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-rw-r--r--networkx/algorithms/approximation/kcomponents.py4
-rw-r--r--networkx/algorithms/bipartite/cluster.py4
-rw-r--r--networkx/algorithms/bipartite/edgelist.py16
-rw-r--r--networkx/algorithms/bipartite/matrix.py4
-rw-r--r--networkx/algorithms/centrality/katz.py8
-rw-r--r--networkx/algorithms/community/kernighan_lin.py4
-rw-r--r--networkx/algorithms/connectivity/edge_augmentation.py4
-rw-r--r--networkx/algorithms/dag.py8
-rw-r--r--networkx/algorithms/distance_measures.py4
-rw-r--r--networkx/algorithms/distance_regular.py4
-rw-r--r--networkx/algorithms/link_prediction.py4
-rw-r--r--networkx/algorithms/planarity.py4
-rw-r--r--networkx/algorithms/shortest_paths/weighted.py16
-rw-r--r--networkx/algorithms/simple_paths.py4
-rw-r--r--networkx/algorithms/tournament.py4
-rw-r--r--networkx/algorithms/tree/branchings.py4
-rw-r--r--networkx/algorithms/tree/mst.py8
17 files changed, 52 insertions, 52 deletions
diff --git a/networkx/algorithms/approximation/kcomponents.py b/networkx/algorithms/approximation/kcomponents.py
index c7659906..12048da1 100644
--- a/networkx/algorithms/approximation/kcomponents.py
+++ b/networkx/algorithms/approximation/kcomponents.py
@@ -240,8 +240,8 @@ class _AntiGraph(nx.Graph):
"""
try:
return iter(set(self._adj) - set(self._adj[n]) - {n})
- except KeyError as e:
- raise NetworkXError(f"The node {n} is not in the graph.") from e
+ except KeyError as err:
+ raise NetworkXError(f"The node {n} is not in the graph.") from err
class AntiAtlasView(Mapping):
"""An adjacency inner dict for AntiGraph"""
diff --git a/networkx/algorithms/bipartite/cluster.py b/networkx/algorithms/bipartite/cluster.py
index 8d1f0547..d8aaf06b 100644
--- a/networkx/algorithms/bipartite/cluster.py
+++ b/networkx/algorithms/bipartite/cluster.py
@@ -110,10 +110,10 @@ def latapy_clustering(G, nodes=None, mode="dot"):
try:
cc_func = modes[mode]
- except KeyError as e:
+ except KeyError as err:
raise nx.NetworkXError(
"Mode for bipartite clustering must be: dot, min or max"
- ) from e
+ ) from err
if nodes is None:
nodes = G
diff --git a/networkx/algorithms/bipartite/edgelist.py b/networkx/algorithms/bipartite/edgelist.py
index cdad6869..77645d20 100644
--- a/networkx/algorithms/bipartite/edgelist.py
+++ b/networkx/algorithms/bipartite/edgelist.py
@@ -129,8 +129,8 @@ def generate_edgelist(G, delimiter=" ", data=True):
"""
try:
part0 = [n for n, d in G.nodes.items() if d["bipartite"] == 0]
- except BaseException as e:
- raise AttributeError("Missing node attribute `bipartite`") from e
+ except BaseException as err:
+ raise AttributeError("Missing node attribute `bipartite`") from err
if data is True or data is False:
for n in part0:
for e in G.edges(n, data=data):
@@ -228,10 +228,10 @@ def parse_edgelist(
try:
u = nodetype(u)
v = nodetype(v)
- except BaseException as e:
+ except BaseException as err:
raise TypeError(
f"Failed to convert nodes {u},{v} " f"to type {nodetype}."
- ) from e
+ ) from err
if len(d) == 0 or data is False:
# no data or data type specified
@@ -240,10 +240,10 @@ def parse_edgelist(
# no edge types specified
try: # try to evaluate as dictionary
edgedata = dict(literal_eval(" ".join(d)))
- except BaseException as e:
+ except BaseException as err:
raise TypeError(
f"Failed to convert edge data ({d})" f"to dictionary."
- ) from e
+ ) from err
else:
# convert edge data to dictionary with specified keys and type
if len(d) != len(data):
@@ -254,11 +254,11 @@ def parse_edgelist(
for (edge_key, edge_type), edge_value in zip(data, d):
try:
edge_value = edge_type(edge_value)
- except BaseException as e:
+ except BaseException as err:
raise TypeError(
f"Failed to convert {edge_key} data "
f"{edge_value} to type {edge_type}."
