From 4a52a71956a8d46fcb7294ac71734504bb09bcc2 Mon Sep 17 00:00:00 2001
From: S. Solomon Darnell
Date: Fri, 28 Mar 2025 21:52:21 -0500
Subject: two version of R2R are here
---
.../networkx/readwrite/tests/test_graphml.py | 1531 ++++++++++++++++++++
1 file changed, 1531 insertions(+)
create mode 100644 .venv/lib/python3.12/site-packages/networkx/readwrite/tests/test_graphml.py
(limited to '.venv/lib/python3.12/site-packages/networkx/readwrite/tests/test_graphml.py')
diff --git a/.venv/lib/python3.12/site-packages/networkx/readwrite/tests/test_graphml.py b/.venv/lib/python3.12/site-packages/networkx/readwrite/tests/test_graphml.py
new file mode 100644
index 00000000..5ffa837e
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/networkx/readwrite/tests/test_graphml.py
@@ -0,0 +1,1531 @@
+import io
+
+import pytest
+
+import networkx as nx
+from networkx.readwrite.graphml import GraphMLWriter
+from networkx.utils import edges_equal, nodes_equal
+
+
+class BaseGraphML:
+ @classmethod
+ def setup_class(cls):
+ cls.simple_directed_data = """
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+"""
+ cls.simple_directed_graph = nx.DiGraph()
+ cls.simple_directed_graph.add_node("n10")
+ cls.simple_directed_graph.add_edge("n0", "n2", id="foo")
+ cls.simple_directed_graph.add_edge("n0", "n2")
+ cls.simple_directed_graph.add_edges_from(
+ [
+ ("n1", "n2"),
+ ("n2", "n3"),
+ ("n3", "n5"),
+ ("n3", "n4"),
+ ("n4", "n6"),
+ ("n6", "n5"),
+ ("n5", "n7"),
+ ("n6", "n8"),
+ ("n8", "n7"),
+ ("n8", "n9"),
+ ]
+ )
+ cls.simple_directed_fh = io.BytesIO(cls.simple_directed_data.encode("UTF-8"))
+
+ cls.attribute_data = """
+
+
+ yellow
+
+
+
+
+ green
+
+
+
+ blue
+
+
+ red
+
+
+
+ turquoise
+
+
+ 1.0
+
+
+ 1.0
+
+
+ 2.0
+
+
+
+
+
+ 1.1
+
+
+
+"""
+ cls.attribute_graph = nx.DiGraph(id="G")
+ cls.attribute_graph.graph["node_default"] = {"color": "yellow"}
+ cls.attribute_graph.add_node("n0", color="green")
+ cls.attribute_graph.add_node("n2", color="blue")
+ cls.attribute_graph.add_node("n3", color="red")
+ cls.attribute_graph.add_node("n4")
+ cls.attribute_graph.add_node("n5", color="turquoise")
+ cls.attribute_graph.add_edge("n0", "n2", id="e0", weight=1.0)
+ cls.attribute_graph.add_edge("n0", "n1", id="e1", weight=1.0)
+ cls.attribute_graph.add_edge("n1", "n3", id="e2", weight=2.0)
+ cls.attribute_graph.add_edge("n3", "n2", id="e3")
+ cls.attribute_graph.add_edge("n2", "n4", id="e4")
+ cls.attribute_graph.add_edge("n3", "n5", id="e5")
+ cls.attribute_graph.add_edge("n5", "n4", id="e6", weight=1.1)
+ cls.attribute_fh = io.BytesIO(cls.attribute_data.encode("UTF-8"))
+
+ cls.node_attribute_default_data = """
+
+ false
+ 0
+ 0
+ 0.0
+ 0.0
+ Foo
+
+
+
+
+
+
+ """
+ cls.node_attribute_default_graph = nx.DiGraph(id="G")
+ cls.node_attribute_default_graph.graph["node_default"] = {
+ "boolean_attribute": False,
+ "int_attribute": 0,
+ "long_attribute": 0,
+ "float_attribute": 0.0,
+ "double_attribute": 0.0,
+ "string_attribute": "Foo",
+ }
+ cls.node_attribute_default_graph.add_node("n0")
+ cls.node_attribute_default_graph.add_node("n1")
+ cls.node_attribute_default_graph.add_edge("n0", "n1", id="e0")
+ cls.node_attribute_default_fh = io.BytesIO(
+ cls.node_attribute_default_data.encode("UTF-8")
+ )
+
+ cls.attribute_named_key_ids_data = """
+
+
+
+
+
+
+ val1
+ val2
+
+
+ val_one
+ val2
+
+
+ edge_value
+
+
+
+"""
+ cls.attribute_named_key_ids_graph = nx.DiGraph()
+ cls.attribute_named_key_ids_graph.add_node("0", prop1="val1", prop2="val2")
+ cls.attribute_named_key_ids_graph.add_node("1", prop1="val_one", prop2="val2")
