"""
*************************
Multi-line Adjacency List
*************************
Read and write NetworkX graphs as multi-line adjacency lists.
The multi-line adjacency list format is useful for graphs with
nodes that can be meaningfully represented as strings. With this format
simple edge data can be stored but node or graph data is not.
Format
------
The first label in a line is the source node label followed by the node degree
d. The next d lines are target node labels and optional edge data.
That pattern repeats for all nodes in the graph.
The graph with edges a-b, a-c, d-e can be represented as the following
adjacency list (anything following the # in a line is a comment)::
# example.multiline-adjlist
a 2
b
c
d 1
e
"""
__all__ = [
"generate_multiline_adjlist",
"write_multiline_adjlist",
"parse_multiline_adjlist",
"read_multiline_adjlist",
]
import networkx as nx
from networkx.utils import open_file
[docs]
def generate_multiline_adjlist(G, delimiter=" "):
"""Generate lines representing the graph `G` in multiline adjacency list format.
Parameters
----------
G : NetworkX graph
delimiter : str, optional (default=" ")
Separator for node labels.
Yields
------
str
A line of data in multiline adjacency list format for a node or one of
its neighbors in `G`.
Examples
--------
>>> G = nx.lollipop_graph(4, 3)
>>> for line in nx.generate_multiline_adjlist(G):
... print(line)
0 3
1 {}
2 {}
3 {}
1 2
2 {}
3 {}
2 1
3 {}
3 1
4 {}
4 1
5 {}
5 1
6 {}
6 0
See Also
--------
write_multiline_adjlist, read_multiline_adjlist
"""
if G.is_directed():
if G.is_multigraph():
for s, nbrs in G.adjacency():
nbr_edges = [
(u, data)
for u, datadict in nbrs.items()
for key, data in datadict.items()
]
deg = len(nbr_edges)
yield str(s) + delimiter + str(deg)
for u, d in nbr_edges:
if d is None:
yield str(u)
else:
yield str(u) + delimiter + str(d)
else: # directed single edges
for s, nbrs in G.adjacency():
deg = len(nbrs)
yield str(s) + delimiter + str(deg)
for u, d in nbrs.items():
if d is None:
yield str(u)
else:
yield str(u) + delimiter + str(d)
else: # undirected
if G.is_multigraph():
seen = set() # helper dict used to avoid duplicate edges
for s, nbrs in G.adjacency():
nbr_edges = [
(u, data)
for u, datadict in nbrs.items()
if u not in seen
for key, data in datadict.items()
]
deg = len(nbr_edges)
yield str(s) + delimiter + str(deg)
for u, d in nbr_edges:
if d is None:
yield str(u)
else:
yield str(u) + delimiter + str(d)
seen.add(s)
else: # undirected single edges
seen = set() # helper dict used to avoid duplicate edges
for s, nbrs in G.adjacency():
nbr_edges = [(u, d) for u, d in nbrs.items() if u not in seen]
deg = len(nbr_edges)
yield str(s) + delimiter + str(deg)
for u, d in nbr_edges:
if d is None:
yield str(u)
else:
yield str(u) + delimiter + str(d)
seen.add(s)
[docs]
@open_file(1, mode="wb")
def write_multiline_adjlist(G, path, delimiter=" ", comments="#", encoding="utf-8"):
"""Write the graph G in multiline adjacency list format to path
Parameters
----------
G : NetworkX graph
path : string or file
Filename or file handle to write to.
Filenames ending in .gz or .bz2 will be compressed.
comments : string, optional
Marker for comment lines
delimiter : string, optional
Separator for node labels
encoding : string, optional
Text encoding.
Examples
--------
>>> from pathlib import Path
>>> import tempfile
>>> tmp_path = Path(tempfile.gettempdir())
>>> G = nx.path_graph(4)
>>> fpath = tmp_path / "test.multi_adjlist"
>>> nx.write_multiline_adjlist(G, fpath)
View the data as stored in the file, ignoring header lines which start with
the comment character ("#" by default):
>>> with open(fpath) as fh:
... lines_from_file = fh.readlines()
>>> print("".join(l for l in lines_from_file if not l.startswith("#")))
0 1
1 {}
1 1
2 {}
2 1
3 {}
3 0
<BLANKLINE>
The path can be a file handle or a string with the name of the file. If a
file handle is provided, it has to be opened in 'wb' mode.
