networkx/networkx

Pattern Findings

3173 matches across 14 categories. Click a row to expand file-level details.

Hyper-Verbose Identifiers2069 hits · 2194 pts

Severity	File	Line	Snippet
LOW	networkx/conftest.py	78	def pytest_collection_modifyitems(config, items):
LOW	networkx/relabel.py	227	def convert_node_labels_to_integers(
LOW	networkx/readwrite/gexf.py	707	def alter_graph_mode_timeformat(self, start_or_end):
LOW	networkx/readwrite/multiline_adjlist.py	39	def generate_multiline_adjlist(G, delimiter=" "):
LOW	networkx/readwrite/json_graph/tests/test_adjacency.py	61	def test_input_data_is_not_modified_when_building_graph(self):
LOW	networkx/readwrite/json_graph/tests/test_adjacency.py	69	def test_adjacency_form_json_serialisable(self):
LOW	networkx/readwrite/json_graph/tests/test_node_link.py	52	def test_graph_with_tuple_nodes(self):
LOW	networkx/readwrite/json_graph/tests/test_cytoscape.py	16	def test_input_data_is_not_modified_when_building_graph():
LOW	networkx/readwrite/tests/test_graph6.py	40	def test_read_equals_from_bytes(self):
LOW	networkx/readwrite/tests/test_graph6.py	78	def test_large_complete_graph(self):
LOW	networkx/readwrite/tests/test_graph6.py	88	def test_complete_bipartite_graph(self):
LOW	networkx/readwrite/tests/test_graph6.py	96	def test_no_directed_or_multi_graphs(self, G):
LOW	networkx/readwrite/tests/test_graph6.py	146	def test_large_complete_graph(self):
LOW	networkx/readwrite/tests/test_graph6.py	154	def test_complete_bipartite_graph(self):
LOW	networkx/readwrite/tests/test_graph6.py	159	def test_no_directed_or_multi_graphs(self, G):
LOW	networkx/readwrite/tests/test_gexf.py	44	def test_dynamic_graph_has_timeformat(time_attr, dyn_attr, tmp_path):
LOW	networkx/readwrite/tests/test_gexf.py	191	def test_read_simple_directed_graphml(self):
LOW	networkx/readwrite/tests/test_gexf.py	199	def test_write_read_simple_directed_graphml(self):
LOW	networkx/readwrite/tests/test_gexf.py	210	def test_read_simple_undirected_graphml(self):
LOW	networkx/readwrite/tests/test_gexf.py	219	def test_read_attribute_graphml(self):
LOW	networkx/readwrite/tests/test_gexf.py	230	def test_directed_edge_in_undirected(self):
LOW	networkx/readwrite/tests/test_gexf.py	247	def test_undirected_edge_in_directed(self):
LOW	networkx/readwrite/tests/test_gexf.py	324	def test_serialize_ints_to_strings(self):
LOW	networkx/readwrite/tests/test_gexf.py	334	def test_write_with_node_attributes(self):
LOW	networkx/readwrite/tests/test_gexf.py	518	def test_multigraph_with_missing_attributes(self):
LOW	networkx/readwrite/tests/test_gexf.py	534	def test_missing_viz_attributes(self):
LOW	networkx/readwrite/tests/test_gexf.py	616	def test_round_trip_mixed_type_float_to_string(self):
LOW	networkx/readwrite/tests/test_gexf.py	628	def test_round_trip_mixed_type_int_to_string(self):
LOW	networkx/readwrite/tests/test_gexf.py	640	def test_type_promotion_integer_to_integer(self):
LOW	networkx/readwrite/tests/test_gexf.py	655	def test_type_promotion_float_to_float(self):
LOW	networkx/readwrite/tests/test_gexf.py	670	def test_meta_description_keywords_round_trip(self):
LOW	networkx/readwrite/tests/test_sparse6.py	50	def test_from_bytes_multigraph_graph(self):
LOW	networkx/readwrite/tests/test_sparse6.py	110	def test_very_large_empty_graph(self):
LOW	networkx/readwrite/tests/test_gml.py	59	def test_parse_gml_cytoscape_bug(self):
LOW	networkx/readwrite/tests/test_gml.py	640	def test_writing_graph_with_multi_element_property_list(self):
LOW	networkx/readwrite/tests/test_gml.py	664	def test_writing_graph_with_one_element_property_list(self):
LOW	networkx/readwrite/tests/test_gml.py	684	def test_reading_graph_with_list_property(self):
LOW	networkx/readwrite/tests/test_gml.py	706	def test_reading_graph_with_single_element_list_property(self):
LOW	networkx/readwrite/tests/test_gml.py	728	def test_stringize_empty_list_tuple(coll):
LOW	networkx/readwrite/tests/test_edgelist.py	80	def test_read_edgelist_no_data(data, extra_kwargs):
LOW	networkx/readwrite/tests/test_edgelist.py	86	def test_read_weighted_edgelist():
LOW	networkx/readwrite/tests/test_edgelist.py	104	def test_read_edgelist_with_data(data, extra_kwargs, expected):
LOW	networkx/readwrite/tests/test_edgelist.py	117	def test_parse_edgelist_no_data(example_graph):
LOW	networkx/readwrite/tests/test_edgelist.py	124	def test_parse_edgelist_with_data_dict(example_graph):
LOW	networkx/readwrite/tests/test_edgelist.py	133	def test_parse_edgelist_with_data_list(example_graph):
LOW	networkx/readwrite/tests/test_edgelist.py	293	def test_edgelist_multidigraph(self, tmp_path):
LOW	networkx/readwrite/tests/test_edgelist.py	304	def test_edgelist_consistent_strip_handling():
LOW	networkx/readwrite/tests/test_adjlist.py	59	def test_multiple_edges_undirected(self):
LOW	networkx/readwrite/tests/test_adjlist.py	69	def test_multiple_edges_directed(self):
LOW	networkx/readwrite/tests/test_adjlist.py	83	def test_multiple_edges_with_data(self):
LOW	networkx/readwrite/tests/test_adjlist.py	209	def test_adjlist_multidigraph(self, tmp_path):
LOW	networkx/readwrite/tests/test_adjlist.py	243	def test_parse_multiline_adjlist(self):
LOW	networkx/readwrite/tests/test_adjlist.py	270	def test_multiline_adjlist_graph(self, tmp_path):
LOW	networkx/readwrite/tests/test_adjlist.py	280	def test_multiline_adjlist_digraph(self, tmp_path):
LOW	networkx/readwrite/tests/test_adjlist.py	290	def test_multiline_adjlist_integers(self, tmp_path):
LOW	networkx/readwrite/tests/test_adjlist.py	300	def test_multiline_adjlist_multigraph(self, tmp_path):
LOW	networkx/readwrite/tests/test_adjlist.py	312	def test_multiline_adjlist_multidigraph(self, tmp_path):
LOW	networkx/readwrite/tests/test_adjlist.py	326	def test_multiline_adjlist_delimiter(self):
LOW	networkx/readwrite/tests/test_adjlist.py	351	def test_adjlist_rstrip_parsing(lines, delim):
LOW	networkx/readwrite/tests/test_text.py	10	def test_generate_network_text_forest_directed():
2009 more matches not shown…