+ cls.attribute_named_key_ids_graph.add_edge("0", "1", edge_prop="edge_value")
+ fh = io.BytesIO(cls.attribute_named_key_ids_data.encode("UTF-8"))
+ cls.attribute_named_key_ids_fh = fh
+
+ cls.attribute_numeric_type_data = """
+
+
+
+
+
+ 1
+
+
+ 2.0
+
+
+ 1
+
+
+ k
+
+
+ 1.0
+
+
+
+"""
+ cls.attribute_numeric_type_graph = nx.DiGraph()
+ cls.attribute_numeric_type_graph.add_node("n0", weight=1)
+ cls.attribute_numeric_type_graph.add_node("n1", weight=2.0)
+ cls.attribute_numeric_type_graph.add_edge("n0", "n1", weight=1)
+ cls.attribute_numeric_type_graph.add_edge("n1", "n1", weight=1.0)
+ fh = io.BytesIO(cls.attribute_numeric_type_data.encode("UTF-8"))
+ cls.attribute_numeric_type_fh = fh
+
+ cls.simple_undirected_data = """
+
+
+
+
+
+
+
+
+
+
+"""
+ #
+ cls.simple_undirected_graph = nx.Graph()
+ cls.simple_undirected_graph.add_node("n10")
+ cls.simple_undirected_graph.add_edge("n0", "n2", id="foo")
+ cls.simple_undirected_graph.add_edges_from([("n1", "n2"), ("n2", "n3")])
+ fh = io.BytesIO(cls.simple_undirected_data.encode("UTF-8"))
+ cls.simple_undirected_fh = fh
+
+ cls.undirected_multigraph_data = """
+
+
+
+
+
+
+
+
+
+
+"""
+ cls.undirected_multigraph = nx.MultiGraph()
+ cls.undirected_multigraph.add_node("n10")
+ cls.undirected_multigraph.add_edge("n0", "n2", id="e0")
+ cls.undirected_multigraph.add_edge("n1", "n2", id="e1")
+ cls.undirected_multigraph.add_edge("n2", "n1", id="e2")
+ fh = io.BytesIO(cls.undirected_multigraph_data.encode("UTF-8"))
+ cls.undirected_multigraph_fh = fh
+
+ cls.undirected_multigraph_no_multiedge_data = """
+
+
+
+
+
+
+
+
+
+
+"""
+ cls.undirected_multigraph_no_multiedge = nx.MultiGraph()
+ cls.undirected_multigraph_no_multiedge.add_node("n10")
+ cls.undirected_multigraph_no_multiedge.add_edge("n0", "n2", id="e0")
+ cls.undirected_multigraph_no_multiedge.add_edge("n1", "n2", id="e1")
+ cls.undirected_multigraph_no_multiedge.add_edge("n2", "n3", id="e2")
+ fh = io.BytesIO(cls.undirected_multigraph_no_multiedge_data.encode("UTF-8"))
+ cls.undirected_multigraph_no_multiedge_fh = fh
+
+ cls.multigraph_only_ids_for_multiedges_data = """
+
+
+
+
+
+
+
+
+
+
+"""
+ cls.multigraph_only_ids_for_multiedges = nx.MultiGraph()
+ cls.multigraph_only_ids_for_multiedges.add_node("n10")
+ cls.multigraph_only_ids_for_multiedges.add_edge("n0", "n2")
+ cls.multigraph_only_ids_for_multiedges.add_edge("n1", "n2", id="e1")
+ cls.multigraph_only_ids_for_multiedges.add_edge("n2", "n1", id="e2")
+ fh = io.BytesIO(cls.multigraph_only_ids_for_multiedges_data.encode("UTF-8"))
+ cls.multigraph_only_ids_for_multiedges_fh = fh
+
+
+class TestReadGraphML(BaseGraphML):
+ def test_read_simple_directed_graphml(self):
+ G = self.simple_directed_graph
+ H = nx.read_graphml(self.simple_directed_fh)
+ assert sorted(G.nodes()) == sorted(H.nodes())
+ assert sorted(G.edges()) == sorted(H.edges())
+ assert sorted(G.edges(data=True)) == sorted(H.edges(data=True))
+ self.simple_directed_fh.seek(0)
+
+ PG = nx.parse_graphml(self.simple_directed_data)
+ assert sorted(G.nodes()) == sorted(PG.nodes())
+ assert sorted(G.edges()) == sorted(PG.edges())
+ assert sorted(G.edges(data=True)) == sorted(PG.edges(data=True))
+
+ 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())
+ 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())
+
+ 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())
+ 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())
+
+ 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())
+ 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())
+
+ 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())
