We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
Double import
I noticed that in `networkx/algorithms/__init__.py`the statement `from networkx.algorithms.triads import *` occurs twice. Is there any reason for this or is this just a blunder?

--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
--- BEGIN FILES ---
Path: `networkx/algorithms/__init__.py`
Content:
```
1 from networkx.algorithms.assortativity import *
2 from networkx.algorithms.boundary import *
3 from networkx.algorithms.bridges import *
4 from networkx.algorithms.chains import *
5 from networkx.algorithms.centrality import *
6 from networkx.algorithms.chordal import *
7 from networkx.algorithms.cluster import *
8 from networkx.algorithms.clique import *
9 from networkx.algorithms.communicability_alg import *
10 from networkx.algorithms.components import *
11 from networkx.algorithms.coloring import *
12 from networkx.algorithms.core import *
13 from networkx.algorithms.covering import *
14 from networkx.algorithms.cycles import *
15 from networkx.algorithms.cuts import *
16 from networkx.algorithms.dag import *
17 from networkx.algorithms.distance_measures import *
18 from networkx.algorithms.distance_regular import *
19 from networkx.algorithms.dominance import *
20 from networkx.algorithms.dominating import *
21 from networkx.algorithms.efficiency import *
22 from networkx.algorithms.euler import *
23 from networkx.algorithms.graphical import *
24 from networkx.algorithms.hierarchy import *
25 from networkx.algorithms.hybrid import *
26 from networkx.algorithms.link_analysis import *
27 from networkx.algorithms.link_prediction import *
28 from networkx.algorithms.lowest_common_ancestors import *
29 from networkx.algorithms.isolate import *
30 from networkx.algorithms.matching import *
31 from networkx.algorithms.minors import *
32 from networkx.algorithms.mis import *
33 from networkx.algorithms.operators import *
34 from networkx.algorithms.planarity import *
35 from networkx.algorithms.reciprocity import *
36 from networkx.algorithms.richclub import *
37 from networkx.algorithms.shortest_paths import *
38 from networkx.algorithms.similarity import *
39 from networkx.algorithms.simple_paths import *
40 from networkx.algorithms.smallworld import *
41 from networkx.algorithms.smetric import *
42 from networkx.algorithms.structuralholes import *
43 from networkx.algorithms.triads import *
44 from networkx.algorithms.sparsifiers import *
45 from networkx.algorithms.swap import *
46 from networkx.algorithms.traversal import *
47 from networkx.algorithms.triads import *
48 from networkx.algorithms.vitality import *
49 from networkx.algorithms.voronoi import *
50 from networkx.algorithms.wiener import *
51 
52 # Make certain subpackages available to the user as direct imports from
53 # the `networkx` namespace.
54 import networkx.algorithms.assortativity
55 import networkx.algorithms.bipartite
56 import networkx.algorithms.node_classification
57 import networkx.algorithms.centrality
58 import networkx.algorithms.chordal
59 import networkx.algorithms.cluster
60 import networkx.algorithms.clique
61 import networkx.algorithms.components
62 import networkx.algorithms.connectivity
63 import networkx.algorithms.community
64 import networkx.algorithms.coloring
65 import networkx.algorithms.flow
66 import networkx.algorithms.isomorphism
67 import networkx.algorithms.link_analysis
68 import networkx.algorithms.lowest_common_ancestors
69 import networkx.algorithms.operators
70 import networkx.algorithms.shortest_paths
71 import networkx.algorithms.tournament
72 import networkx.algorithms.traversal
73 import networkx.algorithms.tree
74 
75 # Make certain functions from some of the previous subpackages available
76 # to the user as direct imports from the `networkx` namespace.