- ) from e
+ ) from err
edgedata.update({edge_key: edge_value})
G.add_node(u, bipartite=0)
G.add_node(v, bipartite=1)
diff --git a/networkx/algorithms/bipartite/matrix.py b/networkx/algorithms/bipartite/matrix.py
index 9d7ee4e3..a4186bd1 100644
--- a/networkx/algorithms/bipartite/matrix.py
+++ b/networkx/algorithms/bipartite/matrix.py
@@ -105,8 +105,8 @@ def biadjacency_matrix(
M = sp.sparse.coo_matrix((data, (row, col)), shape=(nlen, mlen), dtype=dtype)
try:
return M.asformat(format)
- except ValueError as e:
- raise nx.NetworkXError(f"Unknown sparse matrix format: {format}") from e
+ except ValueError as err:
+ raise nx.NetworkXError(f"Unknown sparse matrix format: {format}") from err
def from_biadjacency_matrix(A, create_using=None, edge_attribute="weight"):
diff --git a/networkx/algorithms/centrality/katz.py b/networkx/algorithms/centrality/katz.py
index a113ab0e..87c2df07 100644
--- a/networkx/algorithms/centrality/katz.py
+++ b/networkx/algorithms/centrality/katz.py
@@ -157,12 +157,12 @@ def katz_centrality(
try:
b = dict.fromkeys(G, float(beta))
- except (TypeError, ValueError, AttributeError) as e:
+ except (TypeError, ValueError, AttributeError) as err:
b = beta
if set(beta) != set(G):
raise nx.NetworkXError(
"beta dictionary " "must have a value for every node"
- ) from e
+ ) from err
# make up to max_iter iterations
for i in range(max_iter):
@@ -319,8 +319,8 @@ def katz_centrality_numpy(G, alpha=0.1, beta=1.0, normalized=True, weight=None):
nodelist = list(G)
try:
b = np.ones((len(nodelist), 1)) * float(beta)
- except (TypeError, ValueError, AttributeError) as e:
- raise nx.NetworkXError("beta must be a number") from e
+ except (TypeError, ValueError, AttributeError) as err:
+ raise nx.NetworkXError("beta must be a number") from err
A = nx.adjacency_matrix(G, nodelist=nodelist, weight=weight).todense().T
n = A.shape[0]
diff --git a/networkx/algorithms/community/kernighan_lin.py b/networkx/algorithms/community/kernighan_lin.py
index 3cbbbf70..4388ea26 100644
--- a/networkx/algorithms/community/kernighan_lin.py
+++ b/networkx/algorithms/community/kernighan_lin.py
@@ -100,8 +100,8 @@ def kernighan_lin_bisection(G, partition=None, max_iter=10, weight="weight", see
else:
try:
A, B = partition
- except (TypeError, ValueError) as e:
- raise nx.NetworkXError("partition must be two sets") from e
+ except (TypeError, ValueError) as err:
+ raise nx.NetworkXError("partition must be two sets") from err
if not is_partition(G, (A, B)):
raise nx.NetworkXError("partition invalid")
side = [0] * n
diff --git a/networkx/algorithms/connectivity/edge_augmentation.py b/networkx/algorithms/connectivity/edge_augmentation.py
index 2939d3bc..ecb7513d 100644
--- a/networkx/algorithms/connectivity/edge_augmentation.py
+++ b/networkx/algorithms/connectivity/edge_augmentation.py
@@ -985,9 +985,9 @@ def weighted_bridge_augmentation(G, avail, weight=None):
