Use isort with pre-commit to enforce import guidelines (#5659)

* Add isort to pre-commit

* Run isort on all python files (except __init__.py ones)

15 files changed, 38 insertions, 29 deletions

diff --git a/networkx/algorithms/approximation/clustering_coefficient.py b/networkx/algorithms/approximation/clustering_coefficient.py
index 291753db..d37a7540 100644
--- a/networkx/algorithms/approximation/clustering_coefficient.py
+++ b/networkx/algorithms/approximation/clustering_coefficient.py
@@ -1,5 +1,4 @@
-from networkx.utils import not_implemented_for
-from networkx.utils import py_random_state
+from networkx.utils import not_implemented_for, py_random_state
 
 __all__ = ["average_clustering"]
 
diff --git a/networkx/algorithms/approximation/dominating_set.py b/networkx/algorithms/approximation/dominating_set.py
index 548e21d5..76853230 100644
--- a/networkx/algorithms/approximation/dominating_set.py
+++ b/networkx/algorithms/approximation/dominating_set.py
@@ -11,8 +11,8 @@ incident to an endpoint of at least one edge in *F*.
 
 """
 
-from ..matching import maximal_matching
 from ...utils import not_implemented_for
+from ..matching import maximal_matching
 
 __all__ = ["min_weighted_dominating_set", "min_edge_dominating_set"]
 
diff --git a/networkx/algorithms/approximation/kcomponents.py b/networkx/algorithms/approximation/kcomponents.py
index 7e2333de..239cc0f2 100644
--- a/networkx/algorithms/approximation/kcomponents.py
+++ b/networkx/algorithms/approximation/kcomponents.py
@@ -1,17 +1,15 @@
 """ Fast approximation for k-component structure
 """
 import itertools
-from functools import cached_property
 from collections import defaultdict
 from collections.abc import Mapping
+from functools import cached_property
 
 import networkx as nx
+from networkx.algorithms.approximation import local_node_connectivity
 from networkx.exception import NetworkXError
 from networkx.utils import not_implemented_for
 
-from networkx.algorithms.approximation import local_node_connectivity
-
-
 __all__ = ["k_components"]
 
 
diff --git a/networkx/algorithms/approximation/maxcut.py b/networkx/algorithms/approximation/maxcut.py
index d2b5eced..59dfa63c 100644
--- a/networkx/algorithms/approximation/maxcut.py
+++ b/networkx/algorithms/approximation/maxcut.py
@@ -1,5 +1,5 @@
 import networkx as nx
-from networkx.utils.decorators import py_random_state, not_implemented_for
+from networkx.utils.decorators import not_implemented_for, py_random_state
 
 __all__ = ["randomized_partitioning", "one_exchange"]
 
diff --git a/networkx/algorithms/approximation/ramsey.py b/networkx/algorithms/approximation/ramsey.py
index 9337ccfa..1692477b 100644
--- a/networkx/algorithms/approximation/ramsey.py
+++ b/networkx/algorithms/approximation/ramsey.py
@@ -3,6 +3,7 @@ Ramsey numbers.
 """
 import networkx as nx
 from networkx.utils import not_implemented_for
+
 from ...utils import arbitrary_element
 
 __all__ = ["ramsey_R2"]
diff --git a/networkx/algorithms/approximation/steinertree.py b/networkx/algorithms/approximation/steinertree.py
index f999694d..496098b6 100644
--- a/networkx/algorithms/approximation/steinertree.py
+++ b/networkx/algorithms/approximation/steinertree.py
@@ -1,7 +1,7 @@
 from itertools import chain
 
-from networkx.utils import pairwise, not_implemented_for
 import networkx as nx
+from networkx.utils import not_implemented_for, pairwise
 
 __all__ = ["metric_closure", "steiner_tree"]
 
diff --git a/networkx/algorithms/approximation/tests/test_clique.py b/networkx/algorithms/approximation/tests/test_clique.py
index dadde792..ebda285b 100644
--- a/networkx/algorithms/approximation/tests/test_clique.py
+++ b/networkx/algorithms/approximation/tests/test_clique.py
@@ -2,10 +2,12 @@
 
 
 import networkx as nx
-from networkx.algorithms.approximation import max_clique
-from networkx.algorithms.approximation import clique_removal
-from networkx.algorithms.approximation import large_clique_size
-from networkx.algorithms.approximation import maximum_independent_set
+from networkx.algorithms.approximation import (
+    clique_removal,
+    large_clique_size,
+    max_clique,
+    maximum_independent_set,
+)
 
 
 def is_independent_set(G, nodes):
diff --git a/networkx/algorithms/approximation/tests/test_distance_measures.py b/networkx/algorithms/approximation/tests/test_distance_measures.py
index c9ffd31f..81251503 100644
--- a/networkx/algorithms/approximation/tests/test_distance_measures.py
+++ b/networkx/algorithms/approximation/tests/test_distance_measures.py
@@ -2,6 +2,7 @@
 """
 
 import pytest
+
 import networkx as nx
 from networkx.algorithms.approximation import diameter
 