Cross-Language Confusion118 hits · 590 pts

Severity	File	Line	Snippet
HIGH	networkx/algorithms/simple_paths.py	539	listB.push(length, path)
HIGH	networkx/algorithms/simple_paths.py	559	listB.push(root_length + length, path)
HIGH	networkx/algorithms/operators/tests/test_unary.py	26	nullcc = nx.complement(nx.complement(null))
HIGH	networkx/algorithms/operators/tests/test_unary.py	27	assert nx.is_isomorphic(null, nullcc)
HIGH	networkx/algorithms/operators/tests/test_product.py	20	G = nx.tensor_product(null, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	21	assert nx.is_isomorphic(G, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	23	G = nx.tensor_product(null, empty10)
HIGH	networkx/algorithms/operators/tests/test_product.py	24	assert nx.is_isomorphic(G, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	25	G = nx.tensor_product(null, K3)
HIGH	networkx/algorithms/operators/tests/test_product.py	26	assert nx.is_isomorphic(G, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	27	G = nx.tensor_product(null, K10)
HIGH	networkx/algorithms/operators/tests/test_product.py	28	assert nx.is_isomorphic(G, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	29	G = nx.tensor_product(null, P3)
HIGH	networkx/algorithms/operators/tests/test_product.py	30	assert nx.is_isomorphic(G, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	31	G = nx.tensor_product(null, P10)
HIGH	networkx/algorithms/operators/tests/test_product.py	32	assert nx.is_isomorphic(G, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	33	G = nx.tensor_product(empty10, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	34	assert nx.is_isomorphic(G, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	35	G = nx.tensor_product(K3, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	36	assert nx.is_isomorphic(G, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	37	G = nx.tensor_product(K10, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	38	assert nx.is_isomorphic(G, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	39	G = nx.tensor_product(P3, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	40	assert nx.is_isomorphic(G, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	41	G = nx.tensor_product(P10, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	42	assert nx.is_isomorphic(G, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	138	G = nx.cartesian_product(null, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	139	assert nx.is_isomorphic(G, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	141	G = nx.cartesian_product(null, empty10)
HIGH	networkx/algorithms/operators/tests/test_product.py	142	assert nx.is_isomorphic(G, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	143	G = nx.cartesian_product(null, K3)
HIGH	networkx/algorithms/operators/tests/test_product.py	144	assert nx.is_isomorphic(G, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	145	G = nx.cartesian_product(null, K10)
HIGH	networkx/algorithms/operators/tests/test_product.py	146	assert nx.is_isomorphic(G, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	147	G = nx.cartesian_product(null, P3)
HIGH	networkx/algorithms/operators/tests/test_product.py	148	assert nx.is_isomorphic(G, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	149	G = nx.cartesian_product(null, P10)
HIGH	networkx/algorithms/operators/tests/test_product.py	150	assert nx.is_isomorphic(G, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	151	G = nx.cartesian_product(empty10, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	152	assert nx.is_isomorphic(G, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	153	G = nx.cartesian_product(K3, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	154	assert nx.is_isomorphic(G, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	155	G = nx.cartesian_product(K10, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	156	assert nx.is_isomorphic(G, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	157	G = nx.cartesian_product(P3, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	158	assert nx.is_isomorphic(G, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	159	G = nx.cartesian_product(P10, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	160	assert nx.is_isomorphic(G, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	222	G = nx.lexicographic_product(null, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	223	assert nx.is_isomorphic(G, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	225	G = nx.lexicographic_product(null, empty10)
HIGH	networkx/algorithms/operators/tests/test_product.py	226	assert nx.is_isomorphic(G, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	227	G = nx.lexicographic_product(null, K3)
HIGH	networkx/algorithms/operators/tests/test_product.py	228	assert nx.is_isomorphic(G, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	229	G = nx.lexicographic_product(null, K10)
HIGH	networkx/algorithms/operators/tests/test_product.py	230	assert nx.is_isomorphic(G, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	231	G = nx.lexicographic_product(null, P3)
HIGH	networkx/algorithms/operators/tests/test_product.py	232	assert nx.is_isomorphic(G, null)
HIGH	networkx/algorithms/operators/tests/test_product.py	233	G = nx.lexicographic_product(null, P10)
HIGH	networkx/algorithms/operators/tests/test_product.py	234	assert nx.is_isomorphic(G, null)
58 more matches not shown…