+ 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())
+
+ 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)))
+ ge = sorted(G.edges(data=True))
+ he = sorted(H.edges(data=True))
+ for a, b in zip(ge, he):
+ assert a == b
+ self.attribute_fh.seek(0)
+
+ PG = nx.parse_graphml(self.attribute_data)
+ assert sorted(G.nodes(True)) == sorted(PG.nodes(data=True))
+ ge = sorted(G.edges(data=True))
+ he = sorted(PG.edges(data=True))
+ for a, b in zip(ge, he):
+ assert a == b
+
+ def test_node_default_attribute_graphml(self):
+ G = self.node_attribute_default_graph
+ H = nx.read_graphml(self.node_attribute_default_fh)
+ assert G.graph["node_default"] == H.graph["node_default"]
+
+ def test_directed_edge_in_undirected(self):
+ s = """
+
+
+
+
+
+
+
+
+"""
+ fh = io.BytesIO(s.encode("UTF-8"))
+ pytest.raises(nx.NetworkXError, nx.read_graphml, fh)
+ pytest.raises(nx.NetworkXError, nx.parse_graphml, s)
+
+ def test_undirected_edge_in_directed(self):
+ s = """
+
+
+
+
+
+
+
+
+"""
+ fh = io.BytesIO(s.encode("UTF-8"))
+ pytest.raises(nx.NetworkXError, nx.read_graphml, fh)
+ pytest.raises(nx.NetworkXError, nx.parse_graphml, s)
+
+ def test_key_raise(self):
+ s = """
+
+
+ yellow
+
+
+
+
+ green
+
+
+
+ blue
+
+
+ 1.0
+
+
+
+"""
+ fh = io.BytesIO(s.encode("UTF-8"))
+ pytest.raises(nx.NetworkXError, nx.read_graphml, fh)
+ pytest.raises(nx.NetworkXError, nx.parse_graphml, s)
+
+ def test_hyperedge_raise(self):
+ s = """
+
+
+ yellow
+
+
+
+
+ green
+
+
+
+ blue
+
+
+
+
+
+
+
+
+"""
+ fh = io.BytesIO(s.encode("UTF-8"))
+ pytest.raises(nx.NetworkXError, nx.read_graphml, fh)
+ pytest.raises(nx.NetworkXError, nx.parse_graphml, s)
+
+ def test_multigraph_keys(self):
+ # Test that reading multigraphs uses edge id attributes as keys
+ s = """
+
+
+
+
+
+
+
+
+"""
+ fh = io.BytesIO(s.encode("UTF-8"))
+ G = nx.read_graphml(fh)
+ expected = [("n0", "n1", "e0"), ("n0", "n1", "e1")]
+ assert sorted(G.edges(keys=True)) == expected
+ fh.seek(0)
+ H = nx.parse_graphml(s)
+ assert sorted(H.edges(keys=True)) == expected
+
+ def test_preserve_multi_edge_data(self):
+ """
+ Test that data and keys of edges are preserved on consequent
+ write and reads
+ """
+ G = nx.MultiGraph()
+ G.add_node(1)
+ G.add_node(2)
+ G.add_edges_from(
+ [
+ # edges with no data, no keys:
+ (1, 2),
+ # edges with only data:
+ (1, 2, {"key": "data_key1"}),
+ (1, 2, {"id": "data_id2"}),
+ (1, 2, {"key": "data_key3", "id": "data_id3"}),
+ # edges with both data and keys:
+ (1, 2, 103, {"key": "data_key4"}),
+ (1, 2, 104, {"id": "data_id5"}),
+ (1, 2, 105, {"key": "data_key6", "id": "data_id7"}),
+ ]
+ )
+ fh = io.BytesIO()
+ 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 G._adj == H._adj
+
+ Gadj = {
+ str(node): {
+ str(nbr): {str(ekey): dd for ekey, dd in key_dict.items()}
+ for nbr, key_dict in nbr_dict.items()
+ }
+ for node, nbr_dict in G._adj.items()
+ }
+ fh.seek(0)
+ HH = nx.read_graphml(fh, node_type=str, edge_key_type=str)
+ assert Gadj == HH._adj
+
+ fh.seek(0)
+ string_fh = fh.read()
+ HH = nx.parse_graphml(string_fh, node_type=str, edge_key_type=str)
+ assert Gadj == HH._adj
+
+ def test_yfiles_extension(self):
+ data = """
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ 1
+
+
+
+
+
+
+
+
+
+
+ 2
+
+
+
+
+
+
+
+
+
+
+
+ 3
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+"""
+ fh = io.BytesIO(data.encode("UTF-8"))
+ G = nx.read_graphml(fh, force_multigraph=True)
+ assert list(G.edges()) == [("n0", "n1")]
+ assert G.has_edge("n0", "n1", key="e0")
+ assert G.nodes["n0"]["label"] == "1"
