Upload folder using huggingface_hub (part 11)

.gitattributes

@@ -231,3 +231,23 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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.venv/lib/python3.12/site-packages/networkx-3.6.1.dist-info/INSTALLER

@@ -0,0 +1 @@
+pip

.venv/lib/python3.12/site-packages/networkx-3.6.1.dist-info/METADATA

@@ -0,0 +1,177 @@
+Metadata-Version: 2.4
+Name: networkx
+Version: 3.6.1
+Summary: Python package for creating and manipulating graphs and networks
+Author-email: Aric Hagberg <hagberg@lanl.gov>
+Maintainer-email: NetworkX Developers <networkx-discuss@googlegroups.com>
+License-Expression: BSD-3-Clause
+Project-URL: Homepage, https://networkx.org/
+Project-URL: Bug Tracker, https://github.com/networkx/networkx/issues
+Project-URL: Documentation, https://networkx.org/documentation/stable/
+Project-URL: Source Code, https://github.com/networkx/networkx
+Keywords: Networks,Graph Theory,Mathematics,network,graph,discrete mathematics,math
+Platform: Linux
+Platform: Mac OSX
+Platform: Windows
+Platform: Unix
+Classifier: Development Status :: 5 - Production/Stable
+Classifier: Intended Audience :: Developers
+Classifier: Intended Audience :: Science/Research
+Classifier: Operating System :: OS Independent
+Classifier: Programming Language :: Python :: 3
+Classifier: Programming Language :: Python :: 3.11
+Classifier: Programming Language :: Python :: 3.12
+Classifier: Programming Language :: Python :: 3.13
+Classifier: Programming Language :: Python :: 3.14
+Classifier: Programming Language :: Python :: 3 :: Only
+Classifier: Topic :: Software Development :: Libraries :: Python Modules
+Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
+Classifier: Topic :: Scientific/Engineering :: Information Analysis
+Classifier: Topic :: Scientific/Engineering :: Mathematics
+Classifier: Topic :: Scientific/Engineering :: Physics
+Requires-Python: !=3.14.1,>=3.11
+Description-Content-Type: text/x-rst
+License-File: LICENSE.txt
+Provides-Extra: benchmarking
+Requires-Dist: asv; extra == "benchmarking"
+Requires-Dist: virtualenv; extra == "benchmarking"
+Provides-Extra: default
+Requires-Dist: numpy>=1.25; extra == "default"
+Requires-Dist: scipy>=1.11.2; extra == "default"
+Requires-Dist: matplotlib>=3.8; extra == "default"
+Requires-Dist: pandas>=2.0; extra == "default"
+Provides-Extra: developer
+Requires-Dist: pre-commit>=4.1; extra == "developer"
+Requires-Dist: mypy>=1.15; extra == "developer"
+Provides-Extra: doc
+Requires-Dist: sphinx>=8.0; extra == "doc"
+Requires-Dist: pydata-sphinx-theme>=0.16; extra == "doc"
+Requires-Dist: sphinx-gallery>=0.18; extra == "doc"
+Requires-Dist: numpydoc>=1.8.0; extra == "doc"
+Requires-Dist: pillow>=10; extra == "doc"
+Requires-Dist: texext>=0.6.7; extra == "doc"
+Requires-Dist: myst-nb>=1.1; extra == "doc"
+Requires-Dist: intersphinx-registry; extra == "doc"
+Provides-Extra: example
+Requires-Dist: osmnx>=2.0.0; extra == "example"
+Requires-Dist: momepy>=0.7.2; extra == "example"
+Requires-Dist: contextily>=1.6; extra == "example"
+Requires-Dist: seaborn>=0.13; extra == "example"
+Requires-Dist: cairocffi>=1.7; extra == "example"
+Requires-Dist: igraph>=0.11; extra == "example"
+Requires-Dist: scikit-learn>=1.5; extra == "example"
+Requires-Dist: iplotx>=0.9.0; extra == "example"
+Provides-Extra: extra
+Requires-Dist: lxml>=4.6; extra == "extra"
+Requires-Dist: pygraphviz>=1.14; extra == "extra"
+Requires-Dist: pydot>=3.0.1; extra == "extra"
+Requires-Dist: sympy>=1.10; extra == "extra"
+Provides-Extra: release
+Requires-Dist: build>=0.10; extra == "release"
+Requires-Dist: twine>=4.0; extra == "release"
+Requires-Dist: wheel>=0.40; extra == "release"
+Requires-Dist: changelist==0.5; extra == "release"
+Provides-Extra: test
+Requires-Dist: pytest>=7.2; extra == "test"
+Requires-Dist: pytest-cov>=4.0; extra == "test"
+Requires-Dist: pytest-xdist>=3.0; extra == "test"
+Provides-Extra: test-extras
+Requires-Dist: pytest-mpl; extra == "test-extras"
+Requires-Dist: pytest-randomly; extra == "test-extras"
+Dynamic: license-file
+
+NetworkX
+========
+
+
+.. image::
+    https://github.com/networkx/networkx/actions/workflows/test.yml/badge.svg?branch=main
+    :target: https://github.com/networkx/networkx/actions/workflows/test.yml
+
+.. image::
+    https://img.shields.io/pypi/v/networkx.svg?
+    :target: https://pypi.python.org/pypi/networkx
+
+.. image::
+    https://img.shields.io/pypi/l/networkx.svg?
+    :target: https://github.com/networkx/networkx/blob/main/LICENSE.txt
+
+.. image::
+    https://img.shields.io/pypi/pyversions/networkx.svg?
+    :target: https://pypi.python.org/pypi/networkx
+
+.. image::
+    https://img.shields.io/github/labels/networkx/networkx/good%20first%20issue?color=green&label=contribute
+    :target: https://github.com/networkx/networkx/contribute
+
+.. image::
+    https://insights.linuxfoundation.org/api/badge/health-score?project=networkx
+    :target: https://insights.linuxfoundation.org/project/networkx
+
+
+NetworkX is a Python package for the creation, manipulation,
+and study of the structure, dynamics, and functions
+of complex networks.
+
+- **Website (including documentation):** https://networkx.org
+- **Mailing list:** https://groups.google.com/forum/#!forum/networkx-discuss
+- **Source:** https://github.com/networkx/networkx
+- **Bug reports:** https://github.com/networkx/networkx/issues
+- **Report a security vulnerability:** https://tidelift.com/security
+- **Tutorial:** https://networkx.org/documentation/latest/tutorial.html
+- **GitHub Discussions:** https://github.com/networkx/networkx/discussions
+- **Discord (Scientific Python) invite link:** https://discord.com/invite/vur45CbwMz
+- **NetworkX meetings calendar (open to all):** https://scientific-python.org/calendars/networkx.ics
+
+Simple example
+--------------
+
+Find the shortest path between two nodes in an undirected graph:
+
+.. code:: pycon
+
+    >>> import networkx as nx
+    >>> G = nx.Graph()
+    >>> G.add_edge("A", "B", weight=4)
+    >>> G.add_edge("B", "D", weight=2)
+    >>> G.add_edge("A", "C", weight=3)
+    >>> G.add_edge("C", "D", weight=4)
+    >>> nx.shortest_path(G, "A", "D", weight="weight")
+    ['A', 'B', 'D']
+
+Install
+-------
+
+Install the latest released version of NetworkX:
+
+.. code:: shell
+
+    $ pip install networkx
+
+Install with all optional dependencies:
+
+.. code:: shell
+
+    $ pip install networkx[default]
+
+For additional details,
+please see the `installation guide <https://networkx.org/documentation/stable/install.html>`_.
+
+Bugs
+----
+
+Please report any bugs that you find `here <https://github.com/networkx/networkx/issues>`_.
+Or, even better, fork the repository on `GitHub <https://github.com/networkx/networkx>`_
+and create a pull request (PR). We welcome all changes, big or small, and we
+will help you make the PR if you are new to `git` (just ask on the issue and/or
+see the `contributor guide <https://networkx.org/documentation/latest/developer/contribute.html>`_).
+
+License
+-------
+
+Released under the `3-clause BSD license <https://github.com/networkx/networkx/blob/main/LICENSE.txt>`_::
+
+    Copyright (c) 2004-2025, NetworkX Developers
+    Aric Hagberg <hagberg@lanl.gov>
+    Dan Schult <dschult@colgate.edu>
+    Pieter Swart <swart@lanl.gov>

.venv/lib/python3.12/site-packages/networkx-3.6.1.dist-info/WHEEL

@@ -0,0 +1,5 @@
+Wheel-Version: 1.0
+Generator: setuptools (80.9.0)
+Root-Is-Purelib: true
+Tag: py3-none-any
+

.venv/lib/python3.12/site-packages/networkx-3.6.1.dist-info/entry_points.txt

@@ -0,0 +1,2 @@
+[networkx.backends]
+nx_loopback = networkx.classes.tests.dispatch_interface:backend_interface

.venv/lib/python3.12/site-packages/networkx-3.6.1.dist-info/licenses/LICENSE.txt

@@ -0,0 +1,37 @@
+NetworkX is distributed with the 3-clause BSD license.
+
+::
+
+   Copyright (c) 2004-2025, NetworkX Developers
+   Aric Hagberg <hagberg@lanl.gov>
+   Dan Schult <dschult@colgate.edu>
+   Pieter Swart <swart@lanl.gov>
+   All rights reserved.
+
+   Redistribution and use in source and binary forms, with or without
+   modification, are permitted provided that the following conditions are
+   met:
+
+     * Redistributions of source code must retain the above copyright
+       notice, this list of conditions and the following disclaimer.
+
+     * Redistributions in binary form must reproduce the above
+       copyright notice, this list of conditions and the following
+       disclaimer in the documentation and/or other materials provided
+       with the distribution.
+
+     * Neither the name of the NetworkX Developers nor the names of its
+       contributors may be used to endorse or promote products derived
+       from this software without specific prior written permission.
+
+   THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+   "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+   LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+   A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
+   OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+   SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
+   LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
+   DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
+   THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+   (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+   OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

.venv/lib/python3.12/site-packages/networkx-3.6.1.dist-info/top_level.txt

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+networkx

.venv/lib/python3.12/site-packages/networkx/readwrite/json_graph/__init__.py

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+"""
+*********
+JSON data
+*********
+Generate and parse JSON serializable data for NetworkX graphs.
+
+These formats are suitable for use with the d3.js examples https://d3js.org/
+
+The three formats that you can generate with NetworkX are:
+
+ - node-link like in the d3.js example https://bl.ocks.org/mbostock/4062045
+ - tree like in the d3.js example https://bl.ocks.org/mbostock/4063550
+ - adjacency like in the d3.js example https://bost.ocks.org/mike/miserables/
+"""
+
+from networkx.readwrite.json_graph.node_link import *
+from networkx.readwrite.json_graph.adjacency import *
+from networkx.readwrite.json_graph.tree import *
+from networkx.readwrite.json_graph.cytoscape import *

.venv/lib/python3.12/site-packages/networkx/readwrite/json_graph/adjacency.py

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+import networkx as nx
+
+__all__ = ["adjacency_data", "adjacency_graph"]
+
+_attrs = {"id": "id", "key": "key"}
+
+
+def adjacency_data(G, attrs=_attrs):
+    """Returns data in adjacency format that is suitable for JSON serialization
+    and use in JavaScript documents.
+
+    Parameters
+    ----------
+    G : NetworkX graph
+
+    attrs : dict
+        A dictionary that contains two keys 'id' and 'key'. The corresponding
+        values provide the attribute names for storing NetworkX-internal graph
+        data. The values should be unique. Default value:
+        :samp:`dict(id='id', key='key')`.
+
+        If some user-defined graph data use these attribute names as data keys,
+        they may be silently dropped.
+
+    Returns
+    -------
+    data : dict
+       A dictionary with adjacency formatted data.
+
+    Raises
+    ------
+    NetworkXError
+        If values in attrs are not unique.
+
+    Examples
+    --------
+    >>> from networkx.readwrite import json_graph
+    >>> G = nx.Graph([(1, 2)])
+    >>> data = json_graph.adjacency_data(G)
+
+    To serialize with json
+
+    >>> import json
+    >>> s = json.dumps(data)
+
+    Notes
+    -----
+    Graph, node, and link attributes will be written when using this format
+    but attribute keys must be strings if you want to serialize the resulting
+    data with JSON.
+
+    The default value of attrs will be changed in a future release of NetworkX.
+
+    See Also
+    --------
+    adjacency_graph, node_link_data, tree_data
+    """
+    multigraph = G.is_multigraph()
+    id_ = attrs["id"]
+    # Allow 'key' to be omitted from attrs if the graph is not a multigraph.
+    key = None if not multigraph else attrs["key"]
+    if id_ == key:
+        raise nx.NetworkXError("Attribute names are not unique.")
+    data = {}
+    data["directed"] = G.is_directed()
+    data["multigraph"] = multigraph
+    data["graph"] = list(G.graph.items())
+    data["nodes"] = []
+    data["adjacency"] = []
+    for n, nbrdict in G.adjacency():
+        data["nodes"].append({**G.nodes[n], id_: n})
+        adj = []
+        if multigraph:
+            for nbr, keys in nbrdict.items():
+                for k, d in keys.items():
+                    adj.append({**d, id_: nbr, key: k})
+        else:
+            for nbr, d in nbrdict.items():
+                adj.append({**d, id_: nbr})
+        data["adjacency"].append(adj)
+    return data
+
+
+@nx._dispatchable(graphs=None, returns_graph=True)
+def adjacency_graph(data, directed=False, multigraph=True, attrs=_attrs):
+    """Returns graph from adjacency data format.
+
+    Parameters
+    ----------
+    data : dict
+        Adjacency list formatted graph data
+
+    directed : bool
+        If True, and direction not specified in data, return a directed graph.
+
+    multigraph : bool
+        If True, and multigraph not specified in data, return a multigraph.
+
+    attrs : dict
+        A dictionary that contains two keys 'id' and 'key'. The corresponding
+        values provide the attribute names for storing NetworkX-internal graph
+        data. The values should be unique. Default value:
+        :samp:`dict(id='id', key='key')`.
+
+    Returns
+    -------
+    G : NetworkX graph
+       A NetworkX graph object
+
+    Examples
+    --------
+    >>> from networkx.readwrite import json_graph
+    >>> G = nx.Graph([(1, 2)])
+    >>> data = json_graph.adjacency_data(G)
+    >>> H = json_graph.adjacency_graph(data)
+
+    Notes
+    -----
+    The default value of attrs will be changed in a future release of NetworkX.
+
+    See Also
+    --------
+    adjacency_graph, node_link_data, tree_data
+    """
+    multigraph = data.get("multigraph", multigraph)
+    directed = data.get("directed", directed)
+    if multigraph:
+        graph = nx.MultiGraph()
+    else:
+        graph = nx.Graph()
+    if directed:
+        graph = graph.to_directed()
+    id_ = attrs["id"]
+    # Allow 'key' to be omitted from attrs if the graph is not a multigraph.
+    key = None if not multigraph else attrs["key"]
+    graph.graph = dict(data.get("graph", []))
+    mapping = []
+    for d in data["nodes"]:
+        node_data = d.copy()
+        node = node_data.pop(id_)
+        mapping.append(node)
+        graph.add_node(node)
+        graph.nodes[node].update(node_data)
+    for i, d in enumerate(data["adjacency"]):
+        source = mapping[i]
+        for tdata in d:
+            target_data = tdata.copy()
+            target = target_data.pop(id_)
+            if not multigraph:
+                graph.add_edge(source, target)
+                graph[source][target].update(target_data)
+            else:
+                ky = target_data.pop(key, None)
+                graph.add_edge(source, target, key=ky)
+                graph[source][target][ky].update(target_data)
+    return graph

.venv/lib/python3.12/site-packages/networkx/readwrite/json_graph/cytoscape.py

@@ -0,0 +1,190 @@
+import networkx as nx
+
+__all__ = ["cytoscape_data", "cytoscape_graph"]
+
+
+def cytoscape_data(G, name="name", ident="id"):
+    """Returns data in Cytoscape JSON format (cyjs).
+
+    Parameters
+    ----------
+    G : NetworkX Graph
+        The graph to convert to cytoscape format
+    name : string
+        A string which is mapped to the 'name' node element in cyjs format.
+        Must not have the same value as `ident`.
+    ident : string
+        A string which is mapped to the 'id' node element in cyjs format.
+        Must not have the same value as `name`.
+
+    Returns
+    -------
+    data: dict
+        A dictionary with cyjs formatted data.
+
+    Raises
+    ------
+    NetworkXError
+        If the values for `name` and `ident` are identical.
+
+    See Also
+    --------
+    cytoscape_graph: convert a dictionary in cyjs format to a graph
+
+    References
+    ----------
+    .. [1] Cytoscape user's manual:
+       http://manual.cytoscape.org/en/stable/index.html
+
+    Examples
+    --------
+    >>> from pprint import pprint
+    >>> G = nx.path_graph(2)
+    >>> cyto_data = nx.cytoscape_data(G)
+    >>> pprint(cyto_data, sort_dicts=False)
+    {'data': [],
+     'directed': False,
+     'multigraph': False,
+     'elements': {'nodes': [{'data': {'id': '0', 'value': 0, 'name': '0'}},
+                            {'data': {'id': '1', 'value': 1, 'name': '1'}}],
+                  'edges': [{'data': {'source': 0, 'target': 1}}]}}
+
+    The :mod:`json` package can be used to serialize the resulting data
+
+    >>> import io, json
+    >>> with io.StringIO() as fh:  # replace io with `open(...)` to write to disk
+    ...     json.dump(cyto_data, fh)
+    ...     fh.seek(0)  # doctest: +SKIP
+    ...     print(fh.getvalue()[:64])  # View the first 64 characters
+    {"data": [], "directed": false, "multigraph": false, "elements":
+
+    """
+    if name == ident:
+        raise nx.NetworkXError("name and ident must be different.")
+
+    jsondata = {"data": list(G.graph.items())}
+    jsondata["directed"] = G.is_directed()
+    jsondata["multigraph"] = G.is_multigraph()
+    jsondata["elements"] = {"nodes": [], "edges": []}
+    nodes = jsondata["elements"]["nodes"]
+    edges = jsondata["elements"]["edges"]
+
+    for i, j in G.nodes.items():
+        n = {"data": j.copy()}
+        n["data"]["id"] = j.get(ident) or str(i)
+        n["data"]["value"] = i
+        n["data"]["name"] = j.get(name) or str(i)
+        nodes.append(n)
+
+    if G.is_multigraph():
+        for e in G.edges(keys=True):
+            n = {"data": G.adj[e[0]][e[1]][e[2]].copy()}
+            n["data"]["source"] = e[0]
+            n["data"]["target"] = e[1]
+            n["data"]["key"] = e[2]
+            edges.append(n)
+    else:
+        for e in G.edges():
+            n = {"data": G.adj[e[0]][e[1]].copy()}
+            n["data"]["source"] = e[0]
+            n["data"]["target"] = e[1]
+            edges.append(n)
+    return jsondata
+
+
+@nx._dispatchable(graphs=None, returns_graph=True)
+def cytoscape_graph(data, name="name", ident="id"):
+    """
+    Create a NetworkX graph from a dictionary in cytoscape JSON format.
+
+    Parameters
+    ----------
+    data : dict
+        A dictionary of data conforming to cytoscape JSON format.
+    name : string
+        A string which is mapped to the 'name' node element in cyjs format.
+        Must not have the same value as `ident`.
+    ident : string
+        A string which is mapped to the 'id' node element in cyjs format.
+        Must not have the same value as `name`.
+
+    Returns
+    -------
+    graph : a NetworkX graph instance
+        The `graph` can be an instance of `Graph`, `DiGraph`, `MultiGraph`, or
+        `MultiDiGraph` depending on the input data.
+
+    Raises
+    ------
+    NetworkXError
+        If the `name` and `ident` attributes are identical.
+
+    See Also
+    --------
+    cytoscape_data: convert a NetworkX graph to a dict in cyjs format
+
+    References
+    ----------
+    .. [1] Cytoscape user's manual:
+       http://manual.cytoscape.org/en/stable/index.html
+
+    Examples
+    --------
+    >>> data_dict = {
+    ...     "data": [],
+    ...     "directed": False,
+    ...     "multigraph": False,
+    ...     "elements": {
+    ...         "nodes": [
+    ...             {"data": {"id": "0", "value": 0, "name": "0"}},
+    ...             {"data": {"id": "1", "value": 1, "name": "1"}},
+    ...         ],
+    ...         "edges": [{"data": {"source": 0, "target": 1}}],
+    ...     },
+    ... }
+    >>> G = nx.cytoscape_graph(data_dict)
+    >>> G.name
+    ''
+    >>> G.nodes()
+    NodeView((0, 1))
+    >>> G.nodes(data=True)[0]
+    {'id': '0', 'value': 0, 'name': '0'}
+    >>> G.edges(data=True)
+    EdgeDataView([(0, 1, {'source': 0, 'target': 1})])
+    """
+    if name == ident:
+        raise nx.NetworkXError("name and ident must be different.")
+
+    multigraph = data.get("multigraph")
+    directed = data.get("directed")
+    if multigraph:
+        graph = nx.MultiGraph()
+    else:
+        graph = nx.Graph()
+    if directed:
+        graph = graph.to_directed()
+    graph.graph = dict(data.get("data"))
+    for d in data["elements"]["nodes"]:
+        node_data = d["data"].copy()
+        node = d["data"]["value"]
+
+        if d["data"].get(name):
+            node_data[name] = d["data"].get(name)
+        if d["data"].get(ident):
+            node_data[ident] = d["data"].get(ident)
+
+        graph.add_node(node)
+        graph.nodes[node].update(node_data)
+
+    for d in data["elements"]["edges"]:
+        edge_data = d["data"].copy()
+        sour = d["data"]["source"]
+        targ = d["data"]["target"]
+        if multigraph:
+            key = d["data"].get("key", 0)
+            graph.add_edge(sour, targ, key=key)
+            graph.edges[sour, targ, key].update(edge_data)
+        else:
+            graph.add_edge(sour, targ)
+            graph.edges[sour, targ].update(edge_data)
+    return graph

.venv/lib/python3.12/site-packages/networkx/readwrite/json_graph/node_link.py

@@ -0,0 +1,261 @@
+import warnings
+from itertools import count
+
+import networkx as nx
+
+__all__ = ["node_link_data", "node_link_graph"]
+
+
+def _to_tuple(x):
+    """Converts lists to tuples, including nested lists.
+
+    All other non-list inputs are passed through unmodified. This function is
+    intended to be used to convert potentially nested lists from json files
+    into valid nodes.
+
+    Examples
+    --------
+    >>> _to_tuple([1, 2, [3, 4]])
+    (1, 2, (3, 4))
+    """
+    if not isinstance(x, tuple | list):
+        return x
+    return tuple(map(_to_tuple, x))
+
+
+def node_link_data(
+    G,
+    *,
+    source="source",
+    target="target",
+    name="id",
+    key="key",
+    edges="edges",
+    nodes="nodes",
+):
+    """Returns data in node-link format that is suitable for JSON serialization
+    and use in JavaScript documents.
+
+    Parameters
+    ----------
+    G : NetworkX graph
+    source : string
+        A string that provides the 'source' attribute name for storing NetworkX-internal graph data.
+    target : string
+        A string that provides the 'target' attribute name for storing NetworkX-internal graph data.
+    name : string
+        A string that provides the 'name' attribute name for storing NetworkX-internal graph data.
+    key : string
+        A string that provides the 'key' attribute name for storing NetworkX-internal graph data.
+    edges : string
+        A string that provides the 'edges' attribute name for storing NetworkX-internal graph data.
+    nodes : string
+        A string that provides the 'nodes' attribute name for storing NetworkX-internal graph data.
+
+    Returns
+    -------
+    data : dict
+       A dictionary with node-link formatted data.
+
+    Raises
+    ------
+    NetworkXError
+        If the values of 'source', 'target' and 'key' are not unique.
+
+    Examples
+    --------
+    >>> from pprint import pprint
+    >>> G = nx.Graph([("A", "B")])
+    >>> data1 = nx.node_link_data(G)
+    >>> pprint(data1)
+    {'directed': False,
+     'edges': [{'source': 'A', 'target': 'B'}],
+     'graph': {},
+     'multigraph': False,
+     'nodes': [{'id': 'A'}, {'id': 'B'}]}
+
+    To serialize with JSON
+
+    >>> import json
+    >>> s1 = json.dumps(data1)
+    >>> pprint(s1)
+    ('{"directed": false, "multigraph": false, "graph": {}, "nodes": [{"id": "A"}, '
+     '{"id": "B"}], "edges": [{"source": "A", "target": "B"}]}')
+
+
+    A graph can also be serialized by passing `node_link_data` as an encoder function.
+
+    >>> s1 = json.dumps(G, default=nx.node_link_data)
+    >>> pprint(s1)
+    ('{"directed": false, "multigraph": false, "graph": {}, "nodes": [{"id": "A"}, '
+     '{"id": "B"}], "edges": [{"source": "A", "target": "B"}]}')
+
+    The attribute names for storing NetworkX-internal graph data can
+    be specified as keyword options.
+
+    >>> H = nx.gn_graph(2)
+    >>> data2 = nx.node_link_data(
+    ...     H, edges="links", source="from", target="to", nodes="vertices"
+    ... )
+    >>> pprint(data2)
+    {'directed': True,
+     'graph': {},
+     'links': [{'from': 1, 'to': 0}],
+     'multigraph': False,
+     'vertices': [{'id': 0}, {'id': 1}]}
+
+    Notes
+    -----
+    Graph, node, and edge attributes are stored in this format.  Note that
+    attribute keys will be converted to strings in order to comply with JSON.
+
+    Attribute 'key' is only used for multigraphs.
+
+    To use `node_link_data` in conjunction with `node_link_graph`,
+    the keyword names for the attributes must match.
+
+    See Also
+    --------
+    node_link_graph, adjacency_data, tree_data
+    """
+    multigraph = G.is_multigraph()
+
+    # Allow 'key' to be omitted from attrs if the graph is not a multigraph.
+    key = None if not multigraph else key
+    if len({source, target, key}) < 3:
+        raise nx.NetworkXError("Attribute names are not unique.")
+    data = {
+        "directed": G.is_directed(),
+        "multigraph": multigraph,
+        "graph": G.graph,
+        nodes: [{**G.nodes[n], name: n} for n in G],
+    }
+    if multigraph:
+        data[edges] = [
+            {**d, source: u, target: v, key: k}
+            for u, v, k, d in G.edges(keys=True, data=True)
+        ]
+    else:
+        data[edges] = [{**d, source: u, target: v} for u, v, d in G.edges(data=True)]
+    return data
+
+
+@nx._dispatchable(graphs=None, returns_graph=True)
+def node_link_graph(
+    data,
+    directed=False,
+    multigraph=True,
+    *,
+    source="source",
+    target="target",
+    name="id",
+    key="key",
+    edges="edges",
+    nodes="nodes",
+):
+    """Returns graph from node-link data format.
+
+    Useful for de-serialization from JSON.
+
+    Parameters
+    ----------
+    data : dict
+        node-link formatted graph data
+
+    directed : bool
+        If True, and direction not specified in data, return a directed graph.
+
+    multigraph : bool
+        If True, and multigraph not specified in data, return a multigraph.
+
+    source : string
+        A string that provides the 'source' attribute name for storing NetworkX-internal graph data.
+    target : string
+        A string that provides the 'target' attribute name for storing NetworkX-internal graph data.
+    name : string
+        A string that provides the 'name' attribute name for storing NetworkX-internal graph data.
+    key : string
+        A string that provides the 'key' attribute name for storing NetworkX-internal graph data.
+    edges : string
+        A string that provides the 'edges' attribute name for storing NetworkX-internal graph data.
+    nodes : string
+        A string that provides the 'nodes' attribute name for storing NetworkX-internal graph data.
+
+    Returns
+    -------
+    G : NetworkX graph
+        A NetworkX graph object
+
+    Examples
+    --------
+
+    Create data in node-link format by converting a graph.
+
+    >>> from pprint import pprint
+    >>> G = nx.Graph([("A", "B")])
+    >>> data = nx.node_link_data(G)
+    >>> pprint(data)
+    {'directed': False,
+     'edges': [{'source': 'A', 'target': 'B'}],
+     'graph': {},
+     'multigraph': False,
+     'nodes': [{'id': 'A'}, {'id': 'B'}]}
+
+    Revert data in node-link format to a graph.
+
+    >>> H = nx.node_link_graph(data)
+    >>> print(H.edges)
+    [('A', 'B')]
+
+    To serialize and deserialize a graph with JSON,
+
+    >>> import json
+    >>> d = json.dumps(nx.node_link_data(G))
+    >>> H = nx.node_link_graph(json.loads(d))
+    >>> print(G.edges, H.edges)
+    [('A', 'B')] [('A', 'B')]
+
+
+    Notes
+    -----
+    Attribute 'key' is only used for multigraphs.
+
+    To use `node_link_data` in conjunction with `node_link_graph`,
+    the keyword names for the attributes must match.
+
+    See Also
+    --------
+    node_link_data, adjacency_data, tree_data
+    """
+    multigraph = data.get("multigraph", multigraph)
+    directed = data.get("directed", directed)
+    if multigraph:
+        graph = nx.MultiGraph()
+    else:
+        graph = nx.Graph()
+    if directed:
+        graph = graph.to_directed()
+
+    # Allow 'key' to be omitted from attrs if the graph is not a multigraph.
+    key = None if not multigraph else key
+    graph.graph = data.get("graph", {})
+    c = count()
+    for d in data[nodes]:
+        node = _to_tuple(d.get(name, next(c)))
+        nodedata = {str(k): v for k, v in d.items() if k != name}
+        graph.add_node(node, **nodedata)
+    for d in data[edges]:
+        src = tuple(d[source]) if isinstance(d[source], list) else d[source]
+        tgt = tuple(d[target]) if isinstance(d[target], list) else d[target]
+        if not multigraph:
+            edgedata = {str(k): v for k, v in d.items() if k != source and k != target}
+            graph.add_edge(src, tgt, **edgedata)
+        else:
+            ky = d.get(key, None)
+            edgedata = {
+                str(k): v
+                for k, v in d.items()
+                if k != source and k != target and k != key
+            }
+            graph.add_edge(src, tgt, ky, **edgedata)
+    return graph

.venv/lib/python3.12/site-packages/networkx/readwrite/json_graph/tests/test_adjacency.py

@@ -0,0 +1,78 @@
+import copy
+import json
+
+import pytest
+
+import networkx as nx
+from networkx.readwrite.json_graph import adjacency_data, adjacency_graph
+from networkx.utils import graphs_equal
+
+
+class TestAdjacency:
+    def test_graph(self):
+        G = nx.path_graph(4)
+        H = adjacency_graph(adjacency_data(G))
+        assert graphs_equal(G, H)
+
+    def test_graph_attributes(self):
+        G = nx.path_graph(4)
+        G.add_node(1, color="red")
+        G.add_edge(1, 2, width=7)
+        G.graph["foo"] = "bar"
+        G.graph[1] = "one"
+
+        H = adjacency_graph(adjacency_data(G))
+        assert graphs_equal(G, H)
+        assert H.graph["foo"] == "bar"
+        assert H.nodes[1]["color"] == "red"
+        assert H[1][2]["width"] == 7
+
+        d = json.dumps(adjacency_data(G))
+        H = adjacency_graph(json.loads(d))
+        assert graphs_equal(G, H)
+        assert H.graph["foo"] == "bar"
+        assert H.graph[1] == "one"
+        assert H.nodes[1]["color"] == "red"
+        assert H[1][2]["width"] == 7
+
+    def test_digraph(self):
+        G = nx.DiGraph()
+        nx.add_path(G, [1, 2, 3])
+        H = adjacency_graph(adjacency_data(G))
+        assert H.is_directed()
+        assert graphs_equal(G, H)
+
+    def test_multidigraph(self):
+        G = nx.MultiDiGraph()
+        nx.add_path(G, [1, 2, 3])
+        H = adjacency_graph(adjacency_data(G))
+        assert H.is_directed()
+        assert H.is_multigraph()
+        assert graphs_equal(G, H)
+
+    def test_multigraph(self):
+        G = nx.MultiGraph()
+        G.add_edge(1, 2, key="first")
+        G.add_edge(1, 2, key="second", color="blue")
+        H = adjacency_graph(adjacency_data(G))
+        assert graphs_equal(G, H)
+        assert H[1][2]["second"]["color"] == "blue"
+
+    def test_input_data_is_not_modified_when_building_graph(self):
+        G = nx.path_graph(4)
+        input_data = adjacency_data(G)
+        orig_data = copy.deepcopy(input_data)
+        # Ensure input is unmodified by deserialisation
+        assert graphs_equal(G, adjacency_graph(input_data))
+        assert input_data == orig_data
+
+    def test_adjacency_form_json_serialisable(self):
+        G = nx.path_graph(4)
+        H = adjacency_graph(json.loads(json.dumps(adjacency_data(G))))
+        assert graphs_equal(G, H)
+
+    def test_exception(self):
+        with pytest.raises(nx.NetworkXError):
+            G = nx.MultiDiGraph()
+            attrs = {"id": "node", "key": "node"}
+            adjacency_data(G, attrs)

.venv/lib/python3.12/site-packages/networkx/readwrite/json_graph/tests/test_cytoscape.py

@@ -0,0 +1,78 @@
+import copy
+import json
+
+import pytest
+
+import networkx as nx
+from networkx.readwrite.json_graph import cytoscape_data, cytoscape_graph
+
+
+def test_graph():
+    G = nx.path_graph(4)
+    H = cytoscape_graph(cytoscape_data(G))
+    assert nx.is_isomorphic(G, H)
+
+
+def test_input_data_is_not_modified_when_building_graph():
+    G = nx.path_graph(4)
+    input_data = cytoscape_data(G)
+    orig_data = copy.deepcopy(input_data)
+    # Ensure input is unmodified by cytoscape_graph (gh-4173)
+    cytoscape_graph(input_data)
+    assert input_data == orig_data
+
+
+def test_graph_attributes():
+    G = nx.path_graph(4)
+    G.add_node(1, color="red")
+    G.add_edge(1, 2, width=7)
+    G.graph["foo"] = "bar"
+    G.graph[1] = "one"
+    G.add_node(3, name="node", id="123")
+
+    H = cytoscape_graph(cytoscape_data(G))
+    assert H.graph["foo"] == "bar"
+    assert H.nodes[1]["color"] == "red"
+    assert H[1][2]["width"] == 7
+    assert H.nodes[3]["name"] == "node"
+    assert H.nodes[3]["id"] == "123"
+
+    d = json.dumps(cytoscape_data(G))
+    H = cytoscape_graph(json.loads(d))
+    assert H.graph["foo"] == "bar"
+    assert H.graph[1] == "one"
+    assert H.nodes[1]["color"] == "red"
+    assert H[1][2]["width"] == 7
+    assert H.nodes[3]["name"] == "node"
+    assert H.nodes[3]["id"] == "123"
+
+
+def test_digraph():
+    G = nx.DiGraph()
+    nx.add_path(G, [1, 2, 3])
+    H = cytoscape_graph(cytoscape_data(G))
+    assert H.is_directed()
+    assert nx.is_isomorphic(G, H)
+
+
+def test_multidigraph():
+    G = nx.MultiDiGraph()
+    nx.add_path(G, [1, 2, 3])
+    H = cytoscape_graph(cytoscape_data(G))
+    assert H.is_directed()
+    assert H.is_multigraph()
+
+
+def test_multigraph():
+    G = nx.MultiGraph()
+    G.add_edge(1, 2, key="first")
+    G.add_edge(1, 2, key="second", color="blue")
+    H = cytoscape_graph(cytoscape_data(G))
+    assert nx.is_isomorphic(G, H)
+    assert H[1][2]["second"]["color"] == "blue"
+
+
+def test_exception():
+    with pytest.raises(nx.NetworkXError):
+        G = nx.MultiDiGraph()
+        cytoscape_data(G, name="foo", ident="foo")

.venv/lib/python3.12/site-packages/networkx/readwrite/json_graph/tests/test_node_link.py

@@ -0,0 +1,109 @@
+import json
+
+import pytest
+
+import networkx as nx
+from networkx.readwrite.json_graph import node_link_data, node_link_graph
+
+
+class TestNodeLink:
+    def test_exception_dep(self):
+        G = nx.MultiDiGraph()
+        with pytest.raises(nx.NetworkXError):
+            node_link_data(G, name="node", source="node", target="node", key="node")
+
+    def test_graph(self):
+        G = nx.path_graph(4)
+        H = node_link_graph(node_link_data(G))
+        assert nx.is_isomorphic(G, H)
+
+    def test_graph_attributes(self):
+        G = nx.path_graph(4)
+        G.add_node(1, color="red")
+        G.add_edge(1, 2, width=7)
+        G.graph[1] = "one"
+        G.graph["foo"] = "bar"
+
+        H = node_link_graph(node_link_data(G))
+        assert H.graph["foo"] == "bar"
+        assert H.nodes[1]["color"] == "red"
+        assert H[1][2]["width"] == 7
+
+        d = json.dumps(node_link_data(G))
+        H = node_link_graph(json.loads(d))
+        assert H.graph["foo"] == "bar"
+        assert H.graph["1"] == "one"
+        assert H.nodes[1]["color"] == "red"
+        assert H[1][2]["width"] == 7
+
+    def test_digraph(self):
+        G = nx.DiGraph()
+        H = node_link_graph(node_link_data(G))
+        assert H.is_directed()
+
+    def test_multigraph(self):
+        G = nx.MultiGraph()
+        G.add_edge(1, 2, key="first")
+        G.add_edge(1, 2, key="second", color="blue")
+        H = node_link_graph(node_link_data(G))
+        assert nx.is_isomorphic(G, H)
+        assert H[1][2]["second"]["color"] == "blue"
+
+    def test_graph_with_tuple_nodes(self):
+        G = nx.Graph()
+        G.add_edge((0, 0), (1, 0), color=[255, 255, 0])
+        d = node_link_data(G)
+        dumped_d = json.dumps(d)
+        dd = json.loads(dumped_d)
+        H = node_link_graph(dd)
+        assert H.nodes[(0, 0)] == G.nodes[(0, 0)]
+        assert H[(0, 0)][(1, 0)]["color"] == [255, 255, 0]
+
+    def test_unicode_keys(self):
+        q = "qualité"
+        G = nx.Graph()
+        G.add_node(1, **{q: q})
+        s = node_link_data(G)
+        output = json.dumps(s, ensure_ascii=False)
+        data = json.loads(output)
+        H = node_link_graph(data)
+        assert H.nodes[1][q] == q
+
+    def test_exception(self):
+        G = nx.MultiDiGraph()
+        attrs = {"name": "node", "source": "node", "target": "node", "key": "node"}
+        with pytest.raises(nx.NetworkXError):
+            node_link_data(G, **attrs)
+
+    def test_string_ids(self):
+        q = "qualité"
+        G = nx.DiGraph()
+        G.add_node("A")
+        G.add_node(q)
+        G.add_edge("A", q)
+        data = node_link_data(G)
+        assert data["edges"][0]["source"] == "A"
+        assert data["edges"][0]["target"] == q
+        H = node_link_graph(data)
+        assert nx.is_isomorphic(G, H)
+
+    def test_custom_attrs(self):
+        G = nx.path_graph(4)
+        G.add_node(1, color="red")
+        G.add_edge(1, 2, width=7)
+        G.graph[1] = "one"
+        G.graph["foo"] = "bar"
+
+        attrs = {
+            "source": "c_source",
+            "target": "c_target",
+            "name": "c_id",
+            "key": "c_key",
+            "edges": "c_links",
+        }
+
+        H = node_link_graph(node_link_data(G, **attrs), multigraph=False, **attrs)
+        assert nx.is_isomorphic(G, H)
+        assert H.graph["foo"] == "bar"
+        assert H.nodes[1]["color"] == "red"
+        assert H[1][2]["width"] == 7

.venv/lib/python3.12/site-packages/networkx/readwrite/json_graph/tests/test_tree.py

@@ -0,0 +1,48 @@
+import json
+
+import pytest
+
+import networkx as nx
+from networkx.readwrite.json_graph import tree_data, tree_graph
+
+
+def test_graph():
+    G = nx.DiGraph()
+    G.add_nodes_from([1, 2, 3], color="red")
+    G.add_edge(1, 2, foo=7)
+    G.add_edge(1, 3, foo=10)
+    G.add_edge(3, 4, foo=10)
+    H = tree_graph(tree_data(G, 1))
+    assert nx.is_isomorphic(G, H)
+
+
+def test_graph_attributes():
+    G = nx.DiGraph()
+    G.add_nodes_from([1, 2, 3], color="red")
+    G.add_edge(1, 2, foo=7)
+    G.add_edge(1, 3, foo=10)
+    G.add_edge(3, 4, foo=10)
+    H = tree_graph(tree_data(G, 1))
+    assert H.nodes[1]["color"] == "red"
+
+    d = json.dumps(tree_data(G, 1))
+    H = tree_graph(json.loads(d))
+    assert H.nodes[1]["color"] == "red"
+
+
+def test_exceptions():
+    with pytest.raises(TypeError, match="is not a tree."):
+        G = nx.complete_graph(3)
+        tree_data(G, 0)
+    with pytest.raises(TypeError, match="is not directed."):
+        G = nx.path_graph(3)
+        tree_data(G, 0)
+    with pytest.raises(TypeError, match="is not weakly connected."):
+        G = nx.path_graph(3, create_using=nx.DiGraph)
+        G.add_edge(2, 0)
+        G.add_node(3)
+        tree_data(G, 0)
+    with pytest.raises(nx.NetworkXError, match="must be different."):
+        G = nx.MultiDiGraph()
+        G.add_node(0)
+        tree_data(G, 0, ident="node", children="node")

.venv/lib/python3.12/site-packages/networkx/readwrite/json_graph/tree.py

@@ -0,0 +1,137 @@
+from itertools import chain
+
+import networkx as nx
+
+__all__ = ["tree_data", "tree_graph"]
+
+
+def tree_data(G, root, ident="id", children="children"):
+    """Returns data in tree format that is suitable for JSON serialization
+    and use in JavaScript documents.
+
+    Parameters
+    ----------
+    G : NetworkX graph
+       G must be an oriented tree
+
+    root : node
+       The root of the tree
+
+    ident : string
+        Attribute name for storing NetworkX-internal graph data. `ident` must
+        have a different value than `children`. The default is 'id'.
+
+    children : string
+        Attribute name for storing NetworkX-internal graph data. `children`
+        must have a different value than `ident`. The default is 'children'.
+
+    Returns
+    -------
+    data : dict
+       A dictionary with node-link formatted data.
+
+    Raises
+    ------
+    NetworkXError
+        If `children` and `ident` attributes are identical.
+
+    Examples
+    --------
+    >>> from networkx.readwrite import json_graph
+    >>> G = nx.DiGraph([(1, 2)])
+    >>> data = json_graph.tree_data(G, root=1)
+
+    To serialize with json
+
+    >>> import json
+    >>> s = json.dumps(data)
+
+    Notes
+    -----
+    Node attributes are stored in this format but keys
+    for attributes must be strings if you want to serialize with JSON.
+
+    Graph and edge attributes are not stored.
+
+    See Also
+    --------
+    tree_graph, node_link_data, adjacency_data
+    """
+    if G.number_of_nodes() != G.number_of_edges() + 1:
+        raise TypeError("G is not a tree.")
+    if not G.is_directed():
+        raise TypeError("G is not directed.")
+    if not nx.is_weakly_connected(G):
+        raise TypeError("G is not weakly connected.")
+
+    if ident == children:
+        raise nx.NetworkXError("The values for `id` and `children` must be different.")
+
+    def add_children(n, G):
+        nbrs = G[n]
+        if len(nbrs) == 0:
+            return []
+        children_ = []
+        for child in nbrs:
+            d = {**G.nodes[child], ident: child}
+            c = add_children(child, G)
+            if c:
+                d[children] = c
+            children_.append(d)
+        return children_
+
+    return {**G.nodes[root], ident: root, children: add_children(root, G)}
+
+
+@nx._dispatchable(graphs=None, returns_graph=True)
+def tree_graph(data, ident="id", children="children"):
+    """Returns graph from tree data format.
+
+    Parameters
+    ----------
+    data : dict
+        Tree formatted graph data
+
+    ident : string
+        Attribute name for storing NetworkX-internal graph data. `ident` must
+        have a different value than `children`. The default is 'id'.
+
+    children : string
+        Attribute name for storing NetworkX-internal graph data. `children`
+        must have a different value than `ident`. The default is 'children'.
+
+    Returns
+    -------
+    G : NetworkX DiGraph
+
+    Examples
+    --------
+    >>> from networkx.readwrite import json_graph
+    >>> G = nx.DiGraph([(1, 2)])
+    >>> data = json_graph.tree_data(G, root=1)
+    >>> H = json_graph.tree_graph(data)
+
+    See Also
+    --------
+    tree_data, node_link_data, adjacency_data
+    """
+    graph = nx.DiGraph()
+
+    def add_children(parent, children_):
+        for data in children_:
+            child = data[ident]
+            graph.add_edge(parent, child)
+            grandchildren = data.get(children, [])
+            if grandchildren:
+                add_children(child, grandchildren)
+            nodedata = {
+                str(k): v for k, v in data.items() if k != ident and k != children
+            }
+            graph.add_node(child, **nodedata)
+
+    root = data[ident]
+    children_ = data.get(children, [])
+    nodedata = {str(k): v for k, v in data.items() if k != ident and k != children}
+    graph.add_node(root, **nodedata)
+    add_children(root, children_)
+    return graph

.venv/lib/python3.12/site-packages/networkx/readwrite/leda.py

@@ -0,0 +1,108 @@
+"""
+Read graphs in LEDA format.
+
+LEDA is a C++ class library for efficient data types and algorithms.
+
+Format
+------
+See http://www.algorithmic-solutions.info/leda_guide/graphs/leda_native_graph_fileformat.html
+
+"""
+# Original author: D. Eppstein, UC Irvine, August 12, 2003.
+# The original code at http://www.ics.uci.edu/~eppstein/PADS/ is public domain.
+
+__all__ = ["read_leda", "parse_leda"]
+
+import networkx as nx
+from networkx.exception import NetworkXError
+from networkx.utils import open_file
+
+
+@open_file(0, mode="rb")
+@nx._dispatchable(graphs=None, returns_graph=True)
+def read_leda(path, encoding="UTF-8"):
+    """Read graph in LEDA format from path.
+
+    Parameters
+    ----------
+    path : file or string
+       Filename or file handle to read.
+       Filenames ending in .gz or .bz2 will be decompressed.
+
+    Returns
+    -------
+    G : NetworkX graph
+
+    Examples
+    --------
+    >>> G = nx.read_leda("file.leda")  # doctest: +SKIP
+
+    References
+    ----------
+    .. [1] http://www.algorithmic-solutions.info/leda_guide/graphs/leda_native_graph_fileformat.html
+    """
+    lines = (line.decode(encoding) for line in path)
+    G = parse_leda(lines)
+    return G
+
+
+@nx._dispatchable(graphs=None, returns_graph=True)
+def parse_leda(lines):
+    """Read graph in LEDA format from string or iterable.
+
+    Parameters
+    ----------
+    lines : string or iterable
+       Data in LEDA format.
+
+    Returns
+    -------
+    G : NetworkX graph
+
+    Examples
+    --------
+    >>> G = nx.parse_leda(string)  # doctest: +SKIP
+
+    References
+    ----------
+    .. [1] http://www.algorithmic-solutions.info/leda_guide/graphs/leda_native_graph_fileformat.html
+    """
+    if isinstance(lines, str):
+        lines = iter(lines.split("\n"))
+    lines = iter(
+        [
+            line.rstrip("\n")
+            for line in lines
+            if not (line.startswith(("#", "\n")) or line == "")
+        ]
+    )
+    for i in range(3):
+        next(lines)
+    # Graph
+    du = int(next(lines))  # -1=directed, -2=undirected
+    if du == -1:
+        G = nx.DiGraph()
+    else:
+        G = nx.Graph()
+
+    # Nodes
+    n = int(next(lines))  # number of nodes
+    node = {}
+    for i in range(1, n + 1):  # LEDA counts from 1 to n
+        symbol = next(lines).rstrip().strip("|{}|  ")
+        if symbol == "":
+            symbol = str(i)  # use int if no label - could be trouble
+        node[i] = symbol
+
+    G.add_nodes_from([s for i, s in node.items()])
+
+    # Edges
+    m = int(next(lines))  # number of edges
+    for i in range(m):
+        try:
+            s, t, reversal, label = next(lines).split()
+        except BaseException as err:
+            raise NetworkXError(f"Too few fields in LEDA.GRAPH edge {i + 1}") from err
+        # BEWARE: no handling of reversal edges
+        G.add_edge(node[int(s)], node[int(t)], label=label[2:-2])
+    return G

.venv/lib/python3.12/site-packages/networkx/readwrite/multiline_adjlist.py

@@ -0,0 +1,393 @@
+"""
+*************************
+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
+
+
+def generate_multiline_adjlist(G, delimiter=" "):
+    """Generate a single line of the graph G in multiline adjacency list format.
+
+    Parameters
+    ----------
+    G : NetworkX graph
+
+    delimiter : string, optional
+       Separator for node labels
+
+    Returns
+    -------
+    lines : string
+        Lines of data in multiline adjlist format.
+
+    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)
+
+
+@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
+    --------
+    >>> G = nx.path_graph(4)
+    >>> nx.write_multiline_adjlist(G, "test.multi_adjlist")
+
+    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.
+
+    >>> fh = open("test.multi_adjlist2", "wb")
+    >>> nx.write_multiline_adjlist(G, fh)
+
+    Filenames ending in .gz or .bz2 will be compressed.
+
+    >>> nx.write_multiline_adjlist(G, "test.multi_adjlist.gz")
+
+    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))
+
+
+@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
+
+
+@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
+    --------
+    >>> G = nx.path_graph(4)
+    >>> nx.write_multiline_adjlist(G, "test.multi_adjlistP4")
+    >>> G = nx.read_multiline_adjlist("test.multi_adjlistP4")
+
+    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.multi_adjlistP4", "rb")
+    >>> G = nx.read_multiline_adjlist(fh)
+
+    Filenames ending in .gz or .bz2 will be compressed.
+
+    >>> nx.write_multiline_adjlist(G, "test.multi_adjlistP4.gz")
+    >>> G = nx.read_multiline_adjlist("test.multi_adjlistP4.gz")
+
+    The optional nodetype is a function to convert node strings to nodetype.
+
+    For example
+
+    >>> G = nx.read_multiline_adjlist("test.multi_adjlistP4", 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.multi_adjlistP4")
+
+    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.multi_adjlistP4", create_using=nx.DiGraph)
+
+    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,
+    )

.venv/lib/python3.12/site-packages/networkx/readwrite/p2g.py

@@ -0,0 +1,113 @@
+"""
+This module provides the following: read and write of p2g format
+used in metabolic pathway studies.
+
+See:
+<https://web.archive.org/web/20080626113807/http://www.cs.purdue.edu/homes/koyuturk/pathway/>
+for a description.
+
+The summary is included here:
+
+A file that describes a uniquely labeled graph (with extension ".gr")
+format looks like the following:
+
+
+name
+3 4
+a
+1 2
+b
+
+c
+0 2
+
+"name" is simply a description of what the graph corresponds to. The
+second line displays the number of nodes and number of edges,
+respectively. This sample graph contains three nodes labeled "a", "b",
+and "c". The rest of the graph contains two lines for each node. The
+first line for a node contains the node label. After the declaration
+of the node label, the out-edges of that node in the graph are
+provided. For instance, "a" is linked to nodes 1 and 2, which are
+labeled "b" and "c", while the node labeled "b" has no outgoing
+edges. Observe that node labeled "c" has an outgoing edge to
+itself. Indeed, self-loops are allowed. Node index starts from 0.
+
+"""
+
+import networkx as nx
+from networkx.utils import open_file
+
+
+@open_file(1, mode="w")
+def write_p2g(G, path, encoding="utf-8"):
+    """Write NetworkX graph in p2g format.
+
+    Notes
+    -----
+    This format is meant to be used with directed graphs with
+    possible self loops.
+    """
+    path.write((f"{G.name}\n").encode(encoding))
+    path.write((f"{G.order()} {G.size()}\n").encode(encoding))
+    nodes = list(G)
+    # make dictionary mapping nodes to integers
+    nodenumber = dict(zip(nodes, range(len(nodes))))
+    for n in nodes:
+        path.write((f"{n}\n").encode(encoding))
+        for nbr in G.neighbors(n):
+            path.write((f"{nodenumber[nbr]} ").encode(encoding))
+        path.write("\n".encode(encoding))
+
+
+@open_file(0, mode="r")
+@nx._dispatchable(graphs=None, returns_graph=True)
+def read_p2g(path, encoding="utf-8"):
+    """Read graph in p2g format from path.
+
+    Parameters
+    ----------
+    path : string or file
+       Filename or file handle to read.
+       Filenames ending in .gz or .bz2 will be decompressed.
+
+    Returns
+    -------
+    MultiDiGraph
+
+    Notes
+    -----
+    If you want a DiGraph (with no self loops allowed and no edge data)
+    use D=nx.DiGraph(read_p2g(path))
+    """
+    lines = (line.decode(encoding) for line in path)
+    G = parse_p2g(lines)
+    return G
+
+
+@nx._dispatchable(graphs=None, returns_graph=True)
+def parse_p2g(lines):
+    """Parse p2g format graph from string or iterable.
+
+    Returns
+    -------
+    MultiDiGraph
+    """
+    description = next(lines).strip()
+    # are multiedges (parallel edges) allowed?
+    G = nx.MultiDiGraph(name=description, selfloops=True)
+    nnodes, nedges = map(int, next(lines).split())
+    nodelabel = {}
+    nbrs = {}
+    # loop over the nodes keeping track of node labels and out neighbors
+    # defer adding edges until all node labels are known
+    for i in range(nnodes):
+        n = next(lines).strip()
+        nodelabel[i] = n
+        G.add_node(n)
+        nbrs[n] = map(int, next(lines).split())
+    # now we know all of the node labels so we can add the edges
+    # with the correct labels
+    for n in G:
+        for nbr in nbrs[n]:
+            G.add_edge(n, nodelabel[nbr])
+    return G

.venv/lib/python3.12/site-packages/networkx/readwrite/pajek.py

@@ -0,0 +1,286 @@
+"""
+*****
+Pajek
+*****
+Read graphs in Pajek format.
+
+This implementation handles directed and undirected graphs including
+those with self loops and parallel edges.
+
+Format
+------
+See http://vlado.fmf.uni-lj.si/pub/networks/pajek/doc/draweps.htm
+for format information.
+
+"""
+
+import warnings
+
+import networkx as nx
+from networkx.utils import open_file
+
+__all__ = ["read_pajek", "parse_pajek", "generate_pajek", "write_pajek"]
+
+
+def generate_pajek(G):
+    """Generate lines in Pajek graph format.
+
+    Parameters
+    ----------
+    G : graph
+       A Networkx graph
+
+    References
+    ----------
+    See http://vlado.fmf.uni-lj.si/pub/networks/pajek/doc/draweps.htm
+    for format information.
+    """
+    if G.name == "":
+        name = "NetworkX"
+    else:
+        name = G.name
+    # Apparently many Pajek format readers can't process this line
+    # So we'll leave it out for now.
+    # yield '*network %s'%name
+
+    # write nodes with attributes
+    yield f"*vertices {G.order()}"
+    nodes = list(G)
+    # make dictionary mapping nodes to integers
+    nodenumber = dict(zip(nodes, range(1, len(nodes) + 1)))
+    for n in nodes:
+        # copy node attributes and pop mandatory attributes
+        # to avoid duplication.
+        na = G.nodes.get(n, {}).copy()
+        x = na.pop("x", 0.0)
+        y = na.pop("y", 0.0)
+        try:
+            id = int(na.pop("id", nodenumber[n]))
+        except ValueError as err:
+            err.args += (
+                (
+                    "Pajek format requires 'id' to be an int()."
+                    " Refer to the 'Relabeling nodes' section."
+                ),
+            )
+            raise
+        nodenumber[n] = id
+        shape = na.pop("shape", "ellipse")
+        s = " ".join(map(make_qstr, (id, n, x, y, shape)))
+        # only optional attributes are left in na.
+        for k, v in na.items():
+            if isinstance(v, str) and v.strip() != "":
+                s += f" {make_qstr(k)} {make_qstr(v)}"
+            else:
+                warnings.warn(
+                    f"Node attribute {k} is not processed. {('Empty attribute' if isinstance(v, str) else 'Non-string attribute')}."
+                )
+        yield s
+
+    # write edges with attributes
+    if G.is_directed():
+        yield "*arcs"
+    else:
+        yield "*edges"
+    for u, v, edgedata in G.edges(data=True):
+        d = edgedata.copy()
+        value = d.pop("weight", 1.0)  # use 1 as default edge value
+        s = " ".join(map(make_qstr, (nodenumber[u], nodenumber[v], value)))
+        for k, v in d.items():
+            if isinstance(v, str) and v.strip() != "":
+                s += f" {make_qstr(k)} {make_qstr(v)}"
+            else:
+                warnings.warn(
+                    f"Edge attribute {k} is not processed. {('Empty attribute' if isinstance(v, str) else 'Non-string attribute')}."
+                )
+        yield s
+
+
+@open_file(1, mode="wb")
+def write_pajek(G, path, encoding="UTF-8"):
+    """Write graph in Pajek format to path.
+
+    Parameters
+    ----------
+    G : graph
+       A Networkx graph
+    path : file or string
+       File or filename to write.
+       Filenames ending in .gz or .bz2 will be compressed.
+
+    Examples
+    --------
+    >>> G = nx.path_graph(4)
+    >>> nx.write_pajek(G, "test.netP4")
+
+    Warnings
+    --------
+    Optional node attributes and edge attributes must be non-empty strings.
+    Otherwise it will not be written into the file. You will need to
+    convert those attributes to strings if you want to keep them.
+
+    References
+    ----------
+    See http://vlado.fmf.uni-lj.si/pub/networks/pajek/doc/draweps.htm
+    for format information.
+    """
+    for line in generate_pajek(G):
+        line += "\n"
+        path.write(line.encode(encoding))
+
+
+@open_file(0, mode="rb")
+@nx._dispatchable(graphs=None, returns_graph=True)
+def read_pajek(path, encoding="UTF-8"):
+    """Read graph in Pajek format from path.
+
+    Parameters
+    ----------
+    path : file or string
+       Filename or file handle to read.
+       Filenames ending in .gz or .bz2 will be decompressed.
+
+    Returns
+    -------
+    G : NetworkX MultiGraph or MultiDiGraph.
+
+    Examples
+    --------
+    >>> G = nx.path_graph(4)
+    >>> nx.write_pajek(G, "test.net")
+    >>> G = nx.read_pajek("test.net")
+
+    To create a Graph instead of a MultiGraph use
+
+    >>> G1 = nx.Graph(G)
+
+    References
+    ----------
+    See http://vlado.fmf.uni-lj.si/pub/networks/pajek/doc/draweps.htm
+    for format information.
+    """
+    lines = (line.decode(encoding) for line in path)
+    return parse_pajek(lines)
+
+
+@nx._dispatchable(graphs=None, returns_graph=True)
+def parse_pajek(lines):
+    """Parse Pajek format graph from string or iterable.
+
+    Parameters
+    ----------
+    lines : string or iterable
+       Data in Pajek format.
+
+    Returns
+    -------
+    G : NetworkX graph
+
+    See Also
+    --------
+    read_pajek
+
+    """
+    import shlex
+
+    # multigraph=False
+    if isinstance(lines, str):
+        lines = iter(lines.split("\n"))
+    lines = iter([line.rstrip("\n") for line in lines])
+    G = nx.MultiDiGraph()  # are multiedges allowed in Pajek? assume yes
+    labels = []  # in the order of the file, needed for matrix
+    while lines:
+        try:
+            l = next(lines)
+        except:  # EOF
+            break
+        if l.lower().startswith("*network"):
+            try:
+                label, name = l.split(None, 1)
+            except ValueError:
+                # Line was not of the form:  *network NAME
+                pass
+            else:
+                G.graph["name"] = name
+        elif l.lower().startswith("*vertices"):
+            nodelabels = {}
+            l, nnodes = l.split()
+            for i in range(int(nnodes)):
+                l = next(lines)
+                try:
+                    splitline = [
+                        x.decode("utf-8") for x in shlex.split(str(l).encode("utf-8"))
+                    ]
+                except AttributeError:
+                    splitline = shlex.split(str(l))
+                id, label = splitline[0:2]
+                labels.append(label)
+                G.add_node(label)
+                nodelabels[id] = label
+                G.nodes[label]["id"] = id
+                try:
+                    x, y, shape = splitline[2:5]
+                    G.nodes[label].update(
+                        {"x": float(x), "y": float(y), "shape": shape}
+                    )
+                except:
+                    pass
+                extra_attr = zip(splitline[5::2], splitline[6::2])
+                G.nodes[label].update(extra_attr)
+        elif l.lower().startswith("*edges") or l.lower().startswith("*arcs"):
+            if l.lower().startswith("*edge"):
+                # switch from multidigraph to multigraph
+                G = nx.MultiGraph(G)
+            if l.lower().startswith("*arcs"):
+                # switch to directed with multiple arcs for each existing edge
+                G = G.to_directed()
+            for l in lines:
+                try:
+                    splitline = [
+                        x.decode("utf-8") for x in shlex.split(str(l).encode("utf-8"))
+                    ]
+                except AttributeError:
+                    splitline = shlex.split(str(l))
+
+                if len(splitline) < 2:
+                    continue
+                ui, vi = splitline[0:2]
+                u = nodelabels.get(ui, ui)
+                v = nodelabels.get(vi, vi)
+                # parse the data attached to this edge and put in a dictionary
+                edge_data = {}
+                try:
+                    # there should always be a single value on the edge?
+                    w = splitline[2:3]
+                    edge_data.update({"weight": float(w[0])})
+                except:
+                    pass
+                    # if there isn't, just assign a 1
+                #                    edge_data.update({'value':1})
+                extra_attr = zip(splitline[3::2], splitline[4::2])
+                edge_data.update(extra_attr)
+                # if G.has_edge(u,v):
+                #     multigraph=True
+                G.add_edge(u, v, **edge_data)
+        elif l.lower().startswith("*matrix"):
+            G = nx.DiGraph(G)
+            adj_list = (
+                (labels[row], labels[col], {"weight": int(data)})
+                for (row, line) in enumerate(lines)
+                for (col, data) in enumerate(line.split())
+                if int(data) != 0
+            )
+            G.add_edges_from(adj_list)
+
+    return G
+
+
+def make_qstr(t):
+    """Returns the string representation of t.
+    Add outer double-quotes if the string has a space.
+    """
+    if not isinstance(t, str):
+        t = str(t)
+    if " " in t:
+        t = f'"{t}"'
+    return t

.venv/lib/python3.12/site-packages/networkx/readwrite/sparse6.py

@@ -0,0 +1,379 @@
+# Original author: D. Eppstein, UC Irvine, August 12, 2003.
+# The original code at https://www.ics.uci.edu/~eppstein/PADS/ is public domain.
+"""Functions for reading and writing graphs in the *sparse6* format.
+
+The *sparse6* file format is a space-efficient format for large sparse
+graphs. For small graphs or large dense graphs, use the *graph6* file
+format.
+
+For more information, see the `sparse6`_ homepage.
+
+.. _sparse6: https://users.cecs.anu.edu.au/~bdm/data/formats.html
+
+"""
+
+import networkx as nx
+from networkx.exception import NetworkXError
+from networkx.readwrite.graph6 import data_to_n, n_to_data
+from networkx.utils import not_implemented_for, open_file
+
+__all__ = ["from_sparse6_bytes", "read_sparse6", "to_sparse6_bytes", "write_sparse6"]
+
+
+def _generate_sparse6_bytes(G, nodes, header):
+    """Yield bytes in the sparse6 encoding of a graph.
+
+    `G` is an undirected simple graph. `nodes` is the list of nodes for
+    which the node-induced subgraph will be encoded; if `nodes` is the
+    list of all nodes in the graph, the entire graph will be
+    encoded. `header` is a Boolean that specifies whether to generate
+    the header ``b'>>sparse6<<'`` before the remaining data.
+
+    This function generates `bytes` objects in the following order:
+
+    1. the header (if requested),
+    2. the encoding of the number of nodes,
+    3. each character, one-at-a-time, in the encoding of the requested
+       node-induced subgraph,
+    4. a newline character.
+
+    This function raises :exc:`ValueError` if the graph is too large for
+    the graph6 format (that is, greater than ``2 ** 36`` nodes).
+
+    """
+    n = len(G)
+    if n >= 2**36:
+        raise ValueError(
+            "sparse6 is only defined if number of nodes is less than 2 ** 36"
+        )
+    if header:
+        yield b">>sparse6<<"
+    yield b":"
+    for d in n_to_data(n):
+        yield str.encode(chr(d + 63))
+
+    k = 1
+    while 1 << k < n:
+        k += 1
+
+    def enc(x):
+        """Big endian k-bit encoding of x"""
+        return [1 if (x & 1 << (k - 1 - i)) else 0 for i in range(k)]
+
+    edges = sorted((max(u, v), min(u, v)) for u, v in G.edges())
+    bits = []
+    curv = 0
+    for v, u in edges:
+        if v == curv:  # current vertex edge
+            bits.append(0)
+            bits.extend(enc(u))
+        elif v == curv + 1:  # next vertex edge
+            curv += 1
+            bits.append(1)
+            bits.extend(enc(u))
+        else:  # skip to vertex v and then add edge to u
+            curv = v
+            bits.append(1)
+            bits.extend(enc(v))
+            bits.append(0)
+            bits.extend(enc(u))
+    if k < 6 and n == (1 << k) and ((-len(bits)) % 6) >= k and curv < (n - 1):
+        # Padding special case: small k, n=2^k,
+        # more than k bits of padding needed,
+        # current vertex is not (n-1) --
+        # appending 1111... would add a loop on (n-1)
+        bits.append(0)
+        bits.extend([1] * ((-len(bits)) % 6))
+    else:
+        bits.extend([1] * ((-len(bits)) % 6))
+
+    data = [
+        (bits[i + 0] << 5)
+        + (bits[i + 1] << 4)
+        + (bits[i + 2] << 3)
+        + (bits[i + 3] << 2)
+        + (bits[i + 4] << 1)
+        + (bits[i + 5] << 0)
+        for i in range(0, len(bits), 6)
+    ]
+
+    for d in data:
+        yield str.encode(chr(d + 63))
+    yield b"\n"
+
+
+@nx._dispatchable(graphs=None, returns_graph=True)
+def from_sparse6_bytes(string):
+    """Read an undirected graph in sparse6 format from string.
+
+    Parameters
+    ----------
+    string : string
+       Data in sparse6 format
+
+    Returns
+    -------
+    G : Graph
+
+    Raises
+    ------
+    NetworkXError
+        If the string is unable to be parsed in sparse6 format
+
+    Examples
+    --------
+    >>> G = nx.from_sparse6_bytes(b":A_")
+    >>> sorted(G.edges())
+    [(0, 1), (0, 1), (0, 1)]
+
+    See Also
+    --------
+    read_sparse6, write_sparse6
+
+    References
+    ----------
+    .. [1] Sparse6 specification
+           <https://users.cecs.anu.edu.au/~bdm/data/formats.html>
+
+    """
+    if string.startswith(b">>sparse6<<"):
+        string = string[11:]
+    if not string.startswith(b":"):
+        raise NetworkXError("Expected leading colon in sparse6")
+
+    chars = [c - 63 for c in string[1:]]
+    n, data = data_to_n(chars)
+    k = 1
+    while 1 << k < n:
+        k += 1
+
+    def parseData():
+        """Returns stream of pairs b[i], x[i] for sparse6 format."""
+        chunks = iter(data)
+        d = None  # partial data word
+        dLen = 0  # how many unparsed bits are left in d
+
+        while 1:
+            if dLen < 1:
+                try:
+                    d = next(chunks)
+                except StopIteration:
+                    return
+                dLen = 6
+            dLen -= 1
+            b = (d >> dLen) & 1  # grab top remaining bit
+
+            x = d & ((1 << dLen) - 1)  # partially built up value of x
+            xLen = dLen  # how many bits included so far in x
+            while xLen < k:  # now grab full chunks until we have enough
+                try:
+                    d = next(chunks)
+                except StopIteration:
+                    return
+                dLen = 6
+                x = (x << 6) + d
+                xLen += 6
+            x = x >> (xLen - k)  # shift back the extra bits
+            dLen = xLen - k
+            yield b, x
+
+    v = 0
+
+    G = nx.MultiGraph()
+    G.add_nodes_from(range(n))
+
+    multigraph = False
+    for b, x in parseData():
+        if b == 1:
+            v += 1
+        # padding with ones can cause overlarge number here
+        if x >= n or v >= n:
+            break
+        elif x > v:
+            v = x
+        else:
+            if G.has_edge(x, v):
+                multigraph = True
+            G.add_edge(x, v)
+    if not multigraph:
+        G = nx.Graph(G)
+    return G
+
+
+def to_sparse6_bytes(G, nodes=None, header=True):
+    """Convert an undirected graph to bytes in sparse6 format.
+
+    Parameters
+    ----------
+    G : Graph (undirected)
+
+    nodes: list or iterable
+       Nodes are labeled 0...n-1 in the order provided.  If None the ordering
+       given by ``G.nodes()`` is used.
+
+    header: bool
+       If True add '>>sparse6<<' bytes to head of data.
+
+    Raises
+    ------
+    NetworkXNotImplemented
+        If the graph is directed.
+
+    ValueError
+        If the graph has at least ``2 ** 36`` nodes; the sparse6 format
+        is only defined for graphs of order less than ``2 ** 36``.
+
+    Examples
+    --------
+    >>> nx.to_sparse6_bytes(nx.path_graph(2))
+    b'>>sparse6<<:An\\n'
+
+    See Also
+    --------
+    to_sparse6_bytes, read_sparse6, write_sparse6_bytes
+
+    Notes
+    -----
+    The returned bytes end with a newline character.
+
+    The format does not support edge or node labels.
+
+    References
+    ----------
+    .. [1] Graph6 specification
+           <https://users.cecs.anu.edu.au/~bdm/data/formats.html>
+
+    """
+    if nodes is not None:
+        G = G.subgraph(nodes)
+    G = nx.convert_node_labels_to_integers(G, ordering="sorted")
+    return b"".join(_generate_sparse6_bytes(G, nodes, header))
+
+
+@open_file(0, mode="rb")
+@nx._dispatchable(graphs=None, returns_graph=True)
+def read_sparse6(path):
+    """Read an undirected graph in sparse6 format from path.
+
+    Parameters
+    ----------
+    path : file or string
+       Filename or file handle to read.
+       Filenames ending in .gz or .bz2 will be decompressed.
+
+    Returns
+    -------
+    G : Graph/Multigraph or list of Graphs/MultiGraphs
+       If the file contains multiple lines then a list of graphs is returned
+
+    Raises
+    ------
+    NetworkXError
+        If the string is unable to be parsed in sparse6 format
+
+    Examples
+    --------
+    You can read a sparse6 file by giving the path to the file::
+
+        >>> import tempfile
+        >>> with tempfile.NamedTemporaryFile(delete=False) as f:
+        ...     _ = f.write(b">>sparse6<<:An\\n")
+        ...     _ = f.seek(0)
+        ...     G = nx.read_sparse6(f.name)
+        >>> list(G.edges())
+        [(0, 1)]
+
+    You can also read a sparse6 file by giving an open file-like object::
+
+        >>> 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 Also
+    --------
+    read_sparse6, from_sparse6_bytes
+
+    References
+    ----------
+    .. [1] Sparse6 specification
+           <https://users.cecs.anu.edu.au/~bdm/data/formats.html>
+
+    """
+    glist = []
+    for line in path:
+        line = line.strip()
+        if not len(line):
+            continue
+        glist.append(from_sparse6_bytes(line))
+    if len(glist) == 1:
+        return glist[0]
+    else:
+        return glist
+
+
+@not_implemented_for("directed")
+@open_file(1, mode="wb")
+def write_sparse6(G, path, nodes=None, header=True):
+    """Write graph G to given path in sparse6 format.
+
+    Parameters
+    ----------
+    G : Graph (undirected)
+
+    path : file or string
+       File or filename to write.
+       Filenames ending in .gz or .bz2 will be compressed.
+
+    nodes: list or iterable
+       Nodes are labeled 0...n-1 in the order provided.  If None the ordering
+       given by G.nodes() is used.
+
+    header: bool
+       If True add '>>sparse6<<' string to head of data
+
+    Raises
+    ------
+    NetworkXError
+        If the graph is directed
+
+    Examples
+    --------
+    You can write a sparse6 file by giving the path to the file::
+
+        >>> import tempfile
+        >>> with tempfile.NamedTemporaryFile(delete=False) as f:
+        ...     nx.write_sparse6(nx.path_graph(2), f.name)
+        ...     print(f.read())
+        b'>>sparse6<<:An\\n'
+
+    You can also write a sparse6 file by giving an open file-like object::
+
+        >>> with tempfile.NamedTemporaryFile() as f:
+        ...     nx.write_sparse6(nx.path_graph(2), f)
+        ...     _ = f.seek(0)
+        ...     print(f.read())
+        b'>>sparse6<<:An\\n'
+
+    See Also
+    --------
+    read_sparse6, from_sparse6_bytes
+
+    Notes
+    -----
+    The format does not support edge or node labels.
+
+    References
+    ----------
+    .. [1] Sparse6 specification
+           <https://users.cecs.anu.edu.au/~bdm/data/formats.html>
+
+    """
+    if nodes is not None:
+        G = G.subgraph(nodes)
+    G = nx.convert_node_labels_to_integers(G, ordering="sorted")
+    for b in _generate_sparse6_bytes(G, nodes, header):
+        path.write(b)

.venv/lib/python3.12/site-packages/networkx/readwrite/tests/test_adjlist.py

@@ -0,0 +1,354 @@
+"""
+Unit tests for adjlist.
+"""
+
+import io
+
+import pytest
+
+import networkx as nx
+from networkx.utils import edges_equal, graphs_equal, nodes_equal
+
+
+class TestGenerateAdjlist:
+    @pytest.mark.parametrize("graph_type", [nx.Graph, nx.MultiGraph])
+    def test_undirected(self, graph_type):
+        G = nx.complete_graph(5, create_using=graph_type)
+        lines = [
+            "0 1 2 3 4",
+            "1 2 3 4",
+            "2 3 4",
+            "3 4",
+            "4",
+        ]
+        assert list(nx.generate_adjlist(G)) == lines
+
+    @pytest.mark.parametrize("graph_type", [nx.DiGraph, nx.MultiDiGraph])
+    def test_directed(self, graph_type):
+        G = nx.complete_graph(5, create_using=graph_type)
+        lines = [
+            "0 1 2 3 4",
+            "1 0 2 3 4",
+            "2 0 1 3 4",
+            "3 0 1 2 4",
+            "4 0 1 2 3",
+        ]
+        assert list(nx.generate_adjlist(G)) == lines
+
+        G = nx.path_graph(5, create_using=graph_type)
+        G.add_edge(1, 0)
+        lines = [
+            "0 1",
+            "1 2 0",
+            "2 3",
+            "3 4",
+            "4",
+        ]
+        assert list(nx.generate_adjlist(G)) == lines
+
+    @pytest.mark.parametrize("delimiter", [" ", ",", "\t"])
+    def test_delimiter(self, delimiter):
+        G = nx.complete_graph(3)
+        lines = [
+            f"0{delimiter}1{delimiter}2",
+            f"1{delimiter}2",
+            f"2",
+        ]
+        assert list(nx.generate_adjlist(G, delimiter=delimiter)) == lines
+
+    def test_multiple_edges_undirected(self):
+        G = nx.complete_graph(3, create_using=nx.MultiGraph)
+        G.add_edge(0, 1)
+        lines = [
+            "0 1 1 2",
+            "1 2",
+            "2",
+        ]
+        assert list(nx.generate_adjlist(G)) == lines
+
+    def test_multiple_edges_directed(self):
+        G = nx.complete_graph(3, create_using=nx.MultiDiGraph)
+        G.add_edge(0, 1)
+        lines = [
+            "0 1 1 2",
+            "1 0 2",
+            "2 0 1",
+        ]
+        assert list(nx.generate_adjlist(G)) == lines
+
+        G.add_edge(1, 0)
+        lines[1] = "1 0 0 2"
+        assert list(nx.generate_adjlist(G)) == lines
+
+    def test_multiple_edges_with_data(self):
+        G = nx.complete_graph(3, create_using=nx.MultiGraph)
+        G.add_edge(0, 1, weight=1)
+        G.add_edge(0, 1, weight=2)
+        lines = [
+            "0 1 1 1 2",
+            "1 2",
+            "2",
+        ]
+        assert list(nx.generate_adjlist(G)) == lines
+
+    def test_with_self_loop(self):
+        G = nx.complete_graph(3)
+        G.add_edge(0, 0)
+        lines = [
+            "0 1 2 0",
+            "1 2",
+            "2",
+        ]
+        assert list(nx.generate_adjlist(G)) == lines
+
+
+class TestAdjlist:
+    @classmethod
+    def setup_class(cls):
+        cls.G = nx.Graph(name="test")
+        e = [("a", "b"), ("b", "c"), ("c", "d"), ("d", "e"), ("e", "f"), ("a", "f")]
+        cls.G.add_edges_from(e)
+        cls.G.add_node("g")
+        cls.DG = nx.DiGraph(cls.G)
+        cls.XG = nx.MultiGraph()
+        cls.XG.add_weighted_edges_from([(1, 2, 5), (1, 2, 5), (1, 2, 1), (3, 3, 42)])
+        cls.XDG = nx.MultiDiGraph(cls.XG)
+
+    def test_read_multiline_adjlist_1(self):
+        # Unit test for https://networkx.lanl.gov/trac/ticket/252
+        s = b"""# comment line
+1 2
+# comment line
+2
+3
+"""
+        bytesIO = io.BytesIO(s)
+        G = nx.read_multiline_adjlist(bytesIO)
+        adj = {"1": {"3": {}, "2": {}}, "3": {"1": {}}, "2": {"1": {}}}
+        assert graphs_equal(G, nx.Graph(adj))
+
+    def test_unicode(self, tmp_path):
+        G = nx.Graph()
+        name1 = chr(2344) + chr(123) + chr(6543)
+        name2 = chr(5543) + chr(1543) + chr(324)
+        G.add_edge(name1, "Radiohead", **{name2: 3})
+
+        fname = tmp_path / "adjlist.txt"
+        nx.write_multiline_adjlist(G, fname)
+        H = nx.read_multiline_adjlist(fname)
+        assert graphs_equal(G, H)
+
+    def test_latin1_err(self, tmp_path):
+        G = nx.Graph()
+        name1 = chr(2344) + chr(123) + chr(6543)
+        name2 = chr(5543) + chr(1543) + chr(324)
+        G.add_edge(name1, "Radiohead", **{name2: 3})
+        fname = tmp_path / "adjlist.txt"
+        with pytest.raises(UnicodeEncodeError):
+            nx.write_multiline_adjlist(G, fname, encoding="latin-1")
+
+    def test_latin1(self, tmp_path):
+        G = nx.Graph()
+        name1 = "Bj" + chr(246) + "rk"
+        name2 = chr(220) + "ber"
+        G.add_edge(name1, "Radiohead", **{name2: 3})
+        fname = tmp_path / "adjlist.txt"
+        nx.write_multiline_adjlist(G, fname, encoding="latin-1")
+        H = nx.read_multiline_adjlist(fname, encoding="latin-1")
+        assert graphs_equal(G, H)
+
+    def test_parse_adjlist(self):
+        lines = ["1 2 5", "2 3 4", "3 5", "4", "5"]
+        nx.parse_adjlist(lines, nodetype=int)  # smoke test
+        with pytest.raises(TypeError):
+            nx.parse_adjlist(lines, nodetype="int")
+        lines = ["1 2 5", "2 b", "c"]
+        with pytest.raises(TypeError):
+            nx.parse_adjlist(lines, nodetype=int)
+
+    def test_adjlist_graph(self, tmp_path):
+        G = self.G
+        fname = tmp_path / "adjlist.txt"
+        nx.write_adjlist(G, fname)
+        H = nx.read_adjlist(fname)
+        H2 = nx.read_adjlist(fname)
+        assert H is not H2  # they should be different graphs
+        assert nodes_equal(list(H), list(G))
+        assert edges_equal(list(H.edges()), list(G.edges()))
+
+    def test_adjlist_digraph(self, tmp_path):
+        G = self.DG
+        fname = tmp_path / "adjlist.txt"
+        nx.write_adjlist(G, fname)
+        H = nx.read_adjlist(fname, create_using=nx.DiGraph())
+        H2 = nx.read_adjlist(fname, create_using=nx.DiGraph())
+        assert H is not H2  # they should be different graphs
+        assert nodes_equal(list(H), list(G))
+        assert edges_equal(list(H.edges()), list(G.edges()), directed=True)
+
+    def test_adjlist_integers(self, tmp_path):
+        fname = tmp_path / "adjlist.txt"
+        G = nx.convert_node_labels_to_integers(self.G)
+        nx.write_adjlist(G, fname)
+        H = nx.read_adjlist(fname, nodetype=int)
+        H2 = nx.read_adjlist(fname, nodetype=int)
+        assert H is not H2  # they should be different graphs
+        assert nodes_equal(list(H), list(G))
+        assert edges_equal(list(H.edges()), list(G.edges()))
+
+    def test_adjlist_multigraph(self, tmp_path):
+        G = self.XG
+        fname = tmp_path / "adjlist.txt"
+        nx.write_adjlist(G, fname)
+        H = nx.read_adjlist(fname, nodetype=int, create_using=nx.MultiGraph())
+        H2 = nx.read_adjlist(fname, nodetype=int, create_using=nx.MultiGraph())
+        assert H is not H2  # they should be different graphs
+        assert nodes_equal(list(H), list(G))
+        assert edges_equal(list(H.edges()), list(G.edges()))
+
+    def test_adjlist_multidigraph(self, tmp_path):
+        G = self.XDG
+        fname = tmp_path / "adjlist.txt"
+        nx.write_adjlist(G, fname)
+        H = nx.read_adjlist(fname, nodetype=int, create_using=nx.MultiDiGraph())
+        H2 = nx.read_adjlist(fname, nodetype=int, create_using=nx.MultiDiGraph())
+        assert H is not H2  # they should be different graphs
+        assert nodes_equal(list(H), list(G))
+        assert edges_equal(list(H.edges()), list(G.edges()), directed=True)
+
+    def test_adjlist_delimiter(self):
+        fh = io.BytesIO()
+        G = nx.path_graph(3)
+        nx.write_adjlist(G, fh, delimiter=":")
+        fh.seek(0)
+        H = nx.read_adjlist(fh, nodetype=int, delimiter=":")
+        assert nodes_equal(list(H), list(G))
+        assert edges_equal(list(H.edges()), list(G.edges()))
+
+
+class TestMultilineAdjlist:
+    @classmethod
+    def setup_class(cls):
+        cls.G = nx.Graph(name="test")
+        e = [("a", "b"), ("b", "c"), ("c", "d"), ("d", "e"), ("e", "f"), ("a", "f")]
+        cls.G.add_edges_from(e)
+        cls.G.add_node("g")
+        cls.DG = nx.DiGraph(cls.G)
+        cls.DG.remove_edge("b", "a")
+        cls.DG.remove_edge("b", "c")
+        cls.XG = nx.MultiGraph()
+        cls.XG.add_weighted_edges_from([(1, 2, 5), (1, 2, 5), (1, 2, 1), (3, 3, 42)])
+        cls.XDG = nx.MultiDiGraph(cls.XG)
+
+    def test_parse_multiline_adjlist(self):
+        lines = [
+            "1 2",
+            "b {'weight':3, 'name': 'Frodo'}",
+            "c {}",
+            "d 1",
+            "e {'weight':6, 'name': 'Saruman'}",
+        ]
+        nx.parse_multiline_adjlist(iter(lines))  # smoke test
+        with pytest.raises(TypeError):
+            nx.parse_multiline_adjlist(iter(lines), nodetype=int)
+        nx.parse_multiline_adjlist(iter(lines), edgetype=str)  # smoke test
+        with pytest.raises(TypeError):
+            nx.parse_multiline_adjlist(iter(lines), nodetype=int)
+        lines = ["1 a"]
+        with pytest.raises(TypeError):
+            nx.parse_multiline_adjlist(iter(lines))
+        lines = ["a 2"]
+        with pytest.raises(TypeError):
+            nx.parse_multiline_adjlist(iter(lines), nodetype=int)
+        lines = ["1 2"]
+        with pytest.raises(TypeError):
+            nx.parse_multiline_adjlist(iter(lines))
+        lines = ["1 2", "2 {}"]
+        with pytest.raises(TypeError):
+            nx.parse_multiline_adjlist(iter(lines))
+
+    def test_multiline_adjlist_graph(self, tmp_path):
+        G = self.G
+        fname = tmp_path / "adjlist.txt"
+        nx.write_multiline_adjlist(G, fname)
+        H = nx.read_multiline_adjlist(fname)
+        H2 = nx.read_multiline_adjlist(fname)
+        assert H is not H2  # they should be different graphs
+        assert nodes_equal(list(H), list(G))
+        assert edges_equal(list(H.edges()), list(G.edges()))
+
+    def test_multiline_adjlist_digraph(self, tmp_path):
+        G = self.DG
+        fname = tmp_path / "adjlist.txt"
+        nx.write_multiline_adjlist(G, fname)
+        H = nx.read_multiline_adjlist(fname, create_using=nx.DiGraph())
+        H2 = nx.read_multiline_adjlist(fname, create_using=nx.DiGraph())
+        assert H is not H2  # they should be different graphs
+        assert nodes_equal(list(H), list(G))
+        assert edges_equal(list(H.edges()), list(G.edges()), directed=True)
+
+    def test_multiline_adjlist_integers(self, tmp_path):
+        fname = tmp_path / "adjlist.txt"
+        G = nx.convert_node_labels_to_integers(self.G)
+        nx.write_multiline_adjlist(G, fname)
+        H = nx.read_multiline_adjlist(fname, nodetype=int)
+        H2 = nx.read_multiline_adjlist(fname, nodetype=int)
+        assert H is not H2  # they should be different graphs
+        assert nodes_equal(list(H), list(G))
+        assert edges_equal(list(H.edges()), list(G.edges()))
+
+    def test_multiline_adjlist_multigraph(self, tmp_path):
+        G = self.XG
+        fname = tmp_path / "adjlist.txt"
+        nx.write_multiline_adjlist(G, fname)
+        H = nx.read_multiline_adjlist(fname, nodetype=int, create_using=nx.MultiGraph())
+        H2 = nx.read_multiline_adjlist(
+            fname, nodetype=int, create_using=nx.MultiGraph()
+        )
+        assert H is not H2  # they should be different graphs
+        assert nodes_equal(list(H), list(G))
+        assert edges_equal(list(H.edges()), list(G.edges()))
+
+    def test_multiline_adjlist_multidigraph(self, tmp_path):
+        G = self.XDG
+        fname = tmp_path / "adjlist.txt"
+        nx.write_multiline_adjlist(G, fname)
+        H = nx.read_multiline_adjlist(
+            fname, nodetype=int, create_using=nx.MultiDiGraph()
+        )
+        H2 = nx.read_multiline_adjlist(
+            fname, nodetype=int, create_using=nx.MultiDiGraph()
+        )
+        assert H is not H2  # they should be different graphs
+        assert nodes_equal(list(H), list(G))
+        assert edges_equal(list(H.edges()), list(G.edges()), directed=True)
+
+    def test_multiline_adjlist_delimiter(self):
+        fh = io.BytesIO()
+        G = nx.path_graph(3)
+        nx.write_multiline_adjlist(G, fh, delimiter=":")
+        fh.seek(0)
+        H = nx.read_multiline_adjlist(fh, nodetype=int, delimiter=":")
+        assert nodes_equal(list(H), list(G))
+        assert edges_equal(list(H.edges()), list(G.edges()))
+
+
+@pytest.mark.parametrize(
+    ("lines", "delim"),
+    (
+        (["1 2 5", "2 3 4", "3 5", "4", "5"], None),  # No extra whitespace
+        (["1\t2\t5", "2\t3\t4", "3\t5", "4", "5"], "\t"),  # tab-delimited
+        (
+            ["1\t2\t5", "2\t3\t4", "3\t5\t", "4\t", "5"],
+            "\t",
+        ),  # tab-delimited, extra delims
+        (
+            ["1\t2\t5", "2\t3\t4", "3\t5\t\t\n", "4\t", "5"],
+            "\t",
+        ),  # extra delim+newlines
+    ),
+)
+def test_adjlist_rstrip_parsing(lines, delim):
+    """Regression test related to gh-7465"""
+    expected = nx.Graph([(1, 2), (1, 5), (2, 3), (2, 4), (3, 5)])
+    nx.utils.graphs_equal(nx.parse_adjlist(lines, delimiter=delim), expected)

