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.
See also
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
datakeyword 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