Unused Imports418 hits · 354 pts

Severity	File	Line
LOW	networkx/conftest.py	137
LOW	networkx/conftest.py	144
LOW	networkx/conftest.py	151
LOW	networkx/conftest.py	158
LOW	networkx/conftest.py	165
LOW	networkx/conftest.py	172
LOW	networkx/conftest.py	179
LOW	networkx/convert.py	161
LOW	networkx/__init__.py	15
LOW	networkx/__init__.py	17
LOW	networkx/__init__.py	20
LOW	networkx/__init__.py	20
LOW	networkx/__init__.py	26
LOW	networkx/__init__.py	27
LOW	networkx/__init__.py	28
LOW	networkx/__init__.py	30
LOW	networkx/__init__.py	31
LOW	networkx/__init__.py	33
LOW	networkx/__init__.py	34
LOW	networkx/__init__.py	36
LOW	networkx/__init__.py	37
LOW	networkx/__init__.py	39
LOW	networkx/__init__.py	40
LOW	networkx/__init__.py	42
LOW	networkx/__init__.py	43
LOW	networkx/__init__.py	46
LOW	networkx/__init__.py	47
LOW	networkx/__init__.py	49
LOW	networkx/__init__.py	50
LOW	networkx/__init__.py	52
LOW	networkx/__init__.py	53
LOW	networkx/readwrite/__init__.py	6
LOW	networkx/readwrite/__init__.py	7
LOW	networkx/readwrite/__init__.py	8
LOW	networkx/readwrite/__init__.py	9
LOW	networkx/readwrite/__init__.py	10
LOW	networkx/readwrite/__init__.py	11
LOW	networkx/readwrite/__init__.py	12
LOW	networkx/readwrite/__init__.py	13
LOW	networkx/readwrite/__init__.py	14
LOW	networkx/readwrite/__init__.py	15
LOW	networkx/readwrite/__init__.py	16
LOW	networkx/readwrite/__init__.py	17
LOW	networkx/readwrite/json_graph/__init__.py	16
LOW	networkx/readwrite/json_graph/__init__.py	17
LOW	networkx/readwrite/json_graph/__init__.py	18
LOW	networkx/readwrite/json_graph/__init__.py	19
LOW	networkx/readwrite/tests/test_graphml.py	1103
LOW	networkx/drawing/__init__.py	3
LOW	networkx/drawing/__init__.py	4
LOW	networkx/drawing/__init__.py	5
LOW	networkx/drawing/__init__.py	6
LOW	networkx/drawing/__init__.py	7
LOW	networkx/drawing/nx_pylab.py	1483
LOW	networkx/drawing/nx_pylab.py	1953
LOW	networkx/drawing/nx_pylab.py	1954
LOW	networkx/drawing/nx_pylab.py	2959
LOW	networkx/drawing/nx_pylab.py	2960
LOW	networkx/drawing/nx_pylab.py	1627
LOW	networkx/drawing/nx_pylab.py	1551
358 more matches not shown…

Deep Nesting276 hits · 275 pts

Severity	File	Line
LOW	networkx/relabel.py	130
LOW	networkx/relabel.py	193
LOW	networkx/relabel.py	227
LOW	networkx/convert.py	34
LOW	networkx/convert.py	213
LOW	networkx/convert.py	253
LOW	networkx/convert.py	374
LOW	networkx/convert_matrix.py	496
LOW	networkx/convert_matrix.py	893
LOW	networkx/readwrite/gexf.py	440
LOW	networkx/readwrite/gexf.py	508
LOW	networkx/readwrite/gexf.py	707
LOW	networkx/readwrite/gexf.py	1035
LOW	networkx/readwrite/gexf.py	441
LOW	networkx/readwrite/gml.py	298
LOW	networkx/readwrite/gml.py	528
LOW	networkx/readwrite/gml.py	629
LOW	networkx/readwrite/gml.py	301
LOW	networkx/readwrite/gml.py	377
LOW	networkx/readwrite/gml.py	553
LOW	networkx/readwrite/gml.py	714
LOW	networkx/readwrite/sparse6.py	105
LOW	networkx/readwrite/multiline_adjlist.py	39
LOW	networkx/readwrite/multiline_adjlist.py	196
LOW	networkx/readwrite/text.py	73
LOW	networkx/readwrite/pajek.py	167
LOW	networkx/readwrite/graphml.py	506
LOW	networkx/readwrite/graphml.py	961
LOW	networkx/readwrite/edgelist.py	43
LOW	networkx/readwrite/edgelist.py	177
LOW	networkx/readwrite/json_graph/adjacency.py	8
LOW	networkx/readwrite/tests/test_text.py	1672
LOW	networkx/drawing/layout.py	1608
LOW	networkx/drawing/nx_agraph.py	119
LOW	networkx/drawing/nx_pylab.py	257
LOW	networkx/drawing/nx_pylab.py	170
LOW	networkx/linalg/algebraicconnectivity.py	256
LOW	networkx/linalg/attrmatrix.py	55
LOW	networkx/linalg/attrmatrix.py	147
LOW	networkx/linalg/attrmatrix.py	312
LOW	networkx/classes/graph.py	2012
LOW	networkx/classes/multigraph.py	538
LOW	networkx/classes/reportviews.py	1089
LOW	networkx/classes/reportviews.py	1502
LOW	networkx/classes/function.py	621
LOW	networkx/classes/function.py	760
LOW	networkx/classes/function.py	797
LOW	networkx/classes/function.py	979
LOW	networkx/classes/function.py	1308
LOW	networkx/classes/tests/dispatch_interface.py	67
LOW	networkx/algorithms/planarity.py	449
LOW	networkx/algorithms/planarity.py	502
LOW	networkx/algorithms/planarity.py	535
LOW	networkx/algorithms/planarity.py	584
LOW	networkx/algorithms/planarity.py	694
LOW	networkx/algorithms/planarity.py	1009
LOW	networkx/algorithms/planarity.py	1084
LOW	networkx/algorithms/bridges.py	146
LOW	networkx/algorithms/regular.py	76
LOW	networkx/algorithms/smallworld.py	28
216 more matches not shown…

Cross-File Repetition40 hits · 200 pts

Severity	File	Snippet
HIGH	networkx/readwrite/tests/test_text.py	walk through the cases going from a disconnected to fully connected graph
HIGH	networkx/readwrite/tests/test_text.py	walk through the cases going from a disconnected to fully connected graph
HIGH	networkx/readwrite/tests/test_text.py	walk through the cases going from a disconnected to fully connected graph
HIGH	networkx/readwrite/tests/test_graphml.py	test that a detailed exception is raised when an attribute is of a type not supported by graphml, e.g. a list
HIGH	networkx/readwrite/tests/test_graphml.py	test that a detailed exception is raised when an attribute is of a type not supported by graphml, e.g. a list
HIGH	networkx/readwrite/tests/test_graphml.py	test that a detailed exception is raised when an attribute is of a type not supported by graphml, e.g. a list
HIGH	networkx/classes/graph.py	returns true if graph is a multigraph, false otherwise.
HIGH	networkx/classes/multigraph.py	returns true if graph is a multigraph, false otherwise.
HIGH	networkx/classes/multidigraph.py	returns true if graph is a multigraph, false otherwise.
HIGH	networkx/classes/digraph.py	returns true if graph is a multigraph, false otherwise.
HIGH	networkx/classes/graph.py	returns true if graph is directed, false otherwise.
HIGH	networkx/classes/multigraph.py	returns true if graph is directed, false otherwise.
HIGH	networkx/classes/multidigraph.py	returns true if graph is directed, false otherwise.
HIGH	networkx/classes/digraph.py	returns true if graph is directed, false otherwise.
HIGH	networkx/classes/tests/test_multigraph.py	tests that adding a node to the original graph does not affect the nodes of the subgraph.
HIGH	networkx/classes/tests/test_graph.py	tests that adding a node to the original graph does not affect the nodes of the subgraph.
HIGH	networkx/classes/tests/test_subgraphviews.py	tests that adding a node to the original graph does not affect the nodes of the subgraph.
HIGH	networkx/classes/tests/test_multigraph.py	tests that the node attribute dictionary of the two graphs is the same object.
HIGH	networkx/classes/tests/test_graph.py	tests that the node attribute dictionary of the two graphs is the same object.
HIGH	networkx/classes/tests/test_subgraphviews.py	tests that the node attribute dictionary of the two graphs is the same object.
HIGH	networkx/classes/tests/test_multigraph.py	tests that the edge attribute dictionary of the two graphs is the same object.
HIGH	networkx/classes/tests/test_graph.py	tests that the edge attribute dictionary of the two graphs is the same object.
HIGH	networkx/classes/tests/test_subgraphviews.py	tests that the edge attribute dictionary of the two graphs is the same object.
HIGH	networkx/classes/tests/test_multigraph.py	tests that the graph attribute dictionary of the two graphs is the same object.
HIGH	networkx/classes/tests/test_graph.py	tests that the graph attribute dictionary of the two graphs is the same object.
HIGH	networkx/classes/tests/test_subgraphviews.py	tests that the graph attribute dictionary of the two graphs is the same object.
HIGH	networkx/algorithms/tests/test_structuralholes.py	behavior consistent with isolated node without self-loop. see gh-6916
HIGH	networkx/algorithms/tests/test_structuralholes.py	behavior consistent with isolated node without self-loop. see gh-6916
HIGH	networkx/algorithms/tests/test_structuralholes.py	behavior consistent with isolated node without self-loop. see gh-6916
HIGH	networkx/generators/tests/test_geometric.py	tests that pairs of vertices adjacent if and only if they are within the prescribed radius.
HIGH	networkx/generators/tests/test_geometric.py	tests that pairs of vertices adjacent if and only if they are within the prescribed radius.
HIGH	networkx/generators/tests/test_geometric.py	tests that pairs of vertices adjacent if and only if they are within the prescribed radius.
HIGH	networkx/generators/tests/test_geometric.py	tests for providing an alternate distance metric to the generator.
HIGH	networkx/generators/tests/test_geometric.py	tests for providing an alternate distance metric to the generator.
HIGH	networkx/generators/tests/test_geometric.py	tests for providing an alternate distance metric to the generator.
HIGH	networkx/generators/tests/test_geometric.py	tests for providing an alternate distance metric to the generator.
HIGH	networkx/generators/tests/test_geometric.py	tests for providing an alternate distance metric to the generator.
HIGH	networkx/generators/tests/test_geometric.py	tests using values other than sequential numbers as node ids.
HIGH	networkx/generators/tests/test_geometric.py	tests using values other than sequential numbers as node ids.
HIGH	networkx/generators/tests/test_geometric.py	tests using values other than sequential numbers as node ids.

Self-Referential Comments73 hits · 196 pts

Severity	File	Line	Snippet
MEDIUM	networkx/convert_matrix.py	861	# Create an iterable over (u, v, w) triples and for each triple, add an
MEDIUM	networkx/readwrite/tests/test_text.py	11	# Create a directed forest with labels
MEDIUM	networkx/readwrite/tests/test_text.py	225	# Create a directed forest
MEDIUM	networkx/readwrite/tests/test_text.py	1375	# Create a directed forest with labels
MEDIUM	networkx/drawing/nx_pylab.py	1346	# Create a set with all valid keywords across the three functions and
MEDIUM	networkx/drawing/tests/test_agraph.py	64	# Create an AGraph from an existing (non-multi) Graph
MEDIUM	…workx/drawing/tests/test_image_comparison_pylab_mpl.py	173	# Create a list of edges in the shortest path
MEDIUM	networkx/drawing/tests/test_pylab.py	1200	# Create a single axis object to get consistent pixel coords across
MEDIUM	networkx/drawing/tests/test_pylab.py	1247	# Create a single axis object to get consistent pixel coords across
MEDIUM	networkx/linalg/spectrum.py	48	>>> G = nx.Graph() # Create a graph with 5 nodes and 3 connected components
MEDIUM	networkx/classes/graph.py	1829	# Create a subgraph SG based on a (possibly multigraph) G
MEDIUM	networkx/classes/tests/test_multidigraph.py	399	# Create a quadruply-linked path graph on five nodes.
MEDIUM	networkx/classes/tests/test_multigraph.py	413	# Create a doubly-linked path graph on five nodes.
MEDIUM	networkx/classes/tests/dispatch_interface.py	1	# This file contains utilities for testing the dispatching feature
MEDIUM	networkx/classes/tests/test_graph.py	860	# Create a path graph on five nodes.
MEDIUM	networkx/classes/tests/test_subgraphviews.py	276	# Create a path graph on five nodes.
MEDIUM	networkx/classes/tests/test_digraph.py	307	# Create a doubly-linked path graph on five nodes.
MEDIUM	networkx/algorithms/richclub.py	118	# Create a sorted list of pairs of edge endpoint degrees.
MEDIUM	networkx/algorithms/chains.py	85	# Create a directed graph from the depth-first search tree with
MEDIUM	networkx/algorithms/chains.py	149	# Create a directed version of H that has the DFS edges directed
MEDIUM	networkx/algorithms/chains.py	169	# Create the cycle or cycle prefix starting with the
MEDIUM	networkx/algorithms/node_classification.py	1	"""This module provides the functions for node classification problem.
MEDIUM	networkx/algorithms/tree/branchings.py	543	# Create a new graph of the same class as the input graph
MEDIUM	networkx/algorithms/isomorphism/vf2pp.py	573	# Create the labels dicts based on node_label and default_label
MEDIUM	networkx/algorithms/isomorphism/vf2pp.py	578	# Create the degree dicts based on graph type
MEDIUM	networkx/algorithms/link_analysis/pagerank_alg.py	130	# Create a copy in (right) stochastic form
MEDIUM	networkx/algorithms/connectivity/disjoint_paths.py	7	# Define the default maximum flow function to use for the underlying
MEDIUM	networkx/algorithms/connectivity/connectivity.py	10	# Define the default maximum flow function to use in all flow based
MEDIUM	networkx/algorithms/connectivity/edge_kcomponents.py	376	# This class is a container the holds the auxiliary graph A and
MEDIUM	networkx/algorithms/connectivity/edge_kcomponents.py	408	# Create a relevant graph with the auxiliary edges with weights >= k
MEDIUM	networkx/algorithms/connectivity/edge_kcomponents.py	444	# Create a relevant graph with the auxiliary edges with weights >= k
MEDIUM	networkx/algorithms/connectivity/kcomponents.py	11	# Define the default maximum flow function.
MEDIUM	networkx/algorithms/connectivity/cuts.py	9	# Define the default maximum flow function to use in all flow based
MEDIUM	networkx/algorithms/approximation/steinertree.py	107	# Create a complete graph H from the metric edges
MEDIUM	networkx/algorithms/approximation/steinertree.py	130	# Create an iterator over each edge in each shortest path; repeats are okay
MEDIUM	networkx/algorithms/approximation/traveling_salesman.py	465	# Create the undirected support of z_star
MEDIUM	networkx/algorithms/approximation/traveling_salesman.py	472	# Create the exponential distribution of spanning trees
MEDIUM	networkx/algorithms/approximation/traveling_salesman.py	577	# Create a copy of G without vertex 1.
MEDIUM	networkx/algorithms/approximation/traveling_salesman.py	885	# Create the laplacian matrices
MEDIUM	…kx/algorithms/approximation/tests/test_vertex_cover.py	17	# Create a star graph in which half the nodes are directed in
MEDIUM	…/algorithms/approximation/tests/test_dominating_set.py	36	# Create a star graph in which the center node has the highest
MEDIUM	networkx/algorithms/tests/test_dag.py	51	# Create the directed path graph on four nodes in a diamond shape,
MEDIUM	networkx/algorithms/tests/test_core.py	44	# Create the graph H resulting from the degree sequence
MEDIUM	networkx/algorithms/tests/test_matching.py	536	# Create the path graph with two self-loops.
MEDIUM	networkx/algorithms/bipartite/matrix.py	191	# Create an iterable over (u, v, w) triples and for each triple, add an
MEDIUM	networkx/algorithms/bipartite/__init__.py	1	r"""This module provides functions and operations for bipartite
MEDIUM	networkx/algorithms/bipartite/tests/test_matching.py	160	# Create a bipartite graph based on the transitive closure of G
MEDIUM	networkx/algorithms/shortest_paths/tests/test_astar.py	234	# Create the cycle graph on four nodes, with nodes represented
MEDIUM	…workx/algorithms/shortest_paths/tests/test_weighted.py	363	# Create a triangle in which the edge from node 0 to node 2 has
MEDIUM	…workx/algorithms/shortest_paths/tests/test_weighted.py	429	# Create a triangle in which the edge from node 0 to node 2 has
MEDIUM	networkx/algorithms/community/label_propagation.py	268	# Create a unique label for each node in the graph
MEDIUM	networkx/algorithms/flow/maxflow.py	14	# Define the default flow function for computing maximum flow.
MEDIUM	networkx/generators/social.py	47	# Create the set of all members, and the members of each club.
MEDIUM	networkx/generators/geometric.py	1021	# Create an edge with a certain connection probability
MEDIUM	networkx/generators/line.py	141	# Create a graph specific edge function.
MEDIUM	networkx/generators/trees.py	496	# The following functions support generation of unlabeled trees and forests.
MEDIUM	examples/3d_drawing/plot_3d_animation_walk.py	21	# Define a graph to plot.
MEDIUM	examples/3d_drawing/plot_basic.py	24	# Create the 3D figure
MEDIUM	examples/3d_drawing/plot_3d_animation_basic.py	19	# Define a graph to plot.
MEDIUM	examples/drawing/plot_ego_graph.py	15	# Create a BA model graph - use seed for reproducibility
13 more matches not shown…

Decorative Section Separators40 hits · 117 pts

Severity	File	Line	Snippet
MEDIUM	networkx/drawing/nx_pylab.py	2102	# ---------------------------------------
MEDIUM	…algorithms/connectivity/tests/test_edge_kcomponents.py	10	# ----------------
MEDIUM	…algorithms/connectivity/tests/test_edge_kcomponents.py	12	# ----------------
MEDIUM	…algorithms/connectivity/tests/test_edge_kcomponents.py	132	# ----------------
MEDIUM	…algorithms/connectivity/tests/test_edge_kcomponents.py	134	# ----------------
MEDIUM	…algorithms/connectivity/tests/test_edge_kcomponents.py	188	# ----------------
MEDIUM	…algorithms/connectivity/tests/test_edge_kcomponents.py	190	# ----------------
MEDIUM	…algorithms/connectivity/tests/test_edge_kcomponents.py	422	# ----------------
MEDIUM	…algorithms/connectivity/tests/test_edge_kcomponents.py	424	# ----------------
MEDIUM	networkx/algorithms/tests/test_max_weight_clique.py	168	# --------------------------------------------------------------------------
MEDIUM	networkx/algorithms/coloring/tests/test_coloring.py	785	# --------------------------------------------------------------------------
MEDIUM	networkx/algorithms/coloring/tests/test_coloring.py	797	# --------------------------------------------------------------------------
MEDIUM	networkx/algorithms/coloring/tests/test_coloring.py	829	# --------------------------------------------------------------------------
MEDIUM	networkx/generators/classic.py	45	# -------------------------------------------------------------------
MEDIUM	networkx/generators/classic.py	47	# -------------------------------------------------------------------
MEDIUM	networkx/generators/small.py	141	# -------------------------------------------------------------------------------
MEDIUM	networkx/generators/small.py	143	# -------------------------------------------------------------------------------
MEDIUM	examples/3d_drawing/plot_3d_animation_walk.py	22	# -----------------------
MEDIUM	examples/3d_drawing/plot_3d_animation_walk.py	33	# -------------------------------------------
MEDIUM	examples/3d_drawing/plot_3d_animation_basic.py	20	# -----------------------
MEDIUM	examples/3d_drawing/plot_3d_animation_basic.py	31	# ----------------------------
MEDIUM	…ms/plot_image_segmentation_spectral_graph_partition.py	27	# -----------------------------------------
MEDIUM	…ms/plot_image_segmentation_spectral_graph_partition.py	52	# ---------------------------------
MEDIUM	…ms/plot_image_segmentation_spectral_graph_partition.py	66	# --------------------------------------------------
MEDIUM	…ms/plot_image_segmentation_spectral_graph_partition.py	92	# -------------------------------
MEDIUM	…ms/plot_image_segmentation_spectral_graph_partition.py	140	# --------------------------------
MEDIUM	examples/algorithms/plot_circuits.py	60	# ----------------------------------
MEDIUM	examples/algorithms/plot_subgraphs.py	81	# ---------------------------------
MEDIUM	examples/algorithms/plot_subgraphs.py	108	# ------------------------
MEDIUM	examples/algorithms/plot_subgraphs.py	122	# ------------------------------------------------------------------------
MEDIUM	examples/algorithms/plot_subgraphs.py	128	# ---------------------------------------------
MEDIUM	examples/algorithms/plot_subgraphs.py	143	# ---------------------------------------------
MEDIUM	examples/algorithms/plot_subgraphs.py	154	# --------------------------------------------------------------------------
MEDIUM	examples/algorithms/plot_subgraphs.py	160	# -----------------------------
MEDIUM	examples/algorithms/plot_beam_search.py	75	# ---------------------------------------
MEDIUM	examples/external/plot_igraph.py	16	# ------------------
MEDIUM	examples/external/plot_igraph.py	46	# ------------------
MEDIUM	doc/conf.py	12	# ---------------------
MEDIUM	doc/conf.py	133	# -----------------------
MEDIUM	doc/conf.py	213	# ------------------------