# Note the original edges must be directed towards to root for the
# branching to give us a bridge-augmentation.
A = _minimum_rooted_branching(D, root)
- except nx.NetworkXException as e:
+ except nx.NetworkXException as err:
# If there is no branching then augmentation is not possible
- raise nx.NetworkXUnfeasible("no 2-edge-augmentation possible") from e
+ raise nx.NetworkXUnfeasible("no 2-edge-augmentation possible") from err
# For each edge e, in the branching that did not belong to the directed
# tree T, add the corresponding edge that **GENERATED** it (this is not
diff --git a/networkx/algorithms/dag.py b/networkx/algorithms/dag.py
index fd2a77e9..e6a408e0 100644
--- a/networkx/algorithms/dag.py
+++ b/networkx/algorithms/dag.py
@@ -212,8 +212,8 @@ def topological_generations(G):
for child in G.neighbors(node):
try:
indegree_map[child] -= len(G[node][child]) if multigraph else 1
- except KeyError as e:
- raise RuntimeError("Graph changed during iteration") from e
+ except KeyError as err:
+ raise RuntimeError("Graph changed during iteration") from err
if indegree_map[child] == 0:
zero_indegree.append(child)
del indegree_map[child]
@@ -378,8 +378,8 @@ def lexicographical_topological_sort(G, key=None):
for _, child in G.edges(node):
try:
indegree_map[child] -= 1
- except KeyError as e:
- raise RuntimeError("Graph changed during iteration") from e
+ except KeyError as err:
+ raise RuntimeError("Graph changed during iteration") from err
if indegree_map[child] == 0:
heapq.heappush(zero_indegree, create_tuple(child))
del indegree_map[child]
diff --git a/networkx/algorithms/distance_measures.py b/networkx/algorithms/distance_measures.py
index 6a51d77b..10f0990e 100644
--- a/networkx/algorithms/distance_measures.py
+++ b/networkx/algorithms/distance_measures.py
@@ -251,8 +251,8 @@ def eccentricity(G, v=None, sp=None):
try:
length = sp[n]
L = len(length)
- except TypeError as e:
- raise nx.NetworkXError('Format of "sp" is invalid.') from e
+ except TypeError as err:
+ raise nx.NetworkXError('Format of "sp" is invalid.') from err
if L != order:
if G.is_directed():
msg = (
diff --git a/networkx/algorithms/distance_regular.py b/networkx/algorithms/distance_regular.py
index 0b4ebbfa..cd2ab793 100644
--- a/networkx/algorithms/distance_regular.py
+++ b/networkx/algorithms/distance_regular.py
@@ -158,8 +158,8 @@ def intersection_array(G):
for v in G:
try:
i = path_length[u][v]
- except KeyError as e: # graph must be connected
- raise nx.NetworkXError("Graph is not distance regular.") from e
+ except KeyError as err: # graph must be connected
+ raise nx.NetworkXError("Graph is not distance regular.") from err
# number of neighbors of v at a distance of i-1 from u
c = len([n for n in G[v] if path_length[n][u] == i - 1])
# number of neighbors of v at a distance of i+1 from u
diff --git a/networkx/algorithms/link_prediction.py b/networkx/algorithms/link_prediction.py
index 8c065f49..142157bd 100644
--- a/networkx/algorithms/link_prediction.py
+++ b/networkx/algorithms/link_prediction.py
@@ -582,5 +582,5 @@ def _community(G, u, community):
node_u = G.nodes[u]
try:
return node_u[community]
- except KeyError as e:
- raise nx.NetworkXAlgorithmError("No community information") from e
+ except KeyError as err:
+ raise nx.NetworkXAlgorithmError("No community information") from err
diff --git a/networkx/algorithms/planarity.py b/networkx/algorithms/planarity.py
index 863da5ec..4d1441ef 100644
--- a/networkx/algorithms/planarity.py
+++ b/networkx/algorithms/planarity.py
@@ -875,9 +875,9 @@ class PlanarEmbedding(nx.DiGraph):
for v in self:
try:
sorted_nbrs = set(self.neighbors_cw_order(v))
- except KeyError as e:
+ except KeyError as err:
msg = f"Bad embedding. Missing orientation for a neighbor of {v}"
- raise nx.NetworkXException(msg) from e
+ raise nx.NetworkXException(msg) from err
unsorted_nbrs = set(self[v])
if sorted_nbrs != unsorted_nbrs:
diff --git a/networkx/algorithms/shortest_paths/weighted.py b/networkx/algorithms/shortest_paths/weighted.py
index 5a03f66c..5ae0be4e 100644
--- a/networkx/algorithms/shortest_paths/weighted.py
+++ b/networkx/algorithms/shortest_paths/weighted.py