diff --git a/networkx/algorithms/approximation/tests/test_dominating_set.py b/networkx/algorithms/approximation/tests/test_dominating_set.py
index da1abdc5..892ce34e 100644
--- a/networkx/algorithms/approximation/tests/test_dominating_set.py
+++ b/networkx/algorithms/approximation/tests/test_dominating_set.py
@@ -1,6 +1,8 @@
 import networkx as nx
-from networkx.algorithms.approximation import min_weighted_dominating_set
-from networkx.algorithms.approximation import min_edge_dominating_set
+from networkx.algorithms.approximation import (
+    min_edge_dominating_set,
+    min_weighted_dominating_set,
+)
 
 
 class TestMinWeightDominatingSet:
diff --git a/networkx/algorithms/approximation/tests/test_kcomponents.py b/networkx/algorithms/approximation/tests/test_kcomponents.py
index 60a90e84..6b280313 100644
--- a/networkx/algorithms/approximation/tests/test_kcomponents.py
+++ b/networkx/algorithms/approximation/tests/test_kcomponents.py
@@ -1,5 +1,6 @@
 # Test for approximation to k-components algorithm
 import pytest
+
 import networkx as nx
 from networkx.algorithms.approximation import k_components
 from networkx.algorithms.approximation.kcomponents import _AntiGraph, _same
diff --git a/networkx/algorithms/approximation/tests/test_steinertree.py b/networkx/algorithms/approximation/tests/test_steinertree.py
index 1f55b06f..d58eb666 100644
--- a/networkx/algorithms/approximation/tests/test_steinertree.py
+++ b/networkx/algorithms/approximation/tests/test_steinertree.py
@@ -1,7 +1,7 @@
 import pytest
+
 import networkx as nx
-from networkx.algorithms.approximation.steinertree import metric_closure
-from networkx.algorithms.approximation.steinertree import steiner_tree
+from networkx.algorithms.approximation.steinertree import metric_closure, steiner_tree
 from networkx.utils import edges_equal
 
 
diff --git a/networkx/algorithms/approximation/tests/test_traveling_salesman.py b/networkx/algorithms/approximation/tests/test_traveling_salesman.py
index 193f4379..6f9b3b0c 100644
--- a/networkx/algorithms/approximation/tests/test_traveling_salesman.py
+++ b/networkx/algorithms/approximation/tests/test_traveling_salesman.py
@@ -1,6 +1,8 @@
 """Unit tests for the traveling_salesman module."""
-import pytest
 import random
+
+import pytest
+
 import networkx as nx
 import networkx.algorithms.approximation as nx_app
 
diff --git a/networkx/algorithms/approximation/tests/test_treewidth.py b/networkx/algorithms/approximation/tests/test_treewidth.py
index 5389b949..37619db6 100644
--- a/networkx/algorithms/approximation/tests/test_treewidth.py
+++ b/networkx/algorithms/approximation/tests/test_treewidth.py
@@ -1,10 +1,15 @@
-import networkx as nx
-from networkx.algorithms.approximation import treewidth_min_degree
-from networkx.algorithms.approximation import treewidth_min_fill_in
-from networkx.algorithms.approximation.treewidth import min_fill_in_heuristic
-from networkx.algorithms.approximation.treewidth import MinDegreeHeuristic
 import itertools
 
+import networkx as nx
+from networkx.algorithms.approximation import (
+    treewidth_min_degree,
+    treewidth_min_fill_in,
+)
+from networkx.algorithms.approximation.treewidth import (
+    MinDegreeHeuristic,
+    min_fill_in_heuristic,
+)
+
 
 def is_tree_decomp(graph, decomp):
     """Check if the given tree decomposition is valid."""
diff --git a/networkx/algorithms/approximation/traveling_salesman.py b/networkx/algorithms/approximation/traveling_salesman.py
index 15b231b4..971f9007 100644
--- a/networkx/algorithms/approximation/traveling_salesman.py
+++ b/networkx/algorithms/approximation/traveling_salesman.py
@@ -37,8 +37,7 @@ import math
 
 import networkx as nx
 from networkx.algorithms.tree.mst import random_spanning_tree
-
-from networkx.utils import py_random_state, not_implemented_for, pairwise
+from networkx.utils import not_implemented_for, pairwise, py_random_state
 
 __all__ = [
     "traveling_salesman_problem",
@@ -407,9 +406,8 @@ def asadpour_atsp(G, weight="weight", seed=None, source=None):
     >>> tour
     [0, 2, 1, 0]
     """
+    from math import ceil, exp
     from math import log as ln
-    from math import exp
-    from math import ceil
 
     # Check that G is a complete graph
     N = len(G) - 1
diff --git a/networkx/algorithms/approximation/treewidth.py b/networkx/algorithms/approximation/treewidth.py
index 0a302cbf..61fb1e70 100644
--- a/networkx/algorithms/approximation/treewidth.py
+++ b/networkx/algorithms/approximation/treewidth.py
@@ -29,12 +29,12 @@ There are two different functions for computing a tree decomposition:
 
 """
 
+import itertools
 import sys
+from heapq import heapify, heappop, heappush
 
 import networkx as nx
 from networkx.utils import not_implemented_for
-from heapq import heappush, heappop, heapify
-import itertools
 
 __all__ = ["treewidth_min_degree", "treewidth_min_fill_in"]