read_graphml#

read_graphml(path, node_type=<class 'str'>, edge_key_type=<class 'int'>, force_multigraph=False)[source]#

Read graph in GraphML format from path.

Parameters:

pathfile or string: File or filename to write. Filenames ending in .gz or .bz2 will be compressed.
node_type: Python type (default: str): Convert node ids to this type
edge_key_type: Python type (default: int): Convert graphml edge ids to this type. Multigraphs use id as edge key. Non-multigraphs add to edge attribute dict with name “id”.
force_multigraphbool (default: False): If True, return a multigraph with edge keys. If False (the default) return a multigraph when multiedges are in the graph.

Returns:

graph: NetworkX graph: If parallel edges are present or force_multigraph=True then a MultiGraph or MultiDiGraph is returned. Otherwise a Graph/DiGraph. The returned graph is directed if the file indicates it should be.

Notes

Default node and edge attributes are not propagated to each node and edge. They can be obtained from G.graph and applied to node and edge attributes if desired using something like this:

>>> default_color = G.graph["node_default"]["color"]  
>>> for node, data in G.nodes(data=True):  
...     if "color" not in data:
...         data["color"] = default_color
>>> default_color = G.graph["edge_default"]["color"]  
>>> for u, v, data in G.edges(data=True):  
...     if "color" not in data:
...         data["color"] = default_color

This implementation does not support mixed graphs (directed and unidirected edges together), hypergraphs, nested graphs, or ports.

For multigraphs the GraphML edge “id” will be used as the edge key. If not specified then they “key” attribute will be used. If there is no “key” attribute a default NetworkX multigraph edge key will be provided.

Files with the yEd “yfiles” extension can be read. The type of the node’s shape is preserved in the shape_type node attribute.

yEd compressed files (“file.graphmlz” extension) can be read by renaming the file to “file.graphml.gz”.