read_edgelist#

read_edgelist(path, comments='#', delimiter=None, create_using=None, nodetype=None, data=True, edgetype=None, encoding='utf-8')[source]#

Read a bipartite graph from a list of edges.

Parameters:
pathfile or string

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

commentsstring, optional

The character used to indicate the start of a comment.

delimiterstring, optional

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

create_usingGraph container, optional,

Use specified container to build graph. The default is networkx.Graph, an undirected graph.

nodetypeint, float, str, Python type, optional

Convert node data from strings to specified type

databool or list of (label,type) tuples

Tuples specifying dictionary key names and types for edge data

edgetypeint, float, str, Python type, optional OBSOLETE

Convert edge data from strings to specified type and use as ‘weight’

encoding: string, optional

Specify which encoding to use when reading file.

Returns:
Ggraph

A networkx Graph or other type specified with create_using

See also

parse_edgelist

Notes

Since nodes must be hashable, the function nodetype must return hashable types (e.g. int, float, str, frozenset - or tuples of those, etc.)

Examples

>>> from pathlib import Path
>>> import tempfile
>>> tmp_path = Path(tempfile.gettempdir())

>>> fpath = tmp_path / "test.edgelist"
>>> G = nx.path_graph(4)
>>> G.add_nodes_from([0, 2], bipartite=0)
>>> G.add_nodes_from([1, 3], bipartite=1)
>>> nx.bipartite.write_edgelist(G, fpath)

>>> H = nx.bipartite.read_edgelist(fpath)
>>> H.nodes(data="bipartite")
NodeDataView({'0': 0, '1': 1, '2': 0, '3': 1}, data='bipartite')
>>> H.edges
EdgeView([('0', '1'), ('1', '2'), ('2', '3')])

Nodes read from the file are interpreted as strings by default. The nodetype parameter can be used to convert the nodes to another type:

>>> H = nx.bipartite.read_edgelist(fpath, nodetype=int)
>>> H.edges
EdgeView([(0, 1), (1, 2), (2, 3)])

The optional create_using parameter indicates the type of NetworkX graph created. By default an undirected nx.Graph is returned. To read the data as a directed graph use:

>>> H = nx.bipartite.read_edgelist(fpath, create_using=nx.DiGraph)
>>> H.is_directed()
True

By default, edge data is expected to be stored in a serialized dict-like format keyed by attribute name:

>>> fpath = tmp_path / "test_edgelist.data"
>>> with open(fpath, "w") as fh:
...     _ = fh.write("1 2 {'weight': 3}")

>>> G = nx.bipartite.read_edgelist(fpath, nodetype=int)
>>> G.nodes(data="bipartite")
NodeDataView({1: 0, 2: 1}, data='bipartite')
>>> G.edges(data=True)
EdgeDataView([(1, 2, {'weight': 3})])

Alternatively, edge data stored as a flat list without keys can be parsed by passing in the attribute name and data type via data:

>>> textline = "1 2 red 10"
>>> fpath = tmp_path / "test_edgelist.multidata"
>>> with open(fpath, "w") as fh:  # Create a file with multi edge data attrs
...     _ = fh.write(textline)

>>> G = nx.bipartite.read_edgelist(
...     fpath, nodetype=int, data=[("color", str), ("weight", float)]
... )
>>> G.nodes(data="bipartite")
NodeDataView({1: 0, 2: 1}, data='bipartite')
>>> G.edges(data=True)
EdgeDataView([(1, 2, {'color': 'red', 'weight': 10.0})])
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