write_edgelist#

write_edgelist(G, path, comments='#', delimiter=' ', data=True, encoding='utf-8')[source]#

Write a bipartite graph as a list of edges.

Parameters:
GGraph

A NetworkX bipartite graph

pathfile or string

File or filename to write. If a file is provided, it must be opened in ‘wb’ mode. Filenames ending in .gz or .bz2 will be compressed.

commentsstring, optional

The character used to indicate the start of a comment

delimiterstring, optional

The string used to separate values. The default is whitespace.

databool or list, optional

If False write no edge data. If True write a string representation of the edge data dictionary.. If a list (or other iterable) is provided, write the keys specified in the list.

encoding: string, optional

Specify which encoding to use when writing file.

Examples

>>> from pathlib import Path
>>> import tempfile, gzip
>>> tmp_path = Path(tempfile.gettempdir())
>>> G = nx.path_graph(4)
>>> G.add_nodes_from([0, 2], bipartite=0)
>>> G.add_nodes_from([1, 3], bipartite=1)

Write out the bipartite edgelist to file

>>> fpath = tmp_path / "test.edgelist"
>>> nx.bipartite.write_edgelist(G, fpath)
>>> with open(fpath) as fh:
...     print(fh.read())
0 1 {}
2 1 {}
2 3 {}

A filename ending with “.gz” or “.bz2” will be automatically compressed

>>> fpath = tmp_path / "test_edgelist.gz"
>>> nx.bipartite.write_edgelist(G, fpath)
>>> with gzip.open(fpath) as fh:
...     print(fh.read().decode())
0 1 {}
2 1 {}
2 3 {}

The data keyword argument is used to toggle whether edge attribute data are included:

>>> G = nx.Graph()
>>> G.add_node(1, bipartite=0)
>>> G.add_node(2, bipartite=1)
>>> G.add_edge(1, 2, weight=7, color="red")
>>> fpath = tmp_path / "test.edgelist"
>>> nx.bipartite.write_edgelist(G, fpath, data=False)
>>> with open(fpath) as fh:
...     print(fh.read())
1 2

Or to specify which edge attribute data to include:

>>> nx.bipartite.write_edgelist(G, fpath, data=["color"])
>>> with open(fpath) as fh:
...     print(fh.read())
1 2 red
>>> nx.bipartite.write_edgelist(G, fpath, data=["color", "weight"])
>>> with open(fpath) as fh:
...     print(fh.read())
1 2 red 7