @@ def _avg_deg_conn(G, neighbors, source_degree, target_degree,
     for n,k in source_nodes:
         nbrdeg = target_degree(neighbors(n))
         if weight is None:
-            s = float(sum(dict(nbrdeg).values()))
+            s = float(sum(d for n, d in nbrdeg))
         else: # weight nbr degree by weight of (n,nbr) edge
             if neighbors == G.neighbors:
                 s = float(sum((G[n][nbr].get(weight,1)*d
diff --git a/networkx/algorithms/assortativity/neighbor_degree.py b/networkx/algorithms/assortativity/neighbor_degree.py
index 9e5183ad..d8cbed6d 100644
--- a/networkx/algorithms/assortativity/neighbor_degree.py
+++ b/networkx/algorithms/assortativity/neighbor_degree.py
@@ -19,10 +19,10 @@ def _average_nbr_deg(G, source_degree, target_degree, nodes=None, weight=None):
             deg = 1
         nbrdeg = target_degree(G[n])
         if weight is None:
-            avg[n] = sum(dict(nbrdeg).values())/float(deg)
+            avg[n] = sum(d for n, d in nbrdeg) / float(deg)
         else:
             avg[n] = sum((G[n][nbr].get(weight,1)*d 
-                          for nbr,d in nbrdeg))/float(deg)
+                          for nbr,d in nbrdeg)) / float(deg)
     return avg
 
 def average_neighbor_degree(G, source='out', target='out',
diff --git a/networkx/algorithms/isomorphism/isomorph.py b/networkx/algorithms/isomorphism/isomorph.py
index 84765a80..60b7f915 100644
--- a/networkx/algorithms/isomorphism/isomorph.py
+++ b/networkx/algorithms/isomorphism/isomorph.py
@@ -38,13 +38,13 @@ def could_be_isomorphic(G1,G2):
     d1 = G1.degree()
     t1=nx.triangles(G1)
     c1=nx.number_of_cliques(G1)
-    props1 = [[d, t1[v], c1[v]] for v,d in d1]
+    props1 = [[d, t1[v], c1[v]] for v, d in d1]
     props1.sort()
 
     d2=G2.degree()
     t2=nx.triangles(G2)
     c2=nx.number_of_cliques(G2)
-    props2 = [[d, t2[v], c2[v]] for v,d in d2]
+    props2 = [[d, t2[v], c2[v]] for v, d in d2]
     props2.sort()
 
     if props1 != props2:
@@ -75,12 +75,12 @@ def fast_could_be_isomorphic(G1,G2):
     # Check local properties
     d1 = G1.degree()
     t1 = nx.triangles(G1)
-    props1 = [ [d, t1[v]] for v,d in d1 ]
+    props1 = [ [d, t1[v]] for v, d in d1 ]
     props1.sort()
 
     d2 = G2.degree()
     t2=nx.triangles(G2)
-    props2=[ [d, t2[v]] for v,d in d2 ]
+    props2=[ [d, t2[v]] for v, d in d2 ]
     props2.sort()
 
     if props1 != props2: return False
diff --git a/networkx/generators/threshold.py b/networkx/generators/threshold.py
index 4aa1a768..00490231 100644
--- a/networkx/generators/threshold.py
+++ b/networkx/generators/threshold.py
@@ -358,7 +358,7 @@ def find_creation_sequence(G):
         ds.sort()
         # Update threshold graph nodes
         if ds[-1][0]==0: # all are isolated
-            cs.extend( zip((dsdict), ['i']*(len(ds)-1)+['d']))
+            cs.extend(zip(dsdict, ['i'] * (len(ds) - 1) + ['d']))
             break   # Done!
         # pull off isolated nodes
         while ds[0][0]==0: