diff options
| author | Jarrod Millman <jarrod.millman@gmail.com> | 2021-05-26 08:59:54 -0700 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2021-05-26 08:59:54 -0700 |
| commit | 09b30ba69dd2e81a2728fd1259ca7b4d88470827 (patch) | |
| tree | ec1c723f51473a8ff99fb0195783c607242bb90c | |
| parent | 7771b28bad07f0a07ac08ef8c2c6a17191d36f54 (diff) | |
| download | networkx-09b30ba69dd2e81a2728fd1259ca7b4d88470827.tar.gz | |
Refactor testing utilities (#4829)
* Refactor testing utilities
Change `assert_edges_equal`, `assert_graphs_equal`, and `assert_nodes_equal`
to be more pytest-idiomatic.
For example, `assert_edges_equal` becomes the Boolean function `edges_equal`
and then the assert is done the testing file
(i.e., `assert edges_equal(edges1, edges2)`).
This also makes these utility functions useful in nontesting situations
where you want to compare edges, but not raise an exception based on the result.
* Move testing utility functions
* Use new testing utilities
* Deprecate assert_*_equal testing utilities
* Document node, edge, and graph equality helper functions
* text nits.
* Update networkx/tests/test_convert_pandas.py
Co-authored-by: Ross Barnowski <rossbar@berkeley.edu>
* Update networkx/readwrite/tests/test_sparse6.py
Co-authored-by: Ross Barnowski <rossbar@berkeley.edu>
* Update networkx/readwrite/tests/test_graph6.py
Co-authored-by: Ross Barnowski <rossbar@berkeley.edu>
* Update networkx/generators/tests/test_classic.py
Co-authored-by: Ross Barnowski <rossbar@berkeley.edu>
* Update networkx/algorithms/tree/tests/test_operations.py
Co-authored-by: Ross Barnowski <rossbar@berkeley.edu>
* Update networkx/algorithms/tree/tests/test_coding.py
Co-authored-by: Ross Barnowski <rossbar@berkeley.edu>
* Update networkx/algorithms/tests/test_dag.py
Co-authored-by: Ross Barnowski <rossbar@berkeley.edu>
* Update networkx/algorithms/minors/tests/test_contraction.py
Co-authored-by: Ross Barnowski <rossbar@berkeley.edu>
* add short equality description to docstring
* Suppress known warnings
Co-authored-by: Ross Barnowski <rossbar@berkeley.edu>
Co-authored-by: Dan Schult <dschult@colgate.edu>
53 files changed, 804 insertions, 715 deletions
diff --git a/doc/developer/deprecations.rst b/doc/developer/deprecations.rst index 5fcc1490..57254771 100644 --- a/doc/developer/deprecations.rst +++ b/doc/developer/deprecations.rst @@ -85,5 +85,4 @@ Version 3.0 * In ``networkx.classes`` remove the ``ordered`` module and the four ``Ordered`` classes defined therein. * In ``utils/decorators.py`` remove ``preserve_random_state``. -* In ``testing/utils.py`` remove ``almost_equal``. -* Remove ``testing/test.py``. +* Remove ``testing``. diff --git a/doc/reference/utils.rst b/doc/reference/utils.rst index 636134ee..0be25aac 100644 --- a/doc/reference/utils.rst +++ b/doc/reference/utils.rst @@ -22,7 +22,9 @@ Helper Functions pairwise groups create_random_state - + nodes_equal + edges_equal + graphs_equal Data Structures and Algorithms ------------------------------ diff --git a/doc/release/release_dev.rst b/doc/release/release_dev.rst index 92df26d6..dbb7f846 100644 --- a/doc/release/release_dev.rst +++ b/doc/release/release_dev.rst @@ -117,6 +117,8 @@ Deprecations Deprecate ``almost_equal``. - [`#4833 <https://github.com/networkx/networkx/pull/4833>`_] Deprecate ``run``. +- [`#4829 <https://github.com/networkx/networkx/pull/4829>`_] + Deprecate ``assert_nodes_equal``, ``assert_edges_equal``, and ``assert_graphs_equal``. Contributors ------------ diff --git a/networkx/algorithms/approximation/tests/test_steinertree.py b/networkx/algorithms/approximation/tests/test_steinertree.py index 7fe29192..1f55b06f 100644 --- a/networkx/algorithms/approximation/tests/test_steinertree.py +++ b/networkx/algorithms/approximation/tests/test_steinertree.py @@ -2,7 +2,7 @@ import pytest import networkx as nx from networkx.algorithms.approximation.steinertree import metric_closure from networkx.algorithms.approximation.steinertree import steiner_tree -from networkx.testing.utils import assert_edges_equal +from networkx.utils import edges_equal class TestSteinerTree: @@ -49,7 +49,7 @@ class TestSteinerTree: (5, 7, {"distance": 1, "path": [5, 7]}), (6, 7, {"distance": 11, "path": [6, 5, 7]}), ] - assert_edges_equal(list(M.edges(data=True)), mc) + assert edges_equal(list(M.edges(data=True)), mc) def test_steiner_tree(self): S = steiner_tree(self.G, self.term_nodes) @@ -60,7 +60,7 @@ class TestSteinerTree: (3, 4, {"weight": 10}), (5, 7, {"weight": 1}), ] - assert_edges_equal(list(S.edges(data=True)), expected_steiner_tree) + assert edges_equal(list(S.edges(data=True)), expected_steiner_tree) def test_multigraph_steiner_tree(self): G = nx.MultiGraph() @@ -80,4 +80,4 @@ class TestSteinerTree: (3, 5, 0, {"weight": 1}), ] T = steiner_tree(G, terminal_nodes) - assert_edges_equal(T.edges(data=True, keys=True), expected_edges) + assert edges_equal(T.edges(data=True, keys=True), expected_edges) diff --git a/networkx/algorithms/bipartite/tests/test_edgelist.py b/networkx/algorithms/bipartite/tests/test_edgelist.py index 2a8dc73e..80b2c098 100644 --- a/networkx/algorithms/bipartite/tests/test_edgelist.py +++ b/networkx/algorithms/bipartite/tests/test_edgelist.py @@ -7,7 +7,7 @@ import tempfile import os import networkx as nx -from networkx.testing import assert_edges_equal, assert_nodes_equal, assert_graphs_equal +from networkx.utils import nodes_equal, edges_equal, graphs_equal from networkx.algorithms import bipartite @@ -35,7 +35,7 @@ class TestEdgelist: """ bytesIO = io.BytesIO(s) G = bipartite.read_edgelist(bytesIO, nodetype=int) - assert_edges_equal(G.edges(), [(1, 2), (2, 3)]) + assert edges_equal(G.edges(), [(1, 2), (2, 3)]) def test_read_edgelist_3(self): s = b"""\ @@ -46,11 +46,11 @@ class TestEdgelist: """ bytesIO = io.BytesIO(s) G = bipartite.read_edgelist(bytesIO, nodetype=int, data=False) - assert_edges_equal(G.edges(), [(1, 2), (2, 3)]) + assert edges_equal(G.edges(), [(1, 2), (2, 3)]) bytesIO = io.BytesIO(s) G = bipartite.read_edgelist(bytesIO, nodetype=int, data=True) - assert_edges_equal( + assert edges_equal( G.edges(data=True), [(1, 2, {"weight": 2.0}), (2, 3, {"weight": 3.0})] ) @@ -110,7 +110,7 @@ class TestEdgelist: fd, fname = tempfile.mkstemp() bipartite.write_edgelist(G, fname) H = bipartite.read_edgelist(fname) - assert_graphs_equal(G, H) + assert graphs_equal(G, H) os.close(fd) os.unlink(fname) @@ -138,7 +138,7 @@ class TestEdgelist: fd, fname = tempfile.mkstemp() bipartite.write_edgelist(G, fname, encoding="latin-1") H = bipartite.read_edgelist(fname, encoding="latin-1") - assert_graphs_equal(G, H) + assert graphs_equal(G, H) os.close(fd) os.unlink(fname) @@ -150,8 +150,8 @@ class TestEdgelist: H2 = bipartite.read_edgelist(fname) assert H is not H2 # they should be different graphs G.remove_node("g") # isolated nodes are not written in edgelist - assert_nodes_equal(list(H), list(G)) - assert_edges_equal(list(H.edges()), list(G.edges())) + assert nodes_equal(list(H), list(G)) + assert edges_equal(list(H.edges()), list(G.edges())) os.close(fd) os.unlink(fname) @@ -162,8 +162,8 @@ class TestEdgelist: H = bipartite.read_edgelist(fname, nodetype=int) # isolated nodes are not written in edgelist G.remove_nodes_from(list(nx.isolates(G))) - assert_nodes_equal(list(H), list(G)) - assert_edges_equal(list(H.edges()), list(G.edges())) + assert nodes_equal(list(H), list(G)) + assert edges_equal(list(H.edges()), list(G.edges())) os.close(fd) os.unlink(fname) @@ -174,8 +174,8 @@ class TestEdgelist: H = bipartite.read_edgelist(fname, nodetype=int, create_using=nx.MultiGraph()) H2 = bipartite.read_edgelist(fname, nodetype=int, create_using=nx.MultiGraph()) assert H is not H2 # they should be different graphs - assert_nodes_equal(list(H), list(G)) - assert_edges_equal(list(H.edges()), list(G.edges())) + assert nodes_equal(list(H), list(G)) + assert edges_equal(list(H.edges()), list(G.edges())) os.close(fd) os.unlink(fname) diff --git a/networkx/algorithms/bipartite/tests/test_matrix.py b/networkx/algorithms/bipartite/tests/test_matrix.py index 176741ae..393b71e7 100644 --- a/networkx/algorithms/bipartite/tests/test_matrix.py +++ b/networkx/algorithms/bipartite/tests/test_matrix.py @@ -7,7 +7,7 @@ sparse = pytest.importorskip("scipy.sparse") import networkx as nx from networkx.algorithms import bipartite -from networkx.testing.utils import assert_edges_equal +from networkx.utils import edges_equal class TestBiadjacencyMatrix: @@ -68,12 +68,12 @@ class TestBiadjacencyMatrix: def test_from_biadjacency_weight(self): M = sparse.csc_matrix([[1, 2], [0, 3]]) B = bipartite.from_biadjacency_matrix(M) - assert_edges_equal(B.edges(), [(0, 2), (0, 3), (1, 3)]) + assert edges_equal(B.edges(), [(0, 2), (0, 3), (1, 3)]) B = bipartite.from_biadjacency_matrix(M, edge_attribute="weight") e = [(0, 2, {"weight": 1}), (0, 3, {"weight": 2}), (1, 3, {"weight": 3})] - assert_edges_equal(B.edges(data=True), e) + assert edges_equal(B.edges(data=True), e) def test_from_biadjacency_multigraph(self): M = sparse.csc_matrix([[1, 2], [0, 3]]) B = bipartite.from_biadjacency_matrix(M, create_using=nx.MultiGraph()) - assert_edges_equal(B.edges(), [(0, 2), (0, 3), (0, 3), (1, 3), (1, 3), (1, 3)]) + assert edges_equal(B.edges(), [(0, 2), (0, 3), (0, 3), (1, 3), (1, 3), (1, 3)]) diff --git a/networkx/algorithms/bipartite/tests/test_project.py b/networkx/algorithms/bipartite/tests/test_project.py index dbe75894..d41ec580 100644 --- a/networkx/algorithms/bipartite/tests/test_project.py +++ b/networkx/algorithms/bipartite/tests/test_project.py @@ -1,89 +1,89 @@ import networkx as nx from networkx.algorithms import bipartite -from networkx.testing import assert_edges_equal, assert_nodes_equal +from networkx.utils import nodes_equal, edges_equal class TestBipartiteProject: def test_path_projected_graph(self): G = nx.path_graph(4) P = bipartite.projected_graph(G, [1, 3]) - assert_nodes_equal(list(P), [1, 3]) - assert_edges_equal(list(P.edges()), [(1, 3)]) + assert nodes_equal(list(P), [1, 3]) + assert edges_equal(list(P.edges()), [(1, 3)]) P = bipartite.projected_graph(G, [0, 2]) - assert_nodes_equal(list(P), [0, 2]) - assert_edges_equal(list(P.edges()), [(0, 2)]) + assert nodes_equal(list(P), [0, 2]) + assert edges_equal(list(P.edges()), [(0, 2)]) def test_path_projected_properties_graph(self): G = nx.path_graph(4) G.add_node(1, name="one") G.add_node(2, name="two") P = bipartite.projected_graph(G, [1, 3]) - assert_nodes_equal(list(P), [1, 3]) - assert_edges_equal(list(P.edges()), [(1, 3)]) + assert nodes_equal(list(P), [1, 3]) + assert edges_equal(list(P.edges()), [(1, 3)]) assert P.nodes[1]["name"] == G.nodes[1]["name"] P = bipartite.projected_graph(G, [0, 2]) - assert_nodes_equal(list(P), [0, 2]) - assert_edges_equal(list(P.edges()), [(0, 2)]) + assert nodes_equal(list(P), [0, 2]) + assert edges_equal(list(P.edges()), [(0, 2)]) assert P.nodes[2]["name"] == G.nodes[2]["name"] def test_path_collaboration_projected_graph(self): G = nx.path_graph(4) P = bipartite.collaboration_weighted_projected_graph(G, [1, 3]) - assert_nodes_equal(list(P), [1, 3]) - assert_edges_equal(list(P.edges()), [(1, 3)]) + assert nodes_equal(list(P), [1, 3]) + assert edges_equal(list(P.edges()), [(1, 3)]) P[1][3]["weight"] = 1 P = bipartite.collaboration_weighted_projected_graph(G, [0, 2]) - assert_nodes_equal(list(P), [0, 2]) - assert_edges_equal(list(P.edges()), [(0, 2)]) + assert nodes_equal(list(P), [0, 2]) + assert edges_equal(list(P.edges()), [(0, 2)]) P[0][2]["weight"] = 1 def test_directed_path_collaboration_projected_graph(self): G = nx.DiGraph() nx.add_path(G, range(4)) P = bipartite.collaboration_weighted_projected_graph(G, [1, 3]) - assert_nodes_equal(list(P), [1, 3]) - assert_edges_equal(list(P.edges()), [(1, 3)]) + assert nodes_equal(list(P), [1, 3]) + assert edges_equal(list(P.edges()), [(1, 3)]) P[1][3]["weight"] = 1 P = bipartite.collaboration_weighted_projected_graph(G, [0, 2]) - assert_nodes_equal(list(P), [0, 2]) - assert_edges_equal(list(P.edges()), [(0, 2)]) + assert nodes_equal(list(P), [0, 2]) + assert edges_equal(list(P.edges()), [(0, 2)]) P[0][2]["weight"] = 1 def test_path_weighted_projected_graph(self): G = nx.path_graph(4) P = bipartite.weighted_projected_graph(G, [1, 3]) - assert_nodes_equal(list(P), [1, 3]) - assert_edges_equal(list(P.edges()), [(1, 3)]) + assert nodes_equal(list(P), [1, 3]) + assert edges_equal(list(P.edges()), [(1, 3)]) P[1][3]["weight"] = 1 P = bipartite.weighted_projected_graph(G, [0, 2]) - assert_nodes_equal(list(P), [0, 2]) - assert_edges_equal(list(P.edges()), [(0, 2)]) + assert nodes_equal(list(P), [0, 2]) + assert edges_equal(list(P.edges()), [(0, 2)]) P[0][2]["weight"] = 1 def test_path_weighted_projected_directed_graph(self): G = nx.DiGraph() nx.add_path(G, range(4)) P = bipartite.weighted_projected_graph(G, [1, 3]) - assert_nodes_equal(list(P), [1, 3]) - assert_edges_equal(list(P.edges()), [(1, 3)]) + assert nodes_equal(list(P), [1, 3]) + assert edges_equal(list(P.edges()), [(1, 3)]) P[1][3]["weight"] = 1 P = bipartite.weighted_projected_graph(G, [0, 2]) - assert_nodes_equal(list(P), [0, 2]) - assert_edges_equal(list(P.edges()), [(0, 2)]) + assert nodes_equal(list(P), [0, 2]) + assert edges_equal(list(P.edges()), [(0, 2)]) P[0][2]["weight"] = 1 def test_star_projected_graph(self): G = nx.star_graph(3) P = bipartite.projected_graph(G, [1, 2, 3]) - assert_nodes_equal(list(P), [1, 2, 3]) - assert_edges_equal(list(P.edges()), [(1, 2), (1, 3), (2, 3)]) + assert nodes_equal(list(P), [1, 2, 3]) + assert edges_equal(list(P.edges()), [(1, 2), (1, 3), (2, 3)]) P = bipartite.weighted_projected_graph(G, [1, 2, 3]) - assert_nodes_equal(list(P), [1, 2, 3]) - assert_edges_equal(list(P.edges()), [(1, 2), (1, 3), (2, 3)]) + assert nodes_equal(list(P), [1, 2, 3]) + assert edges_equal(list(P.edges()), [(1, 2), (1, 3), (2, 3)]) P = bipartite.projected_graph(G, [0]) - assert_nodes_equal(list(P), [0]) - assert_edges_equal(list(P.edges()), []) + assert nodes_equal(list(P), [0]) + assert edges_equal(list(P.edges()), []) def test_project_multigraph(self): G = nx.Graph() @@ -92,11 +92,11 @@ class TestBipartiteProject: G.add_edge("a", 2) G.add_edge("b", 2) P = bipartite.projected_graph(G, "ab") - assert_edges_equal(list(P.edges()), [("a", "b")]) + assert edges_equal(list(P.edges()), [("a", "b")]) P = bipartite.weighted_projected_graph(G, "ab") - assert_edges_equal(list(P.edges()), [("a", "b")]) + assert edges_equal(list(P.edges()), [("a", "b")]) P = bipartite.projected_graph(G, "ab", multigraph=True) - assert_edges_equal(list(P.edges()), [("a", "b"), ("a", "b")]) + assert edges_equal(list(P.edges()), [("a", "b"), ("a", "b")]) def test_project_collaboration(self): G = nx.Graph() @@ -118,13 +118,13 @@ class TestBipartiteProject: G.add_edge("A", 2) G.add_edge("B", 2) P = bipartite.projected_graph(G, "AB") - assert_edges_equal(list(P.edges()), [("A", "B")]) + assert edges_equal(list(P.edges()), [("A", "B")]) P = bipartite.weighted_projected_graph(G, "AB") - assert_edges_equal(list(P.edges()), [("A", "B")]) + assert edges_equal(list(P.edges()), [("A", "B")]) assert P["A"]["B"]["weight"] == 1 P = bipartite.projected_graph(G, "AB", multigraph=True) - assert_edges_equal(list(P.edges()), [("A", "B")]) + assert edges_equal(list(P.edges()), [("A", "B")]) G = nx.DiGraph() G.add_edge("A", 1) @@ -132,13 +132,13 @@ class TestBipartiteProject: G.add_edge("A", 2) G.add_edge(2, "B") P = bipartite.projected_graph(G, "AB") - assert_edges_equal(list(P.edges()), [("A", "B")]) + assert edges_equal(list(P.edges()), [("A", "B")]) P = bipartite.weighted_projected_graph(G, "AB") - assert_edges_equal(list(P.edges()), [("A", "B")]) + assert edges_equal(list(P.edges()), [("A", "B")]) assert P["A"]["B"]["weight"] == 2 P = bipartite.projected_graph(G, "AB", multigraph=True) - assert_edges_equal(list(P.edges()), [("A", "B"), ("A", "B")]) + assert edges_equal(list(P.edges()), [("A", "B"), ("A", "B")]) class TestBipartiteWeightedProjection: @@ -184,7 +184,7 @@ class TestBipartiteWeightedProjection: Panswer = nx.Graph() Panswer.add_weighted_edges_from(edges) P = bipartite.weighted_projected_graph(self.G, "ABCDEF") - assert_edges_equal(list(P.edges()), Panswer.edges()) + assert edges_equal(list(P.edges()), Panswer.edges()) for u, v in list(P.edges()): assert P[u][v]["weight"] == Panswer[u][v]["weight"] @@ -201,7 +201,7 @@ class TestBipartiteWeightedProjection: Panswer = nx.Graph() Panswer.add_weighted_edges_from(edges) P = bipartite.weighted_projected_graph(self.N, "ABCDE") - assert_edges_equal(list(P.edges()), Panswer.edges()) + assert edges_equal(list(P.edges()), Panswer.edges()) for u, v in list(P.edges()): assert P[u][v]["weight"] == Panswer[u][v]["weight"] @@ -217,7 +217,7 @@ class TestBipartiteWeightedProjection: Panswer = nx.Graph() Panswer.add_weighted_edges_from(edges) P = bipartite.collaboration_weighted_projected_graph(self.G, "ABCDEF") - assert_edges_equal(list(P.edges()), Panswer.edges()) + assert edges_equal(list(P.edges()), Panswer.edges()) for u, v in list(P.edges()): assert P[u][v]["weight"] == Panswer[u][v]["weight"] @@ -234,7 +234,7 @@ class TestBipartiteWeightedProjection: Panswer = nx.Graph() Panswer.add_weighted_edges_from(edges) P = bipartite.collaboration_weighted_projected_graph(self.N, "ABCDE") - assert_edges_equal(list(P.edges()), Panswer.edges()) + assert edges_equal(list(P.edges()), Panswer.edges()) for u, v in list(P.edges()): assert P[u][v]["weight"] == Panswer[u][v]["weight"] @@ -250,7 +250,7 @@ class TestBipartiteWeightedProjection: Panswer = nx.Graph() Panswer.add_weighted_edges_from(edges) P = bipartite.weighted_projected_graph(self.G, "ABCDEF", ratio=True) - assert_edges_equal(list(P.edges()), Panswer.edges()) + assert edges_equal(list(P.edges()), Panswer.edges()) for u, v in list(P.edges()): assert P[u][v]["weight"] == Panswer[u][v]["weight"] @@ -267,7 +267,7 @@ class TestBipartiteWeightedProjection: Panswer = nx.Graph() Panswer.add_weighted_edges_from(edges) P = bipartite.weighted_projected_graph(self.N, "ABCDE", ratio=True) - assert_edges_equal(list(P.edges()), Panswer.edges()) + assert edges_equal(list(P.edges()), Panswer.edges()) for u, v in list(P.edges()): assert P[u][v]["weight"] == Panswer[u][v]["weight"] @@ -283,7 +283,7 @@ class TestBipartiteWeightedProjection: Panswer = nx.Graph() Panswer.add_weighted_edges_from(edges) P = bipartite.overlap_weighted_projected_graph(self.G, "ABCDEF", jaccard=False) - assert_edges_equal(list(P.edges()), Panswer.edges()) + assert edges_equal(list(P.edges()), Panswer.edges()) for u, v in list(P.edges()): assert P[u][v]["weight"] == Panswer[u][v]["weight"] @@ -300,7 +300,7 @@ class TestBipartiteWeightedProjection: Panswer = nx.Graph() Panswer.add_weighted_edges_from(edges) P = bipartite.overlap_weighted_projected_graph(self.N, "ABCDE", jaccard=False) - assert_edges_equal(list(P.edges()), Panswer.edges()) + assert edges_equal(list(P.edges()), Panswer.edges()) for u, v in list(P.edges()): assert P[u][v]["weight"] == Panswer[u][v]["weight"] @@ -316,7 +316,7 @@ class TestBipartiteWeightedProjection: Panswer = nx.Graph() Panswer.add_weighted_edges_from(edges) P = bipartite.overlap_weighted_projected_graph(self.G, "ABCDEF") - assert_edges_equal(list(P.edges()), Panswer.edges()) + assert edges_equal(list(P.edges()), Panswer.edges()) for u, v in list(P.edges()): assert P[u][v]["weight"] == Panswer[u][v]["weight"] @@ -333,7 +333,7 @@ class TestBipartiteWeightedProjection: Panswer = nx.Graph() Panswer.add_weighted_edges_from(edges) P = bipartite.overlap_weighted_projected_graph(self.N, "ABCDE") - assert_edges_equal(list(P.edges()), Panswer.edges()) + assert edges_equal(list(P.edges()), Panswer.edges()) for u, v in P.edges(): assert P[u][v]["weight"] == Panswer[u][v]["weight"] @@ -345,23 +345,23 @@ class TestBipartiteWeightedProjection: G = bipartite.generic_weighted_projected_graph( B, [0, 2, 4], weight_function=shared ) - assert_nodes_equal(list(G), [0, 2, 4]) - assert_edges_equal( + assert nodes_equal(list(G), [0, 2, 4]) + assert edges_equal( list(list(G.edges(data=True))), [(0, 2, {"weight": 1}), (2, 4, {"weight": 1})], ) G = bipartite.generic_weighted_projected_graph(B, [0, 2, 4]) - assert_nodes_equal(list(G), [0, 2, 4]) - assert_edges_equal( + assert nodes_equal(list(G), [0, 2, 4]) + assert edges_equal( list(list(G.edges(data=True))), [(0, 2, {"weight": 1}), (2, 4, {"weight": 1})], ) B = nx.DiGraph() nx.add_path(B, range(5)) G = bipartite.generic_weighted_projected_graph(B, [0, 2, 4]) - assert_nodes_equal(list(G), [0, 2, 4]) - assert_edges_equal( + assert nodes_equal(list(G), [0, 2, 4]) + assert edges_equal( list(G.edges(data=True)), [(0, 2, {"weight": 1}), (2, 4, {"weight": 1})] ) @@ -383,10 +383,10 @@ class TestBipartiteWeightedProjection: G = bipartite.generic_weighted_projected_graph( B, [0, 1], weight_function=jaccard ) - assert_edges_equal(list(G.edges(data=True)), [(0, 1, {"weight": 1.0})]) + assert edges_equal(list(G.edges(data=True)), [(0, 1, {"weight": 1.0})]) G = bipartite.generic_weighted_projected_graph( B, [0, 1], weight_function=my_weight ) - assert_edges_equal(list(G.edges(data=True)), [(0, 1, {"weight": 10})]) + assert edges_equal(list(G.edges(data=True)), [(0, 1, {"weight": 10})]) G = bipartite.generic_weighted_projected_graph(B, [0, 1]) - assert_edges_equal(list(G.edges(data=True)), [(0, 1, {"weight": 2})]) + assert edges_equal(list(G.edges(data=True)), [(0, 1, {"weight": 2})]) diff --git a/networkx/algorithms/minors/tests/test_contraction.py b/networkx/algorithms/minors/tests/test_contraction.py index 15ea3dd5..34029fb6 100644 --- a/networkx/algorithms/minors/tests/test_contraction.py +++ b/networkx/algorithms/minors/tests/test_contraction.py @@ -2,8 +2,7 @@ import pytest import networkx as nx -from networkx.testing.utils import assert_edges_equal, assert_nodes_equal -from networkx.utils import arbitrary_element +from networkx.utils import arbitrary_element, nodes_equal, edges_equal class TestQuotient: @@ -113,8 +112,8 @@ class TestQuotient: G = nx.path_graph(6) partition = [{0, 1}, {2, 3}, {4, 5}] M = nx.quotient_graph(G, partition, relabel=True) - assert_nodes_equal(M, [0, 1, 2]) - assert_edges_equal(M.edges(), [(0, 1), (1, 2)]) + assert nodes_equal(M, [0, 1, 2]) + assert edges_equal(M.edges(), [(0, 1), (1, 2)]) for n in M: assert M.nodes[n]["nedges"] == 1 assert M.nodes[n]["nnodes"] == 2 @@ -124,8 +123,8 @@ class TestQuotient: G = nx.path_graph(6) partition = {0: [0, 1], 2: [2, 3], 4: [4, 5]} M = nx.quotient_graph(G, partition, relabel=True) - assert_nodes_equal(M, [0, 1, 2]) - assert_edges_equal(M.edges(), [(0, 1), (1, 2)]) + assert nodes_equal(M, [0, 1, 2]) + assert edges_equal(M.edges(), [(0, 1), (1, 2)]) for n in M: assert M.nodes[n]["nedges"] == 1 assert M.nodes[n]["nnodes"] == 2 @@ -135,8 +134,8 @@ class TestQuotient: G = nx.path_graph(6) partition = {0: (0, 1), 2: (2, 3), 4: (4, 5)} M = nx.quotient_graph(G, partition, relabel=True) - assert_nodes_equal(M, [0, 1, 2]) - assert_edges_equal(M.edges(), [(0, 1), (1, 2)]) + assert nodes_equal(M, [0, 1, 2]) + assert edges_equal(M.edges(), [(0, 1), (1, 2)]) for n in M: assert M.nodes[n]["nedges"] == 1 assert M.nodes[n]["nnodes"] == 2 @@ -146,8 +145,8 @@ class TestQuotient: G = nx.path_graph(6) partition = {0: {0, 1}, 2: {2, 3}, 4: {4, 5}} M = nx.quotient_graph(G, partition, relabel=True) - assert_nodes_equal(M, [0, 1, 2]) - assert_edges_equal(M.edges(), [(0, 1), (1, 2)]) + assert nodes_equal(M, [0, 1, 2]) + assert edges_equal(M.edges(), [(0, 1), (1, 2)]) for n in M: assert M.nodes[n]["nedges"] == 1 assert M.nodes[n]["nnodes"] == 2 @@ -157,8 +156,8 @@ class TestQuotient: G = nx.MultiGraph(nx.path_graph(6)) partition = [{0, 1}, {2, 3}, {4, 5}] M = nx.quotient_graph(G, partition, relabel=True) - assert_nodes_equal(M, [0, 1, 2]) - assert_edges_equal(M.edges(), [(0, 1), (1, 2)]) + assert nodes_equal(M, [0, 1, 2]) + assert edges_equal(M.edges(), [(0, 1), (1, 2)]) for n in M: assert M.nodes[n]["nedges"] == 1 assert M.nodes[n]["nnodes"] == 2 @@ -169,8 +168,8 @@ class TestQuotient: nx.add_path(G, range(6)) partition = [{0, 1}, {2, 3}, {4, 5}] M = nx.quotient_graph(G, partition, relabel=True) - assert_nodes_equal(M, [0, 1, 2]) - assert_edges_equal(M.edges(), [(0, 1), (1, 2)]) + assert nodes_equal(M, [0, 1, 2]) + assert edges_equal(M.edges(), [(0, 1), (1, 2)]) for n in M: assert M.nodes[n]["nedges"] == 1 assert M.nodes[n]["nnodes"] == 2 @@ -181,8 +180,8 @@ class TestQuotient: nx.add_path(G, range(6)) partition = [{0, 1}, {2, 3}, {4, 5}] M = nx.quotient_graph(G, partition, relabel=True) - assert_nodes_equal(M, [0, 1, 2]) - assert_edges_equal(M.edges(), [(0, 1), (1, 2)]) + assert nodes_equal(M, [0, 1, 2]) + assert edges_equal(M.edges(), [(0, 1), (1, 2)]) for n in M: assert M.nodes[n]["nedges"] == 1 assert M.nodes[n]["nnodes"] == 2 @@ -200,8 +199,8 @@ class TestQuotient: G[i][i + 1]["weight"] = i + 1 partition = [{0, 1}, {2, 3}, {4, 5}] M = nx.quotient_graph(G, partition, relabel=True) - assert_nodes_equal(M, [0, 1, 2]) - assert_edges_equal(M.edges(), [(0, 1), (1, 2)]) + assert nodes_equal(M, [0, 1, 2]) + assert edges_equal(M.edges(), [(0, 1), (1, 2)]) assert M[0][1]["weight"] == 2 assert M[1][2]["weight"] == 4 for n in M: @@ -213,8 +212,8 @@ class TestQuotient: G = nx.barbell_graph(3, 0) partition = [{0, 1, 2}, {3, 4, 5}] M = nx.quotient_graph(G, partition, relabel=True) - assert_nodes_equal(M, [0, 1]) - assert_edges_equal(M.edges(), [(0, 1)]) + assert nodes_equal(M, [0, 1]) + assert edges_equal(M.edges(), [(0, 1)]) for n in M: assert M.nodes[n]["nedges"] == 3 assert M.nodes[n]["nnodes"] == 3 @@ -226,8 +225,8 @@ class TestQuotient: G.add_edge(0, 5) partition = [{0, 1, 2}, {3, 4, 5}] M = nx.quotient_graph(G, partition, relabel=True) - assert_nodes_equal(M, [0, 1]) - assert_edges_equal(M.edges(), [(0, 1)]) + assert nodes_equal(M, [0, 1]) + assert edges_equal(M.edges(), [(0, 1)]) assert M[0][1]["weight"] == 2 for n in M: assert M.nodes[n]["nedges"] == 3 @@ -238,8 +237,8 @@ class TestQuotient: G = nx.path_graph(6) partition = [[0, 1], [2, 3], [4, 5]] M = nx.quotient_graph(G, partition, relabel=True) - assert_nodes_equal(M.nodes(), [0, 1, 2]) - assert_edges_equal(M.edges(), [(0, 1), (1, 2)]) + assert nodes_equal(M.nodes(), [0, 1, 2]) + assert edges_equal(M.edges(), [(0, 1), (1, 2)]) for n in M.nodes(): assert M.nodes[n]["nedges"] == 1 assert M.nodes[n]["nnodes"] == 2 @@ -249,8 +248,8 @@ class TestQuotient: G = nx.MultiGraph(nx.path_graph(6)) partition = [[0, 1], [2, 3], [4, 5]] M = nx.quotient_graph(G, partition, create_using=nx.MultiGraph(), relabel=True) - assert_nodes_equal(M.nodes(), [0, 1, 2]) - assert_edges_equal(M.edges(), [(0, 1), (1, 2)]) + assert nodes_equal(M.nodes(), [0, 1, 2]) + assert edges_equal(M.edges(), [(0, 1), (1, 2)]) for n in M.nodes(): assert M.nodes[n]["nedges"] == 1 assert M.nodes[n]["nnodes"] == 2 @@ -260,13 +259,13 @@ class TestQuotient: G = nx.path_graph(6) partition = [] H = nx.quotient_graph(G, partition, relabel=True) - assert_nodes_equal(H.nodes(), []) - assert_edges_equal(H.edges(), []) + assert nodes_equal(H.nodes(), []) + assert edges_equal(H.edges(), []) partition = [[0, 1], [2, 3], [5]] H = nx.quotient_graph(G, partition, relabel=True) - assert_nodes_equal(H.nodes(), [0, 1, 2]) - assert_edges_equal(H.edges(), [(0, 1)]) + assert nodes_equal(H.nodes(), [0, 1, 2]) + assert edges_equal(H.edges(), [(0, 1)]) class TestContraction: @@ -323,7 +322,7 @@ class TestContraction: expected.add_edge(0, 1) expected.add_edge(0, 0) expected.add_edge(0, 0) - assert_edges_equal(actual.edges, expected.edges) + assert edges_equal(actual.edges, expected.edges) def test_multigraph_keys(self): """Tests that multiedge keys are reset in new graph.""" @@ -338,7 +337,7 @@ class TestContraction: expected.add_edge(0, 1, 2) # keyed as 2 b/c 2 edges already in G expected.add_edge(0, 0, 0) expected.add_edge(0, 0, 1) # this comes from (0, 2, 5) - assert_edges_equal(actual.edges, expected.edges) + assert edges_equal(actual.edges, expected.edges) def test_node_attributes(self): """Tests that node contraction preserves node attributes.""" @@ -390,12 +389,12 @@ class TestContraction: expected = nx.complete_graph([0, 2, 3]) expected.add_edge(0, 0) expected.add_edge(0, 0) - assert_edges_equal(actual.edges, expected.edges) + assert edges_equal(actual.edges, expected.edges) actual = nx.contracted_nodes(G, 1, 0) expected = nx.complete_graph([1, 2, 3]) expected.add_edge(1, 1) expected.add_edge(1, 1) - assert_edges_equal(actual.edges, expected.edges) + assert edges_equal(actual.edges, expected.edges) def test_undirected_edge_contraction(self): """Tests for edge contraction in an undirected graph.""" diff --git a/networkx/algorithms/operators/tests/test_all.py b/networkx/algorithms/operators/tests/test_all.py index 9502bbf9..bcb9127f 100644 --- a/networkx/algorithms/operators/tests/test_all.py +++ b/networkx/algorithms/operators/tests/test_all.py @@ -1,6 +1,6 @@ import pytest import networkx as nx -from networkx.testing import assert_edges_equal +from networkx.utils import edges_equal def test_union_all_attributes(): @@ -150,7 +150,7 @@ def test_union_all_and_compose_all(): G = nx.union_all([G1, G2]) H = nx.compose_all([G1, G2]) - assert_edges_equal(G.edges(), H.edges()) + assert edges_equal(G.edges(), H.edges()) assert not G.has_edge("A", "1") pytest.raises(nx.NetworkXError, nx.union, K3, P3) H1 = nx.union_all([H, G1], rename=("H", "G1")) @@ -188,7 +188,7 @@ def test_union_all_and_compose_all(): assert not H1.has_edge("NB", "NA") G = nx.compose_all([G, G]) - assert_edges_equal(G.edges(), H.edges()) + assert edges_equal(G.edges(), H.edges()) G2 = nx.union_all([G2, G2], rename=("", "copy")) assert sorted(G2.nodes()) == [ diff --git a/networkx/algorithms/operators/tests/test_binary.py b/networkx/algorithms/operators/tests/test_binary.py index c6b4adf9..d9e15403 100644 --- a/networkx/algorithms/operators/tests/test_binary.py +++ b/networkx/algorithms/operators/tests/test_binary.py @@ -1,6 +1,6 @@ import pytest import networkx as nx -from networkx.testing import assert_edges_equal +from networkx.utils import edges_equal def test_union_attributes(): @@ -236,7 +236,7 @@ def test_union_and_compose(): G = nx.union(G1, G2) H = nx.compose(G1, G2) - assert_edges_equal(G.edges(), H.edges()) + assert edges_equal(G.edges(), H.edges()) assert not G.has_edge("A", 1) pytest.raises(nx.NetworkXError, nx.union, K3, P3) H1 = nx.union(H, G1, rename=("H", "G1")) @@ -274,7 +274,7 @@ def test_union_and_compose(): assert not H1.has_edge("NB", "NA") G = nx.compose(G, G) - assert_edges_equal(G.edges(), H.edges()) + assert edges_equal(G.edges(), H.edges()) G2 = nx.union(G2, G2, rename=("", "copy")) assert sorted(G2.nodes()) == [ diff --git a/networkx/algorithms/operators/tests/test_product.py b/networkx/algorithms/operators/tests/test_product.py index 2737233b..f79c1a2e 100644 --- a/networkx/algorithms/operators/tests/test_product.py +++ b/networkx/algorithms/operators/tests/test_product.py @@ -1,6 +1,6 @@ import pytest import networkx as nx -from networkx.testing import assert_edges_equal +from networkx.utils import edges_equal def test_tensor_product_raises(): @@ -375,7 +375,7 @@ def test_graph_power(): G.add_edge(9, 2) H = nx.power(G, 2) - assert_edges_equal( + assert edges_equal( list(H.edges()), [ (0, 1), diff --git a/networkx/algorithms/tests/test_boundary.py b/networkx/algorithms/tests/test_boundary.py index 16ac8eab..6e7c1b74 100644 --- a/networkx/algorithms/tests/test_boundary.py +++ b/networkx/algorithms/tests/test_boundary.py @@ -3,7 +3,7 @@ from itertools import combinations import pytest import networkx as nx -from networkx.testing import assert_edges_equal +from networkx.utils import edges_equal from networkx import convert_node_labels_to_integers as cnlti @@ -117,11 +117,11 @@ class TestEdgeBoundary: assert ilen(nx.edge_boundary(K10, [4, 5, 6, 7])) == 24 assert ilen(nx.edge_boundary(K10, [3, 4, 5, 6, 7])) == 25 assert ilen(nx.edge_boundary(K10, [8, 9, 10])) == 21 - assert_edges_equal( + assert edges_equal( nx.edge_boundary(K10, [4, 5, 6], [9, 10]), [(4, 9), (4, 10), (5, 9), (5, 10), (6, 9), (6, 10)], ) - assert_edges_equal( + assert edges_equal( nx.edge_boundary(K10, [1, 2, 3], [3, 4, 5]), [(1, 3), (1, 4), (1, 5), (2, 3), (2, 4), (2, 5), (3, 4), (3, 5)], ) diff --git a/networkx/algorithms/tests/test_core.py b/networkx/algorithms/tests/test_core.py index a5392774..9caabfc1 100644 --- a/networkx/algorithms/tests/test_core.py +++ b/networkx/algorithms/tests/test_core.py @@ -1,5 +1,5 @@ import networkx as nx -from networkx.testing.utils import assert_nodes_equal +from networkx.utils import nodes_equal class TestCore: @@ -57,10 +57,10 @@ class TestCore: nodes_by_core = [ sorted([n for n in core if core[n] == val]) for val in range(4) ] - assert_nodes_equal(nodes_by_core[0], [21]) - assert_nodes_equal(nodes_by_core[1], [17, 18, 19, 20]) - assert_nodes_equal(nodes_by_core[2], [9, 10, 11, 12, 13, 14, 15, 16]) - assert_nodes_equal(nodes_by_core[3], [1, 2, 3, 4, 5, 6, 7, 8]) + assert nodes_equal(nodes_by_core[0], [21]) + assert nodes_equal(nodes_by_core[1], [17, 18, 19, 20]) + assert nodes_equal(nodes_by_core[2], [9, 10, 11, 12, 13, 14, 15, 16]) + assert nodes_equal(nodes_by_core[3], [1, 2, 3, 4, 5, 6, 7, 8]) def test_core_number(self): # smoke test real name @@ -71,9 +71,9 @@ class TestCore: nodes_by_core = [ sorted([n for n in core if core[n] == val]) for val in range(3) ] - assert_nodes_equal(nodes_by_core[0], [0]) - assert_nodes_equal(nodes_by_core[1], [1, 3]) - assert_nodes_equal(nodes_by_core[2], [2, 4, 5, 6]) + assert nodes_equal(nodes_by_core[0], [0]) + assert nodes_equal(nodes_by_core[1], [1, 3]) + assert nodes_equal(nodes_by_core[2], [2, 4, 5, 6]) def test_directed_find_cores(self): """core number had a bug for directed graphs found in issue #1959""" @@ -171,9 +171,9 @@ class TestCore: nodes_by_layer = [ sorted([n for n in layers if layers[n] == val]) for val in range(1, 7) ] - assert_nodes_equal(nodes_by_layer[0], [21]) - assert_nodes_equal(nodes_by_layer[1], [17, 18, 19, 20]) - assert_nodes_equal(nodes_by_layer[2], [10, 12, 13, 14, 15, 16]) - assert_nodes_equal(nodes_by_layer[3], [9, 11]) - assert_nodes_equal(nodes_by_layer[4], [1, 2, 4, 5, 6, 8]) - assert_nodes_equal(nodes_by_layer[5], [3, 7]) + assert nodes_equal(nodes_by_layer[0], [21]) + assert nodes_equal(nodes_by_layer[1], [17, 18, 19, 20]) + assert nodes_equal(nodes_by_layer[2], [10, 12, 13, 14, 15, 16]) + assert nodes_equal(nodes_by_layer[3], [9, 11]) + assert nodes_equal(nodes_by_layer[4], [1, 2, 4, 5, 6, 8]) + assert nodes_equal(nodes_by_layer[5], [3, 7]) diff --git a/networkx/algorithms/tests/test_dag.py b/networkx/algorithms/tests/test_dag.py index c0fac32c..1472866d 100644 --- a/networkx/algorithms/tests/test_dag.py +++ b/networkx/algorithms/tests/test_dag.py @@ -4,8 +4,7 @@ from collections import deque import pytest import networkx as nx -from networkx.testing.utils import assert_edges_equal -from networkx.utils import pairwise +from networkx.utils import edges_equal, pairwise # Recipe from the itertools documentation. def _consume(iterator): @@ -283,14 +282,14 @@ class TestDAG: def test_transitive_closure(self): G = nx.DiGraph([(1, 2), (2, 3), (3, 4)]) solution = [(1, 2), (1, 3), (1, 4), (2, 3), (2, 4), (3, 4)] - assert_edges_equal(nx.transitive_closure(G).edges(), solution) + assert edges_equal(nx.transitive_closure(G).edges(), solution) G = nx.DiGraph([(1, 2), (2, 3), (2, 4)]) solution = [(1, 2), (1, 3), (1, 4), (2, 3), (2, 4)] - assert_edges_equal(nx.transitive_closure(G).edges(), solution) + assert edges_equal(nx.transitive_closure(G).edges(), solution) G = nx.DiGraph([(1, 2), (2, 3), (3, 1)]) solution = [(1, 2), (2, 1), (2, 3), (3, 2), (1, 3), (3, 1)] soln = sorted(solution + [(n, n) for n in G]) - assert_edges_equal(sorted(nx.transitive_closure(G).edges()), soln) + assert edges_equal(sorted(nx.transitive_closure(G).edges()), soln) G = nx.Graph([(1, 2), (2, 3), (3, 4)]) pytest.raises(nx.NetworkXNotImplemented, nx.transitive_closure, G) @@ -310,35 +309,35 @@ class TestDAG: G = nx.DiGraph([(1, 2), (2, 3), (3, 4)]) solution = [(1, 2), (1, 3), (1, 4), (2, 3), (2, 4), (3, 4)] soln = sorted(solution + [(n, n) for n in G]) - assert_edges_equal(nx.transitive_closure(G).edges(), solution) - assert_edges_equal(nx.transitive_closure(G, False).edges(), solution) - assert_edges_equal(nx.transitive_closure(G, True).edges(), soln) - assert_edges_equal(nx.transitive_closure(G, None).edges(), solution) + assert edges_equal(nx.transitive_closure(G).edges(), solution) + assert edges_equal(nx.transitive_closure(G, False).edges(), solution) + assert edges_equal(nx.transitive_closure(G, True).edges(), soln) + assert edges_equal(nx.transitive_closure(G, None).edges(), solution) G = nx.DiGraph([(1, 2), (2, 3), (2, 4)]) solution = [(1, 2), (1, 3), (1, 4), (2, 3), (2, 4)] soln = sorted(solution + [(n, n) for n in G]) - assert_edges_equal(nx.transitive_closure(G).edges(), solution) - assert_edges_equal(nx.transitive_closure(G, False).edges(), solution) - assert_edges_equal(nx.transitive_closure(G, True).edges(), soln) - assert_edges_equal(nx.transitive_closure(G, None).edges(), solution) + assert edges_equal(nx.transitive_closure(G).edges(), solution) + assert edges_equal(nx.transitive_closure(G, False).edges(), solution) + assert edges_equal(nx.transitive_closure(G, True).edges(), soln) + assert edges_equal(nx.transitive_closure(G, None).edges(), solution) G = nx.DiGraph([(1, 2), (2, 3), (3, 1)]) solution = sorted([(1, 2), (2, 1), (2, 3), (3, 2), (1, 3), (3, 1)]) soln = sorted(solution + [(n, n) for n in G]) - assert_edges_equal(sorted(nx.transitive_closure(G).edges()), soln) - assert_edges_equal(sorted(nx.transitive_closure(G, False).edges()), soln) - assert_edges_equal(sorted(nx.transitive_closure(G, None).edges()), solution) - assert_edges_equal(sorted(nx.transitive_closure(G, True).edges()), soln) + assert edges_equal(sorted(nx.transitive_closure(G).edges()), soln) + assert edges_equal(sorted(nx.transitive_closure(G, False).edges()), soln) + assert edges_equal(sorted(nx.transitive_closure(G, None).edges()), solution) + assert edges_equal(sorted(nx.transitive_closure(G, True).edges()), soln) def test_transitive_closure_dag(self): G = nx.DiGraph([(1, 2), (2, 3), (3, 4)]) transitive_closure = nx.algorithms.dag.transitive_closure_dag solution = [(1, 2), (1, 3), (1, 4), (2, 3), (2, 4), (3, 4)] - assert_edges_equal(transitive_closure(G).edges(), solution) + assert edges_equal(transitive_closure(G).edges(), solution) G = nx.DiGraph([(1, 2), (2, 3), (2, 4)]) solution = [(1, 2), (1, 3), (1, 4), (2, 3), (2, 4)] - assert_edges_equal(transitive_closure(G).edges(), solution) + assert edges_equal(transitive_closure(G).edges(), solution) G = nx.Graph([(1, 2), (2, 3), (3, 4)]) pytest.raises(nx.NetworkXNotImplemented, transitive_closure, G) @@ -358,11 +357,11 @@ class TestDAG: G = nx.DiGraph([(1, 2), (1, 3), (1, 4), (2, 3), (2, 4), (3, 4)]) transitive_reduction = nx.algorithms.dag.transitive_reduction solution = [(1, 2), (2, 3), (3, 4)] - assert_edges_equal(transitive_reduction(G).edges(), solution) + assert edges_equal(transitive_reduction(G).edges(), solution) G = nx.DiGraph([(1, 2), (1, 3), (1, 4), (2, 3), (2, 4)]) transitive_reduction = nx.algorithms.dag.transitive_reduction solution = [(1, 2), (2, 3), (2, 4)] - assert_edges_equal(transitive_reduction(G).edges(), solution) + assert edges_equal(transitive_reduction(G).edges(), solution) G = nx.Graph([(1, 2), (2, 3), (3, 4)]) pytest.raises(nx.NetworkXNotImplemented, transitive_reduction, G) diff --git a/networkx/algorithms/tests/test_link_prediction.py b/networkx/algorithms/tests/test_link_prediction.py index 34b58c4c..bbb58299 100644 --- a/networkx/algorithms/tests/test_link_prediction.py +++ b/networkx/algorithms/tests/test_link_prediction.py @@ -13,7 +13,7 @@ def _test_func(G, ebunch, expected, predict_func, **kwargs): assert len(exp_dict) == len(res_dict) for p in exp_dict: - assert nx.testing.almost_equal(exp_dict[p], res_dict[p], places=7) + assert exp_dict[p] == pytest.approx(res_dict[p], abs=1e-7) class TestResourceAllocationIndex: diff --git a/networkx/algorithms/tests/test_matching.py b/networkx/algorithms/tests/test_matching.py index 5252e1cc..0487227f 100644 --- a/networkx/algorithms/tests/test_matching.py +++ b/networkx/algorithms/tests/test_matching.py @@ -4,7 +4,7 @@ import math import networkx as nx from networkx.algorithms.matching import matching_dict_to_set -from networkx.testing import assert_edges_equal +from networkx.utils import edges_equal class TestMaxWeightMatching: @@ -30,10 +30,10 @@ class TestMaxWeightMatching: """Single edge""" G = nx.Graph() G.add_edge(0, 1) - assert_edges_equal( + assert edges_equal( nx.max_weight_matching(G), matching_dict_to_set({0: 1, 1: 0}) ) - assert_edges_equal( + assert edges_equal( nx.min_weight_matching(G), matching_dict_to_set({0: 1, 1: 0}) ) @@ -42,11 +42,11 @@ class TestMaxWeightMatching: G = nx.Graph() G.add_edge("one", "two", weight=10) G.add_edge("two", "three", weight=11) - assert_edges_equal( + assert edges_equal( nx.max_weight_matching(G), matching_dict_to_set({"three": "two", "two": "three"}), ) - assert_edges_equal( + assert edges_equal( nx.min_weight_matching(G), matching_dict_to_set({"one": "two", "two": "one"}), ) @@ -57,16 +57,16 @@ class TestMaxWeightMatching: G.add_edge(1, 2, weight=5) G.add_edge(2, 3, weight=11) G.add_edge(3, 4, weight=5) - assert_edges_equal( + assert edges_equal( nx.max_weight_matching(G), matching_dict_to_set({2: 3, 3: 2}) ) - assert_edges_equal( + assert edges_equal( nx.max_weight_matching(G, 1), matching_dict_to_set({1: 2, 2: 1, 3: 4, 4: 3}) ) - assert_edges_equal( + assert edges_equal( nx.min_weight_matching(G), matching_dict_to_set({1: 2, 3: 4}) ) - assert_edges_equal( + assert edges_equal( nx.min_weight_matching(G, 1), matching_dict_to_set({1: 2, 3: 4}) ) @@ -75,11 +75,11 @@ class TestMaxWeightMatching: G = nx.Graph() G.add_edge("one", "two", weight=10, abcd=11) G.add_edge("two", "three", weight=11, abcd=10) - assert_edges_equal( + assert edges_equal( nx.max_weight_matching(G, weight="abcd"), matching_dict_to_set({"one": "two", "two": "one"}), ) - assert_edges_equal( + assert edges_equal( nx.min_weight_matching(G, weight="abcd"), matching_dict_to_set({"three": "two"}), ) @@ -91,10 +91,10 @@ class TestMaxWeightMatching: G.add_edge(2, 3, weight=math.exp(1)) G.add_edge(1, 3, weight=3.0) G.add_edge(1, 4, weight=math.sqrt(2.0)) - assert_edges_equal( + assert edges_equal( nx.max_weight_matching(G), matching_dict_to_set({1: 4, 2: 3, 3: 2, 4: 1}) ) - assert_edges_equal( + assert edges_equal( nx.min_weight_matching(G), matching_dict_to_set({1: 4, 2: 3, 3: 2, 4: 1}) ) @@ -106,16 +106,16 @@ class TestMaxWeightMatching: G.add_edge(2, 3, weight=1) G.add_edge(2, 4, weight=-1) G.add_edge(3, 4, weight=-6) - assert_edges_equal( + assert edges_equal( nx.max_weight_matching(G), matching_dict_to_set({1: 2, 2: 1}) ) - assert_edges_equal( + assert edges_equal( nx.max_weight_matching(G, 1), matching_dict_to_set({1: 3, 2: 4, 3: 1, 4: 2}) ) - assert_edges_equal( + assert edges_equal( nx.min_weight_matching(G), matching_dict_to_set({1: 2, 3: 4}) ) - assert_edges_equal( + assert edges_equal( nx.min_weight_matching(G, 1), matching_dict_to_set({1: 2, 3: 4}) ) @@ -124,13 +124,13 @@ class TestMaxWeightMatching: G = nx.Graph() G.add_weighted_edges_from([(1, 2, 8), (1, 3, 9), (2, 3, 10), (3, 4, 7)]) answer = matching_dict_to_set({1: 2, 2: 1, 3: 4, 4: 3}) - assert_edges_equal(nx.max_weight_matching(G), answer) - assert_edges_equal(nx.min_weight_matching(G), answer) + assert edges_equal(nx.max_weight_matching(G), answer) + assert edges_equal(nx.min_weight_matching(G), answer) G.add_weighted_edges_from([(1, 6, 5), (4, 5, 6)]) answer = matching_dict_to_set({1: 6, 2: 3, 3: 2, 4: 5, 5: 4, 6: 1}) - assert_edges_equal(nx.max_weight_matching(G), answer) - assert_edges_equal(nx.min_weight_matching(G), answer) + assert edges_equal(nx.max_weight_matching(G), answer) + assert edges_equal(nx.min_weight_matching(G), answer) def test_s_t_blossom(self): """Create S-blossom, relabel as T-blossom, use for augmentation:""" @@ -139,19 +139,19 @@ class TestMaxWeightMatching: [(1, 2, 9), (1, 3, 8), (2, 3, 10), (1, 4, 5), (4, 5, 4), (1, 6, 3)] ) answer = matching_dict_to_set({1: 6, 2: 3, 3: 2, 4: 5, 5: 4, 6: 1}) - assert_edges_equal(nx.max_weight_matching(G), answer) - assert_edges_equal(nx.min_weight_matching(G), answer) + assert edges_equal(nx.max_weight_matching(G), answer) + assert edges_equal(nx.min_weight_matching(G), answer) G.add_edge(4, 5, weight=3) G.add_edge(1, 6, weight=4) - assert_edges_equal(nx.max_weight_matching(G), answer) - assert_edges_equal(nx.min_weight_matching(G), answer) + assert edges_equal(nx.max_weight_matching(G), answer) + assert edges_equal(nx.min_weight_matching(G), answer) G.remove_edge(1, 6) G.add_edge(3, 6, weight=4) answer = matching_dict_to_set({1: 2, 2: 1, 3: 6, 4: 5, 5: 4, 6: 3}) - assert_edges_equal(nx.max_weight_matching(G), answer) - assert_edges_equal(nx.min_weight_matching(G), answer) + assert edges_equal(nx.max_weight_matching(G), answer) + assert edges_equal(nx.min_weight_matching(G), answer) def test_nested_s_blossom(self): """Create nested S-blossom, use for augmentation:""" @@ -192,8 +192,8 @@ class TestMaxWeightMatching: ] ) answer = matching_dict_to_set({1: 2, 2: 1, 3: 4, 4: 3, 5: 6, 6: 5, 7: 8, 8: 7}) - assert_edges_equal(nx.max_weight_matching(G), answer) - assert_edges_equal(nx.min_weight_matching(G), answer) + assert edges_equal(nx.max_weight_matching(G), answer) + assert edges_equal(nx.min_weight_matching(G), answer) def test_nested_s_blossom_expand(self): """Create nested S-blossom, augment, expand recursively:""" @@ -213,8 +213,8 @@ class TestMaxWeightMatching: ] ) answer = matching_dict_to_set({1: 2, 2: 1, 3: 5, 4: 6, 5: 3, 6: 4, 7: 8, 8: 7}) - assert_edges_equal(nx.max_weight_matching(G), answer) - assert_edges_equal(nx.min_weight_matching(G), answer) + assert edges_equal(nx.max_weight_matching(G), answer) + assert edges_equal(nx.min_weight_matching(G), answer) def test_s_blossom_relabel_expand(self): """Create S-blossom, relabel as T, expand:""" @@ -232,8 +232,8 @@ class TestMaxWeightMatching: ] ) answer = matching_dict_to_set({1: 6, 2: 3, 3: 2, 4: 8, 5: 7, 6: 1, 7: 5, 8: 4}) - assert_edges_equal(nx.max_weight_matching(G), answer) - assert_edges_equal(nx.min_weight_matching(G), answer) + assert edges_equal(nx.max_weight_matching(G), answer) + assert edges_equal(nx.min_weight_matching(G), answer) def test_nested_s_blossom_relabel_expand(self): """Create nested S-blossom, relabel as T, expand:""" @@ -252,8 +252,8 @@ class TestMaxWeightMatching: ] ) answer = matching_dict_to_set({1: 8, 2: 3, 3: 2, 4: 7, 5: 6, 6: 5, 7: 4, 8: 1}) - assert_edges_equal(nx.max_weight_matching(G), answer) - assert_edges_equal(nx.min_weight_matching(G), answer) + assert edges_equal(nx.max_weight_matching(G), answer) + assert edges_equal(nx.min_weight_matching(G), answer) def test_nasty_blossom1(self): """Create blossom, relabel as T in more than one way, expand, @@ -276,8 +276,8 @@ class TestMaxWeightMatching: ) ansdict = {1: 6, 2: 3, 3: 2, 4: 8, 5: 7, 6: 1, 7: 5, 8: 4, 9: 10, 10: 9} answer = matching_dict_to_set(ansdict) - assert_edges_equal(nx.max_weight_matching(G), answer) - assert_edges_equal(nx.min_weight_matching(G), answer) + assert edges_equal(nx.max_weight_matching(G), answer) + assert edges_equal(nx.min_weight_matching(G), answer) def test_nasty_blossom2(self): """Again but slightly different:""" @@ -298,8 +298,8 @@ class TestMaxWeightMatching: ) ans = {1: 6, 2: 3, 3: 2, 4: 8, 5: 7, 6: 1, 7: 5, 8: 4, 9: 10, 10: 9} answer = matching_dict_to_set(ans) - assert_edges_equal(nx.max_weight_matching(G), answer) - assert_edges_equal(nx.min_weight_matching(G), answer) + assert edges_equal(nx.max_weight_matching(G), answer) + assert edges_equal(nx.min_weight_matching(G), answer) def test_nasty_blossom_least_slack(self): """Create blossom, relabel as T, expand such that a new @@ -322,8 +322,8 @@ class TestMaxWeightMatching: ) ans = {1: 6, 2: 3, 3: 2, 4: 8, 5: 7, 6: 1, 7: 5, 8: 4, 9: 10, 10: 9} answer = matching_dict_to_set(ans) - assert_edges_equal(nx.max_weight_matching(G), answer) - assert_edges_equal(nx.min_weight_matching(G), answer) + assert edges_equal(nx.max_weight_matching(G), answer) + assert edges_equal(nx.min_weight_matching(G), answer) def test_nasty_blossom_augmenting(self): """Create nested blossom, relabel as T in more than one way""" @@ -362,8 +362,8 @@ class TestMaxWeightMatching: 12: 11, } answer = matching_dict_to_set(ans) - assert_edges_equal(nx.max_weight_matching(G), answer) - assert_edges_equal(nx.min_weight_matching(G), answer) + assert edges_equal(nx.max_weight_matching(G), answer) + assert edges_equal(nx.min_weight_matching(G), answer) def test_nasty_blossom_expand_recursively(self): """Create nested S-blossom, relabel as S, expand recursively:""" @@ -385,8 +385,8 @@ class TestMaxWeightMatching: ) ans = {1: 2, 2: 1, 3: 5, 4: 9, 5: 3, 6: 7, 7: 6, 8: 10, 9: 4, 10: 8} answer = matching_dict_to_set(ans) - assert_edges_equal(nx.max_weight_matching(G), answer) - assert_edges_equal(nx.min_weight_matching(G), answer) + assert edges_equal(nx.max_weight_matching(G), answer) + assert edges_equal(nx.min_weight_matching(G), answer) def test_wrong_graph_type(self): error = nx.NetworkXNotImplemented diff --git a/networkx/algorithms/tree/tests/test_coding.py b/networkx/algorithms/tree/tests/test_coding.py index 845ad720..42568aff 100644 --- a/networkx/algorithms/tree/tests/test_coding.py +++ b/networkx/algorithms/tree/tests/test_coding.py @@ -3,8 +3,7 @@ from itertools import product import pytest import networkx as nx -from networkx.testing import assert_nodes_equal -from networkx.testing import assert_edges_equal +from networkx.utils import nodes_equal, edges_equal class TestPruferSequence: @@ -46,24 +45,24 @@ class TestPruferSequence: # Example from Wikipedia. sequence = [3, 3, 3, 4] tree = nx.from_prufer_sequence(sequence) - assert_nodes_equal(list(tree), list(range(6))) + assert nodes_equal(list(tree), list(range(6))) edges = [(0, 3), (1, 3), (2, 3), (3, 4), (4, 5)] - assert_edges_equal(list(tree.edges()), edges) + assert edges_equal(list(tree.edges()), edges) def test_decoding2(self): # Example from "An Optimal Algorithm for Prufer Codes". sequence = [2, 4, 0, 1, 3, 3] tree = nx.from_prufer_sequence(sequence) - assert_nodes_equal(list(tree), list(range(8))) + assert nodes_equal(list(tree), list(range(8))) edges = [(0, 1), (0, 4), (1, 3), (2, 4), (2, 5), (3, 6), (3, 7)] - assert_edges_equal(list(tree.edges()), edges) + assert edges_equal(list(tree.edges()), edges) def test_inverse(self): """Tests that the encoding and decoding functions are inverses.""" for T in nx.nonisomorphic_trees(4): T2 = nx.from_prufer_sequence(nx.to_prufer_sequence(T)) - assert_nodes_equal(list(T), list(T2)) - assert_edges_equal(list(T.edges()), list(T2.edges())) + assert nodes_equal(list(T), list(T2)) + assert edges_equal(list(T.edges()), list(T2.edges())) for seq in product(range(4), repeat=2): seq2 = nx.to_prufer_sequence(nx.from_prufer_sequence(seq)) @@ -87,7 +86,7 @@ class TestNestedTuple: T = nx.full_rary_tree(2, 2 ** 3 - 1) expected = (((), ()), ((), ())) actual = nx.to_nested_tuple(T, 0) - assert_nodes_equal(expected, actual) + assert nodes_equal(expected, actual) def test_canonical_form(self): T = nx.Graph() @@ -109,5 +108,5 @@ class TestNestedTuple: balanced = (((), ()), ((), ())) T = nx.from_nested_tuple(balanced, sensible_relabeling=True) edges = [(0, 1), (0, 2), (1, 3), (1, 4), (2, 5), (2, 6)] - assert_nodes_equal(list(T), list(range(2 ** 3 - 1))) - assert_edges_equal(list(T.edges()), edges) + assert nodes_equal(list(T), list(range(2 ** 3 - 1))) + assert edges_equal(list(T.edges()), edges) diff --git a/networkx/algorithms/tree/tests/test_mst.py b/networkx/algorithms/tree/tests/test_mst.py index cc042e05..5253a29f 100644 --- a/networkx/algorithms/tree/tests/test_mst.py +++ b/networkx/algorithms/tree/tests/test_mst.py @@ -3,7 +3,7 @@ import pytest import networkx as nx -from networkx.testing import assert_nodes_equal, assert_edges_equal +from networkx.utils import nodes_equal, edges_equal def test_unknown_algorithm(): @@ -69,14 +69,14 @@ class MinimumSpanningTreeTestBase: # Edges from the spanning edges functions don't come in sorted # orientation, so we need to sort each edge individually. actual = sorted((min(u, v), max(u, v), d) for u, v, d in edges) - assert_edges_equal(actual, self.minimum_spanning_edgelist) + assert edges_equal(actual, self.minimum_spanning_edgelist) def test_maximum_edges(self): edges = nx.maximum_spanning_edges(self.G, algorithm=self.algo) # Edges from the spanning edges functions don't come in sorted # orientation, so we need to sort each edge individually. actual = sorted((min(u, v), max(u, v), d) for u, v, d in edges) - assert_edges_equal(actual, self.maximum_spanning_edgelist) + assert edges_equal(actual, self.maximum_spanning_edgelist) def test_without_data(self): edges = nx.minimum_spanning_edges(self.G, algorithm=self.algo, data=False) @@ -84,7 +84,7 @@ class MinimumSpanningTreeTestBase: # orientation, so we need to sort each edge individually. actual = sorted((min(u, v), max(u, v)) for u, v in edges) expected = [(u, v) for u, v, d in self.minimum_spanning_edgelist] - assert_edges_equal(actual, expected) + assert edges_equal(actual, expected) def test_nan_weights(self): # Edge weights NaN never appear in the spanning tree. see #2164 @@ -95,7 +95,7 @@ class MinimumSpanningTreeTestBase: ) actual = sorted((min(u, v), max(u, v)) for u, v in edges) expected = [(u, v) for u, v, d in self.minimum_spanning_edgelist] - assert_edges_equal(actual, expected) + assert edges_equal(actual, expected) # Now test for raising exception edges = nx.minimum_spanning_edges( G, algorithm=self.algo, data=False, ignore_nan=False @@ -130,7 +130,7 @@ class MinimumSpanningTreeTestBase: ) actual = sorted((min(u, v), max(u, v)) for u, v in edges) shift = [(u + 1, v + 1) for u, v, d in self.minimum_spanning_edgelist] - assert_edges_equal(actual, shift) + assert edges_equal(actual, shift) def test_isolated_node(self): # now try again with an isolated node @@ -155,28 +155,28 @@ class MinimumSpanningTreeTestBase: ) actual = sorted((min(u, v), max(u, v)) for u, v in edges) shift = [(u + 1, v + 1) for u, v, d in self.minimum_spanning_edgelist] - assert_edges_equal(actual, shift) + assert edges_equal(actual, shift) def test_minimum_tree(self): T = nx.minimum_spanning_tree(self.G, algorithm=self.algo) actual = sorted(T.edges(data=True)) - assert_edges_equal(actual, self.minimum_spanning_edgelist) + assert edges_equal(actual, self.minimum_spanning_edgelist) def test_maximum_tree(self): T = nx.maximum_spanning_tree(self.G, algorithm=self.algo) actual = sorted(T.edges(data=True)) - assert_edges_equal(actual, self.maximum_spanning_edgelist) + assert edges_equal(actual, self.maximum_spanning_edgelist) def test_disconnected(self): G = nx.Graph([(0, 1, dict(weight=1)), (2, 3, dict(weight=2))]) T = nx.minimum_spanning_tree(G, algorithm=self.algo) - assert_nodes_equal(list(T), list(range(4))) - assert_edges_equal(list(T.edges()), [(0, 1), (2, 3)]) + assert nodes_equal(list(T), list(range(4))) + assert edges_equal(list(T.edges()), [(0, 1), (2, 3)]) def test_empty_graph(self): G = nx.empty_graph(3) T = nx.minimum_spanning_tree(G, algorithm=self.algo) - assert_nodes_equal(sorted(T), list(range(3))) + assert nodes_equal(sorted(T), list(range(3))) assert T.number_of_edges() == 0 def test_attributes(self): @@ -187,7 +187,7 @@ class MinimumSpanningTreeTestBase: G.graph["foo"] = "bar" T = nx.minimum_spanning_tree(G, algorithm=self.algo) assert T.graph == G.graph - assert_nodes_equal(T, G) + assert nodes_equal(T, G) for u, v in T.edges(): assert T.adj[u][v] == G.adj[u][v] @@ -198,11 +198,11 @@ class MinimumSpanningTreeTestBase: G.add_edge(1, 2, weight=1, distance=1) G.add_node(3) T = nx.minimum_spanning_tree(G, algorithm=self.algo, weight="distance") - assert_nodes_equal(sorted(T), list(range(4))) - assert_edges_equal(sorted(T.edges()), [(0, 2), (1, 2)]) + assert nodes_equal(sorted(T), list(range(4))) + assert edges_equal(sorted(T.edges()), [(0, 2), (1, 2)]) T = nx.maximum_spanning_tree(G, algorithm=self.algo, weight="distance") - assert_nodes_equal(sorted(T), list(range(4))) - assert_edges_equal(sorted(T.edges()), [(0, 1), (0, 2)]) + assert nodes_equal(sorted(T), list(range(4))) + assert edges_equal(sorted(T.edges()), [(0, 1), (0, 2)]) class TestBoruvka(MinimumSpanningTreeTestBase): @@ -222,7 +222,7 @@ class TestBoruvka(MinimumSpanningTreeTestBase): # Edges from the spanning edges functions don't come in sorted # orientation, so we need to sort each edge individually. actual = sorted((min(u, v), max(u, v), d) for u, v, d in edges) - assert_edges_equal(actual, self.minimum_spanning_edgelist) + assert edges_equal(actual, self.minimum_spanning_edgelist) class MultigraphMSTTestBase(MinimumSpanningTreeTestBase): @@ -238,7 +238,7 @@ class MultigraphMSTTestBase(MinimumSpanningTreeTestBase): G.add_edge(0, 1, key="b", weight=1) min_edges = nx.minimum_spanning_edges mst_edges = min_edges(G, algorithm=self.algo, data=False) - assert_edges_equal([(0, 1, "b")], list(mst_edges)) + assert edges_equal([(0, 1, "b")], list(mst_edges)) def test_multigraph_keys_max(self): """Tests that the maximum spanning edges of a multigraph @@ -250,7 +250,7 @@ class MultigraphMSTTestBase(MinimumSpanningTreeTestBase): G.add_edge(0, 1, key="b", weight=1) max_edges = nx.maximum_spanning_edges mst_edges = max_edges(G, algorithm=self.algo, data=False) - assert_edges_equal([(0, 1, "a")], list(mst_edges)) + assert edges_equal([(0, 1, "a")], list(mst_edges)) class TestKruskal(MultigraphMSTTestBase): @@ -275,11 +275,11 @@ class TestPrim(MultigraphMSTTestBase): G.add_edge(0, 1, key="a", weight=2) G.add_edge(0, 1, key="b", weight=1) T = nx.minimum_spanning_tree(G) - assert_edges_equal([(0, 1, 1)], list(T.edges(data="weight"))) + assert edges_equal([(0, 1, 1)], list(T.edges(data="weight"))) def test_multigraph_keys_tree_max(self): G = nx.MultiGraph() G.add_edge(0, 1, key="a", weight=2) G.add_edge(0, 1, key="b", weight=1) T = nx.maximum_spanning_tree(G) - assert_edges_equal([(0, 1, 2)], list(T.edges(data="weight"))) + assert edges_equal([(0, 1, 2)], list(T.edges(data="weight"))) diff --git a/networkx/algorithms/tree/tests/test_operations.py b/networkx/algorithms/tree/tests/test_operations.py index 21b2afde..3f580dde 100644 --- a/networkx/algorithms/tree/tests/test_operations.py +++ b/networkx/algorithms/tree/tests/test_operations.py @@ -3,8 +3,7 @@ """ import networkx as nx -from networkx.testing import assert_nodes_equal -from networkx.testing import assert_edges_equal +from networkx.utils import nodes_equal, edges_equal class TestJoin: @@ -27,8 +26,8 @@ class TestJoin: T = nx.empty_graph(1) actual = nx.join([(T, 0)]) expected = nx.path_graph(2) - assert_nodes_equal(list(expected), list(actual)) - assert_edges_equal(list(expected.edges()), list(actual.edges())) + assert nodes_equal(list(expected), list(actual)) + assert edges_equal(list(expected.edges()), list(actual.edges())) def test_basic(self): """Tests for joining multiple subtrees at a root node.""" diff --git a/networkx/classes/tests/historical_tests.py b/networkx/classes/tests/historical_tests.py index f41f94da..daa5dbaf 100644 --- a/networkx/classes/tests/historical_tests.py +++ b/networkx/classes/tests/historical_tests.py @@ -2,7 +2,7 @@ import pytest import networkx as nx from networkx import convert_node_labels_to_integers as cnlti -from networkx.testing import assert_edges_equal, assert_nodes_equal +from networkx.utils import nodes_equal, edges_equal class HistoricalTests: @@ -258,22 +258,22 @@ class HistoricalTests: else: elist = [("A", "B"), ("A", "C"), ("B", "C"), ("B", "D")] # nbunch can be a list - assert_edges_equal(list(G.edges(["A", "B"])), elist) + assert edges_equal(list(G.edges(["A", "B"])), elist) # nbunch can be a set - assert_edges_equal(G.edges({"A", "B"}), elist) + assert edges_equal(G.edges({"A", "B"}), elist) # nbunch can be a graph G1 = self.G() G1.add_nodes_from("AB") - assert_edges_equal(G.edges(G1), elist) + assert edges_equal(G.edges(G1), elist) # nbunch can be a dict with nodes as keys ndict = {"A": "thing1", "B": "thing2"} - assert_edges_equal(G.edges(ndict), elist) + assert edges_equal(G.edges(ndict), elist) # nbunch can be a single node - assert_edges_equal(list(G.edges("A")), [("A", "B"), ("A", "C")]) - assert_nodes_equal(sorted(G), ["A", "B", "C", "D"]) + assert edges_equal(list(G.edges("A")), [("A", "B"), ("A", "C")]) + assert nodes_equal(sorted(G), ["A", "B", "C", "D"]) # nbunch can be nothing (whole graph) - assert_edges_equal( + assert edges_equal( list(G.edges()), [("A", "B"), ("A", "C"), ("B", "D"), ("C", "B"), ("C", "D")], ) @@ -330,8 +330,8 @@ class HistoricalTests: G = self.G() G.add_edges_from([("A", "B"), ("A", "C"), ("B", "D"), ("C", "B"), ("C", "D")]) SG = G.subgraph(["A", "B", "D"]) - assert_nodes_equal(list(SG), ["A", "B", "D"]) - assert_edges_equal(list(SG.edges()), [("A", "B"), ("B", "D")]) + assert nodes_equal(list(SG), ["A", "B", "D"]) + assert edges_equal(list(SG.edges()), [("A", "B"), ("B", "D")]) def test_to_directed(self): G = self.G() @@ -400,7 +400,7 @@ class HistoricalTests: G.add_edges_from([("A", "B"), ("A", "C"), ("B", "D"), ("C", "B"), ("C", "D")]) G.add_nodes_from("GJK") assert sorted(G.nodes()) == ["A", "B", "C", "D", "G", "J", "K"] - assert_edges_equal( + assert edges_equal( G.edges(), [("A", "B"), ("A", "C"), ("B", "D"), ("C", "B"), ("C", "D")] ) diff --git a/networkx/classes/tests/test_digraph.py b/networkx/classes/tests/test_digraph.py index 76702827..0eb12079 100644 --- a/networkx/classes/tests/test_digraph.py +++ b/networkx/classes/tests/test_digraph.py @@ -1,7 +1,7 @@ import pytest import networkx as nx -from networkx.testing import assert_nodes_equal +from networkx.utils import nodes_equal from .test_graph import BaseGraphTester, BaseAttrGraphTester from .test_graph import TestGraph as _TestGraph from .test_graph import TestEdgeSubgraph as _TestGraphEdgeSubgraph @@ -128,7 +128,7 @@ class BaseDiGraphTester(BaseGraphTester): y = Foo() G = nx.DiGraph() G.add_edge(x, y) - assert_nodes_equal(G.nodes(), G.reverse().nodes()) + assert nodes_equal(G.nodes(), G.reverse().nodes()) assert [(y, x)] == list(G.reverse().edges()) diff --git a/networkx/classes/tests/test_function.py b/networkx/classes/tests/test_function.py index 9723f434..5c3fbe95 100644 --- a/networkx/classes/tests/test_function.py +++ b/networkx/classes/tests/test_function.py @@ -1,7 +1,7 @@ import random import pytest import networkx as nx -from networkx.testing.utils import assert_edges_equal, assert_nodes_equal +from networkx.utils import nodes_equal, edges_equal class TestFunction: @@ -17,13 +17,13 @@ class TestFunction: self.DGedges = [(0, 1), (0, 2), (0, 3), (1, 0), (1, 1), (1, 2)] def test_nodes(self): - assert_nodes_equal(self.G.nodes(), list(nx.nodes(self.G))) - assert_nodes_equal(self.DG.nodes(), list(nx.nodes(self.DG))) + assert nodes_equal(self.G.nodes(), list(nx.nodes(self.G))) + assert nodes_equal(self.DG.nodes(), list(nx.nodes(self.DG))) def test_edges(self): - assert_edges_equal(self.G.edges(), list(nx.edges(self.G))) + assert edges_equal(self.G.edges(), list(nx.edges(self.G))) assert sorted(self.DG.edges()) == sorted(nx.edges(self.DG)) - assert_edges_equal( + assert edges_equal( self.G.edges(nbunch=[0, 1, 3]), list(nx.edges(self.G, nbunch=[0, 1, 3])) ) assert sorted(self.DG.edges(nbunch=[0, 1, 3])) == sorted( @@ -31,15 +31,15 @@ class TestFunction: ) def test_degree(self): - assert_edges_equal(self.G.degree(), list(nx.degree(self.G))) + assert edges_equal(self.G.degree(), list(nx.degree(self.G))) assert sorted(self.DG.degree()) == sorted(nx.degree(self.DG)) - assert_edges_equal( + assert edges_equal( self.G.degree(nbunch=[0, 1]), list(nx.degree(self.G, nbunch=[0, 1])) ) assert sorted(self.DG.degree(nbunch=[0, 1])) == sorted( nx.degree(self.DG, nbunch=[0, 1]) ) - assert_edges_equal( + assert edges_equal( self.G.degree(weight="weight"), list(nx.degree(self.G, weight="weight")) ) assert sorted(self.DG.degree(weight="weight")) == sorted( @@ -66,11 +66,11 @@ class TestFunction: G = self.G.copy() nlist = [12, 13, 14, 15] nx.add_star(G, nlist) - assert_edges_equal(G.edges(nlist), [(12, 13), (12, 14), (12, 15)]) + assert edges_equal(G.edges(nlist), [(12, 13), (12, 14), (12, 15)]) G = self.G.copy() nx.add_star(G, nlist, weight=2.0) - assert_edges_equal( + assert edges_equal( G.edges(nlist, data=True), [ (12, 13, {"weight": 2.0}), @@ -82,22 +82,22 @@ class TestFunction: G = self.G.copy() nlist = [12] nx.add_star(G, nlist) - assert_nodes_equal(G, list(self.G) + nlist) + assert nodes_equal(G, list(self.G) + nlist) G = self.G.copy() nlist = [] nx.add_star(G, nlist) - assert_nodes_equal(G.nodes, self.Gnodes) - assert_edges_equal(G.edges, self.G.edges) + assert nodes_equal(G.nodes, self.Gnodes) + assert edges_equal(G.edges, self.G.edges) def test_add_path(self): G = self.G.copy() nlist = [12, 13, 14, 15] nx.add_path(G, nlist) - assert_edges_equal(G.edges(nlist), [(12, 13), (13, 14), (14, 15)]) + assert edges_equal(G.edges(nlist), [(12, 13), (13, 14), (14, 15)]) G = self.G.copy() nx.add_path(G, nlist, weight=2.0) - assert_edges_equal( + assert edges_equal( G.edges(nlist, data=True), [ (12, 13, {"weight": 2.0}), @@ -109,38 +109,38 @@ class TestFunction: G = self.G.copy() nlist = [None] nx.add_path(G, nlist) - assert_edges_equal(G.edges(nlist), []) - assert_nodes_equal(G, list(self.G) + [None]) + assert edges_equal(G.edges(nlist), []) + assert nodes_equal(G, list(self.G) + [None]) G = self.G.copy() nlist = iter([None]) nx.add_path(G, nlist) - assert_edges_equal(G.edges([None]), []) - assert_nodes_equal(G, list(self.G) + [None]) + assert edges_equal(G.edges([None]), []) + assert nodes_equal(G, list(self.G) + [None]) G = self.G.copy() nlist = [12] nx.add_path(G, nlist) - assert_edges_equal(G.edges(nlist), []) - assert_nodes_equal(G, list(self.G) + [12]) + assert edges_equal(G.edges(nlist), []) + assert nodes_equal(G, list(self.G) + [12]) G = self.G.copy() nlist = iter([12]) nx.add_path(G, nlist) - assert_edges_equal(G.edges([12]), []) - assert_nodes_equal(G, list(self.G) + [12]) + assert edges_equal(G.edges([12]), []) + assert nodes_equal(G, list(self.G) + [12]) G = self.G.copy() nlist = [] nx.add_path(G, nlist) - assert_edges_equal(G.edges, self.G.edges) - assert_nodes_equal(G, list(self.G)) + assert edges_equal(G.edges, self.G.edges) + assert nodes_equal(G, list(self.G)) G = self.G.copy() nlist = iter([]) nx.add_path(G, nlist) - assert_edges_equal(G.edges, self.G.edges) - assert_nodes_equal(G, list(self.G)) + assert edges_equal(G.edges, self.G.edges) + assert nodes_equal(G, list(self.G)) def test_add_cycle(self): G = self.G.copy() @@ -172,13 +172,13 @@ class TestFunction: G = self.G.copy() nlist = [12] nx.add_cycle(G, nlist) - assert_nodes_equal(G, list(self.G) + nlist) + assert nodes_equal(G, list(self.G) + nlist) G = self.G.copy() nlist = [] nx.add_cycle(G, nlist) - assert_nodes_equal(G.nodes, self.Gnodes) - assert_edges_equal(G.edges, self.G.edges) + assert nodes_equal(G.nodes, self.Gnodes) + assert edges_equal(G.edges, self.G.edges) def test_subgraph(self): assert ( @@ -212,12 +212,12 @@ class TestFunction: def test_create_empty_copy(self): G = nx.create_empty_copy(self.G, with_data=False) - assert_nodes_equal(G, list(self.G)) + assert nodes_equal(G, list(self.G)) assert G.graph == {} assert G._node == {}.fromkeys(self.G.nodes(), {}) assert G._adj == {}.fromkeys(self.G.nodes(), {}) G = nx.create_empty_copy(self.G) - assert_nodes_equal(G, list(self.G)) + assert nodes_equal(G, list(self.G)) assert G.graph == self.G.graph assert G._node == self.G._node assert G._adj == {}.fromkeys(self.G.nodes(), {}) @@ -684,9 +684,9 @@ def test_is_empty(): def test_selfloops(graph_type): G = nx.complete_graph(3, create_using=graph_type) G.add_edge(0, 0) - assert_nodes_equal(nx.nodes_with_selfloops(G), [0]) - assert_edges_equal(nx.selfloop_edges(G), [(0, 0)]) - assert_edges_equal(nx.selfloop_edges(G, data=True), [(0, 0, {})]) + assert nodes_equal(nx.nodes_with_selfloops(G), [0]) + assert edges_equal(nx.selfloop_edges(G), [(0, 0)]) + assert edges_equal(nx.selfloop_edges(G, data=True), [(0, 0, {})]) assert nx.number_of_selfloops(G) == 1 @@ -697,17 +697,17 @@ def test_selfloop_edges_attr(graph_type): G = nx.complete_graph(3, create_using=graph_type) G.add_edge(0, 0) G.add_edge(1, 1, weight=2) - assert_edges_equal( + assert edges_equal( nx.selfloop_edges(G, data=True), [(0, 0, {}), (1, 1, {"weight": 2})] ) - assert_edges_equal(nx.selfloop_edges(G, data="weight"), [(0, 0, None), (1, 1, 2)]) + assert edges_equal(nx.selfloop_edges(G, data="weight"), [(0, 0, None), (1, 1, 2)]) def test_selfloop_edges_multi_with_data_and_keys(): G = nx.complete_graph(3, create_using=nx.MultiGraph) G.add_edge(0, 0, weight=10) G.add_edge(0, 0, weight=100) - assert_edges_equal( + assert edges_equal( nx.selfloop_edges(G, data="weight", keys=True), [(0, 0, 0, 10), (0, 0, 1, 100)], ) diff --git a/networkx/classes/tests/test_graph.py b/networkx/classes/tests/test_graph.py index 476f5e14..9b31cd5f 100644 --- a/networkx/classes/tests/test_graph.py +++ b/networkx/classes/tests/test_graph.py @@ -1,15 +1,10 @@ import pickle import gc import platform +import pytest import networkx as nx -from networkx.testing.utils import ( - assert_graphs_equal, - assert_edges_equal, - assert_nodes_equal, -) - -import pytest +from networkx.utils import nodes_equal, edges_equal, graphs_equal class BaseGraphTester: @@ -82,9 +77,9 @@ class BaseGraphTester: def test_edges(self): G = self.K3 - assert_edges_equal(G.edges(), [(0, 1), (0, 2), (1, 2)]) - assert_edges_equal(G.edges(0), [(0, 1), (0, 2)]) - assert_edges_equal(G.edges([0, 1]), [(0, 1), (0, 2), (1, 2)]) + assert edges_equal(G.edges(), [(0, 1), (0, 2), (1, 2)]) + assert edges_equal(G.edges(0), [(0, 1), (0, 2)]) + assert edges_equal(G.edges([0, 1]), [(0, 1), (0, 2), (1, 2)]) with pytest.raises(nx.NetworkXError): G.edges(-1) @@ -103,13 +98,13 @@ class BaseGraphTester: def test_nbunch_iter(self): G = self.K3 - assert_nodes_equal(G.nbunch_iter(), self.k3nodes) # all nodes - assert_nodes_equal(G.nbunch_iter(0), [0]) # single node - assert_nodes_equal(G.nbunch_iter([0, 1]), [0, 1]) # sequence + assert nodes_equal(G.nbunch_iter(), self.k3nodes) # all nodes + assert nodes_equal(G.nbunch_iter(0), [0]) # single node + assert nodes_equal(G.nbunch_iter([0, 1]), [0, 1]) # sequence # sequence with none in graph - assert_nodes_equal(G.nbunch_iter([-1]), []) + assert nodes_equal(G.nbunch_iter([-1]), []) # string sequence with none in graph - assert_nodes_equal(G.nbunch_iter("foo"), []) + assert nodes_equal(G.nbunch_iter("foo"), []) # node not in graph doesn't get caught upon creation of iterator bunch = G.nbunch_iter(-1) # but gets caught when iterator used @@ -146,8 +141,8 @@ class BaseGraphTester: def test_selfloops(self): G = self.K3.copy() G.add_edge(0, 0) - assert_nodes_equal(nx.nodes_with_selfloops(G), [0]) - assert_edges_equal(nx.selfloop_edges(G), [(0, 0)]) + assert nodes_equal(nx.nodes_with_selfloops(G), [0]) + assert edges_equal(nx.selfloop_edges(G), [(0, 0)]) assert nx.number_of_selfloops(G) == 1 G.remove_edge(0, 0) G.add_edge(0, 0) @@ -169,12 +164,12 @@ class BaseAttrGraphTester(BaseGraphTester): assert sorted(d for n, d in G.degree(weight="weight")) == [2, 3, 5] assert dict(G.degree(weight="weight")) == {1: 2, 2: 5, 3: 3} assert G.degree(1, weight="weight") == 2 - assert_nodes_equal((G.degree([1], weight="weight")), [(1, 2)]) + assert nodes_equal((G.degree([1], weight="weight")), [(1, 2)]) - assert_nodes_equal((d for n, d in G.degree(weight="other")), [3, 7, 4]) + assert nodes_equal((d for n, d in G.degree(weight="other")), [3, 7, 4]) assert dict(G.degree(weight="other")) == {1: 3, 2: 7, 3: 4} assert G.degree(1, weight="other") == 3 - assert_edges_equal((G.degree([1], weight="other")), [(1, 3)]) + assert edges_equal((G.degree([1], weight="other")), [(1, 3)]) def add_attributes(self, G): G.graph["foo"] = [] @@ -354,12 +349,12 @@ class BaseAttrGraphTester(BaseGraphTester): def test_node_attr(self): G = self.K3.copy() G.add_node(1, foo="bar") - assert_nodes_equal(G.nodes(), [0, 1, 2]) - assert_nodes_equal(G.nodes(data=True), [(0, {}), (1, {"foo": "bar"}), (2, {})]) + assert nodes_equal(G.nodes(), [0, 1, 2]) + assert nodes_equal(G.nodes(data=True), [(0, {}), (1, {"foo": "bar"}), (2, {})]) G.nodes[1]["foo"] = "baz" - assert_nodes_equal(G.nodes(data=True), [(0, {}), (1, {"foo": "baz"}), (2, {})]) - assert_nodes_equal(G.nodes(data="foo"), [(0, None), (1, "baz"), (2, None)]) - assert_nodes_equal( + assert nodes_equal(G.nodes(data=True), [(0, {}), (1, {"foo": "baz"}), (2, {})]) + assert nodes_equal(G.nodes(data="foo"), [(0, None), (1, "baz"), (2, None)]) + assert nodes_equal( G.nodes(data="foo", default="bar"), [(0, "bar"), (1, "baz"), (2, "bar")] ) @@ -367,34 +362,34 @@ class BaseAttrGraphTester(BaseGraphTester): G = self.K3.copy() a = {"foo": "bar"} G.add_node(3, **a) - assert_nodes_equal(G.nodes(), [0, 1, 2, 3]) - assert_nodes_equal( + assert nodes_equal(G.nodes(), [0, 1, 2, 3]) + assert nodes_equal( G.nodes(data=True), [(0, {}), (1, {}), (2, {}), (3, {"foo": "bar"})] ) def test_edge_lookup(self): G = self.Graph() G.add_edge(1, 2, foo="bar") - assert_edges_equal(G.edges[1, 2], {"foo": "bar"}) + assert edges_equal(G.edges[1, 2], {"foo": "bar"}) def test_edge_attr(self): G = self.Graph() G.add_edge(1, 2, foo="bar") - assert_edges_equal(G.edges(data=True), [(1, 2, {"foo": "bar"})]) - assert_edges_equal(G.edges(data="foo"), [(1, 2, "bar")]) + assert edges_equal(G.edges(data=True), [(1, 2, {"foo": "bar"})]) + assert edges_equal(G.edges(data="foo"), [(1, 2, "bar")]) def test_edge_attr2(self): G = self.Graph() G.add_edges_from([(1, 2), (3, 4)], foo="foo") - assert_edges_equal( + assert edges_equal( G.edges(data=True), [(1, 2, {"foo": "foo"}), (3, 4, {"foo": "foo"})] ) - assert_edges_equal(G.edges(data="foo"), [(1, 2, "foo"), (3, 4, "foo")]) + assert edges_equal(G.edges(data="foo"), [(1, 2, "foo"), (3, 4, "foo")]) def test_edge_attr3(self): G = self.Graph() G.add_edges_from([(1, 2, {"weight": 32}), (3, 4, {"weight": 64})], foo="foo") - assert_edges_equal( + assert edges_equal( G.edges(data=True), [ (1, 2, {"foo": "foo", "weight": 32}), @@ -404,27 +399,27 @@ class BaseAttrGraphTester(BaseGraphTester): G.remove_edges_from([(1, 2), (3, 4)]) G.add_edge(1, 2, data=7, spam="bar", bar="foo") - assert_edges_equal( + assert edges_equal( G.edges(data=True), [(1, 2, {"data": 7, "spam": "bar", "bar": "foo"})] ) def test_edge_attr4(self): G = self.Graph() G.add_edge(1, 2, data=7, spam="bar", bar="foo") - assert_edges_equal( + assert edges_equal( G.edges(data=True), [(1, 2, {"data": 7, "spam": "bar", "bar": "foo"})] ) G[1][2]["data"] = 10 # OK to set data like this - assert_edges_equal( + assert edges_equal( G.edges(data=True), [(1, 2, {"data": 10, "spam": "bar", "bar": "foo"})] ) G.adj[1][2]["data"] = 20 - assert_edges_equal( + assert edges_equal( G.edges(data=True), [(1, 2, {"data": 20, "spam": "bar", "bar": "foo"})] ) G.edges[1, 2]["data"] = 21 # another spelling, "edge" - assert_edges_equal( + assert edges_equal( G.edges(data=True), [(1, 2, {"data": 21, "spam": "bar", "bar": "foo"})] ) G.adj[1][2]["listdata"] = [20, 200] @@ -436,7 +431,7 @@ class BaseAttrGraphTester(BaseGraphTester): "listdata": [20, 200], "weight": 20, } - assert_edges_equal(G.edges(data=True), [(1, 2, dd)]) + assert edges_equal(G.edges(data=True), [(1, 2, dd)]) def test_to_undirected(self): G = self.K3 @@ -474,10 +469,10 @@ class BaseAttrGraphTester(BaseGraphTester): G = self.K3.copy() G.add_edge(0, 0) G.add_edge(1, 1, weight=2) - assert_edges_equal( + assert edges_equal( nx.selfloop_edges(G, data=True), [(0, 0, {}), (1, 1, {"weight": 2})] ) - assert_edges_equal( + assert edges_equal( nx.selfloop_edges(G, data="weight"), [(0, 0, None), (1, 1, 2)] ) @@ -657,9 +652,9 @@ class TestGraph(BaseAttrGraphTester): def test_edges_data(self): G = self.K3 all_edges = [(0, 1, {}), (0, 2, {}), (1, 2, {})] - assert_edges_equal(G.edges(data=True), all_edges) - assert_edges_equal(G.edges(0, data=True), [(0, 1, {}), (0, 2, {})]) - assert_edges_equal(G.edges([0, 1], data=True), all_edges) + assert edges_equal(G.edges(data=True), all_edges) + assert edges_equal(G.edges(0, data=True), [(0, 1, {}), (0, 2, {})]) + assert edges_equal(G.edges([0, 1], data=True), all_edges) with pytest.raises(nx.NetworkXError): G.edges(-1, True) @@ -723,9 +718,9 @@ class TestGraph(BaseAttrGraphTester): GG = G.copy() H = self.Graph() GG.update(H) - assert_graphs_equal(G, GG) + assert graphs_equal(G, GG) H.update(G) - assert_graphs_equal(H, G) + assert graphs_equal(H, G) # update nodes only H = self.Graph() diff --git a/networkx/classes/tests/test_graphviews.py b/networkx/classes/tests/test_graphviews.py index 806117f0..15e37b4a 100644 --- a/networkx/classes/tests/test_graphviews.py +++ b/networkx/classes/tests/test_graphviews.py @@ -1,7 +1,7 @@ import pytest import networkx as nx -from networkx.testing import assert_edges_equal, assert_nodes_equal +from networkx.utils import nodes_equal, edges_equal # Note: SubGraph views are not tested here. They have their own testing file @@ -111,8 +111,8 @@ class TestToDirected: def test_already_directed(self): dd = nx.to_directed(self.dv) Mdd = nx.to_directed(self.Mdv) - assert_edges_equal(dd.edges, self.dv.edges) - assert_edges_equal(Mdd.edges, self.Mdv.edges) + assert edges_equal(dd.edges, self.dv.edges) + assert edges_equal(Mdd.edges, self.Mdv.edges) def test_pickle(self): import pickle @@ -150,8 +150,8 @@ class TestToUndirected: def test_already_directed(self): uu = nx.to_undirected(self.uv) Muu = nx.to_undirected(self.Muv) - assert_edges_equal(uu.edges, self.uv.edges) - assert_edges_equal(Muu.edges, self.Muv.edges) + assert edges_equal(uu.edges, self.uv.edges) + assert edges_equal(Muu.edges, self.Muv.edges) def