+ assert G.nodes["n1"]["label"] == "2"
+ assert G.nodes["n2"]["label"] == "3"
+ assert G.nodes["n0"]["shape_type"] == "rectangle"
+ assert G.nodes["n1"]["shape_type"] == "rectangle"
+ assert G.nodes["n2"]["shape_type"] == "com.yworks.flowchart.terminator"
+ assert G.nodes["n2"]["description"] == "description\nline1\nline2"
+ fh.seek(0)
+ G = nx.read_graphml(fh)
+ assert list(G.edges()) == [("n0", "n1")]
+ assert G["n0"]["n1"]["id"] == "e0"
+ assert G.nodes["n0"]["label"] == "1"
+ assert G.nodes["n1"]["label"] == "2"
+ assert G.nodes["n2"]["label"] == "3"
+ assert G.nodes["n0"]["shape_type"] == "rectangle"
+ assert G.nodes["n1"]["shape_type"] == "rectangle"
+ assert G.nodes["n2"]["shape_type"] == "com.yworks.flowchart.terminator"
+ assert G.nodes["n2"]["description"] == "description\nline1\nline2"
+
+ H = nx.parse_graphml(data, force_multigraph=True)
+ assert list(H.edges()) == [("n0", "n1")]
+ assert H.has_edge("n0", "n1", key="e0")
+ assert H.nodes["n0"]["label"] == "1"
+ assert H.nodes["n1"]["label"] == "2"
+ assert H.nodes["n2"]["label"] == "3"
+
+ H = nx.parse_graphml(data)
+ assert list(H.edges()) == [("n0", "n1")]
+ assert H["n0"]["n1"]["id"] == "e0"
+ assert H.nodes["n0"]["label"] == "1"
+ assert H.nodes["n1"]["label"] == "2"
+ assert H.nodes["n2"]["label"] == "3"
+
+ def test_bool(self):
+ s = """
+
+
+ false
+
+
+
+ true
+
+
+
+ false
+
+
+ FaLsE
+
+
+ True
+
+
+ 0
+
+
+ 1
+
+
+
+"""
+ fh = io.BytesIO(s.encode("UTF-8"))
+ G = nx.read_graphml(fh)
+ H = nx.parse_graphml(s)
+ for graph in [G, H]:
+ assert graph.nodes["n0"]["test"]
+ assert not graph.nodes["n2"]["test"]
+ assert not graph.nodes["n3"]["test"]
+ assert graph.nodes["n4"]["test"]
+ assert not graph.nodes["n5"]["test"]
+ assert graph.nodes["n6"]["test"]
+
+ def test_graphml_header_line(self):
+ good = """
+
+
+ false
+
+
+
+ true
+
+
+
+"""
+ bad = """
+
+
+ false
+
+
+
+ true
+
+
+
+"""
+ ugly = """
+
+
+ false
+
+
+
+ true
+
+
+
+"""
+ for s in (good, bad):
+ fh = io.BytesIO(s.encode("UTF-8"))
+ G = nx.read_graphml(fh)
+ H = nx.parse_graphml(s)
+ for graph in [G, H]:
+ assert graph.nodes["n0"]["test"]
+
+ fh = io.BytesIO(ugly.encode("UTF-8"))
+ pytest.raises(nx.NetworkXError, nx.read_graphml, fh)
+ pytest.raises(nx.NetworkXError, nx.parse_graphml, ugly)
+
+ def test_read_attributes_with_groups(self):
+ data = """\
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ 2
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Group 3
+
+
+
+
+
+
+
+
+
+ Folder 3
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Group 1
+
+
+
+
+
+
+
+
+
+ Folder 1
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ 1
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ 3
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Group 2
+
+
+
+
+
+
+
+
+
+ Folder 2
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ 5
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ 6
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ 9
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+"""
+ # verify that nodes / attributes are correctly read when part of a group
+ fh = io.BytesIO(data.encode("UTF-8"))
+ G = nx.read_graphml(fh)
+ data = [x for _, x in G.nodes(data=True)]
+ assert len(data) == 9
+ for node_data in data:
+ assert node_data["CustomProperty"] != ""
+
+ def test_long_attribute_type(self):
+ # test that graphs with attr.type="long" (as produced by botch and
+ # dose3) can be parsed
+ s = """
+
+
+
+
+ 4284
+
+
+"""
+ fh = io.BytesIO(s.encode("UTF-8"))
+ G = nx.read_graphml(fh)
+ expected = [("n1", {"cudfversion": 4284})]
+ assert sorted(G.nodes(data=True)) == expected
