How do I copy, but not deepcopy, a networkx Graph? - networkx

Question

I want to compare the state of a networkx.Graph object n before a function call d(n) (with side effects) with the state afterwards.
There are mutable object node attributes such as n.node[0]['attribute'], which I want to compare.
Obviously,
before = n
d()
after = n
assert id(before.node[0]['attribute']) == id(after.node[0]['attribute'])
succeeds trivially, because
before == after
but if I set before=n.copy(), a deep copy is made, and therefore id(before.node[0]['attribute']) != id(after.node[0]['attribute']). How do I get a copy of a Graph object without copying all node attribute objects?

Answer 1

Calling the copy method gives a deep copy. All attributes of the new graph are copies of the original graph. Calling the constructor (e.g. Graph(G)) gives a shallow copy where the graph structure is copied but the data attributes are references those in the original graph.
From the copy method docs
All copies reproduce the graph structure, but data attributes may be
handled in different ways. There are four types of copies of a graph
that people might want.
Deepcopy -- The default behavior is a "deepcopy" where the graph
structure as well as all data attributes and any objects they might
contain are copied. The entire graph object is new so that changes in
the copy do not affect the original object.
Data Reference (Shallow) -- For a shallow copy (with_data=False) the
graph structure is copied but the edge, node and graph attribute dicts
are references to those in the original graph. This saves time and
memory but could cause confusion if you change an attribute in one
graph and it changes the attribute in the other.
In [1]: import networkx as nx
In [2]: G = nx.Graph()
In [3]: G.add_node(1, color=['red'])
In [4]: G_deep = G.copy()
In [5]: G_deep.node[1]['color'].append('blue')
In [6]: list(G.nodes(data=True))
Out[6]: [(1, {'color': ['red']})]
In [7]: list(G_deep.nodes(data=True))
Out[7]: [(1, {'color': ['red', 'blue']})]
In [8]: G_shallow = nx.Graph(G)
In [9]: G_shallow.node[1]['color'].append('blue')
In [10]: list(G.nodes(data=True))
Out[10]: [(1, {'color': ['red', 'blue']})]
In [11]: list(G_shallow.nodes(data=True))
Out[11]: [(1, {'color': ['red', 'blue']})]

Answer 2

Try this:
G = # your graph
G2 = nx.Graph() # or whatever type of graph `G` is
G2.add_edges_from(G.edges())

Answer 3

Please also note that if your networkx graph contains objects of objects..., even a deepcopy would not work. It would return an error that there are too many levels.
Normally, I would think what exactly is of interest in the graph and just create a new one with that.