test_pickle(self): import pickle @@ -207,8 +207,8 @@ class TestChainsOfViews: for G in self.graphs: H = pickle.loads(pickle.dumps(G, -1)) - assert_edges_equal(H.edges, G.edges) - assert_nodes_equal(H.nodes, G.nodes) + assert edges_equal(H.edges, G.edges) + assert nodes_equal(H.nodes, G.nodes) def test_subgraph_of_subgraph(self): SGv = nx.subgraph(self.G, range(3, 7)) @@ -239,19 +239,19 @@ class TestChainsOfViews: assert RG._graph is self.G assert SSG._graph is self.G assert SG._graph is RG - assert_edges_equal(SG.edges, SSG.edges) + assert edges_equal(SG.edges, SSG.edges) # should be same as morphing the graph CG = self.G.copy() CG.remove_nodes_from(hide_nodes) CG.remove_edges_from(hide_edges) - assert_edges_equal(CG.edges(nodes), SSG.edges) + assert edges_equal(CG.edges(nodes), SSG.edges) CG.remove_nodes_from([0, 1, 2, 3]) - assert_edges_equal(CG.edges, SSG.edges) + assert edges_equal(CG.edges, SSG.edges) # switch order: subgraph first, then restricted view SSSG = self.G.subgraph(nodes) RSG = nx.restricted_view(SSSG, hide_nodes, hide_edges) assert RSG._graph is not self.G - assert_edges_equal(RSG.edges, CG.edges) + assert edges_equal(RSG.edges, CG.edges) def test_subgraph_copy(self): for origG in self.graphs: diff --git a/networkx/classes/tests/test_multidigraph.py b/networkx/classes/tests/test_multidigraph.py index 2bf184c6..0e84890e 100644 --- a/networkx/classes/tests/test_multidigraph.py +++ b/networkx/classes/tests/test_multidigraph.py @@ -1,5 +1,5 @@ import pytest -from networkx.testing import assert_edges_equal +from networkx.utils import edges_equal import networkx as nx from .test_multigraph import BaseMultiGraphTester from .test_multigraph import TestMultiGraph as _TestMultiGraph @@ -156,9 +156,9 @@ class BaseMultiDiGraphTester(BaseMultiGraphTester): # the result is traversal order dependent so we # can't use the is_shallow() test here. try: - assert_edges_equal(H.edges(), [(0, 1), (1, 2), (2, 0)]) + assert edges_equal(H.edges(), [(0, 1), (1, 2), (2, 0)]) except AssertionError: - assert_edges_equal(H.edges(), [(0, 1), (1, 2), (1, 2), (2, 0)]) + assert edges_equal(H.edges(), [(0, 1), (1, 2), (1, 2), (2, 0)]) H = G.to_undirected() self.is_deep(H, G) diff --git a/networkx/classes/tests/test_multigraph.py b/networkx/classes/tests/test_multigraph.py index ec07c229..bf2e98e0 100644 --- a/networkx/classes/tests/test_multigraph.py +++ b/networkx/classes/tests/test_multigraph.py @@ -1,7 +1,7 @@ import pytest import networkx as nx -from networkx.testing.utils import assert_edges_equal +from networkx.utils import edges_equal from .test_graph import BaseAttrGraphTester from .test_graph import TestGraph as _TestGraph @@ -119,31 +119,31 @@ class BaseMultiGraphTester(BaseAttrGraphTester): G = self.Graph() G.add_edge(1, 2, foo="bar") G.add_edge(1, 2, "key", foo="biz") - assert_edges_equal(G.edges[1, 2, 0], {"foo": "bar"}) - assert_edges_equal(G.edges[1, 2, "key"], {"foo": "biz"}) + assert edges_equal(G.edges[1, 2, 0], {"foo": "bar"}) + assert edges_equal(G.edges[1, 2, "key"], {"foo": "biz"}) def test_edge_attr4(self): G = self.Graph() G.add_edge(1, 2, key=0, data=7, spam="bar", bar="foo") - assert_edges_equal( + assert edges_equal( G.edges(data=True), [(1, 2, {"data": 7, "spam": "bar", "bar": "foo"})] ) G[1][2][0]["data"] = 10 # OK to set data like this - assert_edges_equal( + assert edges_equal( G.edges(data=True), [(1, 2, {"data": 10, "spam": "bar", "bar": "foo"})] ) G.adj[1][2][0]["data"] = 20 - assert_edges_equal( + assert edges_equal( G.edges(data=True), [(1, 2, {"data": 20, "spam": "bar", "bar": "foo"})] ) G.edges[1, 2, 0]["data"] = 21 # another spelling, "edge" - assert_edges_equal( + assert edges_equal( G.edges(data=True), [(1, 2, {"data": 21, "spam": "bar", "bar": "foo"})] ) G.adj[1][2][0]["listdata"] = [20, 200] G.adj[1][2][0]["weight"] = 20 - assert_edges_equal( + assert edges_equal( G.edges(data=True), [ ( diff --git a/networkx/conftest.py b/networkx/conftest.py index 0d39779c..ad541ba0 100644 --- a/networkx/conftest.py +++ b/networkx/conftest.py @@ -139,6 +139,24 @@ def set_warnings(): warnings.filterwarnings( "ignore", category=DeprecationWarning, message="`almost_equal`" ) + warnings.filterwarnings( + "ignore", category=DeprecationWarning, message="`assert_nodes_equal`" + ) + warnings.filterwarnings( + "ignore", category=DeprecationWarning, message="`assert_edges_equal`" + ) + warnings.filterwarnings( + "ignore", category=DeprecationWarning, message="`assert_graphs_equal`" + ) + warnings.filterwarnings( + "ignore", category=DeprecationWarning, message="networkx.hits_scipy" + ) + warnings.filterwarnings( + "ignore", category=DeprecationWarning, message="networkx.hits_numpy" + ) + warnings.filterwarnings( + "ignore", category=DeprecationWarning, message="preserve_random_state" + ) @pytest.fixture(autouse=True) diff --git a/networkx/drawing/tests/test_agraph.py b/networkx/drawing/tests/test_agraph.py index bf91f335..33e77c36 100644 --- a/networkx/drawing/tests/test_agraph.py +++ b/networkx/drawing/tests/test_agraph.py @@ -6,7 +6,7 @@ import pytest pygraphviz = pytest.importorskip("pygraphviz") -from networkx.testing import assert_edges_equal, assert_nodes_equal, assert_graphs_equal +from networkx.utils import nodes_equal, edges_equal, graphs_equal import networkx as nx @@ -20,8 +20,8 @@ class TestAGraph: return G def assert_equal(self, G1, G2): - assert_nodes_equal(G1.nodes(), G2.nodes()) - assert_edges_equal(G1.edges(), G2.edges()) + assert nodes_equal(G1.nodes(), G2.nodes()) + assert edges_equal(G1.edges(), G2.edges()) assert G1.graph["metal"] == G2.graph["metal"] def agraph_checks(self, G): @@ -188,21 +188,21 @@ class TestAGraph: G = nx.Graph() A = nx.nx_agraph.to_agraph(G) H = nx.nx_agraph.from_agraph(A) - # assert_graphs_equal(G, H) + # assert graphs_equal(G, H) AA = nx.nx_agraph.to_agraph(H) HH = nx.nx_agraph.from_agraph(AA) - assert_graphs_equal(H, HH) + assert graphs_equal(H, HH) G.graph["graph"] = {} G.graph["node"] = {} G.graph["edge"] = {} - assert_graphs_equal(G, HH) + assert graphs_equal(G, HH) @pytest.mark.xfail(reason="integer->string node conversion in round trip") def test_round_trip_integer_nodes(self): G = nx.complete_graph(3) A = nx.nx_agraph.to_agraph(G) H = nx.nx_agraph.from_agraph(A) - assert_graphs_equal(G, H) + assert graphs_equal(G, H) def test_graphviz_alias(self): G = self.build_graph(nx.Graph()) diff --git a/networkx/drawing/tests/test_pydot.py b/networkx/drawing/tests/test_pydot.py index 4ebe2e7e..39371880 100644 --- a/networkx/drawing/tests/test_pydot.py +++ b/networkx/drawing/tests/test_pydot.py @@ -3,7 +3,7 @@ from io import StringIO import tempfile import os import networkx as nx -from networkx.testing import assert_graphs_equal +from networkx.utils import graphs_equal import pytest @@ -36,7 +36,7 @@ class TestPydot: G2 = G.__class__(nx.nx_pydot.from_pydot(P)) # Validate the original and resulting graphs to be the same. - assert_graphs_equal(G, G2) + assert graphs_equal(G, G2) fd, fname = tempfile.mkstemp() @@ -77,7 +77,7 @@ class TestPydot: Hin = G.__class__(Hin) # Validate the original and resulting graphs to be the same. - assert_graphs_equal(G, Hin) + assert graphs_equal(G, Hin) os.close(fd) os.unlink(fname) @@ -96,4 +96,4 @@ class TestPydot: nx.nx_pydot.write_dot(G, fh) fh.seek(0) H = nx.nx_pydot.read_dot(fh) - assert_graphs_equal(G, H) + assert graphs_equal(G, H) diff --git a/networkx/generators/tests/test_atlas.py b/networkx/generators/tests/test_atlas.py index e9ce00b2..c5d1d7ee 100644 --- a/networkx/generators/tests/test_atlas.py +++ b/networkx/generators/tests/test_atlas.py @@ -3,7 +3,7 @@ from itertools import groupby import pytest import networkx as nx -from networkx.testing import assert_edges_equal, assert_nodes_equal +from networkx.utils import nodes_equal, edges_equal from networkx import graph_atlas from networkx import graph_atlas_g from networkx.generators.atlas import NUM_GRAPHS @@ -23,8 +23,8 @@ class TestAtlasGraph: def test_graph(self): G = graph_atlas(6) - assert_nodes_equal(G.nodes(), range(3)) - assert_edges_equal(G.edges(), [(0, 1), (0, 2)]) + assert nodes_equal(G.nodes(), range(3)) + assert edges_equal(G.edges(), [(0, 1), (0, 2)]) class TestAtlasGraphG: diff --git a/networkx/generators/tests/test_classic.py b/networkx/generators/tests/test_classic.py index 3ec36f0f..24077725 100644 --- a/networkx/generators/tests/test_classic.py +++ b/networkx/generators/tests/test_classic.py @@ -10,8 +10,7 @@ import itertools import pytest import networkx as nx from networkx.algorithms.isomorphism.isomorph import graph_could_be_isomorphic -from networkx.testing import assert_edges_equal -from networkx.testing import assert_nodes_equal +from networkx.utils import nodes_equal, edges_equal is_isomorphic = graph_could_be_isomorphic @@ -135,7 +134,7 @@ class TestGeneratorClassic: ) mb = nx.barbell_graph(m1, m2, create_using=nx.MultiGraph()) - assert_edges_equal(mb.edges(), b.edges()) + assert edges_equal(mb.edges(), b.edges()) def test_binomial_tree(self): graphs = (None, nx.Graph, nx.DiGraph, nx.MultiGraph, nx.MultiDiGraph) @@ -154,10 +153,10 @@ class TestGeneratorClassic: assert nx.number_of_edges(g) == m * (m - 1) // 2 mg = nx.complete_graph(m, create_using=nx.MultiGraph) - assert_edges_equal(mg.edges(), g.edges()) + assert edges_equal(mg.edges(), g.edges()) g = nx.complete_graph("abc") - assert_nodes_equal(g.nodes(), ["a", "b", "c"]) + assert nodes_equal(g.nodes(), ["a", "b", "c"]) assert g.size() == 3 def test_complete_digraph(self): @@ -179,18 +178,18 @@ class TestGeneratorClassic: nx.NetworkXError, nx.circular_ladder_graph, 5, create_using=nx.DiGraph ) mG = nx.circular_ladder_graph(5, create_using=nx.MultiGraph) - assert_edges_equal(mG.edges(), G.edges()) + assert edges_equal(mG.edges(), G.edges()) def test_circulant_graph(self): # Ci_n(1) is the cycle graph for all n Ci6_1 = nx.circulant_graph(6, [1]) C6 = nx.cycle_graph(6) - assert_edges_equal(Ci6_1.edges(), C6.edges()) + assert edges_equal(Ci6_1.edges(), C6.edges()) # Ci_n(1, 2, ..., n div 2) is the complete graph for all n Ci7 = nx.circulant_graph(7, [1, 2, 3]) K7 = nx.complete_graph(7) - assert_edges_equal(Ci7.edges(), K7.edges()) + assert edges_equal(Ci7.edges(), K7.edges()) # Ci_6(1, 3) is K_3,3 i.e. the utility graph Ci6_1_3 = nx.circulant_graph(6, [1, 3]) @@ -199,9 +198,9 @@ class TestGeneratorClassic: def test_cycle_graph(self): G = nx.cycle_graph(4) - assert_edges_equal(G.edges(), [(0, 1), (0, 3), (1, 2), (2, 3)]) + assert edges_equal(G.edges(), [(0, 1), (0, 3), (1, 2), (2, 3)]) mG = nx.cycle_graph(4, create_using=nx.MultiGraph) - assert_edges_equal(mG.edges(), [(0, 1), (0, 3), (1, 2), (2, 3)]) + assert edges_equal(mG.edges(), [(0, 1), (0, 3), (1, 2), (2, 3)]) G = nx.cycle_graph(4, create_using=nx.DiGraph) assert not G.has_edge(2, 1) assert G.has_edge(1, 2) @@ -217,10 +216,10 @@ class TestGeneratorClassic: def test_dorogovtsev_goltsev_mendes_graph(self): G = nx.dorogovtsev_goltsev_mendes_graph(0) - assert_edges_equal(G.edges(), [(0, 1)]) - assert_nodes_equal(list(G), [0, 1]) + assert edges_equal(G.edges(), [(0, 1)]) + assert nodes_equal(list(G), [0, 1]) G = nx.dorogovtsev_goltsev_mendes_graph(1) - assert_edges_equal(G.edges(), [(0, 1), (0, 2), (1, 2)]) + assert edges_equal(G.edges(), [(0, 1), (0, 2), (1, 2)]) assert nx.average_clustering(G) == 1.0 assert sorted(nx.triangles(G).values()) == [1, 1, 1] G = nx.dorogovtsev_goltsev_mendes_graph(10) @@ -316,7 +315,7 @@ class TestGeneratorClassic: g = nx.ladder_graph(2) mg = nx.ladder_graph(2, create_using=nx.MultiGraph) - assert_edges_equal(mg.edges(), g.edges()) + assert edges_equal(mg.edges(), g.edges()) def test_lollipop_graph(self): # number of nodes = m1 + m2 @@ -342,7 +341,7 @@ class TestGeneratorClassic: ) mb = nx.lollipop_graph(m1, m2, create_using=nx.MultiGraph) - assert_edges_equal(mb.edges(), b.edges()) + assert edges_equal(mb.edges(), b.edges()) g = nx.lollipop_graph([1, 2, 3, 4], "abc") assert len(g) == 7 @@ -368,7 +367,7 @@ class TestGeneratorClassic: assert not dp.has_edge(1, 0) mp = nx.path_graph(10, create_using=nx.MultiGraph) - assert_edges_equal(mp.edges(), p.edges()) + assert edges_equal(mp.edges(), p.edges()) G = nx.path_graph("abc") assert len(G) == 3 @@ -391,7 +390,7 @@ class TestGeneratorClassic: pytest.raises(nx.NetworkXError, star_graph, 10, create_using=nx.DiGraph) ms = star_graph(10, create_using=nx.MultiGraph) - assert_edges_equal(ms.edges(), s.edges()) + assert edges_equal(ms.edges(), s.edges()) G = star_graph("abcdefg") assert len(G) == 7 @@ -423,7 +422,7 @@ class TestGeneratorClassic: pytest.raises(nx.NetworkXError, nx.wheel_graph, 10, create_using=nx.DiGraph) mg = nx.wheel_graph(10, create_using=nx.MultiGraph()) - assert_edges_equal(mg.edges(), g.edges()) + assert edges_equal(mg.edges(), g.edges()) G = nx.wheel_graph("abc") assert len(G) == 3 @@ -433,15 +432,15 @@ class TestGeneratorClassic: """Tests that the complete 0-partite graph is the null graph.""" G = nx.complete_multipartite_graph() H = nx.null_graph() - assert_nodes_equal(G, H) - assert_edges_equal(G.edges(), H.edges()) + assert nodes_equal(G, H) + assert edges_equal(G.edges(), H.edges()) def test_complete_1_partite_graph(self): """Tests that the complete 1-partite graph is the empty graph.""" G = nx.complete_multipartite_graph(3) H = nx.empty_graph(3) - assert_nodes_equal(G, H) - assert_edges_equal(G.edges(), H.edges()) + assert nodes_equal(G, H) + assert edges_equal(G.edges(), H.edges()) def test_complete_2_partite_graph(self): """Tests that the complete 2-partite graph is the complete bipartite @@ -450,8 +449,8 @@ class TestGeneratorClassic: """ G = nx.complete_multipartite_graph(2, 3) H = nx.complete_bipartite_graph(2, 3) - assert_nodes_equal(G, H) - assert_edges_equal(G.edges(), H.edges()) + assert nodes_equal(G, H) + assert edges_equal(G.edges(), H.edges()) def test_complete_multipartite_graph(self): """Tests for generating the complete multipartite graph.""" diff --git a/networkx/generators/tests/test_ego.py b/networkx/generators/tests/test_ego.py index 3b16b0fe..19458c11 100644 --- a/networkx/generators/tests/test_ego.py +++ b/networkx/generators/tests/test_ego.py @@ -4,7 +4,7 @@ ego graph """ import networkx as nx -from networkx.testing.utils import assert_edges_equal, assert_nodes_equal +from networkx.utils import nodes_equal, edges_equal class TestGeneratorEgo: @@ -19,21 +19,21 @@ class TestGeneratorEgo: assert nx.is_isomorphic(nx.star_graph(3), H) G = nx.path_graph(3) H = nx.ego_graph(G, 0) - assert_edges_equal(H.edges(), [(0, 1)]) + assert edges_equal(H.edges(), [(0, 1)]) H = nx.ego_graph(G, 0, undirected=True) - assert_edges_equal(H.edges(), [(0, 1)]) + assert edges_equal(H.edges(), [(0, 1)]) H = nx.ego_graph(G, 0, center=False) - assert_edges_equal(H.edges(), []) + assert edges_equal(H.edges(), []) def test_ego_distance(self): G = nx.Graph() G.add_edge(0, 1, weight=2, distance=1) G.add_edge(1, 2, weight=2, distance=2) G.add_edge(2, 3, weight=2, distance=1) - assert_nodes_equal(nx.ego_graph(G, 0, radius=3).nodes(), [0, 1, 2, 3]) + assert nodes_equal(nx.ego_graph(G, 0, radius=3).nodes(), [0, 1, 2, 3]) eg = nx.ego_graph(G, 0, radius=3, distance="weight") - assert_nodes_equal(eg.nodes(), [0, 1]) + assert nodes_equal(eg.nodes(), [0, 1]) eg = nx.ego_graph(G, 0, radius=3, distance="weight", undirected=True) - assert_nodes_equal(eg.nodes(), [0, 1]) + assert nodes_equal(eg.nodes(), [0, 1]) eg = nx.ego_graph(G, 0, radius=3, distance="distance") - assert_nodes_equal(eg.nodes(), [0, 1, 2]) + assert nodes_equal(eg.nodes(), [0, 1, 2]) diff --git a/networkx/generators/tests/test_interval_graph.py b/networkx/generators/tests/test_interval_graph.py index 0c7b4292..26f1f0ef 100644 --- a/networkx/generators/tests/test_interval_graph.py +++ b/networkx/generators/tests/test_interval_graph.py @@ -6,7 +6,7 @@ import pytest import networkx as nx from networkx.generators.interval_graph import interval_graph -from networkx.testing import assert_edges_equal +from networkx.utils import edges_equal class TestIntervalGraph: @@ -44,7 +44,7 @@ class TestIntervalGraph: actual_g = interval_graph(intervals) assert set(actual_g.nodes) == set(expected_graph.nodes) - assert_edges_equal(expected_graph, actual_g) + assert edges_equal(expected_graph, actual_g) def test_interval_graph_1(self): intervals = [(1, 2), (2, 3), (3, 4), (1, 4)] @@ -62,7 +62,7 @@ class TestIntervalGraph: actual_g = interval_graph(intervals) assert set(actual_g.nodes) == set(expected_graph.nodes) - assert_edges_equal(expected_graph, actual_g) + assert edges_equal(expected_graph, actual_g) def test_interval_graph_2(self): intervals = [(1, 2), [3, 5], [6, 8], (9, 10)] @@ -73,7 +73,7 @@ class TestIntervalGraph: actual_g = interval_graph(intervals) assert set(actual_g.nodes) == set(expected_graph.nodes) - assert_edges_equal(expected_graph, actual_g) + assert edges_equal(expected_graph, actual_g) def test_interval_graph_3(self): intervals = [(1, 4), [3, 5], [2.5, 4]] @@ -89,7 +89,7 @@ class TestIntervalGraph: actual_g = interval_graph(intervals) assert set(actual_g.nodes) == set(expected_graph.nodes) - assert_edges_equal(expected_graph, actual_g) + assert edges_equal(expected_graph, actual_g) def test_interval_graph_4(self): """test all possible overlaps""" @@ -141,4 +141,4 @@ class TestIntervalGraph: actual_g = interval_graph(intervals) assert set(actual_g.nodes) == set(expected_graph.nodes) - assert_edges_equal(expected_graph, actual_g) + assert edges_equal(expected_graph, actual_g) diff --git a/networkx/generators/tests/test_lattice.py b/networkx/generators/tests/test_lattice.py index 3f72d095..07271e3a 100644 --- a/networkx/generators/tests/test_lattice.py +++ b/networkx/generators/tests/test_lattice.py @@ -3,7 +3,7 @@ import pytest import networkx as nx -from networkx.testing import assert_edges_equal +from networkx.utils import edges_equal from itertools import product @@ -76,7 +76,7 @@ class TestGrid2DGraph: assert nx.is_isomorphic(H, G) G = nx.grid_2d_graph(5, 6) H = nx.grid_2d_graph(range(5), range(6)) - assert_edges_equal(H, G) + assert edges_equal(H, G) class TestGridGraph: diff --git a/networkx/generators/tests/test_line.py b/networkx/generators/tests/test_line.py index fec8893c..e072728d 100644 --- a/networkx/generators/tests/test_line.py +++ b/networkx/generators/tests/test_line.py @@ -2,7 +2,7 @@ import networkx as nx import pytest import networkx.generators.line as line -from networkx.testing.utils import assert_edges_equal +from networkx.utils import edges_equal def test_node_func(): @@ -29,7 +29,7 @@ def test_edge_func(): G.add_edge(2, 3) ef = line._edge_func(G) expected = [(1, 2), (2, 3)] - assert_edges_equal(ef(), expected) + assert edges_equal(ef(), expected) # digraph G = nx.MultiDiGraph() @@ -74,19 +74,19 @@ class TestGeneratorLine: G = nx.DiGraph() G.add_edges_from([(0, 1), (1, 2), (2, 3)]) L = nx.line_graph(G) - assert_edges_equal(L.edges(), [((0, 1), (1, 2)), ((1, 2), (2, 3))]) + assert edges_equal(L.edges(), [((0, 1), (1, 2)), ((1, 2), (2, 3))]) def test_create1(self): G = nx.DiGraph() G.add_edges_from([(0, 1), (1, 2), (2, 3)]) L = nx.line_graph(G, create_using=nx.Graph()) - assert_edges_equal(L.edges(), [((0, 1), (1, 2)), ((1, 2), (2, 3))]) + assert edges_equal(L.edges(), [((0, 1), (1, 2)), ((1, 2), (2, 3))]) def test_create2(self): G = nx.Graph() G.add_edges_from([(0, 1), (1, 2), (2, 3)]) L = nx.line_graph(G, create_using=nx.DiGraph()) - assert_edges_equal(L.edges(), [((0, 1), (1, 2)), ((1, 2), (2, 3))]) + assert edges_equal(L.edges(), [((0, 1), (1, 2)), ((1, 2), (2, 3))]) class TestGeneratorInverseLine: diff --git a/networkx/generators/tests/test_nonisomorphic_trees.py b/networkx/generators/tests/test_nonisomorphic_trees.py index cb6eea86..ced1cbe1 100644 --- a/networkx/generators/tests/test_nonisomorphic_trees.py +++ b/networkx/generators/tests/test_nonisomorphic_trees.py @@ -6,7 +6,7 @@ Generators - Non Isomorphic Trees Unit tests for WROM algorithm generator in generators/nonisomorphic_trees.py """ import networkx as nx -from networkx.testing import assert_edges_equal +from networkx.utils import edges_equal class TestGeneratorNonIsomorphicTrees: @@ -48,9 +48,9 @@ class TestGeneratorNonIsomorphicTrees: def f(x): return list(nx.nonisomorphic_trees(x)) - assert_edges_equal(f(3)[0].edges(), [(0, 1), (0, 2)]) - assert_edges_equal(f(4)[0].edges(), [(0, 1), (0, 3), (1, 2)]) - assert_edges_equal(f(4)[1].edges(), [(0, 1), (0, 2), (0, 3)]) + assert edges_equal(f(3)[0].edges(), [(0, 1), (0, 2)]) + assert edges_equal(f(4)[0].edges(), [(0, 1), (0, 3), (1, 2)]) + assert edges_equal(f(4)[1].edges(), [(0, 1), (0, 2), (0, 3)]) def test_nonisomorphic_trees_matrix(self): trees_2 = [[[0, 1], [1, 0]]] diff --git a/networkx/generators/tests/test_spectral_graph_forge.py b/networkx/generators/tests/test_spectral_graph_forge.py index b260f72e..48377a99 100644 --- a/networkx/generators/tests/test_spectral_graph_forge.py +++ b/networkx/generators/tests/test_spectral_graph_forge.py @@ -6,7 +6,7 @@ pytest.importorskip("scipy") from networkx import is_isomorphic from networkx.exception import NetworkXError -from networkx.testing import assert_nodes_equal +from networkx.utils import nodes_equal from networkx.generators.spectral_graph_forge import spectral_graph_forge from networkx.generators import karate_club_graph @@ -19,28 +19,28 @@ def test_spectral_graph_forge(): # common cases, just checking node number preserving and difference # between identity and modularity cases H = spectral_graph_forge(G, 0.1, transformation="identity", seed=seed) - assert_nodes_equal(G, H) + assert nodes_equal(G, H) I = spectral_graph_forge(G, 0.1, transformation="identity", seed=seed) - assert_nodes_equal(G, H) + assert nodes_equal(G, H) assert is_isomorphic(I, H) I = spectral_graph_forge(G, 0.1, transformation="modularity", seed=seed) - assert_nodes_equal(G, I) + assert nodes_equal(G, I) assert not is_isomorphic(I, H) # with all the eigenvectors, output graph is identical to the input one H = spectral_graph_forge(G, 1, transformation="modularity", seed=seed) - assert_nodes_equal(G, H) + assert nodes_equal(G, H) assert is_isomorphic(G, H) # invalid alpha input value, it is silently truncated in [0,1] H = spectral_graph_forge(G, -1, transformation="identity", seed=seed) - assert_nodes_equal(G, H) + assert nodes_equal(G, H) H = spectral_graph_forge(G, 10, transformation="identity", seed=seed) - assert_nodes_equal(G, H) + assert nodes_equal(G, H) assert is_isomorphic(G, H) # invalid transformation mode, checking the error raising diff --git a/networkx/generators/tests/test_trees.py b/networkx/generators/tests/test_trees.py index 85573ff5..908167fd 100644 --- a/networkx/generators/tests/test_trees.py +++ b/networkx/generators/tests/test_trees.py @@ -1,6 +1,6 @@ -import networkx as nx -from networkx.utils import arbitrary_element import pytest +import networkx as nx +from networkx.utils import arbitrary_element, graphs_equal @pytest.mark.parametrize("prefix_tree_fn", (nx.prefix_tree, nx.prefix_tree_recursive)) @@ -78,7 +78,7 @@ def test_basic_prefix_tree(prefix_tree_fn): ) def test_implementations_consistent(strings): """Ensure results are consistent between prefix_tree implementations.""" - nx.testing.assert_graphs_equal( + assert graphs_equal( nx.prefix_tree(strings), nx.prefix_tree_recursive(strings), ) diff --git a/networkx/readwrite/tests/test_adjlist.py b/networkx/readwrite/tests/test_adjlist.py index 0066111a..2713895c 100644 --- a/networkx/readwrite/tests/test_adjlist.py +++ b/networkx/readwrite/tests/test_adjlist.py @@ -6,7 +6,7 @@ import pytest import os import tempfile import networkx as nx -from networkx.testing import assert_nodes_equal, assert_edges_equal, assert_graphs_equal +from networkx.utils import nodes_equal, edges_equal, graphs_equal class TestAdjlist: @@ -32,7 +32,7 @@ class TestAdjlist: bytesIO = io.BytesIO(s) G = nx.read_multiline_adjlist(bytesIO) adj = {"1": {"3": {}, "2": {}}, "3": {"1": {}}, "2": {"1": {}}} - assert_graphs_equal(G, nx.Graph(adj)) + assert graphs_equal(G, nx.Graph(adj)) def test_unicode(self): G = nx.Graph() @@ -42,7 +42,7 @@ class TestAdjlist: fd, fname = tempfile.mkstemp() nx.write_multiline_adjlist(G, fname) H = nx.read_multiline_adjlist(fname) - assert_graphs_equal(G, H) + assert graphs_equal(G, H) os.close(fd) os.unlink(fname) @@ -66,7 +66,7 @@ class TestAdjlist: fd, fname = tempfile.mkstemp() nx.write_multiline_adjlist(G, fname, encoding="latin-1") H = nx.read_multiline_adjlist(fname, encoding="latin-1") - assert_graphs_equal(G, H) + assert graphs_equal(G, H) os.close(fd) os.unlink(fname) @@ -86,8 +86,8 @@ class TestAdjlist: H = nx.read_adjlist(fname) H2 = nx.read_adjlist(fname) assert H is not H2 # they should be different graphs - assert_nodes_equal(list(H), list(G)) - assert_edges_equal(list(H.edges()), list(G.edges())) + assert nodes_equal(list(H), list(G)) + assert edges_equal(list(H.edges()), list(G.edges())) os.close(fd) os.unlink(fname) @@ -98,8 +98,8 @@ class TestAdjlist: H = nx.read_adjlist(fname, create_using=nx.DiGraph()) H2 = nx.read_adjlist(fname, create_using=nx.DiGraph()) assert H is not H2 # they should be different graphs - assert_nodes_equal(list(H), list(G)) - assert_edges_equal(list(H.edges()), list(G.edges())) + assert nodes_equal(list(H), list(G)) + assert edges_equal(list(H.edges()), list(G.edges())) os.close(fd) os.unlink(fname) @@ -110,8 +110,8 @@ class TestAdjlist: H = nx.read_adjlist(fname, nodetype=int) H2 = nx.read_adjlist(fname, nodetype=int) assert H is not H2 # they should be different graphs - assert_nodes_equal(list(H), list(G)) - assert_edges_equal(list(H.edges()), list(G.edges())) + assert nodes_equal(list(H), list(G)) + assert edges_equal(list(H.edges()), list(G.edges())) os.close(fd) os.unlink(fname) @@ -122,8 +122,8 @@ class TestAdjlist: H = nx.read_adjlist(fname, nodetype=int, create_using=nx.MultiGraph()) H2 = nx.read_adjlist(fname, nodetype=int, create_using=nx.MultiGraph()) assert H is not H2 # they should be different graphs - assert_nodes_equal(list(H), list(G)) - assert_edges_equal(list(H.edges()), list(G.edges())) + assert nodes_equal(list(H), list(G)) + assert edges_equal(list(H.edges()), list(G.edges())) os.close(fd) os.unlink(fname) @@ -134,8 +134,8 @@ class TestAdjlist: H = nx.read_adjlist(fname, nodetype=int, create_using=nx.MultiDiGraph()) H2 = nx.read_adjlist(fname, nodetype=int, create_using=nx.MultiDiGraph()) assert H is not H2 # they should be different graphs - assert_nodes_equal(list(H), list(G)) - assert_edges_equal(list(H.edges()), list(G.edges())) + assert nodes_equal(list(H), list(G)) + assert edges_equal(list(H.edges()), list(G.edges())) os.close(fd) os.unlink(fname) @@ -145,8 +145,8 @@ class TestAdjlist: nx.write_adjlist(G, fh, delimiter=":") fh.seek(0) H = nx.read_adjlist(fh, nodetype=int, delimiter=":") - assert_nodes_equal(list(H), list(G)) - assert_edges_equal(list(H.edges()), list(G.edges())) + assert nodes_equal(list(H), list(G)) + assert edges_equal(list(H.edges()), list(G.edges())) class TestMultilineAdjlist: @@ -197,8 +197,8 @@ class TestMultilineAdjlist: H = nx.read_multiline_adjlist(fname) H2 = nx.read_multiline_adjlist(fname) assert H is not H2 # they should be different graphs - assert_nodes_equal(list(H), list(G)) - assert_edges_equal(list(H.edges()), list(G.edges())) + assert nodes_equal(list(H), list(G)) + assert edges_equal(list(H.edges()), list(G.edges())) os.close(fd) os.unlink(fname) @@ -209,8 +209,8 @@ class TestMultilineAdjlist: H = nx.read_multiline_adjlist(fname, create_using=nx.DiGraph()) H2 = nx.read_multiline_adjlist(fname, create_using=nx.DiGraph()) assert H is not H2 # they should be different graphs - assert_nodes_equal(list(H), list(G)) - assert_edges_equal(list(H.edges()), list(G.edges())) + assert nodes_equal(list(H), list(G)) + assert edges_equal(list(H.edges()), list(G.edges())) os.close(fd) os.unlink(fname) @@ -221,8 +221,8 @@ class TestMultilineAdjlist: H = nx.read_multiline_adjlist(fname, nodetype=int) H2 = nx.read_multiline_adjlist(fname, nodetype=int) assert H is not H2 # they should be different graphs - assert_nodes_equal(list(H), list(G)) - assert_edges_equal(list(H.edges()), list(G.edges())) + assert nodes_equal(list(H), list(G)) + assert edges_equal(list(H.edges()), list(G.edges())) os.close(fd) os.unlink(fname) @@ -235,8 +235,8 @@ class TestMultilineAdjlist: fname, nodetype=int, create_using=nx.MultiGraph() ) assert H is not H2 # they should be different graphs - assert_nodes_equal(list(H), list(G)) - assert_edges_equal(list(H.edges()), list(G.edges())) + assert nodes_equal(list(H), list(G)) + assert edges_equal(list(H.edges()), list(G.edges())) os.close(fd) os.unlink(fname) @@ -251,8 +251,8 @@ class TestMultilineAdjlist: fname, nodetype=int, create_using=nx.MultiDiGraph() ) assert H is not H2 # they should be different graphs - assert_nodes_equal(list(H), list(G)) - assert_edges_equal(list(H.edges()), list(G.edges())) + assert nodes_equal(list(H), list(G)) + assert edges_equal(list(H.edges()), list(G.edges())) os.close(fd) os.unlink(fname) @@ -262,5 +262,5 @@ class TestMultilineAdjlist: nx.write_multiline_adjlist(G, fh, delimiter=":") fh.seek(0) H = nx.read_multiline_adjlist(fh, nodetype=int, delimiter=":") - assert_nodes_equal(list(H), list(G)) - assert_edges_equal(list(H.edges()), list(G.edges())) + assert nodes_equal(list(H), list(G)) + assert edges_equal(list(H.edges()), list(G.edges())) diff --git a/networkx/readwrite/tests/test_edgelist.py b/networkx/readwrite/tests/test_edgelist.py index de3f0146..a9f498df 100644 --- a/networkx/readwrite/tests/test_edgelist.py +++ b/networkx/readwrite/tests/test_edgelist.py @@ -8,7 +8,7 @@ import os import textwrap import networkx as nx -from networkx.testing import assert_edges_equal, assert_nodes_equal, assert_graphs_equal +from networkx.utils import nodes_equal, edges_equal, graphs_equal edges_no_data = textwrap.dedent( @@ -81,13 +81,13 @@ _expected_edges_multiattr = [ def test_read_edgelist_no_data(data, extra_kwargs): bytesIO = io.BytesIO(data.encode("utf-8")) G = nx.read_edgelist(bytesIO, nodetype=int, data=False, **extra_kwargs) - assert_edges_equal(G.edges(), [(1, 2), (2, 3)]) + assert edges_equal(G.edges(), [(1, 2), (2, 3)]) def test_read_weighted_edgelist(): bytesIO = io.BytesIO(edges_with_values.encode("utf-8")) G = nx.read_weighted_edgelist(bytesIO, nodetype=int) - assert_edges_equal(G.edges(data=True), _expected_edges_weights) + assert edges_equal(G.edges(data=True), _expected_edges_weights) @pytest.mark.parametrize( @@ -101,7 +101,7 @@ def test_read_weighted_edgelist(): def test_read_edgelist_with_data(data, extra_kwargs, expected): bytesIO = io.BytesIO(data.encode("utf-8")) G = nx.read_edgelist(bytesIO, nodetype=int, **extra_kwargs) - assert_edges_equal(G.edges(data=True), expected) + assert edges_equal(G.edges(data=True), expected) @pytest.fixture @@ -114,8 +114,8 @@ def example_graph(): def test_parse_edgelist_no_data(example_graph): G = example_graph H = nx.parse_edgelist(["1 2", "2 3", "3 4"], nodetype=int) - assert_nodes_equal(G.nodes, H.nodes) - assert_edges_equal(G.edges, H.edges) + assert nodes_equal(G.nodes, H.nodes) + assert edges_equal(G.edges, H.edges) def test_parse_edgelist_with_data_dict(example_graph): @@ -124,8 +124,8 @@ def test_parse_edgelist_with_data_dict(example_graph): ["1 2 {'weight': 3}", "2 3 {'weight': 27}", "3 4 {'weight': 3.0}"], nodetype=int, ) - assert_nodes_equal(G.nodes, H.nodes) - assert_edges_equal(G.edges(data=True), H.edges(data=True)) + assert nodes_equal(G.nodes, H.nodes) + assert edges_equal(G.edges(data=True), H.edges(data=True)) def test_parse_edgelist_with_data_list(example_graph): @@ -133,8 +133,8 @@ def test_parse_edgelist_with_data_list(example_graph): H = nx.parse_edgelist( ["1 2 3", "2 3 27", "3 4 3.0"], nodetype=int, data=(("weight", float),) ) - assert_nodes_equal(G.nodes, H.nodes) - assert_edges_equal(G.edges(data=True), H.edges(data=True)) + assert nodes_equal(G.nodes, H.nodes) + assert edges_equal(G.edges(data=True), H.edges(data=True)) def test_parse_edgelist(): @@ -216,7 +216,7 @@ class TestEdgelist: fd, fname = tempfile.mkstemp() nx.write_edgelist(G, fname) H = nx.read_edgelist(fname) - assert_graphs_equal(G, H) + assert graphs_equal(G, H) os.close(fd) os.unlink(fname) @@ -240,7 +240,7 @@ class TestEdgelist: fd, fname = tempfile.mkstemp() nx.write_edgelist(G, fname, encoding="latin-1") H = nx.read_edgelist(fname, encoding="latin-1") - assert_graphs_equal(G, H) + assert graphs_equal(G, H) os.close(fd) os.unlink(fname) @@ -252,8 +252,8 @@ class TestEdgelist: H2 = nx.read_edgelist(fname) assert H is not H2 # they should be different graphs G.remove_node("g") # isolated nodes are not written in edgelist - assert_nodes_equal(list(H), list(G)) - assert_edges_equal(list(H.edges()), list(G.edges())) + assert nodes_equal(list(H), list(G)) + assert edges_equal(list(H.edges()), list(G.edges())) os.close(fd) os.unlink(fname) @@ -265,8 +265,8 @@ class TestEdgelist: H2 = nx.read_edgelist(fname, create_using=nx.DiGraph()) assert H is not H2 # they should be different graphs G.remove_node("g") # isolated nodes are not written in edgelist - assert_nodes_equal(list(H), list(G)) - assert_edges_equal(list(H.edges()), list(G.edges())) + assert nodes_equal(list(H), list(G)) + assert edges_equal(list(H.edges()), list(G.edges())) os.close(fd) os.unlink(fname) @@ -277,8 +277,8 @@ class TestEdgelist: H = nx.read_edgelist(fname, nodetype=int) # isolated nodes are not written in edgelist G.remove_nodes_from(list(nx.isolates(G))) - assert_nodes_equal(list(H), list(G)) - assert_edges_equal(list(H.edges()), list(G.edges())) + assert nodes_equal(list(H), list(G)) + assert edges_equal(list(H.edges()), list(G.edges())) os.close(fd) os.unlink(fname) @@ -289,8 +289,8 @@ class TestEdgelist: H = nx.read_edgelist(fname, nodetype=int, create_using=nx.MultiGraph()) H2 = nx.read_edgelist(fname, nodetype=int, create_using=nx.MultiGraph()) assert H is not H2 # they should be different graphs - assert_nodes_equal(list(H), list(G)) - assert_edges_equal(list(H.edges()), list(G.edges())) + assert nodes_equal(list(H), list(G)) + assert edges_equal(list(H.edges()), list(G.edges())) os.close(fd) os.unlink(fname) @@ -301,7 +301,7 @@ class TestEdgelist: H = nx.read_edgelist(fname, nodetype=int, create_using=nx.MultiDiGraph()) H2 = nx.read_edgelist(fname, nodetype=int, create_using=nx.MultiDiGraph()) assert H is not H2 # they should be different graphs - assert_nodes_equal(list(H), list(G)) - assert_edges_equal(list(H.edges()), list(G.edges())) + assert nodes_equal(list(H), list(G)) + assert edges_equal(list(H.edges()), list(G.edges())) os.close(fd) os.unlink(fname) diff --git a/networkx/readwrite/tests/test_gpickle.py b/networkx/readwrite/tests/test_gpickle.py index e92991db..5059d6db 100644 --- a/networkx/readwrite/tests/test_gpickle.py +++ b/networkx/readwrite/tests/test_gpickle.py @@ -2,11 +2,7 @@ import os import tempfile import networkx as nx -from networkx.testing.utils import ( - assert_graphs_equal, - assert_edges_equal, - assert_nodes_equal, -) +from networkx.utils import nodes_equal, edges_equal, graphs_equal class TestGpickle: @@ -53,9 +49,9 @@ class TestGpickle: (fd, fname) = tempfile.mkstemp() nx.write_gpickle(G, fname) Gin = nx.read_gpickle(fname) - assert_nodes_equal(list(G.nodes(data=True)), list(Gin.nodes(data=True))) - assert_edges_equal(list(G.edges(data=True)), list(Gin.edges(data=True))) - assert_graphs_equal(G, Gin) + assert nodes_equal(list(G.nodes(data=True)), list(Gin.nodes(data=True))) + assert edges_equal(list(G.edges(data=True)), list(Gin.edges(data=True))) + assert graphs_equal(G, Gin) os.close(fd) os.unlink(fname) @@ -74,6 +70,6 @@ class TestGpickle: nx.write_gpickle(G, f, 0) f.seek(0) Gin = nx.read_gpickle(f) - assert_nodes_equal(list(G.nodes(data=True)), list(Gin.nodes(data=True))) - assert_edges_equal(list(G.edges(data=True)), list(Gin.edges(data=True))) - assert_graphs_equal(G, Gin) + assert nodes_equal(list(G.nodes(data=True)), list(Gin.nodes(data=True))) + assert edges_equal(list(G.edges(data=True)), list(Gin.edges(data=True))) + assert graphs_equal(G, Gin) diff --git a/networkx/readwrite/tests/test_graph6.py b/networkx/readwrite/tests/test_graph6.py index 74d7cea1..ec9c1347 100644 --- a/networkx/readwrite/tests/test_graph6.py +++ b/networkx/readwrite/tests/test_graph6.py @@ -4,8 +4,7 @@ import pytest import networkx as nx import networkx.readwrite.graph6 as g6 -from networkx.testing.utils import assert_edges_equal -from networkx.testing.utils import assert_nodes_equal +from networkx.utils import nodes_equal, edges_equal class TestGraph6Utils: @@ -20,8 +19,8 @@ class TestFromGraph6Bytes: def test_from_graph6_bytes(self): data = b"DF{" G = nx.from_graph6_bytes(data) - assert_nodes_equal(G.nodes(), [0, 1, 2, 3, 4]) - assert_edges_equal( + assert nodes_equal(G.nodes(), [0, 1, 2, 3, 4]) + assert edges_equal( G.edges(), [(0, 3), (0, 4), (1, 3), (1, 4), (2, 3), (2, 4), (3, 4)] ) @@ -30,8 +29,8 @@ class TestFromGraph6Bytes: G = nx.from_graph6_bytes(data) fh = BytesIO(data) Gin = nx.read_graph6(fh) - assert_nodes_equal(G.nodes(), Gin.nodes()) - assert_edges_equal(G.edges(), Gin.edges()) + assert nodes_equal(G.nodes(), Gin.nodes()) + assert edges_equal(G.edges(), Gin.edges()) class TestReadGraph6: @@ -100,8 +99,8 @@ class TestWriteGraph6: nx.write_graph6(G, f) f.seek(0) H = nx.read_graph6(f) - assert_nodes_equal(G.nodes(), H.nodes()) - assert_edges_equal(G.edges(), H.edges()) + assert nodes_equal(G.nodes(), H.nodes()) + assert edges_equal(G.edges(), H.edges()) def test_write_path(self): with tempfile.NamedTemporaryFile() as f: diff --git a/networkx/readwrite/tests/test_graphml.py b/networkx/readwrite/tests/test_graphml.py index 75f1a91b..fbbc1953 100644 --- a/networkx/readwrite/tests/test_graphml.py +++ b/networkx/readwrite/tests/test_graphml.py @@ -1,6 +1,6 @@ import pytest import networkx as nx -from networkx.testing.utils import assert_edges_equal, assert_nodes_equal +from networkx.utils import nodes_equal, edges_equal from networkx.readwrite.graphml import GraphMLWriter import io import tempfile @@ -293,51 +293,51 @@ class TestReadGraphML(BaseGraphML): def test_read_simple_undirected_graphml(self): G = self.simple_undirected_graph H = nx.read_graphml(self.simple_undirected_fh) - assert_nodes_equal(G.nodes(), H.nodes()) - assert_edges_equal(G.edges(), H.edges()) + assert nodes_equal(G.nodes(), H.nodes()) + assert edges_equal(G.edges(), H.edges()) self.simple_undirected_fh.seek(0) PG = nx.parse_graphml(self.simple_undirected_data) - assert_nodes_equal(G.nodes(), PG.nodes()) - assert_edges_equal(G.edges(), PG.edges()) + assert nodes_equal(G.nodes(), PG.nodes()) + assert edges_equal(G.edges(), PG.edges()) def test_read_undirected_multigraph_graphml(self): G = self.undirected_multigraph H = nx.read_graphml(self.undirected_multigraph_fh) - assert_nodes_equal(G.nodes(), H.nodes()) - assert_edges_equal(G.edges(), H.edges()) + assert nodes_equal(G.nodes(), H.nodes()) + assert edges_equal(G.edges(), H.edges()) self.undirected_multigraph_fh.seek(0) PG = nx.parse_graphml(self.undirected_multigraph_data) - assert_nodes_equal(G.nodes(), PG.nodes()) - assert_edges_equal(G.edges(), PG.edges()) + assert nodes_equal(G.nodes(), PG.nodes()) + assert edges_equal(G.edges(), PG.edges()) def test_read_undirected_multigraph_no_multiedge_graphml(self): G = self.undirected_multigraph_no_multiedge H = nx.read_graphml(self.undirected_multigraph_no_multiedge_fh) - assert_nodes_equal(G.nodes(), H.nodes()) - assert_edges_equal(G.edges(), H.edges()) + assert nodes_equal(G.nodes(), H.nodes()) + assert edges_equal(G.edges(), H.edges()) self.undirected_multigraph_no_multiedge_fh.seek(0) PG = nx.parse_graphml(self.undirected_multigraph_no_multiedge_data) - assert_nodes_equal(G.nodes(), PG.nodes()) - assert_edges_equal(G.edges(), PG.edges()) + assert nodes_equal(G.nodes(), PG.nodes()) + assert edges_equal(G.edges(), PG.edges()) def test_read_undirected_multigraph_only_ids_for_multiedges_graphml(self): G = self.multigraph_only_ids_for_multiedges H = nx.read_graphml(self.multigraph_only_ids_for_multiedges_fh) - assert_nodes_equal(G.nodes(), H.nodes()) - assert_edges_equal(G.edges(), H.edges()) + assert nodes_equal(G.nodes(), H.nodes()) + assert edges_equal(G.edges(), H.edges()) self.multigraph_only_ids_for_multiedges_fh.seek(0) PG = nx.parse_graphml(self.multigraph_only_ids_for_multiedges_data) - assert_nodes_equal(G.nodes(), PG.nodes()) - assert_edges_equal(G.edges(), PG.edges()) + assert nodes_equal(G.nodes(), PG.nodes()) + assert edges_equal(G.edges(), PG.edges()) def test_read_attribute_graphml(self): G = self.attribute_graph H = nx.read_graphml(self.attribute_fh) - assert_nodes_equal(G.nodes(True), sorted(H.nodes(data=True))) + assert nodes_equal(G.nodes(True), sorted(H.nodes(data=True))) ge = sorted(G.edges(data=True)) he = sorted(H.edges(data=True)) for a, b in zip(ge, he): @@ -494,7 +494,7 @@ class TestReadGraphML(BaseGraphML): nx.write_graphml(G, fh) fh.seek(0) H = nx.read_graphml(fh, node_type=int) - assert_edges_equal(G.edges(data=True, keys=True), H.edges(data=True, keys=True)) + assert edges_equal(G.edges(data=True, keys=True), H.edges(data=True, keys=True)) assert G._adj == H._adj Gadj = { @@ -1073,9 +1073,9 @@ class TestWriteGraphML(BaseGraphML): H = nx.read_graphml(fh) fh.seek(0) - assert_nodes_equal(G.nodes(), H.nodes()) - assert_edges_equal(G.edges(), H.edges()) - assert_edges_equal(G.edges(data=True), H.edges(data=True)) + assert nodes_equal(G.nodes(), H.nodes()) + assert edges_equal(G.edges(), H.edges()) + assert edges_equal(G.edges(data=True), H.edges(data=True)) self.attribute_named_key_ids_fh.seek(0) xml = parse(fh) @@ -1118,9 +1118,9 @@ class TestWriteGraphML(BaseGraphML): H = nx.read_graphml(fh) fh.seek(0) - assert_nodes_equal(G.nodes(), H.nodes()) - assert_edges_equal(G.edges(), H.edges()) - assert_edges_equal(G.edges(data=True), H.edges(data=True)) + assert nodes_equal(G.nodes(), H.nodes()) + assert edges_equal(G.edges(), H.edges()) + assert edges_equal(G.edges(data=True), H.edges(data=True)) self.attribute_numeric_type_fh.seek(0) xml = parse(fh) @@ -1146,7 +1146,7 @@ class TestWriteGraphML(BaseGraphML): self.writer(G, fname) H = nx.read_graphml(fname) assert H.is_multigraph() - assert_edges_equal(G.edges(keys=True), H.edges(keys=True)) + assert edges_equal(G.edges(keys=True), H.edges(keys=True)) assert G._adj == H._adj os.close(fd) os.unlink(fname) @@ -1162,8 +1162,8 @@ class TestWriteGraphML(BaseGraphML): self.writer(G, fh) fh.seek(0) H = nx.read_graphml(fh, node_type=int) - assert_nodes_equal(G.nodes(), H.nodes()) - assert_edges_equal(G.edges(), H.edges()) + assert nodes_equal(G.nodes(), H.nodes()) + assert edges_equal(G.edges(), H.edges()) assert G.graph == H.graph def test_mixed_type_attributes(self): diff --git a/networkx/readwrite/tests/test_p2g.py b/networkx/readwrite/tests/test_p2g.py index 0b1a910f..93ab1381 100644 --- a/networkx/readwrite/tests/test_p2g.py +++ b/networkx/readwrite/tests/test_p2g.py @@ -1,7 +1,7 @@ import networkx as nx import io from networkx.readwrite.p2g import read_p2g, write_p2g -from networkx.testing import assert_edges_equal +from networkx.utils import edges_equal class TestP2G: @@ -29,7 +29,7 @@ c assert G.name == "name" assert sorted(G) == ["a", "b", "c"] edges = [(str(u), str(v)) for u, v in G.edges()] - assert_edges_equal(G.edges(), [("a", "c"), ("a", "b"), ("c", "a"), ("c", "c")]) + assert edges_equal(G.edges(), [("a", "c"), ("a", "b"), ("c", "a"), ("c", "c")]) def test_write_p2g(self): s = b"""foo @@ -58,4 +58,4 @@ c write_p2g(G, fh) fh.seek(0) H = read_p2g(fh) - assert_edges_equal(G.edges(), H.edges()) + assert edges_equal(G.edges(), H.edges()) diff --git a/networkx/readwrite/tests/test_pajek.py b/networkx/readwrite/tests/test_pajek.py index 7d7e4c48..d5b6f728 100644 --- a/networkx/readwrite/tests/test_pajek.py +++ b/networkx/readwrite/tests/test_pajek.py @@ -4,7 +4,7 @@ Pajek tests import networkx as nx import os import tempfile -from networkx.testing import assert_edges_equal, assert_nodes_equal +from networkx.utils import nodes_equal, edges_equal class TestPajek: @@ -39,12 +39,12 @@ class TestPajek: data = """*Vertices 2\n1 "1"\n2 "2"\n*Edges\n1 2\n2 1""" G = nx.parse_pajek(data) assert sorted(G.nodes()) == ["1", "2"] - assert_edges_equal(G.edges(), [("1", "2"), ("1", "2")]) + assert edges_equal(G.edges(), [("1", "2"), ("1", "2")]) def test_parse_pajek(self): G = nx.parse_pajek(self.data) assert sorted(G.nodes()) == ["A1", "Bb", "C", "D2"] - assert_edges_equal( + assert edges_equal( G.edges(), [ ("A1", "A1"), @@ -62,7 +62,7 @@ class TestPajek: G = nx.parse_pajek(data) assert set(G.nodes()) == {"one", "two", "three"} assert G.nodes["two"] == {"id": "2"} - assert_edges_equal( + assert edges_equal( set(G.edges()), {("one", "one"), ("two", "one"), ("two", "two"), ("two", "three")}, ) @@ -71,7 +71,7 @@ class TestPajek: G = nx.parse_pajek(self.data) Gin = nx.read_pajek(self.fname) assert sorted(G.nodes()) == sorted(Gin.nodes()) - assert_edges_equal(G.edges(), Gin.edges()) + assert edges_equal(G.edges(), Gin.edges()) assert self.G.graph == Gin.graph for n in G: assert G.nodes[n] == Gin.nodes[n] @@ -84,8 +84,8 @@ class TestPajek: nx.write_pajek(G, fh) fh.seek(0) H = nx.read_pajek(fh) - assert_nodes_equal(list(G), list(H)) - assert_edges_equal(list(G.edges()), list(H.edges())) + assert nodes_equal(list(G), list(H)) + assert edges_equal(list(G.edges()), list(H.edges())) # Graph name is left out for now, therefore it is not tested. # assert_equal(G.graph, H.graph) @@ -124,6 +124,6 @@ class TestPajek: nx.write_pajek(G, fh) fh.seek(0) H = nx.read_pajek(fh) - assert_nodes_equal(list(G), list(H)) - assert_edges_equal(list(G.edges()), list(H.edges())) + assert nodes_equal(list(G), list(H)) + assert edges_equal(list(G.edges()), list(H.edges())) assert G.graph == H.graph diff --git a/networkx/readwrite/tests/test_sparse6.py b/networkx/readwrite/tests/test_sparse6.py index 141d8230..ac694d65 100644 --- a/networkx/readwrite/tests/test_sparse6.py +++ b/networkx/readwrite/tests/test_sparse6.py @@ -3,19 +3,18 @@ import tempfile import pytest import networkx as nx -from networkx.testing.utils import assert_edges_equal -from networkx.testing.utils import assert_nodes_equal +from networkx.utils import nodes_equal, edges_equal class TestSparseGraph6: def test_from_sparse6_bytes(self): data = b":Q___eDcdFcDeFcE`GaJ`IaHbKNbLM" G = nx.from_sparse6_bytes(data) - assert_nodes_equal( + assert nodes_equal( sorted(G.nodes()), [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17], ) - assert_edges_equal( + assert edges_equal( G.edges(), [ (0, 1), @@ -61,8 +60,8 @@ class TestSparseGraph6: G = nx.from_sparse6_bytes(data) fh = BytesIO(data) Gin = nx.read_sparse6(fh) - assert_nodes_equal(G.nodes(), Gin.nodes()) - assert_edges_equal(G.edges(), Gin.edges()) + assert nodes_equal(G.nodes(), Gin.nodes()) + assert edges_equal(G.edges(), Gin.edges()) def test_read_many_graph6(self): # Read many graphs into list @@ -71,7 +70,7 @@ class TestSparseGraph6: glist = nx.read_sparse6(fh) assert len(glist) == 2 for G in glist: - assert_nodes_equal( + assert nodes_equal( G.nodes(), [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17], ) @@ -152,7 +151,7 @@ class TestWriteSparse6: gstr = gstr.getvalue().rstrip() g2 = nx.from_sparse6_bytes(gstr) assert g2.order() == g.order() - assert_edges_equal(g2.edges(), g.edges()) + assert edges_equal(g2.edges(), g.edges()) def test_no_directed_graphs(self): with pytest.raises(nx.NetworkXNotImplemented): diff --git a/networkx/testing/utils.py b/networkx/testing/utils.py index 68faf230..b16c3c1c 100644 --- a/networkx/testing/utils.py +++ b/networkx/testing/utils.py @@ -1,3 +1,6 @@ +import warnings +from networkx.utils import nodes_equal, edges_equal, graphs_equal + __all__ = [ "assert_nodes_equal", "assert_edges_equal", @@ -7,8 +10,6 @@ __all__ = [ def almost_equal(x, y, places=7): - import warnings - warnings.warn( ( "`almost_equal` is deprecated and will be removed in version 3.0.\n" @@ -20,55 +21,33 @@ def almost_equal(x, y, places=7): def assert_nodes_equal(nodes1, nodes2): - # Assumes iterables of nodes, or (node,datadict) tuples - nlist1 = list(nodes1) - nlist2 = list(nodes2) - try: - d1 = dict(nlist1) - d2 = dict(nlist2) - except (ValueError, TypeError): - d1 = dict.fromkeys(nlist1) - d2 = dict.fromkeys(nlist2) - assert d1 == d2 + warnings.warn( + ( + "`assert_nodes_equal` is deprecated and will be removed in version 3.0.\n" + "Use `from networkx.utils import nodes_equal` and `assert nodes_equal` instead.\n" + ), + DeprecationWarning, + ) + assert nodes_equal(nodes1, nodes2) def assert_edges_equal(edges1, edges2): - # Assumes iterables with u,v nodes as - # edge tuples (u,v), or - # edge tuples with data dicts (u,v,d), or - # edge tuples with keys and data dicts (u,v,k, d) - from collections import defaultdict - - d1 = defaultdict(dict) - d2 = defaultdict(dict) - c1 = 0 - for c1, e in enumerate(edges1): - u, v = e[0], e[1] - data = [e[2:]] - if v in d1[u]: - data = d1[u][v] + data - d1[u][v] = data - d1[v][u] = data - c2 = 0 - for c2, e in enumerate(edges2): - u, v = e[0], e[1] - data = [e[2:]] - if v in d2[u]: - data = d2[u][v] + data - d2[u][v] = data - d2[v][u] = data - assert c1 == c2 - # can check one direction because lengths are the same. - for n, nbrdict in d1.items(): - for nbr, datalist in nbrdict.items(): - assert n in d2 - assert nbr in d2[n] - d2datalist = d2[n][nbr] - for data in datalist: - assert datalist.count(data) == d2datalist.count(data) + warnings.warn( + ( + "`assert_edges_equal` is deprecated and will be removed in version 3.0.\n" + "Use `from networkx.utils import edges_equal` and `assert edges_equal` instead.\n" + ), + DeprecationWarning, + ) + assert edges_equal(edges1, edges2) def assert_graphs_equal(graph1, graph2): - assert graph1.adj == graph2.adj - assert graph1.nodes == graph2.nodes - assert graph1.graph == graph2.graph + warnings.warn( + ( + "`assert_graphs_equal` is deprecated and will be removed in version 3.0.\n" + "Use `from networkx.utils import graphs_equal` and `assert graphs_equal` instead.\n" + ), + DeprecationWarning, + ) + assert graphs_equal(graph1, graph2) diff --git a/networkx/tests/test_convert.py b/networkx/tests/test_convert.py index dad757c0..a99b6001 100644 --- a/networkx/tests/test_convert.py +++ b/networkx/tests/test_convert.py @@ -1,7 +1,7 @@ import pytest import networkx as nx -from networkx.testing import assert_nodes_equal, assert_edges_equal, assert_graphs_equal +from networkx.utils import nodes_equal, edges_equal, graphs_equal from networkx.convert import ( to_networkx_graph, to_dict_of_dicts, @@ -27,11 +27,11 @@ class TestConvert: # Dict of [dicts, lists] GG = source(dod) - assert_graphs_equal(G, GG) + assert graphs_equal(G, GG) GW = to_networkx_graph(dod) - assert_graphs_equal(G, GW) + assert graphs_equal(G, GW) GI = nx.Graph(dod) - assert_graphs_equal(G, GI) + assert graphs_equal(G, GI) # With nodelist keyword P4 = nx.path_graph(4) @@ -40,7 +40,7 @@ class TestConvert: P3.graph = {} dod = dest(P4, nodelist=[0, 1, 2]) Gdod = nx.Graph(dod) - assert_graphs_equal(Gdod, P3) + assert graphs_equal(Gdod, P3) def test_exceptions(self): # NX graph @@ -78,14 +78,14 @@ class TestConvert: # Dict of [dicts, lists] dod = dest(G) GG = source(dod) - assert_nodes_equal(sorted(G.nodes()), sorted(GG.nodes())) - assert_edges_equal(sorted(G.edges()), sorted(GG.edges())) + assert nodes_equal(sorted(G.nodes()), sorted(GG.nodes())) + assert edges_equal(sorted(G.edges()), sorted(GG.edges())) GW = to_networkx_graph(dod) - assert_nodes_equal(sorted(G.nodes()), sorted(GW.nodes())) - assert_edges_equal(sorted(G.edges()), sorted(GW.edges())) + assert nodes_equal(sorted(G.nodes()), sorted(GW.nodes())) + assert edges_equal(sorted(G.edges()), sorted(GW.edges())) GI = nx.Graph(dod) - assert_nodes_equal(sorted(G.nodes()), sorted(GI.nodes())) - assert_edges_equal(sorted(G.edges()), sorted(GI.edges())) + assert nodes_equal(sorted(G.nodes()), sorted(GI.nodes())) + assert edges_equal(sorted(G.edges()), sorted(GI.edges())) G = cycle_graph(10, create_using=nx.DiGraph) dod = dest(G) @@ -108,11 +108,11 @@ class TestConvert: # Dict of dicts dod = to_dict_of_dicts(G) GG = from_dict_of_dicts(dod, create_using=nx.Graph) - assert_nodes_equal(sorted(G.nodes()), sorted(GG.nodes())) - assert_edges_equal(sorted(G.edges()), sorted(GG.edges())) + assert nodes_equal(sorted(G.nodes()), sorted(GG.nodes())) + assert edges_equal(sorted(G.edges()), sorted(GG.edges())) GW = to_networkx_graph(dod, create_using=nx.Graph) - assert_nodes_equal(sorted(G.nodes()), sorted(GW.nodes())) - assert_edges_equal(sorted(G.edges()), sorted(GW.edges())) + assert nodes_equal(sorted(G.nodes()), sorted(GW.nodes())) + assert edges_equal(sorted(G.edges()), sorted(GW.edges())) GI = nx.Graph(dod) assert sorted(G.nodes()) == sorted(GI.nodes()) assert sorted(G.edges()) == sorted(GI.edges()) @@ -122,14 +122,14 @@ class TestConvert: GG = from_dict_of_lists(dol, create_using=nx.Graph) # dict of lists throws away edge data so set it to none enone = [(u, v, {}) for (u, v, d) in G.edges(data=True)] - assert_nodes_equal(sorted(G.nodes()), sorted(GG.nodes())) - assert_edges_equal(enone, sorted(GG.edges(data=True))) + assert nodes_equal(sorted(G.nodes()), sorted(GG.nodes())) + assert edges_equal(enone, sorted(GG.edges(data=True))) GW = to_networkx_graph(dol, create_using=nx.Graph) - assert_nodes_equal(sorted(G.nodes()), sorted(GW.nodes())) - assert_edges_equal(enone, sorted(GW.edges(data=True))) + assert nodes_equal(sorted(G.nodes()), sorted(GW.nodes())) + assert edges_equal(enone, sorted(GW.edges(data=True))) GI = nx.Graph(dol) - assert_nodes_equal(sorted(G.nodes()), sorted(GI.nodes())) - assert_edges_equal(enone, sorted(GI.edges(data=True))) + assert nodes_equal(sorted(G.nodes()), sorted(GI.nodes())) + assert edges_equal(enone, sorted(GI.edges(data=True))) def test_with_multiedges_self_loops(self): G = cycle_graph(10) @@ -149,14 +149,14 @@ class TestConvert: # with self loops, OK dod = to_dict_of_dicts(XGS) GG = from_dict_of_dicts(dod, create_using=nx.Graph) - assert_nodes_equal(XGS.nodes(), GG.nodes()) - assert_edges_equal(XGS.edges(), GG.edges()) + assert nodes_equal(XGS.nodes(), GG.nodes()) + assert edges_equal(XGS.edges(), GG.edges()) GW = to_networkx_graph(dod, create_using=nx.Graph) - assert_nodes_equal(XGS.nodes(), GW.nodes()) - assert_edges_equal(XGS.edges(), GW.edges()) + assert nodes_equal(XGS.nodes(), GW.nodes()) + assert edges_equal(XGS.edges(), GW.edges()) GI = nx.Graph(dod) - assert_nodes_equal(XGS.nodes(), GI.nodes()) - assert_edges_equal(XGS.edges(), GI.edges()) + assert nodes_equal(XGS.nodes(), GI.nodes()) + assert edges_equal(XGS.edges(), GI.edges()) # Dict of lists # with self loops, OK @@ -164,71 +164,71 @@ class TestConvert: GG = from_dict_of_lists(dol, create_using=nx.Graph) # dict of lists throws away edge data so set it to none enone = [(u, v, {}) for (u, v, d) in XGS.edges(data=True)] - assert_nodes_equal(sorted(XGS.nodes()), sorted(GG.nodes())) - assert_edges_equal(enone, sorted(GG.edges(data=True))) + assert nodes_equal(sorted(XGS.nodes()), sorted(GG.nodes())) + assert edges_equal(enone, sorted(GG.edges(data=True))) GW = to_networkx_graph(dol, create_using=nx.Graph) - assert_nodes_equal(sorted(XGS.nodes()), sorted(GW.nodes())) - assert_edges_equal(enone, sorted(GW.edges(data=True))) + assert nodes_equal(sorted(XGS.nodes()), sorted(GW.nodes())) + assert edges_equal(enone, sorted(GW.edges(data=True))) GI = nx.Graph(dol) - assert_nodes_equal(sorted(XGS.nodes()), sorted(GI.nodes())) - assert_edges_equal(enone, sorted(GI.edges(data=True))) + assert nodes_equal(sorted(XGS.nodes()), sorted(GI.nodes())) + assert edges_equal(enone, sorted(GI.edges(data=True))) # Dict of dicts # with multiedges, OK dod = to_dict_of_dicts(XGM) GG = from_dict_of_dicts(dod, create_using=nx.MultiGraph, multigraph_input=True) - assert_nodes_equal(sorted(XGM.nodes()), sorted(GG.nodes())) - assert_edges_equal(sorted(XGM.edges()), sorted(GG.edges())) + assert nodes_equal(sorted(XGM.nodes()), sorted(GG.nodes())) + assert edges_equal(sorted(XGM.edges()), sorted(GG.edges())) GW = to_networkx_graph(dod, create_using=nx.MultiGraph, multigraph_input=True) - assert_nodes_equal(sorted(XGM.nodes()), sorted(GW.nodes())) - assert_edges_equal(sorted(XGM.edges()), sorted(GW.edges())) + assert nodes_equal(sorted(XGM.nodes()), sorted(GW.nodes())) + assert edges_equal(sorted(XGM.edges()), sorted(GW.edges())) GI = nx.MultiGraph(dod) # convert can't tell whether to duplicate edges! - assert_nodes_equal(sorted(XGM.nodes()), sorted(GI.nodes())) + assert nodes_equal(sorted(XGM.nodes()), sorted(GI.nodes())) # assert_not_equal(sorted(XGM.edges()), sorted(GI.edges())) assert not sorted(XGM.edges()) == sorted(GI.edges()) GE = from_dict_of_dicts(dod, create_using=nx.MultiGraph, multigraph_input=False) - assert_nodes_equal(sorted(XGM.nodes()), sorted(GE.nodes())) + assert nodes_equal(sorted(XGM.nodes()), sorted(GE.nodes())) assert sorted(XGM.edges()) != sorted(GE.edges()) GI = nx.MultiGraph(XGM) - assert_nodes_equal(sorted(XGM.nodes()), sorted(GI.nodes())) - assert_edges_equal(sorted(XGM.edges()), sorted(GI.edges())) + assert nodes_equal(sorted(XGM.nodes()), sorted(GI.nodes())) + assert edges_equal(sorted(XGM.edges()), sorted(GI.edges())) GM = nx.MultiGraph(G) - assert_nodes_equal(sorted(GM.nodes()), sorted(G.nodes())) - assert_edges_equal(sorted(GM.edges()), sorted(G.edges())) + assert nodes_equal(sorted(GM.nodes()), sorted(G.nodes())) + assert edges_equal(sorted(GM.edges()), sorted(G.edges())) # Dict of lists # with multiedges, OK, but better write as DiGraph else you'll # get double edges dol = to_dict_of_lists(G) GG = from_dict_of_lists(dol, create_using=nx.MultiGraph) - assert_nodes_equal(sorted(G.nodes()), sorted(GG.nodes())) - assert_edges_equal(sorted(G.edges()), sorted(GG.edges())) + assert nodes_equal(sorted(G.nodes()), sorted(GG.nodes())) + assert edges_equal(sorted(G.edges()), sorted(GG.edges())) GW = to_networkx_graph(dol, create_using=nx.MultiGraph) - assert_nodes_equal(sorted(G.nodes()), sorted(GW.nodes())) - assert_edges_equal(sorted(G.edges()), sorted(GW.edges())) + assert nodes_equal(sorted(G.nodes()), sorted(GW.nodes())) + assert edges_equal(sorted(G.edges()), sorted(GW.edges())) GI = nx.MultiGraph(dol) - assert_nodes_equal(sorted(G.nodes()), sorted(GI.nodes())) - assert_edges_equal(sorted(G.edges()), sorted(GI.edges())) + assert nodes_equal(sorted(G.nodes()), sorted(GI.nodes())) + assert edges_equal(sorted(G.edges()), sorted(GI.edges())) def test_edgelists(self): P = nx.path_graph(4) e = [(0, 1), (1, 2), (2, 3)] G = nx.Graph(e) - assert_nodes_equal(sorted(G.nodes()), sorted(P.nodes())) - assert_edges_equal(sorted(G.edges()), sorted(P.edges())) - assert_edges_equal(sorted(G.edges(data=True)), sorted(P.edges(data=True))) + assert nodes_equal(sorted(G.nodes()), sorted(P.nodes())) + assert edges_equal(sorted(G.edges()), sorted(P.edges())) + assert edges_equal(sorted(G.edges(data=True)), sorted(P.edges(data=True))) e = [(0, 1, {}), (1, 2, {}), (2, 3, {})] G = nx.Graph(e) - assert_nodes_equal(sorted(G.nodes()), sorted(P.nodes())) - assert_edges_equal(sorted(G.edges()), sorted(P.edges())) - assert_edges_equal(sorted(G.edges(data=True)), sorted(P.edges(data=True))) + assert nodes_equal(sorted(G.nodes()), sorted(P.nodes())) + assert edges_equal(sorted(G.edges()), sorted(P.edges())) + assert edges_equal(sorted(G.edges(data=True)), sorted(P.edges(data=True))) e = ((n, n + 1) for n in range(3)) G = nx.Graph(e) - assert_nodes_equal(sorted(G.nodes()), sorted(P.nodes())) - assert_edges_equal(sorted(G.edges()), sorted(P.edges())) - assert_edges_equal(sorted(G.edges(data=True)), sorted(P.edges(data=True))) + assert nodes_equal(sorted(G.nodes()), sorted(P.nodes())) + assert edges_equal(sorted(G.edges()), sorted(P.edges())) + assert edges_equal(sorted(G.edges(data=True)), sorted(P.edges(data=True))) def test_directed_to_undirected(self): edges1 = [(0, 1), (1, 2), (2, 0)] @@ -260,7 +260,7 @@ class TestConvert: def test_to_edgelist(self): G = nx.Graph([(1, 1)]) elist = nx.to_edgelist(G, nodelist=list(G)) - assert_edges_equal(G.edges(data=True), elist) + assert edges_equal(G.edges(data=True), elist) def test_custom_node_attr_dict_safekeeping(self): class custom_dict(dict): diff --git a/networkx/tests/test_convert_numpy.py b/networkx/tests/test_convert_numpy.py index b62f823f..f155de35 100644 --- a/networkx/tests/test_convert_numpy.py +++ b/networkx/tests/test_convert_numpy.py @@ -4,7 +4,7 @@ np = pytest.importorskip("numpy") import networkx as nx from networkx.generators.classic import barbell_graph, cycle_graph, path_graph -from networkx.testing.utils import assert_graphs_equal +from networkx.utils import graphs_equal def test_to_numpy_matrix_deprecation(): @@ -201,9 +201,9 @@ class TestConvertNumpyMatrix: expected.add_weighted_edges_from([(u, v, 1) for (u, v) in edges]) expected.add_edge(1, 1, weight=2) actual = nx.from_numpy_matrix(A, parallel_edges=True, create_using=nx.DiGraph) - assert_graphs_equal(actual, expected) + assert graphs_equal(actual, expected) actual = nx.from_numpy_matrix(A, parallel_edges=False, create_using=nx.DiGraph) - assert_graphs_equal(actual, expected) + assert graphs_equal(actual, expected) # Now each integer entry in the adjacency matrix is interpreted as the # number of parallel edges in the graph if the appropriate keyword # argument is specified. @@ -213,7 +213,7 @@ class TestConvertNumpyMatrix: actual = nx.from_numpy_matrix( A, parallel_edges=True, create_using=nx.MultiDiGraph ) - assert_graphs_equal(actual, expected) + assert graphs_equal(actual, expected) expected = nx.MultiDiGraph() expected.add_edges_from(set(edges), weight=1) # The sole self-loop (edge 0) on vertex 1 should have weight 2. @@ -221,7 +221,7 @@ class TestConvertNumpyMatrix: actual = nx.from_numpy_matrix( A, parallel_edges=False, create_using=nx.MultiDiGraph ) - assert_graphs_equal(actual, expected) + assert graphs_equal(actual, expected) def test_symmetric(self): """Tests that a symmetric matrix has edges added only once to an @@ -232,7 +232,7 @@ class TestConvertNumpyMatrix: G = nx.from_numpy_matrix(A, create_using=nx.MultiGraph) expected = nx.MultiGraph() expected.add_edge(0, 1, weight=1) - assert_graphs_equal(G, expected) + assert graphs_equal(G, expected) def test_dtype_int_graph(self): """Test that setting dtype int actually gives an integer matrix. @@ -375,9 +375,9 @@ class TestConvertNumpyArray: expected.add_weighted_edges_from([(u, v, 1) for (u, v) in edges]) expected.add_edge(1, 1, weight=2) actual = nx.from_numpy_array(A, parallel_edges=True, create_using=nx.DiGraph) - assert_graphs_equal(actual, expected) + assert graphs_equal(actual, expected) actual = nx.from_numpy_array(A, parallel_edges=False, create_using=nx.DiGraph) - assert_graphs_equal(actual, expected) + assert graphs_equal(actual, expected) # Now each integer entry in the adjacency matrix is interpreted as the # number of parallel edges in the graph if the appropriate keyword # argument is specified. @@ -387,7 +387,7 @@ class TestConvertNumpyArray: actual = nx.from_numpy_array( A, parallel_edges=True, create_using=nx.MultiDiGraph ) - assert_graphs_equal(actual, expected) + assert graphs_equal(actual, expected) expected = nx.MultiDiGraph() expected.add_edges_from(set(edges), weight=1) # The sole self-loop (edge 0) on vertex 1 should have weight 2. @@ -395,7 +395,7 @@ class TestConvertNumpyArray: actual = nx.from_numpy_array( A, parallel_edges=False, create_using=nx.MultiDiGraph ) - assert_graphs_equal(actual, expected) + assert graphs_equal(actual, expected) def test_symmetric(self): """Tests that a symmetric array has edges added only once to an @@ -406,7 +406,7 @@ class TestConvertNumpyArray: G = nx.from_numpy_array(A, create_using=nx.MultiGraph) expected = nx.MultiGraph() expected.add_edge(0, 1, weight=1) - assert_graphs_equal(G, expected) + assert graphs_equal(G, expected) def test_dtype_int_graph(self): """Test that setting dtype int actually gives an integer array. diff --git a/networkx/tests/test_convert_pandas.py b/networkx/tests/test_convert_pandas.py index 1ad735a7..93be091f 100644 --- a/networkx/tests/test_convert_pandas.py +++ b/networkx/tests/test_convert_pandas.py @@ -1,8 +1,6 @@ import pytest import networkx as nx -from networkx.testing import assert_nodes_equal -from networkx.testing import assert_edges_equal -from networkx.testing import assert_graphs_equal +from networkx.utils import nodes_equal, edges_equal, graphs_equal np = pytest.importorskip("numpy") pd = pytest.importorskip("pandas") @@ -39,12 +37,12 @@ class TestConvertPandas: ] ) G = nx.from_pandas_edgelist(self.df, 0, "b", True) - assert_graphs_equal(G, Gtrue) + assert graphs_equal(G, Gtrue) # MultiGraph MGtrue = nx.MultiGraph(Gtrue) MGtrue.add_edge("A", "D", cost=16, weight=4) MG = nx.from_pandas_edgelist(self.mdf, 0, "b", True, nx.MultiGraph()) - assert_graphs_equal(MG, MGtrue) + assert graphs_equal(MG, MGtrue) def test_from_edgelist_multi_attr(self): Gtrue = nx.Graph( @@ -55,7 +53,7 @@ class TestConvertPandas: ] ) G = nx.from_pandas_edgelist(self.df, 0, "b", ["weight", "cost"]) - assert_graphs_equal(G, Gtrue) + assert graphs_equal(G, Gtrue) def test_from_edgelist_multi_attr_incl_target(self): Gtrue = nx.Graph( @@ -66,7 +64,7 @@ class TestConvertPandas: ] ) G = nx.from_pandas_edgelist(self.df, 0, "b", [0, "b", "weight"]) - assert_graphs_equal(G, Gtrue) + assert graphs_equal(G, Gtrue) def test_from_edgelist_multidigraph_and_edge_attr(self): # example from issue #2374 @@ -101,8 +99,8 @@ class TestConvertPandas: edge_attr=["St", "Co", "Mi"], create_using=nx.MultiDiGraph, ) - assert_graphs_equal(G1, Gtrue) - assert_graphs_equal(G2, Gtrue) + assert graphs_equal(G1, Gtrue) + assert graphs_equal(G2, Gtrue) def test_from_edgelist_one_attr(self): Gtrue = nx.Graph( @@ -113,7 +111,7 @@ class TestConvertPandas: ] ) G = nx.from_pandas_edgelist(self.df, 0, "b", "weight") - assert_graphs_equal(G, Gtrue) + assert graphs_equal(G, Gtrue) def test_from_edgelist_int_attr_name(self): # note: this also tests that edge_attr can be `source` @@ -121,7 +119,7 @@ class TestConvertPandas: [("E", "C", {0: "C"}), ("B", "A", {0: "B"}), ("A", "D", {0: "A"})] ) G = nx.from_pandas_edgelist(self.df, 0, "b", 0) - assert_graphs_equal(G, Gtrue) + assert graphs_equal(G, Gtrue) def test_from_edgelist_invalid_attr(self): pytest.raises( @@ -148,7 +146,7 @@ class TestConvertPandas: def test_from_edgelist_no_attr(self): Gtrue = nx.Graph([("E", "C", {}), ("B", "A", {}), ("A", "D", {})]) G = nx.from_pandas_edgelist(self.df, 0, "b") - assert_graphs_equal(G, Gtrue) + assert graphs_equal(G, Gtrue) def test_from_edgelist(self): # Pandas DataFrame @@ -162,11 +160,11 @@ class TestConvertPandas: edges = pd.DataFrame({"source": source, "target": target, "weight": weight}) GG = nx.from_pandas_edgelist(edges, edge_attr="weight") - assert_nodes_equal(G.nodes(), GG.nodes()) - assert_edges_equal(G.edges(), GG.edges()) + assert nodes_equal(G.nodes(), GG.nodes()) + assert edges_equal(G.edges(), GG.edges()) GW = nx.to_networkx_graph(edges, create_using=nx.Graph) - assert_nodes_equal(G.nodes(), GW.nodes()) - assert_edges_equal(G.edges(), GW.edges()) + assert nodes_equal(G.nodes(), GW.nodes()) + assert edges_equal(G.edges(), GW.edges()) def test_to_edgelist_default_source_or_target_col_exists(self): @@ -223,13 +221,13 @@ class TestConvertPandas: Gtrue = graph([(1, 1), (1, 2)]) df = nx.to_pandas_edgelist(Gtrue) G = nx.from_pandas_edgelist(df, create_using=graph) - assert_graphs_equal(Gtrue, G) + assert graphs_equal(Gtrue, G) # adjacency adj = {1: {1: {"weight": 1}, 2: {"weight": 1}}, 2: {1: {"weight": 1}}} Gtrue = graph(adj) df = nx.to_pandas_adjacency(Gtrue, dtype=int) G = nx.from_pandas_adjacency(df, create_using=graph) - assert_graphs_equal(Gtrue, G) + assert graphs_equal(Gtrue, G) def test_from_adjacency_named(self): # example from issue #3105 @@ -271,7 +269,7 @@ class TestConvertPandas: edge_key="attr1", create_using=nx.MultiGraph(), ) - assert_graphs_equal(G, Gtrue) + assert graphs_equal(G, Gtrue) df_roundtrip = nx.to_pandas_edgelist(G, edge_key="attr1") df_roundtrip = df_roundtrip.sort_values("attr1") @@ -289,7 +287,7 @@ class TestConvertPandas: ] ) G = nx.from_pandas_edgelist(self.df, 0, "b", True, edge_key="weight") - assert_graphs_equal(G, Gtrue) + assert graphs_equal(G, Gtrue) def test_nonexisting_edgekey_raises(self): with pytest.raises(nx.exception.NetworkXError): diff --git a/networkx/tests/test_convert_scipy.py b/networkx/tests/test_convert_scipy.py index c246152a..cf4fa818 100644 --- a/networkx/tests/test_convert_scipy.py +++ b/networkx/tests/test_convert_scipy.py @@ -5,7 +5,7 @@ sp = pytest.importorskip("scipy") import scipy.sparse # call as sp.sparse import networkx as nx -from networkx.testing import assert_graphs_equal +from networkx.utils import graphs_equal from networkx.generators.classic import barbell_graph, cycle_graph, path_graph @@ -230,11 +230,11 @@ class TestConvertScipy: actual = nx.from_scipy_sparse_matrix( A, parallel_edges=True, create_using=nx.DiGraph ) - assert_graphs_equal(actual, expected) + assert graphs_equal(actual, expected) actual = nx.from_scipy_sparse_matrix( A, parallel_edges=False, create_using=nx.DiGraph ) - assert_graphs_equal(actual, expected) + assert graphs_equal(actual, expected) # Now each integer entry in the adjacency matrix is interpreted as the # number of parallel edges in the graph if the appropriate keyword # argument is specified. @@ -244,7 +244,7 @@ class TestConvertScipy: actual = nx.from_scipy_sparse_matrix( A, parallel_edges=True, create_using=nx.MultiDiGraph ) - assert_graphs_equal(actual, expected) + assert graphs_equal(actual, expected) expected = nx.MultiDiGraph() expected.add_edges_from(set(edges), weight=1) # The sole self-loop (edge 0) on vertex 1 should have weight 2. @@ -252,7 +252,7 @@ class TestConvertScipy: actual = nx.from_scipy_sparse_matrix( A, parallel_edges=False, create_using=nx.MultiDiGraph ) - assert_graphs_equal(actual, expected) + assert graphs_equal(actual, expected) def test_symmetric(self): """Tests that a symmetric matrix has edges added only once to an @@ -264,7 +264,7 @@ class TestConvertScipy: G = nx.from_scipy_sparse_matrix(A, create_using=nx.MultiGraph) expected = nx.MultiGraph() expected.add_edge(0, 1, weight=1) - assert_graphs_equal(G, expected) + assert graphs_equal(G, expected) @pytest.mark.parametrize("sparse_format", ("csr", "csc", "dok")) @@ -283,4 +283,4 @@ def test_from_scipy_sparse_matrix_formats(sparse_format): ] ) A = sp.sparse.coo_matrix([[0, 3, 2], [3, 0, 1], [2, 1, 0]]).asformat(sparse_format) - assert_graphs_equal(expected, nx.from_scipy_sparse_matrix(A)) + assert graphs_equal(expected, nx.from_scipy_sparse_matrix(A)) diff --git a/networkx/tests/test_relabel.py b/networkx/tests/test_relabel.py index c4c6e9bc..20118bb0 100644 --- a/networkx/tests/test_relabel.py +++ b/networkx/tests/test_relabel.py @@ -1,7 +1,7 @@ import pytest import networkx as nx from networkx.generators.classic import empty_graph -from networkx.testing import assert_nodes_equal, assert_edges_equal +from networkx.utils import nodes_equal, edges_equal class TestRelabel: @@ -29,7 +29,7 @@ class TestRelabel: degH = (d for n, d in H.degree()) degG = (d for n, d in G.degree()) assert sorted(degH) == sorted(degG) - assert_nodes_equal(H.nodes(), [1000, 1001, 1002, 1003]) + assert nodes_equal(H.nodes(), [1000, 1001, 1002, 1003]) H = nx.convert_node_labels_to_integers(G, ordering="increasing degree") degH = (d for n, d in H.degree()) @@ -92,7 +92,7 @@ class TestRelabel: G.add_edges_from([("A", "B"), ("A", "C"), ("B", "C"), ("C", "D")]) mapping = {"A": "aardvark", "B": "bear", "C": "cat", "D": "dog"} H = nx.relabel_nodes(G, mapping) - assert_nodes_equal(H.nodes(), ["aardvark", "bear", "cat", "dog"]) + assert nodes_equal(H.nodes(), ["aardvark", "bear", "cat", "dog"]) def test_relabel_nodes_function(self): G = nx.empty_graph() @@ -103,13 +103,13 @@ class TestRelabel: return ord(n) H = nx.relabel_nodes(G, mapping) - assert_nodes_equal(H.nodes(), [65, 66, 67, 68]) + assert nodes_equal(H.nodes(), [65, 66, 67, 68]) def test_relabel_nodes_graph(self): G = nx.Graph([("A", "B"), ("A", "C"), ("B", "C"), ("C", "D")]) mapping = {"A": "aardvark", "B": "bear", "C": "cat", "D": "dog"} H = nx.relabel_nodes(G, mapping) - assert_nodes_equal(H.nodes(), ["aardvark", "bear", "cat", "dog"]) + assert nodes_equal(H.nodes(), ["aardvark", "bear", "cat", "dog"]) def test_relabel_nodes_orderedgraph(self): G = nx.OrderedGraph() @@ -123,39 +123,39 @@ class TestRelabel: G = nx.DiGraph([("A", "B"), ("A", "C"), ("B", "C"), ("C", "D")]) mapping = {"A": "aardvark", "B": "bear", "C": "cat", "D": "dog"} H = nx.relabel_nodes(G, mapping, copy=False) - assert_nodes_equal(H.nodes(), ["aardvark", "bear", "cat", "dog"]) + assert nodes_equal(H.nodes(), ["aardvark", "bear", "cat", "dog"]) def test_relabel_nodes_multigraph(self): G = nx.MultiGraph([("a", "b"), ("a", "b")]) mapping = {"a": "aardvark", "b": "bear"} G = nx.relabel_nodes(G, mapping, copy=False) - assert_nodes_equal(G.nodes(), ["aardvark", "bear"]) - assert_edges_equal(G.edges(), [("aardvark", "bear"), ("aardvark", "bear")]) + assert nodes_equal(G.nodes(), ["aardvark", "bear"]) + assert edges_equal(G.edges(), [("aardvark", "bear"), ("aardvark", "bear")]) def test_relabel_nodes_multidigraph(self): G = nx.MultiDiGraph([("a", "b"), ("a", "b")]) mapping = {"a": "aardvark", "b": "bear"} G = nx.relabel_nodes(G, mapping, copy=False) - assert_nodes_equal(G.nodes(), ["aardvark", "bear"]) - assert_edges_equal(G.edges(), [("aardvark", "bear"), ("aardvark", "bear")]) + assert nodes_equal(G.nodes(), ["aardvark", "bear"]) + assert edges_equal(G.edges(), [("aardvark", "bear"), ("aardvark", "bear")]) def test_relabel_isolated_nodes_to_same(self): G = nx.Graph() G.add_nodes_from(range(4)) mapping = {1: 1} H = nx.relabel_nodes(G, mapping, copy=False) - assert_nodes_equal(H.nodes(), list(range(4))) + assert nodes_equal(H.nodes(), list(range(4))) def test_relabel_nodes_missing(self): G = nx.Graph([("A", "B"), ("A", "C"), ("B", "C"), ("C", "D")]) mapping = {0: "aardvark"} # copy=True H = nx.relabel_nodes(G, mapping, copy=True) - assert_nodes_equal(H.nodes, G.nodes) + assert nodes_equal(H.nodes, G.nodes) # copy=False GG = G.copy() nx.relabel_nodes(G, mapping, copy=False) - assert_nodes_equal(G.nodes, GG.nodes) + assert nodes_equal(G.nodes, GG.nodes) def test_relabel_copy_name(self): G = nx.Graph() @@ -181,13 +181,13 @@ class TestRelabel: def test_relabel_selfloop(self): G = nx.DiGraph([(1, 1), (1, 2), (2, 3)]) G = nx.relabel_nodes(G, {1: "One", 2: "Two", 3: "Three"}, copy=False) - assert_nodes_equal(G.nodes(), ["One", "Three", "Two"]) + assert nodes_equal(G.nodes(), ["One", "Three", "Two"]) G = nx.MultiDiGraph([(1, 1), (1, 2), (2, 3)]) G = nx.relabel_nodes(G, {1: "One", 2: "Two", 3: "Three"}, copy=False) - assert_nodes_equal(G.nodes(), ["One", "Three", "Two"]) + assert nodes_equal(G.nodes(), ["One", "Three", "Two"]) G = nx.MultiDiGraph([(1, 1)]) G = nx.relabel_nodes(G, {1: 0}, copy=False) - assert_nodes_equal(G.nodes(), [0]) + assert nodes_equal(G.nodes(), [0]) def test_relabel_multidigraph_inout_merge_nodes(self): for MG in (nx.MultiGraph, nx.MultiDiGraph): diff --git a/networkx/utils/misc.py b/networkx/utils/misc.py index 2df5f48b..ad6e3506 100644 --- a/networkx/utils/misc.py +++ b/networkx/utils/misc.py @@ -41,6 +41,9 @@ __all__ = [ "create_random_state", "create_py_random_state", "PythonRandomInterface", + "nodes_equal", + "edges_equal", + "graphs_equal", ] @@ -540,3 +543,107 @@ def create_py_random_state(random_state=None): return random.Random(random_state) msg = f"{random_state} cannot be used to generate a random.Random instance" raise ValueError(msg) + + +def nodes_equal(nodes1, nodes2): + """Check if nodes are equal. + + Equality here means equal as Python objects. + Node data must match if included. + The order of nodes is not relevant. + + Parameters + ---------- + nodes1, nodes2 : iterables of nodes, or (node, datadict) tuples + + Returns + ------- + bool + True if nodes are equal, False otherwise. + """ + nlist1 = list(nodes1) + nlist2 = list(nodes2) + try: + d1 = dict(nlist1) + d2 = dict(nlist2) + except (ValueError, TypeError): + d1 = dict.fromkeys(nlist1) + d2 = dict.fromkeys(nlist2) + return d1 == d2 + + +def edges_equal(edges1, edges2): + """Check if edges are equal. + + Equality here means equal as Python objects. + Edge data must match if included. + The order of the edges is not relevant. + + Parameters + ---------- + edges1, edges2 : iterables of with u, v nodes as + edge tuples (u, v), or + edge tuples with data dicts (u, v, d), or + edge tuples with keys and data dicts (u, v, k, d) + + Returns + ------- + bool + True if edges are equal, False otherwise. + """ + from collections import defaultdict + + d1 = defaultdict(dict) + d2 = defaultdict(dict) + c1 = 0 + for c1, e in enumerate(edges1): + u, v = e[0], e[1] + data = [e[2:]] + if v in d1[u]: + data = d1[u][v] + data + d1[u][v] = data + d1[v][u] = data + c2 = 0 + for c2, e in enumerate(edges2): + u, v = e[0], e[1] + data = [e[2:]] + if v in d2[u]: + data = d2[u][v] + data + d2[u][v] = data + d2[v][u] = data + if c1 != c2: + return False + # can check one direction because lengths are the same. + for n, nbrdict in d1.items(): + for nbr, datalist in nbrdict.items(): + if n not in d2: + return False + if nbr not in d2[n]: + return False + d2datalist = d2[n][nbr] + for data in datalist: + if datalist.count(data) != d2datalist.count(data): + return False + return True + + +def graphs_equal(graph1, graph2): + """Check if graphs are equal. + + Equality here means equal as Python objects (not isomorphism). + Node, edge and graph data must match. + + Parameters + ---------- + graph1, graph2 : graph + + Returns + ------- + bool + True if graphs are equal, False otherwise. + """ + return ( + graph1.adj == graph2.adj + and graph1.nodes == graph2.nodes + and graph1.graph == graph2.graph + ) |