+ fh.seek(0)
+ H = nx.parse_graphml(s)
+ assert sorted(H.nodes(data=True)) == expected
+
+
+class TestWriteGraphML(BaseGraphML):
+ writer = staticmethod(nx.write_graphml_lxml)
+
+ @classmethod
+ def setup_class(cls):
+ BaseGraphML.setup_class()
+ _ = pytest.importorskip("lxml.etree")
+
+ def test_write_interface(self):
+ try:
+ import lxml.etree
+
+ assert nx.write_graphml == nx.write_graphml_lxml
+ except ImportError:
+ assert nx.write_graphml == nx.write_graphml_xml
+
+ def test_write_read_simple_directed_graphml(self):
+ G = self.simple_directed_graph
+ G.graph["hi"] = "there"
+ fh = io.BytesIO()
+ self.writer(G, fh)
+ fh.seek(0)
+ H = nx.read_graphml(fh)
+ assert sorted(G.nodes()) == sorted(H.nodes())
+ assert sorted(G.edges()) == sorted(H.edges())
+ assert sorted(G.edges(data=True)) == sorted(H.edges(data=True))
+ self.simple_directed_fh.seek(0)
+
+ def test_GraphMLWriter_add_graphs(self):
+ gmlw = GraphMLWriter()
+ G = self.simple_directed_graph
+ H = G.copy()
+ gmlw.add_graphs([G, H])
+
+ def test_write_read_simple_no_prettyprint(self):
+ G = self.simple_directed_graph
+ G.graph["hi"] = "there"
+ G.graph["id"] = "1"
+ fh = io.BytesIO()
+ self.writer(G, fh, prettyprint=False)
+ fh.seek(0)
+ H = nx.read_graphml(fh)
+ assert sorted(G.nodes()) == sorted(H.nodes())
+ assert sorted(G.edges()) == sorted(H.edges())
+ assert sorted(G.edges(data=True)) == sorted(H.edges(data=True))
+ self.simple_directed_fh.seek(0)
+
+ def test_write_read_attribute_named_key_ids_graphml(self):
+ from xml.etree.ElementTree import parse
+
+ G = self.attribute_named_key_ids_graph
+ fh = io.BytesIO()
+ self.writer(G, fh, named_key_ids=True)
+ fh.seek(0)
+ 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))
+ self.attribute_named_key_ids_fh.seek(0)
+
+ xml = parse(fh)
+ # Children are the key elements, and the graph element
+ children = list(xml.getroot())
+ assert len(children) == 4
+
+ keys = [child.items() for child in children[:3]]
+
+ assert len(keys) == 3
+ assert ("id", "edge_prop") in keys[0]
+ assert ("attr.name", "edge_prop") in keys[0]
+ assert ("id", "prop2") in keys[1]
+ assert ("attr.name", "prop2") in keys[1]
+ assert ("id", "prop1") in keys[2]
+ assert ("attr.name", "prop1") in keys[2]
+
+ # Confirm the read graph nodes/edge are identical when compared to
+ # default writing behavior.
+ default_behavior_fh = io.BytesIO()
+ nx.write_graphml(G, default_behavior_fh)
+ default_behavior_fh.seek(0)
+ H = nx.read_graphml(default_behavior_fh)
+
+ named_key_ids_behavior_fh = io.BytesIO()
+ nx.write_graphml(G, named_key_ids_behavior_fh, named_key_ids=True)
+ named_key_ids_behavior_fh.seek(0)
+ J = nx.read_graphml(named_key_ids_behavior_fh)
+
+ assert all(n1 == n2 for (n1, n2) in zip(H.nodes, J.nodes))
+ assert all(e1 == e2 for (e1, e2) in zip(H.edges, J.edges))
+
+ def test_write_read_attribute_numeric_type_graphml(self):
+ from xml.etree.ElementTree import parse
+
+ G = self.attribute_numeric_type_graph
+ fh = io.BytesIO()
+ self.writer(G, fh, infer_numeric_types=True)
+ fh.seek(0)
+ 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))
+ self.attribute_numeric_type_fh.seek(0)
+
+ xml = parse(fh)
+ # Children are the key elements, and the graph element
+ children = list(xml.getroot())
+ assert len(children) == 3
+
+ keys = [child.items() for child in children[:2]]
+
+ assert len(keys) == 2
+ assert ("attr.type", "double") in keys[0]
+ assert ("attr.type", "double") in keys[1]
+
+ def test_more_multigraph_keys(self, tmp_path):
+ """Writing keys as edge id attributes means keys become strings.