@@ -233,8 +233,8 @@ def dijkstra_path_length(G, source, target, weight="weight"):
length = _dijkstra(G, source, weight, target=target)
try:
return length[target]
- except KeyError as e:
- raise nx.NetworkXNoPath(f"Node {target} not reachable from {source}") from e
+ except KeyError as err:
+ raise nx.NetworkXNoPath(f"Node {target} not reachable from {source}") from err
def single_source_dijkstra_path(G, source, cutoff=None, weight="weight"):
@@ -742,8 +742,8 @@ def multi_source_dijkstra(G, sources, target=None, cutoff=None, weight="weight")
return (dist, paths)
try:
return (dist[target], paths[target])
- except KeyError as e:
- raise nx.NetworkXNoPath(f"No path to {target}.") from e
+ except KeyError as err:
+ raise nx.NetworkXNoPath(f"No path to {target}.") from err
def _dijkstra(G, source, weight, pred=None, paths=None, cutoff=None, target=None):
@@ -1465,8 +1465,8 @@ def bellman_ford_path_length(G, source, target, weight="weight"):
try:
return length[target]
- except KeyError as e:
- raise nx.NetworkXNoPath(f"node {target} not reachable from {source}") from e
+ except KeyError as err:
+ raise nx.NetworkXNoPath(f"node {target} not reachable from {source}") from err
def single_source_bellman_ford_path(G, source, weight="weight"):
@@ -1654,9 +1654,9 @@ def single_source_bellman_ford(G, source, target=None, weight="weight"):
return (dist, paths)
try:
return (dist[target], paths[target])
- except KeyError as e:
+ except KeyError as err:
msg = f"Node {target} not reachable from {source}"
- raise nx.NetworkXNoPath(msg) from e
+ raise nx.NetworkXNoPath(msg) from err
def all_pairs_bellman_ford_path_length(G, weight="weight"):
diff --git a/networkx/algorithms/simple_paths.py b/networkx/algorithms/simple_paths.py
index e4a53b24..b99272e7 100644
--- a/networkx/algorithms/simple_paths.py
+++ b/networkx/algorithms/simple_paths.py
@@ -224,8 +224,8 @@ def all_simple_paths(G, source, target, cutoff=None):
else:
try:
targets = set(target)
- except TypeError as e:
- raise nx.NodeNotFound(f"target node {target} not in graph") from e
+ except TypeError as err:
+ raise nx.NodeNotFound(f"target node {target} not in graph") from err
if source in targets:
return _empty_generator()
if cutoff is None:
diff --git a/networkx/algorithms/tournament.py b/networkx/algorithms/tournament.py
index cedd2bc0..bace64ba 100644
--- a/networkx/algorithms/tournament.py
+++ b/networkx/algorithms/tournament.py
@@ -59,8 +59,8 @@ def index_satisfying(iterable, condition):
# exception.
try:
return i + 1
- except NameError as e:
- raise ValueError("iterable must be non-empty") from e
+ except NameError as err:
+ raise ValueError("iterable must be non-empty") from err
@not_implemented_for("undirected")
diff --git a/networkx/algorithms/tree/branchings.py b/networkx/algorithms/tree/branchings.py
index 410be310..33c17cc8 100644
--- a/networkx/algorithms/tree/branchings.py
+++ b/networkx/algorithms/tree/branchings.py
@@ -221,8 +221,8 @@ class MultiDiGraph_EdgeKey(nx.MultiDiGraph):
def remove_edge_with_key(self, key):
try:
u, v, _ = self.edge_index[key]
- except KeyError as e:
- raise KeyError(f"Invalid edge key {key!r}") from e
+ except KeyError as err:
+ raise KeyError(f"Invalid edge key {key!r}") from err
else:
del self.edge_index[key]
self._cls.remove_edge(u, v, key)
diff --git a/networkx/algorithms/tree/mst.py b/networkx/algorithms/tree/mst.py
index 5bf193fc..17480fb8 100644
--- a/networkx/algorithms/tree/mst.py
+++ b/networkx/algorithms/tree/mst.py
@@ -435,9 +435,9 @@ def minimum_spanning_edges(
"""
try:
algo = ALGORITHMS[algorithm]
- except KeyError as e:
+ except KeyError as err:
msg = f"{algorithm} is not a valid choice for an algorithm."
- raise ValueError(msg) from e
+ raise ValueError(msg) from err
return algo(
G, minimum=True, weight=weight, keys=keys, data=data, ignore_nan=ignore_nan
@@ -528,9 +528,9 @@ def maximum_spanning_edges(
"""
try:
algo = ALGORITHMS[algorithm]
- except KeyError as e:
+ except KeyError as err:
msg = f"{algorithm} is not a valid choice for an algorithm."
- raise ValueError(msg) from e
+ raise ValueError(msg) from err
return algo(
G, minimum=False, weight=weight, keys=keys, data=data, ignore_nan=ignore_nan
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