77 from networkx.algorithms.bipartite import complete_bipartite_graph
78 from networkx.algorithms.bipartite import is_bipartite
79 from networkx.algorithms.bipartite import project
80 from networkx.algorithms.bipartite import projected_graph
81 from networkx.algorithms.connectivity import all_pairs_node_connectivity
82 from networkx.algorithms.connectivity import all_node_cuts
83 from networkx.algorithms.connectivity import average_node_connectivity
84 from networkx.algorithms.connectivity import edge_connectivity
85 from networkx.algorithms.connectivity import edge_disjoint_paths
86 from networkx.algorithms.connectivity import k_components
87 from networkx.algorithms.connectivity import k_edge_components
88 from networkx.algorithms.connectivity import k_edge_subgraphs
89 from networkx.algorithms.connectivity import k_edge_augmentation
90 from networkx.algorithms.connectivity import is_k_edge_connected
91 from networkx.algorithms.connectivity import minimum_edge_cut
92 from networkx.algorithms.connectivity import minimum_node_cut
93 from networkx.algorithms.connectivity import node_connectivity
94 from networkx.algorithms.connectivity import node_disjoint_paths
95 from networkx.algorithms.connectivity import stoer_wagner
96 from networkx.algorithms.flow import capacity_scaling
97 from networkx.algorithms.flow import cost_of_flow
98 from networkx.algorithms.flow import gomory_hu_tree
99 from networkx.algorithms.flow import max_flow_min_cost
100 from networkx.algorithms.flow import maximum_flow
101 from networkx.algorithms.flow import maximum_flow_value
102 from networkx.algorithms.flow import min_cost_flow
103 from networkx.algorithms.flow import min_cost_flow_cost
104 from networkx.algorithms.flow import minimum_cut
105 from networkx.algorithms.flow import minimum_cut_value
106 from networkx.algorithms.flow import network_simplex
107 from networkx.algorithms.isomorphism import could_be_isomorphic
108 from networkx.algorithms.isomorphism import fast_could_be_isomorphic
109 from networkx.algorithms.isomorphism import faster_could_be_isomorphic
110 from networkx.algorithms.isomorphism import is_isomorphic
111 from networkx.algorithms.tree.branchings import maximum_branching
112 from networkx.algorithms.tree.branchings import maximum_spanning_arborescence
113 from networkx.algorithms.tree.branchings import minimum_branching
114 from networkx.algorithms.tree.branchings import minimum_spanning_arborescence
115 from networkx.algorithms.tree.coding import *
116 from networkx.algorithms.tree.operations import *
117 from networkx.algorithms.tree.recognition import *
118 from networkx.algorithms.tree.mst import *
119
```
--- END FILES ---

Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.

Here is an example:

```diff
diff --git a/examples/server_async.py b/examples/server_async.py
--- a/examples/server_async.py
+++ b/examples/server_async.py
@@ -313,4 +313,4 @@
 
 
 if __name__ == "__main__":
-    asyncio.run(run_async_server("."), debug=True)
+    asyncio.run(run_async_server(), debug=True)
diff --git a/examples/server_sync.py b/examples/server_sync.py
--- a/examples/server_sync.py
+++ b/examples/server_sync.py
@@ -313,5 +313,5 @@
 
 
 if __name__ == "__main__":
-    server = run_sync_server(".")
+    server = run_sync_server()
     server.shutdown()

```

diff --git a/networkx/algorithms/__init__.py b/networkx/algorithms/__init__.py
--- a/networkx/algorithms/__init__.py
+++ b/networkx/algorithms/__init__.py
@@ -40,7 +40,6 @@
 from networkx.algorithms.smallworld import *
 from networkx.algorithms.smetric import *
 from networkx.algorithms.structuralholes import *
-from networkx.algorithms.triads import *
 from networkx.algorithms.sparsifiers import *
 from networkx.algorithms.swap import *
 from networkx.algorithms.traversal import *

{"golden_diff": "diff --git a/networkx/algorithms/__init__.py b/networkx/algorithms/__init__.py\n--- a/networkx/algorithms/__init__.py\n+++ b/networkx/algorithms/__init__.py\n@@ -40,7 +40,6 @@\n from networkx.algorithms.smallworld import *\n from networkx.algorithms.smetric import *\n from networkx.algorithms.structuralholes import *\n-from networkx.algorithms.triads import *\n from networkx.algorithms.sparsifiers import *\n from networkx.algorithms.swap import *\n from networkx.algorithms.traversal import *\n", "issue": "Double import\nI noticed that in `networkx/algorithms/__init__.py`the statement `from networkx.algorithms.triads import *` occurs twice. Is there any reason for this or is this just a blunder?\n", "before_files": [{"content": "from networkx.algorithms.assortativity import *\nfrom networkx.algorithms.boundary import *\nfrom networkx.algorithms.bridges import *\nfrom networkx.algorithms.chains import *\nfrom networkx.algorithms.centrality import *\nfrom networkx.algorithms.chordal import *\nfrom networkx.algorithms.cluster import *\nfrom networkx.algorithms.clique import *\nfrom networkx.algorithms.communicability_alg import *\nfrom networkx.algorithms.components import *\nfrom networkx.algorithms.coloring import *\nfrom networkx.algorithms.core import *\nfrom networkx.algorithms.covering import *\nfrom networkx.algorithms.cycles import *\nfrom networkx.algorithms.cuts import *\nfrom networkx.algorithms.dag import *\nfrom networkx.algorithms.distance_measures import *\nfrom networkx.algorithms.distance_regular import *\nfrom networkx.algorithms.dominance import *\nfrom networkx.algorithms.dominating import *\nfrom networkx.algorithms.efficiency import *\nfrom networkx.algorithms.euler import *\nfrom networkx.algorithms.graphical import *\nfrom networkx.algorithms.hierarchy import *\nfrom networkx.algorithms.hybrid import *\nfrom networkx.algorithms.link_analysis import *\nfrom networkx.algorithms.link_prediction import *\nfrom networkx.algorithms.lowest_common_ancestors import *\nfrom networkx.algorithms.isolate import *\nfrom networkx.algorithms.matching import *\nfrom networkx.algorithms.minors import *\nfrom networkx.algorithms.mis import *\nfrom networkx.algorithms.operators import *\nfrom networkx.algorithms.planarity import *\nfrom networkx.algorithms.reciprocity import *\nfrom networkx.algorithms.richclub import *\nfrom networkx.algorithms.shortest_paths import *\nfrom networkx.algorithms.similarity import *\nfrom networkx.algorithms.simple_paths import *\nfrom networkx.algorithms.smallworld import *\nfrom networkx.algorithms.smetric import *\nfrom networkx.algorithms.structuralholes import *\nfrom networkx.algorithms.triads import *\nfrom networkx.algorithms.sparsifiers import *\nfrom networkx.algorithms.swap import *\nfrom networkx.algorithms.traversal import *\nfrom networkx.algorithms.triads import *\nfrom networkx.algorithms.vitality import *\nfrom networkx.algorithms.voronoi import *\nfrom networkx.algorithms.wiener import *\n\n# Make certain subpackages available to the user as direct imports from\n# the `networkx` namespace.\nimport networkx.algorithms.assortativity\nimport networkx.algorithms.bipartite\nimport networkx.algorithms.node_classification\nimport networkx.algorithms.centrality\nimport networkx.algorithms.chordal\nimport networkx.algorithms.cluster\nimport networkx.algorithms.clique\nimport networkx.algorithms.components\nimport networkx.algorithms.connectivity\nimport networkx.algorithms.community\nimport networkx.algorithms.coloring\nimport networkx.algorithms.flow\nimport networkx.algorithms.isomorphism\nimport networkx.algorithms.link_analysis\nimport networkx.algorithms.lowest_common_ancestors\nimport networkx.algorithms.operators\nimport networkx.algorithms.shortest_paths\nimport networkx.algorithms.tournament\nimport networkx.algorithms.traversal\nimport networkx.algorithms.tree\n\n# Make certain functions from some of the previous subpackages available\n# to the user as direct imports from the `networkx` namespace.\nfrom networkx.algorithms.bipartite import complete_bipartite_graph\nfrom networkx.algorithms.bipartite import is_bipartite\nfrom networkx.algorithms.bipartite import project\nfrom networkx.algorithms.bipartite import projected_graph\nfrom networkx.algorithms.connectivity import all_pairs_node_connectivity\nfrom networkx.algorithms.connectivity import all_node_cuts\nfrom networkx.algorithms.connectivity import average_node_connectivity\nfrom networkx.algorithms.connectivity import edge_connectivity\nfrom networkx.algorithms.connectivity import edge_disjoint_paths\nfrom networkx.algorithms.connectivity import k_components\nfrom networkx.algorithms.connectivity import k_edge_components\nfrom networkx.algorithms.connectivity import k_edge_subgraphs\nfrom networkx.algorithms.connectivity import k_edge_augmentation\nfrom networkx.algorithms.connectivity import is_k_edge_connected\nfrom networkx.algorithms.connectivity import minimum_edge_cut\nfrom networkx.algorithms.connectivity import minimum_node_cut\nfrom networkx.algorithms.connectivity import node_connectivity\nfrom networkx.algorithms.connectivity import node_disjoint_paths\nfrom networkx.algorithms.connectivity import stoer_wagner\nfrom networkx.algorithms.flow import capacity_scaling\nfrom networkx.algorithms.flow import cost_of_flow\nfrom networkx.algorithms.flow import gomory_hu_tree\nfrom networkx.algorithms.flow import max_flow_min_cost\nfrom networkx.algorithms.flow import maximum_flow\nfrom networkx.algorithms.flow import maximum_flow_value\nfrom networkx.algorithms.flow import min_cost_flow\nfrom networkx.algorithms.flow import min_cost_flow_cost\nfrom networkx.algorithms.flow import minimum_cut\nfrom networkx.algorithms.flow import minimum_cut_value\nfrom networkx.algorithms.flow import network_simplex\nfrom networkx.algorithms.isomorphism import could_be_isomorphic\nfrom networkx.algorithms.isomorphism import fast_could_be_isomorphic\nfrom networkx.algorithms.isomorphism import faster_could_be_isomorphic\nfrom networkx.algorithms.isomorphism import is_isomorphic\nfrom networkx.algorithms.tree.branchings import maximum_branching\nfrom networkx.algorithms.tree.branchings import maximum_spanning_arborescence\nfrom networkx.algorithms.tree.branchings import minimum_branching\nfrom networkx.algorithms.tree.branchings import minimum_spanning_arborescence\nfrom networkx.algorithms.tree.coding import *\nfrom networkx.algorithms.tree.operations import *\nfrom networkx.algorithms.tree.recognition import *\nfrom networkx.algorithms.tree.mst import *\n", "path": "networkx/algorithms/__init__.py"}], "after_files": [{"content": "from networkx.algorithms.assortativity import *\nfrom networkx.algorithms.boundary import *\nfrom networkx.algorithms.bridges import *\nfrom networkx.algorithms.chains import *\nfrom networkx.algorithms.centrality import *\nfrom networkx.algorithms.chordal import *\nfrom networkx.algorithms.cluster import *\nfrom networkx.algorithms.clique import *\nfrom networkx.algorithms.communicability_alg import *\nfrom networkx.algorithms.components import *\nfrom networkx.algorithms.coloring import *\nfrom networkx.algorithms.core import *\nfrom networkx.algorithms.covering import *\nfrom networkx.algorithms.cycles import *\nfrom networkx.algorithms.cuts import *\nfrom networkx.algorithms.dag import *\nfrom networkx.algorithms.distance_measures import *\nfrom networkx.algorithms.distance_regular import *\nfrom networkx.algorithms.dominance import *\nfrom networkx.algorithms.dominating import *\nfrom networkx.algorithms.efficiency import *\nfrom networkx.algorithms.euler import *\nfrom networkx.algorithms.graphical import *\nfrom networkx.algorithms.hierarchy import *\nfrom networkx.algorithms.hybrid import *\nfrom networkx.algorithms.link_analysis import *\nfrom networkx.algorithms.link_prediction import *\nfrom networkx.algorithms.lowest_common_ancestors import *\nfrom networkx.algorithms.isolate import *\nfrom networkx.algorithms.matching import *\nfrom networkx.algorithms.minors import *\nfrom networkx.algorithms.mis import *\nfrom networkx.algorithms.operators import *\nfrom networkx.algorithms.planarity import *\nfrom networkx.algorithms.reciprocity import *\nfrom networkx.algorithms.richclub import *\nfrom networkx.algorithms.shortest_paths import *\nfrom networkx.algorithms.similarity import *\nfrom networkx.algorithms.simple_paths import *\nfrom networkx.algorithms.smallworld import *\nfrom networkx.algorithms.smetric import *\nfrom networkx.algorithms.structuralholes import *\nfrom networkx.algorithms.sparsifiers import *\nfrom networkx.algorithms.swap import *\nfrom networkx.algorithms.traversal import *\nfrom networkx.algorithms.triads import *\nfrom networkx.algorithms.vitality import *\nfrom networkx.algorithms.voronoi import *\nfrom networkx.algorithms.wiener import *\n\n# Make certain subpackages available to the user as direct imports from\n# the `networkx` namespace.