+ The original keys are stored as data, so read them back in
+ if `str(key) == edge_id`
+ This allows the adjacency to remain the same.
+ """
+ G = nx.MultiGraph()
+ G.add_edges_from([("a", "b", 2), ("a", "b", 3)])
+ fname = tmp_path / "test.graphml"
+ 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 G._adj == H._adj
+
+ def test_default_attribute(self):
+ G = nx.Graph(name="Fred")
+ G.add_node(1, label=1, color="green")
+ nx.add_path(G, [0, 1, 2, 3])
+ G.add_edge(1, 2, weight=3)
+ G.graph["node_default"] = {"color": "yellow"}
+ G.graph["edge_default"] = {"weight": 7}
+ fh = io.BytesIO()
+ 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 G.graph == H.graph
+
+ def test_mixed_type_attributes(self):
+ G = nx.MultiGraph()
+ G.add_node("n0", special=False)
+ G.add_node("n1", special=0)
+ G.add_edge("n0", "n1", special=False)
+ G.add_edge("n0", "n1", special=0)
+ fh = io.BytesIO()
+ self.writer(G, fh)
+ fh.seek(0)
+ H = nx.read_graphml(fh)
+ assert not H.nodes["n0"]["special"]
+ assert H.nodes["n1"]["special"] == 0
+ assert not H.edges["n0", "n1", 0]["special"]
+ assert H.edges["n0", "n1", 1]["special"] == 0
+
+ def test_str_number_mixed_type_attributes(self):
+ G = nx.MultiGraph()
+ G.add_node("n0", special="hello")
+ G.add_node("n1", special=0)
+ G.add_edge("n0", "n1", special="hello")
+ G.add_edge("n0", "n1", special=0)
+ fh = io.BytesIO()
+ self.writer(G, fh)
+ fh.seek(0)
+ H = nx.read_graphml(fh)
+ assert H.nodes["n0"]["special"] == "hello"
+ assert H.nodes["n1"]["special"] == 0
+ assert H.edges["n0", "n1", 0]["special"] == "hello"
+ assert H.edges["n0", "n1", 1]["special"] == 0
+
+ def test_mixed_int_type_number_attributes(self):
+ np = pytest.importorskip("numpy")
+ G = nx.MultiGraph()
+ G.add_node("n0", special=np.int64(0))
+ G.add_node("n1", special=1)
+ G.add_edge("n0", "n1", special=np.int64(2))
+ G.add_edge("n0", "n1", special=3)
+ fh = io.BytesIO()
+ self.writer(G, fh)
+ fh.seek(0)
+ H = nx.read_graphml(fh)
+ assert H.nodes["n0"]["special"] == 0
+ assert H.nodes["n1"]["special"] == 1
+ assert H.edges["n0", "n1", 0]["special"] == 2
+ assert H.edges["n0", "n1", 1]["special"] == 3
+
+ def test_multigraph_to_graph(self, tmp_path):
+ # test converting multigraph to graph if no parallel edges found
+ G = nx.MultiGraph()
+ G.add_edges_from([("a", "b", 2), ("b", "c", 3)]) # no multiedges
+ fname = tmp_path / "test.graphml"
+ self.writer(G, fname)
+ H = nx.read_graphml(fname)
+ assert not H.is_multigraph()
+ H = nx.read_graphml(fname, force_multigraph=True)
+ assert H.is_multigraph()
+
+ # add a multiedge
+ G.add_edge("a", "b", "e-id")
+ fname = tmp_path / "test.graphml"
+ self.writer(G, fname)
+ H = nx.read_graphml(fname)
+ assert H.is_multigraph()
+ H = nx.read_graphml(fname, force_multigraph=True)
+ assert H.is_multigraph()
+
+ def test_write_generate_edge_id_from_attribute(self, tmp_path):
+ from xml.etree.ElementTree import parse
+
+ G = nx.Graph()
+ G.add_edges_from([("a", "b"), ("b", "c"), ("a", "c")])
+ edge_attributes = {e: str(e) for e in G.edges}
+ nx.set_edge_attributes(G, edge_attributes, "eid")
+ fname = tmp_path / "test.graphml"
+ # set edge_id_from_attribute e.g. "eid" for write_graphml()
+ self.writer(G, fname, edge_id_from_attribute="eid")
+ # set edge_id_from_attribute e.g. "eid" for generate_graphml()
+ generator = nx.generate_graphml(G, edge_id_from_attribute="eid")
+
+ H = nx.read_graphml(fname)
+ assert nodes_equal(G.nodes(), H.nodes())
+ assert edges_equal(G.edges(), H.edges())
+ # NetworkX adds explicit edge "id" from file as attribute
+ nx.set_edge_attributes(G, edge_attributes, "id")
+ assert edges_equal(G.edges(data=True), H.edges(data=True))
+
+ tree = parse(fname)
+ children = list(tree.getroot())
+ assert len(children) == 2
+ edge_ids = [
+ edge.attrib["id"]
+ for edge in tree.getroot().findall(
+ ".//{http://graphml.graphdrawing.org/xmlns}edge"
+ )
+ ]
+ # verify edge id value is equal to specified attribute value
+ assert sorted(edge_ids) == sorted(edge_attributes.values())
+
+ # check graphml generated from generate_graphml()
+ data = "".join(generator)
+ J = nx.parse_graphml(data)
+ assert sorted(G.nodes()) == sorted(J.nodes())
+ assert sorted(G.edges()) == sorted(J.edges())
+ # NetworkX adds explicit edge "id" from file as attribute
+ nx.set_edge_attributes(G, edge_attributes, "id")
+ assert edges_equal(G.edges(data=True), J.edges(data=True))
+
+ def test_multigraph_write_generate_edge_id_from_attribute(self, tmp_path):
+ from xml.etree.ElementTree import parse
+
+ G = nx.MultiGraph()
+ G.add_edges_from([("a", "b"), ("b", "c"), ("a", "c"), ("a", "b")])
+ edge_attributes = {e: str(e) for e in G.edges}
+ nx.set_edge_attributes(G, edge_attributes, "eid")
+ fname = tmp_path / "test.graphml"
+ # set edge_id_from_attribute e.g. "eid" for write_graphml()
+ self.writer(G, fname, edge_id_from_attribute="eid")
+ # set edge_id_from_attribute e.g. "eid" for generate_graphml()
+ generator = nx.generate_graphml(G, edge_id_from_attribute="eid")
+
+ H = nx.read_graphml(fname)
+ assert H.is_multigraph()
+ H = nx.read_graphml(fname, force_multigraph=True)
+ assert H.is_multigraph()
+
+ assert nodes_equal(G.nodes(), H.nodes())
+ assert edges_equal(G.edges(), H.edges())
+ assert sorted(data.get("eid") for u, v, data in H.edges(data=True)) == sorted(
+ edge_attributes.values()
+ )
+ # NetworkX uses edge_ids as keys in multigraphs if no key
+ assert sorted(key for u, v, key in H.edges(keys=True)) == sorted(
+ edge_attributes.values()
+ )
+
+ tree = parse(fname)
+ children = list(tree.getroot())
+ assert len(children) == 2
+ edge_ids = [
+ edge.attrib["id"]
+ for edge in tree.getroot().findall(
+ ".//{http://graphml.graphdrawing.org/xmlns}edge"
+ )
+ ]
+ # verify edge id value is equal to specified attribute value
+ assert sorted(edge_ids) == sorted(edge_attributes.values())
+
+ # check graphml generated from generate_graphml()
+ graphml_data = "".join(generator)
+ J = nx.parse_graphml(graphml_data)
+ assert J.is_multigraph()
+
+ assert nodes_equal(G.nodes(), J.nodes())
+ assert edges_equal(G.edges(), J.edges())
+ assert sorted(data.get("eid") for u, v, data in J.edges(data=True)) == sorted(
+ edge_attributes.values()
+ )
+ # NetworkX uses edge_ids as keys in multigraphs if no key
+ assert sorted(key for u, v, key in J.edges(keys=True)) == sorted(
+ edge_attributes.values()
+ )
+
+ def test_numpy_float64(self, tmp_path):
+ np = pytest.importorskip("numpy")
+ wt = np.float64(3.4)
+ G = nx.Graph([(1, 2, {"weight": wt})])
+ fname = tmp_path / "test.graphml"
+ self.writer(G, fname)
+ H = nx.read_graphml(fname, node_type=int)
+ assert G.edges == H.edges
+ wtG = G[1][2]["weight"]
+ wtH = H[1][2]["weight"]
+ assert wtG == pytest.approx(wtH, abs=1e-6)
