read_sparse6(path)

Parameters

path : file or string

File or filename to write.

Raises

NetworkXError

If the string is unable to be parsed in sparse6 format

Returns

G : Graph/Multigraph or list of Graphs/MultiGraphs

If the file contains multiple lines then a list of graphs is returned

Read an undirected graph in sparse6 format from path.

See Also

from_sparse6_bytes

read_sparse6

Examples

>>> import tempfile
>>> with tempfile.NamedTemporaryFile() as f:
...     _ = f.write(b">>sparse6<<:An\n")
...     _ = f.seek(0)
...     G = nx.read_sparse6(f.name)
>>> list(G.edges())
[(0, 1)]

>>> import tempfile
>>> with tempfile.NamedTemporaryFile() as f:
...     _ = f.write(b">>sparse6<<:An\n")
...     _ = f.seek(0)
...     G = nx.read_sparse6(f)
>>> list(G.edges())
[(0, 1)]

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

networkx.readwrite.sparse6.read_sparse6 networkx.readwrite.sparse6.write_sparse6 networkx.readwrite.sparse6.from_sparse6_bytes networkx.readwrite.sparse6.to_sparse6_bytes

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them

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GitHub : /networkx/readwrite/sparse6.py#251
type: <class 'function'>
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