import io
import os
import tempfile
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, dict(key="data_key1")),
(1, 2, dict(id="data_id2")),
(1, 2, dict(key="data_key3", id="data_id3")),
# edges with both data and keys:
(1, 2, 103, dict(key="data_key4")),
(1, 2, 104, dict(id="data_id5")),
(1, 2, 105, dict(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):
"""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)])
fd, fname = tempfile.mkstemp()
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
os.close(fd)
os.unlink(fname)
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_numpy_float(self):
np = pytest.importorskip("numpy")
wt = np.float_(3.4)
G = nx.Graph([(1, 2, {"weight": wt})])
fd, fname = tempfile.mkstemp()
self.writer(G, fname)
H = nx.read_graphml(fname, node_type=int)
assert G._adj == H._adj
os.close(fd)
os.unlink(fname)
def test_multigraph_to_graph(self):
# 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
fd, fname = tempfile.mkstemp()
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()
os.close(fd)
os.unlink(fname)
# add a multiedge
G.add_edge("a", "b", "e-id")
fd, fname = tempfile.mkstemp()
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()
os.close(fd)
os.unlink(fname)
def test_write_generate_edge_id_from_attribute(self):
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")
fd, fname = tempfile.mkstemp()
# 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 sepcified 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))
os.close(fd)
os.unlink(fname)
def test_multigraph_write_generate_edge_id_from_attribute(self):
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")
fd, fname = tempfile.mkstemp()
# 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 sepcified 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()
)
os.close(fd)
os.unlink(fname)
def test_numpy_float64(self):
np = pytest.importorskip("numpy")
wt = np.float64(3.4)
G = nx.Graph([(1, 2, {"weight": wt})])
fd, fname = tempfile.mkstemp()
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
os.close(fd)
os.unlink(fname)
def test_numpy_float32(self):
np = pytest.importorskip("numpy")
wt = np.float32(3.4)
G = nx.Graph([(1, 2, {"weight": wt})])
fd, fname = tempfile.mkstemp()
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
os.close(fd)
os.unlink(fname)
def test_numpy_float64_inference(self):
np = pytest.importorskip("numpy")
G = self.attribute_numeric_type_graph
G.edges[("n1", "n1")]["weight"] = np.float64(1.1)
fd, fname = tempfile.mkstemp()
self.writer(G, fname, infer_numeric_types=True)
H = nx.read_graphml(fname)
assert G._adj == H._adj
os.close(fd)
os.unlink(fname)
def test_unicode_attributes(self):
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)
fd, fname = tempfile.mkstemp()
self.writer(G, fname)
H = nx.read_graphml(fname, node_type=node_type)
assert G._adj == H._adj
os.close(fd)
os.unlink(fname)
def test_unicode_escape(self):
# test for handling json escaped stings in python 2 Issue #1880
import json
a = dict(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)