+ assert type(wtG) == np.float64
+ assert type(wtH) == float
+
+ def test_numpy_float32(self, tmp_path):
+ np = pytest.importorskip("numpy")
+ wt = np.float32(3.4)
+ G = nx.Graph([(1, 2, {"weight": wt})])
+ fname = tmp_path / "test.graphml"
+ self.writer(G, fname)
+ H = nx.read_graphml(fname, node_type=int)
+ assert G.edges == H.edges
+ wtG = G[1][2]["weight"]
+ wtH = H[1][2]["weight"]
+ assert wtG == pytest.approx(wtH, abs=1e-6)
+ assert type(wtG) == np.float32
+ assert type(wtH) == float
+
+ def test_numpy_float64_inference(self, tmp_path):
+ np = pytest.importorskip("numpy")
+ G = self.attribute_numeric_type_graph
+ G.edges[("n1", "n1")]["weight"] = np.float64(1.1)
+ fname = tmp_path / "test.graphml"
+ self.writer(G, fname, infer_numeric_types=True)
+ H = nx.read_graphml(fname)
+ assert G._adj == H._adj
+
+ def test_unicode_attributes(self, tmp_path):
+ G = nx.Graph()
+ name1 = chr(2344) + chr(123) + chr(6543)
+ name2 = chr(5543) + chr(1543) + chr(324)
+ node_type = str
+ G.add_edge(name1, "Radiohead", foo=name2)
+ fname = tmp_path / "test.graphml"
+ self.writer(G, fname)
+ H = nx.read_graphml(fname, node_type=node_type)
+ assert G._adj == H._adj
+
+ def test_unicode_escape(self):
+ # test for handling json escaped strings in python 2 Issue #1880
+ import json
+
+ a = {"a": '{"a": "123"}'} # an object with many chars to escape
+ sa = json.dumps(a)
+ G = nx.Graph()
+ G.graph["test"] = sa
+ fh = io.BytesIO()
+ self.writer(G, fh)
+ fh.seek(0)
+ H = nx.read_graphml(fh)
+ assert G.graph["test"] == H.graph["test"]
+
+
+class TestXMLGraphML(TestWriteGraphML):
+ writer = staticmethod(nx.write_graphml_xml)
+
+ @classmethod
+ def setup_class(cls):
+ TestWriteGraphML.setup_class()
+
+
+def test_exception_for_unsupported_datatype_node_attr():
+ """Test that a detailed exception is raised when an attribute is of a type
+ not supported by GraphML, e.g. a list"""
+ pytest.importorskip("lxml.etree")
+ # node attribute
+ G = nx.Graph()
+ G.add_node(0, my_list_attribute=[0, 1, 2])
+ fh = io.BytesIO()
+ with pytest.raises(TypeError, match="GraphML does not support"):
+ nx.write_graphml(G, fh)
+
+
+def test_exception_for_unsupported_datatype_edge_attr():
+ """Test that a detailed exception is raised when an attribute is of a type
+ not supported by GraphML, e.g. a list"""
+ pytest.importorskip("lxml.etree")
+ # edge attribute
+ G = nx.Graph()
+ G.add_edge(0, 1, my_list_attribute=[0, 1, 2])
+ fh = io.BytesIO()
+ with pytest.raises(TypeError, match="GraphML does not support"):
+ nx.write_graphml(G, fh)
+
+
+def test_exception_for_unsupported_datatype_graph_attr():
+ """Test that a detailed exception is raised when an attribute is of a type
+ not supported by GraphML, e.g. a list"""
+ pytest.importorskip("lxml.etree")
+ # graph attribute
+ G = nx.Graph()
+ G.graph["my_list_attribute"] = [0, 1, 2]
+ fh = io.BytesIO()
+ with pytest.raises(TypeError, match="GraphML does not support"):
+ nx.write_graphml(G, fh)
+
+
+def test_empty_attribute():
+ """Tests that a GraphML string with an empty attribute can be parsed
+ correctly."""
+ s = """
+
+
+
+
+
+ aaa
+ bbb
+
+
+ ccc
+
+
+
+ """
+ fh = io.BytesIO(s.encode("UTF-8"))
+ G = nx.read_graphml(fh)
+ assert G.nodes["0"] == {"foo": "aaa", "bar": "bbb"}
+ assert G.nodes["1"] == {"foo": "ccc", "bar": ""}
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