\nimport networkx.algorithms.assortativity\nimport networkx.algorithms.bipartite\nimport networkx.algorithms.node_classification\nimport networkx.algorithms.centrality\nimport networkx.algorithms.chordal\nimport networkx.algorithms.cluster\nimport networkx.algorithms.clique\nimport networkx.algorithms.components\nimport networkx.algorithms.connectivity\nimport networkx.algorithms.community\nimport networkx.algorithms.coloring\nimport networkx.algorithms.flow\nimport networkx.algorithms.isomorphism\nimport networkx.algorithms.link_analysis\nimport networkx.algorithms.lowest_common_ancestors\nimport networkx.algorithms.operators\nimport networkx.algorithms.shortest_paths\nimport networkx.algorithms.tournament\nimport networkx.algorithms.traversal\nimport networkx.algorithms.tree\n\n# Make certain functions from some of the previous subpackages available\n# to the user as direct imports from the `networkx` namespace.\nfrom networkx.algorithms.bipartite import complete_bipartite_graph\nfrom networkx.algorithms.bipartite import is_bipartite\nfrom networkx.algorithms.bipartite import project\nfrom networkx.algorithms.bipartite import projected_graph\nfrom networkx.algorithms.connectivity import all_pairs_node_connectivity\nfrom networkx.algorithms.connectivity import all_node_cuts\nfrom networkx.algorithms.connectivity import average_node_connectivity\nfrom networkx.algorithms.connectivity import edge_connectivity\nfrom networkx.algorithms.connectivity import edge_disjoint_paths\nfrom networkx.algorithms.connectivity import k_components\nfrom networkx.algorithms.connectivity import k_edge_components\nfrom networkx.algorithms.connectivity import k_edge_subgraphs\nfrom networkx.algorithms.connectivity import k_edge_augmentation\nfrom networkx.algorithms.connectivity import is_k_edge_connected\nfrom networkx.algorithms.connectivity import minimum_edge_cut\nfrom networkx.algorithms.connectivity import minimum_node_cut\nfrom networkx.algorithms.connectivity import node_connectivity\nfrom networkx.algorithms.connectivity import node_disjoint_paths\nfrom networkx.algorithms.connectivity import stoer_wagner\nfrom networkx.algorithms.flow import capacity_scaling\nfrom networkx.algorithms.flow import cost_of_flow\nfrom networkx.algorithms.flow import gomory_hu_tree\nfrom networkx.algorithms.flow import max_flow_min_cost\nfrom networkx.algorithms.flow import maximum_flow\nfrom networkx.algorithms.flow import maximum_flow_value\nfrom networkx.algorithms.flow import min_cost_flow\nfrom networkx.algorithms.flow import min_cost_flow_cost\nfrom networkx.algorithms.flow import minimum_cut\nfrom networkx.algorithms.flow import minimum_cut_value\nfrom networkx.algorithms.flow import network_simplex\nfrom networkx.algorithms.isomorphism import could_be_isomorphic\nfrom networkx.algorithms.isomorphism import fast_could_be_isomorphic\nfrom networkx.algorithms.isomorphism import faster_could_be_isomorphic\nfrom networkx.algorithms.isomorphism import is_isomorphic\nfrom networkx.algorithms.tree.branchings import maximum_branching\nfrom networkx.algorithms.tree.branchings import maximum_spanning_arborescence\nfrom networkx.algorithms.tree.branchings import minimum_branching\nfrom networkx.algorithms.tree.branchings import minimum_spanning_arborescence\nfrom networkx.algorithms.tree.coding import *\nfrom networkx.algorithms.tree.operations import *\nfrom networkx.algorithms.tree.recognition import *\nfrom networkx.algorithms.tree.mst import *\n", "path": "networkx/algorithms/__init__.py"}]}