>>> fpath = tmp_path / "test.multi_adjlist2"
>>> with open(fpath, "wb") as fh:
... nx.write_multiline_adjlist(G, fh)
>>> with open(fpath) as fh:
... lines_from_file = fh.readlines()
>>> print("".join(l for l in lines_from_file if not l.startswith("#")))
0 1
1 {}
1 1
2 {}
2 1
3 {}
3 0
<BLANKLINE>
See Also
--------
read_multiline_adjlist
"""
import sys
import time
pargs = comments + " ".join(sys.argv)
header = (
f"{pargs}\n"
+ comments
+ f" GMT {time.asctime(time.gmtime())}\n"
+ comments
+ f" {G.name}\n"
)
path.write(header.encode(encoding))
for multiline in generate_multiline_adjlist(G, delimiter):
multiline += "\n"
path.write(multiline.encode(encoding))
[docs]
@nx._dispatchable(graphs=None, returns_graph=True)
def parse_multiline_adjlist(
lines, comments="#", delimiter=None, create_using=None, nodetype=None, edgetype=None
):
"""Parse lines of a multiline adjacency list representation of a graph.
Parameters
----------
lines : list or iterator of strings
Input data in multiline adjlist format
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 edges 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
The graph corresponding to the lines in multiline adjacency list format.
Examples
--------
>>> lines = [
... "1 2",
... "2 {'weight':3, 'name': 'Frodo'}",
... "3 {}",
... "2 1",
... "5 {'weight':6, 'name': 'Saruman'}",
... ]
>>> G = nx.parse_multiline_adjlist(iter(lines), nodetype=int)
>>> list(G)
[1, 2, 3, 5]
"""
from ast import literal_eval
G = nx.empty_graph(0, create_using)
for line in lines:
p = line.find(comments)
if p >= 0:
line = line[:p]
if not line:
continue
try:
(u, deg) = line.rstrip("\n").split(delimiter)
deg = int(deg)
except BaseException as err:
raise TypeError(f"Failed to read node and degree on line ({line})") from err
if nodetype is not None:
try:
u = nodetype(u)
except BaseException as err:
raise TypeError(
f"Failed to convert node ({u}) to type {nodetype}"
) from err
G.add_node(u)
for i in range(deg):
while True:
try:
line = next(lines)
except StopIteration as err:
msg = f"Failed to find neighbor for node ({u})"
raise TypeError(msg) from err
p = line.find(comments)
if p >= 0:
line = line[:p]
if line:
break
vlist = line.rstrip("\n").split(delimiter)
numb = len(vlist)
if numb < 1:
continue # isolated node
v = vlist.pop(0)
data = "".join(vlist)
if nodetype is not None:
try:
v = nodetype(v)
except BaseException as err:
raise TypeError(
f"Failed to convert node ({v}) to type {nodetype}"
) from err
if edgetype is not None:
try:
edgedata = {"weight": edgetype(data)}
except BaseException as err:
raise TypeError(
f"Failed to convert edge data ({data}) to type {edgetype}"
) from err
else:
try: # try to evaluate
edgedata = literal_eval(data)
except:
edgedata = {}
G.add_edge(u, v, **edgedata)
return G
[docs]
@open_file(0, mode="rb")
@nx._dispatchable(graphs=None, returns_graph=True)
def 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 decompressed.
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
Examples
--------
>>> from pathlib import Path
>>> import tempfile
>>> tmp_path = Path(tempfile.gettempdir())
>>> G = nx.path_graph(4)
>>> fpath = tmp_path / "test.multi_adjlistP4"
>>> nx.write_multiline_adjlist(G, fpath)
>>> H = nx.read_multiline_adjlist(fpath)
Data read from the file are interpreted as strings by default, regardless of
the node type of the original graph.
>>> G.edges
EdgeView([(0, 1), (1, 2), (2, 3)])
>>> H.edges
EdgeView([('0', '1'), ('1', '2'), ('2', '3')])
The node data can be converted to a specific type with the `nodetype`
parameter.
>>> H = nx.read_multiline_adjlist(fpath, nodetype=int)
>>> H.edges
EdgeView([(0, 1), (1, 2), (2, 3)])
>>> nx.utils.edges_equal(G.edges, H.edges)
True
Since nodes must be hashable, the function `nodetype` must return hashable
types (e.g. int, float, str, frozenset - or tuples of those, etc.)
The optional `create_using` parameter indicates the type of NetworkX graph
created. The default is ``nx.Graph``, an undirected graph. To read the data
as a directed graph use:
>>> H = nx.read_multiline_adjlist(fpath, create_using=nx.DiGraph)
>>> H.is_directed()
True
The path can be a file or a string with the name of the file. If a
file is provided, it has to be opened in 'rb' mode.
>>> with open(fpath, "rb") as fh:
... H = nx.read_multiline_adjlist(fh, nodetype=int)
>>> H.edges
EdgeView([(0, 1), (1, 2), (2, 3)])
Notes
-----
This format does not store graph, node, or edge data.
See Also
--------
write_multiline_adjlist
"""
lines = (line.decode(encoding) for line in path)
return parse_multiline_adjlist(
lines,
comments=comments,
delimiter=delimiter,
create_using=create_using,
nodetype=nodetype,
edgetype=edgetype,
)