Over-Commented Block62 hits · 60 pts

Severity	File	Line	Snippet
LOW	networkx/convert_matrix.py	861	# Create an iterable over (u, v, w) triples and for each triple, add an
LOW	networkx/readwrite/text.py	341	# (1) children to traverse into after showing this node.
LOW	networkx/drawing/layout.py	681
LOW	networkx/linalg/attrmatrix.py	121	else:
LOW	networkx/algorithms/chains.py	81
LOW	networkx/algorithms/chains.py	141	visited.add(v)
LOW	networkx/algorithms/distance_regular.py	261	# Here is an alternate implementation based directly on the
LOW	networkx/algorithms/matching.py	381	# The algorithm is taken from "Efficient Algorithms for Finding Maximum
LOW	networkx/algorithms/matching.py	441	mate = {}
LOW	networkx/algorithms/matching.py	461
LOW	networkx/algorithms/matching.py	481	# If b is a (possibly trivial) top-level S-blossom,
LOW	networkx/algorithms/cycles.py	601	# must not construct longer cycles along (u, v).
LOW	networkx/algorithms/tree/branchings.py	281	# These are the buckets from the paper.
LOW	networkx/algorithms/tree/branchings.py	301
LOW	networkx/algorithms/tree/branchings.py	521
LOW	networkx/algorithms/tree/mst.py	101	minwt = wt
LOW	networkx/algorithms/tree/mst.py	121	# component was empty, so that part of the forest has been
LOW	networkx/algorithms/tree/mst.py	841	# The result is a MultiGraph version of G so that parallel edges are
LOW	networkx/algorithms/tree/mst.py	901	# There are two cases for the total spanning tree additive weight.
LOW	networkx/algorithms/tree/tests/test_mst.py	621	# expect to see each tree. This test uses a near minimum sample size where
LOW	networkx/algorithms/tree/tests/test_mst.py	741
LOW	networkx/algorithms/isomorphism/tree_isomorphism.py	141	# each node has a label, initially set to 0
LOW	networkx/algorithms/isomorphism/isomorphvf2.py	501	This function returns True if it is adding the candidate pair
LOW	networkx/algorithms/isomorphism/isomorphvf2.py	701	# core_1[n] contains the index of the node paired with n, which is m,
LOW	networkx/algorithms/isomorphism/isomorphvf2.py	741	# Basically, when we test the look-ahead rules R_pred and R_succ, we
LOW	networkx/algorithms/isomorphism/vf2pp.py	481
LOW	networkx/algorithms/isomorphism/tests/test_common.py	41	# vf2pp_subgraph_isomorphism()
LOW	networkx/algorithms/isomorphism/tests/test_ismags.py	101	id="katebi-paper-fig2",
LOW	networkx/algorithms/connectivity/edge_augmentation.py	761	>>> G = nx.Graph([(0, 1), (0, 2), (1, 2)])
LOW	networkx/algorithms/connectivity/edge_augmentation.py	941
LOW	networkx/algorithms/connectivity/kcutsets.py	141	# and step 5: build the associated residual network R
LOW	…orithms/approximation/tests/test_traveling_salesman.py	781	)
LOW	…kx/algorithms/centrality/tests/test_load_centrality.py	261	for n in sorted(G):
LOW	networkx/algorithms/tests/test_cycles.py	621	}
LOW	networkx/algorithms/tests/test_dag.py	741	assert not nx.is_arborescence(B)
LOW	networkx/algorithms/tests/test_richclub.py	141	# T = nx.balanced_tree(2,10)
LOW	networkx/algorithms/tests/test_wiener.py	21	# In P_n, there are n - 1 pairs of vertices at distance one, n -
LOW	networkx/algorithms/bipartite/matching.py	281	# for u in G:
LOW	networkx/algorithms/traversal/beamsearch.py	81	#
LOW	networkx/algorithms/community/leiden.py	601	continue
LOW	networkx/algorithms/community/leiden.py	621
LOW	networkx/algorithms/community/tests/test_quality.py	481	# (0,1)=2, (1,2)=3, (0,2)=1
LOW	networkx/algorithms/flow/utils.py	121	]
LOW	networkx/algorithms/flow/tests/test_maxflow.py	121	# H
LOW	networkx/algorithms/flow/tests/test_maxflow.py	401	# flow solution using capacity=my_cap
LOW	networkx/utils/backends.py	1	# Notes about NetworkX namespace objects set up here:
LOW	networkx/utils/backends.py	821	# ##########################
LOW	networkx/utils/backends.py	841	# `backend_priority` before running with the default "networkx" implementation.
LOW	networkx/utils/backends.py	861	# +-------+-------+
LOW	networkx/utils/backends.py	901	group3 = graph_backend_names - seen
LOW	networkx/utils/decorators.py	961	# in addition to some try-blocks if needed.
LOW	networkx/generators/expanders.py	21	#
LOW	networkx/generators/atlas.py	21	#: This is the absolute path of the gzipped text file containing the
LOW	networkx/generators/atlas.py	41	#: import gzip
LOW	examples/algorithms/plot_subgraphs.py	141	###############################################################################
LOW	examples/algorithms/plot_beam_search.py	61	width = initial_width * pow(2, i)
LOW	examples/geospatial/plot_points.py	21	# are a format for storing geographic data that is backed
LOW	examples/geospatial/plot_polygons.py	21	# used as a file format for geographic data.
LOW	examples/geospatial/plot_delaunay.py	21	# read in example data from a geopackage file. Geopackages
LOW	examples/geospatial/plot_delaunay.py	41	# the bounding box of the point pattern. This is controlled by the "clip" argument.
2 more matches not shown…

