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# read_multiline_adjlist

read_multiline_adjlist(path, comments='#', delimiter=None, create_using=None, nodetype=None, edgetype=None, encoding='utf-8')

  Read graph in multi-line adjacency list format from path.

  Parameters:
    path string or file

      Filename or file handle to read. Filenames ending in .gz or .bz2 will be uncompressed.

    create_using NetworkX graph constructor, optional (default=nx.Graph)

      Graph type to create. If graph instance, then cleared before populated.

    nodetype Python type, optional

      Convert nodes to this type.

    edgetype Python type, optional

      Convert edge data to this type.

    comments string, optional

      Marker for comment lines

    delimiter string, optional

      Separator for node labels. The default is whitespace.

  Returns:
    G: NetworkX graph

  See also

  `write_multiline_adjlist`

  Notes

  This format does not store graph, node, or edge data.

  Examples

      >>> G = nx.path_graph(4)
      >>> nx.write_multiline_adjlist(G, "test.adjlist")
      >>> G = nx.read_multiline_adjlist("test.adjlist")

  The path can be a file or a string with the name of the file. If a file s provided, it has to be opened in ‘rb’ mode.

      >>> fh = open("test.adjlist", "rb")
      >>> G = nx.read_multiline_adjlist(fh)

  Filenames ending in .gz or .bz2 will be compressed.

      >>> nx.write_multiline_adjlist(G, "test.adjlist.gz")
      >>> G = nx.read_multiline_adjlist("test.adjlist.gz")

  The optional nodetype is a function to convert node strings to nodetype.

  For example

      >>> G = nx.read_multiline_adjlist("test.adjlist", nodetype=int)

  will attempt to convert all nodes to integer type.

  The optional edgetype is a function to convert edge data strings to edgetype.

      >>> G = nx.read_multiline_adjlist("test.adjlist")

  The optional create_using parameter is a NetworkX graph container. The default is Graph(), an undirected graph. To read the data as a directed graph use

      >>> G = nx.read_multiline_adjlist("test.adjlist", create_using=nx.DiGraph)