Redundant / Tautological Comments39 hits · 44 pts

Severity	File	Line	Snippet
LOW	networkx/readwrite/gexf.py	580	# Check if the type of the attribute value is consistent with the type of the attribute
LOW	networkx/drawing/nx_pylab.py	2034	# Check if edge_color is an array of floats and map to edge_cmap.
LOW	networkx/algorithms/planarity.py	1114	# Check if opposite half-edge exists
LOW	networkx/algorithms/chains.py	145	# Check if the root is in the graph G. If not, raise NodeNotFound
LOW	networkx/algorithms/smallworld.py	108	# Check if the graph is still connected
LOW	networkx/algorithms/smallworld.py	232	# Check if the graph is still connected
LOW	networkx/algorithms/similarity.py	1583	# Check if k is provided and validate it against the number of nodes
LOW	networkx/algorithms/dominating.py	221	# Check if u's unseen-degree changed while in the heap
LOW	networkx/algorithms/structuralholes.py	149	# Check if scipy is available
LOW	networkx/algorithms/structuralholes.py	265	# Check if scipy is available
LOW	networkx/algorithms/matching.py	615	# Set label to S.
LOW	networkx/algorithms/graphical.py	179	# Add back to the list any non-zero stubs that were removed
LOW	networkx/algorithms/graphical.py	261	if dk < k + 1: # Check if already past Durfee index
LOW	networkx/algorithms/graphical.py	265	if dk < k + run_size: # Check if end of run is past Durfee index
LOW	networkx/algorithms/graphical.py	469	# Check if target is now totally connected
LOW	networkx/algorithms/planar_drawing.py	428	# Check if the face has already been calculated
LOW	networkx/algorithms/isomorphism/vf2pp.py	493	# Check if SG and FG have the same labels, and check that the
LOW	…workx/algorithms/isomorphism/tests/test_isomorphvf2.py	370	# Check if StopIteration exception returns False
LOW	networkx/algorithms/link_analysis/pagerank_alg.py	263	# Assign dangling_weights to any dangling nodes (nodes with no out links)
LOW	networkx/algorithms/connectivity/kcutsets.py	130	# Check if X is a k-node-cutset
LOW	networkx/algorithms/approximation/traveling_salesman.py	933	# Check if the for loop terminated without changing any gamma
LOW	…workx/algorithms/approximation/tests/test_treewidth.py	24	# Check if each connected pair of nodes are at least once together in a bag
LOW	…workx/algorithms/approximation/tests/test_treewidth.py	33	# Check if the nodes associated with vertex v form a connected subset of T
LOW	networkx/algorithms/tests/test_planar_drawing.py	134	# Check if float numbers are basically equal, for python >=3.5 there is
LOW	networkx/algorithms/tests/test_planar_drawing.py	164	# Check if end points are different
LOW	networkx/algorithms/tests/test_planar_drawing.py	181	# Check if intersection lies between the points
LOW	networkx/algorithms/tests/test_planarity.py	387	# Check if we can remove the node
LOW	networkx/algorithms/assortativity/connectivity.py	105	# Check if `source_nodes` is actually a single node in the graph.
LOW	networkx/algorithms/community/local.py	113	# Check if nbr should be removed from boundary nodes
LOW	networkx/algorithms/community/modularity_max.py	199	# Check if replaced dq is row max
LOW	networkx/algorithms/community/modularity_max.py	430	# Check if strictly better or tie
LOW	networkx/utils/backends.py	593	# Check if any graph comes from a backend
LOW	networkx/utils/backends.py	2059	# Iterate over the items in `cache` to see if any are compatible.
LOW	networkx/utils/mapped_queue.py	252	# Set child_pos to index of smaller child.
LOW	networkx/generators/degree_seq.py	525	# Add back to the list any nonzero stubs that were removed
LOW	networkx/generators/degree_seq.py	628	# Check if source is now totally connected
LOW	networkx/generators/community.py	577	# Check if dimensions match
LOW	examples/algorithms/plot_blockmodel.py	70	# Set positions to mean of positions of internal nodes from original graph
LOW	examples/algorithms/plot_greedy_coloring.py	22	# Assign colors to nodes based on the greedy coloring

Excessive Try-Catch Wrapping22 hits · 22 pts

Severity	File	Line	Snippet
LOW	networkx/convert.py	90	except Exception as err:
LOW	networkx/convert.py	99	except Exception as err1:
LOW	networkx/convert.py	106	except Exception as err2:
LOW	networkx/convert.py	120	except Exception as err:
LOW	networkx/convert.py	131	except Exception as err:
LOW	networkx/convert.py	139	except Exception as err:
LOW	networkx/convert.py	152	except Exception as err:
LOW	networkx/convert.py	166	except Exception as err:
LOW	networkx/convert.py	180	except Exception as err:
LOW	networkx/convert_matrix.py	212	except Exception as err:
LOW	networkx/convert_matrix.py	1274	except Exception as err:
LOW	networkx/readwrite/gml.py	413	except Exception:
LOW	networkx/readwrite/edgelist.py	260	except Exception as err:
LOW	networkx/readwrite/edgelist.py	276	except Exception as err:
LOW	networkx/readwrite/edgelist.py	290	except Exception as err:
LOW	networkx/readwrite/tests/test_text.py	1740	except Exception:
LOW	networkx/classes/multigraph.py	375	except Exception as err:
LOW	networkx/classes/multidigraph.py	366	except Exception as err:
LOW	…lgorithms/connectivity/tests/test_edge_augmentation.py	385	except Exception:
LOW	networkx/utils/backends.py	87	except Exception as exc:
LOW	networkx/utils/backends.py	1447	except Exception:
LOW	networkx/utils/backends.py	1467	except Exception:

AI Slop Vocabulary10 hits · 16 pts

Severity	File	Line	Snippet
MEDIUM	networkx/classes/tests/dispatch_interface.py	6	# This is comprehensive, but only tests the `test_override_dispatch`
LOW	networkx/algorithms/threshold.py	341	# if type is 'i' just add nodea
LOW	networkx/algorithms/centrality/reaching.py	198	# If the graph is unweighted, simply return the proportion of nodes
LOW	networkx/algorithms/bipartite/basic.py	141	# this should maybe just return False?
LOW	…kx/algorithms/assortativity/tests/test_connectivity.py	140	# just return the connectivity value itself?
MEDIUM	networkx/algorithms/community/lukes.py	115	# - brevity: we can leverage global "safe_G"
LOW	networkx/algorithms/community/centrality.py	123	# If the graph is already empty, simply return its connected
LOW	networkx/generators/line.py	475	# in this case either triangle works, so just use T
LOW	networkx/generators/harary_graph.py	145	# In case of connectivity 1, simply return the path graph.
LOW	networkx/generators/random_graphs.py	797	# For simplicity, if p == 0 or 1, just return BA

Docstring Block Structure2 hits · 10 pts

Severity	File	Line	Snippet
HIGH	benchmarks/benchmarks/utils.py	9	Generate a string name for a graph-generating function and its arguments. This function takes a graph constructor (
HIGH	benchmarks/benchmarks/utils.py	45	Generate a graph using the given function and assign random edge weights. Parameters: weight_seed (int

Overly Generic Function Names3 hits · 2 pts

Severity	File	Line	Snippet
LOW	networkx/classes/tests/test_graphviews.py	39	def my_method(self):
LOW	networkx/classes/tests/test_graphviews.py	337	def my_method(self):
LOW	networkx/generators/random_graphs.py	1382	def my_function(b):

Verbosity Indicators1 hit · 0 pts

Severity	File	Line	Snippet
LOW	networkx/algorithms/isomorphism/vf2pp.py	902	and node1 is mapped to node2. The purpose of this function is to avoid brute

Score History

Severity Breakdown

Pattern Findings