.venv/lib/python3.12/site-packages/networkx/readwrite/tests/test_edgelist.py

@@ -0,0 +1,318 @@
+"""
+Unit tests for edgelists.
+"""
+
+import io
+import textwrap
+
+import pytest
+
+import networkx as nx
+from networkx.utils import edges_equal, graphs_equal, nodes_equal
+
+edges_no_data = textwrap.dedent(
+    """
+    # comment line
+    1 2
+    # comment line
+    2 3
+    """
+)
+
+
+edges_with_values = textwrap.dedent(
+    """
+    # comment line
+    1 2 2.0
+    # comment line
+    2 3 3.0
+    """
+)
+
+
+edges_with_weight = textwrap.dedent(
+    """
+    # comment line
+    1 2 {'weight':2.0}
+    # comment line
+    2 3 {'weight':3.0}
+    """
+)
+
+
+edges_with_multiple_attrs = textwrap.dedent(
+    """
+    # comment line
+    1 2 {'weight':2.0, 'color':'green'}
+    # comment line
+    2 3 {'weight':3.0, 'color':'red'}
+    """
+)
+
+
+edges_with_multiple_attrs_csv = textwrap.dedent(
+    """
+    # comment line
+    1, 2, {'weight':2.0, 'color':'green'}
+    # comment line
+    2, 3, {'weight':3.0, 'color':'red'}
+    """
+)
+
+
+_expected_edges_weights = [(1, 2, {"weight": 2.0}), (2, 3, {"weight": 3.0})]
+_expected_edges_multiattr = [
+    (1, 2, {"weight": 2.0, "color": "green"}),
+    (2, 3, {"weight": 3.0, "color": "red"}),
+]
+
+
+@pytest.mark.parametrize(
+    ("data", "extra_kwargs"),
+    (
+        (edges_no_data, {}),
+        (edges_with_values, {}),
+        (edges_with_weight, {}),
+        (edges_with_multiple_attrs, {}),
+        (edges_with_multiple_attrs_csv, {"delimiter": ","}),
+    ),
+)
+def test_read_edgelist_no_data(data, extra_kwargs):
+    bytesIO = io.BytesIO(data.encode("utf-8"))
+    G = nx.read_edgelist(bytesIO, nodetype=int, data=False, **extra_kwargs)
+    assert edges_equal(G.edges(), [(1, 2), (2, 3)])
+
+
+def test_read_weighted_edgelist():
+    bytesIO = io.BytesIO(edges_with_values.encode("utf-8"))
+    G = nx.read_weighted_edgelist(bytesIO, nodetype=int)
+    assert edges_equal(G.edges(data=True), _expected_edges_weights)
+
+
+@pytest.mark.parametrize(
+    ("data", "extra_kwargs", "expected"),
+    (
+        (edges_with_weight, {}, _expected_edges_weights),
+        (edges_with_multiple_attrs, {}, _expected_edges_multiattr),
+        (
+            edges_with_multiple_attrs_csv,
+            {"delimiter": ","},
+            _expected_edges_multiattr,
+        ),
+    ),
+)
+def test_read_edgelist_with_data(data, extra_kwargs, expected):
+    bytesIO = io.BytesIO(data.encode("utf-8"))
+    G = nx.read_edgelist(bytesIO, nodetype=int, **extra_kwargs)
+    assert edges_equal(G.edges(data=True), expected)
+
+
+@pytest.fixture
+def example_graph():
+    G = nx.Graph()
+    G.add_weighted_edges_from([(1, 2, 3.0), (2, 3, 27.0), (3, 4, 3.0)])
+    return G
+
+
+def test_parse_edgelist_no_data(example_graph):
+    G = example_graph
+    H = nx.parse_edgelist(["1 2", "2 3", "3 4"], nodetype=int)
+    assert nodes_equal(G.nodes, H.nodes)
+    assert edges_equal(G.edges, H.edges)
+
+
+def test_parse_edgelist_with_data_dict(example_graph):
+    G = example_graph
+    H = nx.parse_edgelist(
+        ["1 2 {'weight': 3}", "2 3 {'weight': 27}", "3 4 {'weight': 3.0}"], nodetype=int
+    )
+    assert nodes_equal(G.nodes, H.nodes)
+    assert edges_equal(G.edges(data=True), H.edges(data=True))
+
+
+def test_parse_edgelist_with_data_list(example_graph):
+    G = example_graph
+    H = nx.parse_edgelist(
+        ["1 2 3", "2 3 27", "3 4 3.0"], nodetype=int, data=(("weight", float),)
+    )
+    assert nodes_equal(G.nodes, H.nodes)
+    assert edges_equal(G.edges(data=True), H.edges(data=True))
+
+
+def test_parse_edgelist():
+    # ignore lines with less than 2 nodes
+    lines = ["1;2", "2 3", "3 4"]
+    G = nx.parse_edgelist(lines, nodetype=int)
+    assert list(G.edges()) == [(2, 3), (3, 4)]
+    # unknown nodetype
+    with pytest.raises(TypeError, match="Failed to convert nodes"):
+        lines = ["1 2", "2 3", "3 4"]
+        nx.parse_edgelist(lines, nodetype="nope")
+    # lines have invalid edge format
+    with pytest.raises(TypeError, match="Failed to convert edge data"):
+        lines = ["1 2 3", "2 3", "3 4"]
+        nx.parse_edgelist(lines, nodetype=int)
+    # edge data and data_keys not the same length
+    with pytest.raises(IndexError, match="not the same length"):
+        lines = ["1 2 3", "2 3 27", "3 4 3.0"]
+        nx.parse_edgelist(
+            lines, nodetype=int, data=(("weight", float), ("capacity", int))
+        )
+    # edge data can't be converted to edge type
+    with pytest.raises(TypeError, match="Failed to convert"):
+        lines = ["1 2 't1'", "2 3 't3'", "3 4 't3'"]
+        nx.parse_edgelist(lines, nodetype=int, data=(("weight", float),))
+
+
+def test_comments_None():
+    edgelist = ["node#1 node#2", "node#2 node#3"]
+    # comments=None supported to ignore all comment characters
+    G = nx.parse_edgelist(edgelist, comments=None)
+    H = nx.Graph([e.split(" ") for e in edgelist])
+    assert edges_equal(G.edges, H.edges)
+
+
+class TestEdgelist:
+    @classmethod
+    def setup_class(cls):
+        cls.G = nx.Graph(name="test")
+        e = [("a", "b"), ("b", "c"), ("c", "d"), ("d", "e"), ("e", "f"), ("a", "f")]
+        cls.G.add_edges_from(e)
+        cls.G.add_node("g")
+        cls.DG = nx.DiGraph(cls.G)
+        cls.XG = nx.MultiGraph()
+        cls.XG.add_weighted_edges_from([(1, 2, 5), (1, 2, 5), (1, 2, 1), (3, 3, 42)])
+        cls.XDG = nx.MultiDiGraph(cls.XG)
+
+    def test_write_edgelist_1(self):
+        fh = io.BytesIO()
+        G = nx.Graph()
+        G.add_edges_from([(1, 2), (2, 3)])
+        nx.write_edgelist(G, fh, data=False)
+        fh.seek(0)
+        assert fh.read() == b"1 2\n2 3\n"
+
+    def test_write_edgelist_2(self):
+        fh = io.BytesIO()
+        G = nx.Graph()
+        G.add_edges_from([(1, 2), (2, 3)])
+        nx.write_edgelist(G, fh, data=True)
+        fh.seek(0)
+        assert fh.read() == b"1 2 {}\n2 3 {}\n"
+
+    def test_write_edgelist_3(self):
+        fh = io.BytesIO()
+        G = nx.Graph()
+        G.add_edge(1, 2, weight=2.0)
+        G.add_edge(2, 3, weight=3.0)
+        nx.write_edgelist(G, fh, data=True)
+        fh.seek(0)
+        assert fh.read() == b"1 2 {'weight': 2.0}\n2 3 {'weight': 3.0}\n"
+
+    def test_write_edgelist_4(self):
+        fh = io.BytesIO()
+        G = nx.Graph()
+        G.add_edge(1, 2, weight=2.0)
+        G.add_edge(2, 3, weight=3.0)
+        nx.write_edgelist(G, fh, data=[("weight")])
+        fh.seek(0)
+        assert fh.read() == b"1 2 2.0\n2 3 3.0\n"
+
+    def test_unicode(self, tmp_path):
+        G = nx.Graph()
+        name1 = chr(2344) + chr(123) + chr(6543)
+        name2 = chr(5543) + chr(1543) + chr(324)
+        G.add_edge(name1, "Radiohead", **{name2: 3})
+        fname = tmp_path / "el.txt"
+        nx.write_edgelist(G, fname)
+        H = nx.read_edgelist(fname)
+        assert graphs_equal(G, H)
+
+    def test_latin1_issue(self, tmp_path):
+        G = nx.Graph()
+        name1 = chr(2344) + chr(123) + chr(6543)
+        name2 = chr(5543) + chr(1543) + chr(324)
+        G.add_edge(name1, "Radiohead", **{name2: 3})
+        fname = tmp_path / "el.txt"
+        with pytest.raises(UnicodeEncodeError):
+            nx.write_edgelist(G, fname, encoding="latin-1")
+
+    def test_latin1(self, tmp_path):
+        G = nx.Graph()
+        name1 = "Bj" + chr(246) + "rk"
+        name2 = chr(220) + "ber"
+        G.add_edge(name1, "Radiohead", **{name2: 3})
+        fname = tmp_path / "el.txt"
+
+        nx.write_edgelist(G, fname, encoding="latin-1")
+        H = nx.read_edgelist(fname, encoding="latin-1")
+        assert graphs_equal(G, H)
+
+    def test_edgelist_graph(self, tmp_path):
+        G = self.G
+        fname = tmp_path / "el.txt"
+        nx.write_edgelist(G, fname)
+        H = nx.read_edgelist(fname)
+        H2 = nx.read_edgelist(fname)
+        assert H is not H2  # they should be different graphs
+        G.remove_node("g")  # isolated nodes are not written in edgelist
+        assert nodes_equal(list(H), list(G))
+        assert edges_equal(list(H.edges()), list(G.edges()))
+
+    def test_edgelist_digraph(self, tmp_path):
+        G = self.DG
+        fname = tmp_path / "el.txt"
+        nx.write_edgelist(G, fname)
+        H = nx.read_edgelist(fname, create_using=nx.DiGraph())
+        H2 = nx.read_edgelist(fname, create_using=nx.DiGraph())
+        assert H is not H2  # they should be different graphs
+        G.remove_node("g")  # isolated nodes are not written in edgelist
+        assert nodes_equal(list(H), list(G))
+        assert edges_equal(list(H.edges()), list(G.edges()), directed=True)
+
+    def test_edgelist_integers(self, tmp_path):
+        G = nx.convert_node_labels_to_integers(self.G)
+        fname = tmp_path / "el.txt"
+        nx.write_edgelist(G, fname)
+        H = nx.read_edgelist(fname, nodetype=int)
+        # isolated nodes are not written in edgelist
+        G.remove_nodes_from(list(nx.isolates(G)))
+        assert nodes_equal(list(H), list(G))
+        assert edges_equal(list(H.edges()), list(G.edges()))
+
+    def test_edgelist_multigraph(self, tmp_path):
+        G = self.XG
+        fname = tmp_path / "el.txt"
+        nx.write_edgelist(G, fname)
+        H = nx.read_edgelist(fname, nodetype=int, create_using=nx.MultiGraph())
+        H2 = nx.read_edgelist(fname, nodetype=int, create_using=nx.MultiGraph())
+        assert H is not H2  # they should be different graphs
+        assert nodes_equal(list(H), list(G))
+        assert edges_equal(list(H.edges()), list(G.edges()))
+
+    def test_edgelist_multidigraph(self, tmp_path):
+        G = self.XDG
+        fname = tmp_path / "el.txt"
+        nx.write_edgelist(G, fname)
+        H = nx.read_edgelist(fname, nodetype=int, create_using=nx.MultiDiGraph())
+        H2 = nx.read_edgelist(fname, nodetype=int, create_using=nx.MultiDiGraph())
+        assert H is not H2  # they should be different graphs
+        assert nodes_equal(list(H), list(G))
+        assert edges_equal(list(H.edges()), list(G.edges()), directed=True)
+
+
+def test_edgelist_consistent_strip_handling():
+    """See gh-7462
+
+    Input when printed looks like::
+
+        1       2       3
+        2       3
+        3       4       3.0
+
+    Note the trailing \\t after the `3` in the second row, indicating an empty
+    data value.
+    """
+    s = io.StringIO("1\t2\t3\n2\t3\t\n3\t4\t3.0")
+    G = nx.parse_edgelist(s, delimiter="\t", nodetype=int, data=[("value", str)])
+    assert sorted(G.edges(data="value")) == [(1, 2, "3"), (2, 3, ""), (3, 4, "3.0")]

.venv/lib/python3.12/site-packages/networkx/readwrite/tests/test_gexf.py

@@ -0,0 +1,612 @@
+import io
+import time
+
+import pytest
+
+import networkx as nx
+
+
+def test_gexf_v1_3(tmp_path):
+    """'Basic graph' example from https://gexf.net/schema.html"""
+    # GEXF file from published example
+    data = """<?xml version="1.0" encoding="UTF-8"?>
+<gexf xmlns="http://gexf.net/1.3" version="1.3">
+    <graph mode="static" defaultedgetype="directed">
+        <nodes>
+            <node id="0" label="Hello" />
+            <node id="1" label="Word" />
+        </nodes>
+        <edges>
+            <edge source="0" target="1" />
+        </edges>
+    </graph>
+</gexf>
+"""
+    with open(fname := (tmp_path / "basic.gexf"), "w") as fh:
+        fh.write(data)
+
+    # Expected output based on xml input
+    expected = nx.DiGraph([("0", "1")])
+    nx.set_node_attributes(expected, {"0": "Hello", "1": "Word"}, name="label")
+    expected.graph = {"mode": "static", "edge_default": {}}
+
+    # Load example with version explicitly set
+    G = nx.read_gexf(fname, version="1.3")
+    assert nx.utils.graphs_equal(G, expected)
+
+    # And with the "default" version
+    G = nx.read_gexf(fname)
+    assert nx.utils.graphs_equal(G, expected)
+
+
+@pytest.mark.parametrize("time_attr", ("start", "end"))
+@pytest.mark.parametrize("dyn_attr", ("static", "dynamic"))
+def test_dynamic_graph_has_timeformat(time_attr, dyn_attr, tmp_path):
+    """Ensure that graphs which have a 'start' or 'stop' attribute get a
+    'timeformat' attribute upon parsing. See gh-7914."""
+    G = nx.MultiGraph(mode=dyn_attr)
+    G.add_node(0)
+    G.nodes[0][time_attr] = 1
+    # Write out
+    fname = tmp_path / "foo.gexf"
+    nx.write_gexf(G, fname)
+    # Check that timeformat is added to saved data
+    with open(fname) as fh:
+        assert 'timeformat="long"' in fh.read()
+    # Round-trip
+    H = nx.read_gexf(fname)
+    # If any node has a "start" or "end" attr, it is considered dynamic
+    # regardless of the graph "mode" attr
+    assert H.graph["mode"] == "dynamic"
+    assert nx.utils.nodes_equal(G.edges, H.edges)
+
+
+class TestGEXF:
+    @classmethod
+    def setup_class(cls):
+        cls.simple_directed_data = """<?xml version="1.0" encoding="UTF-8"?>
+<gexf xmlns="http://www.gexf.net/1.2draft" version="1.2">
+    <graph mode="static" defaultedgetype="directed">
+        <nodes>
+            <node id="0" label="Hello" />
+            <node id="1" label="Word" />
+        </nodes>
+        <edges>
+            <edge id="0" source="0" target="1" />
+        </edges>
+    </graph>
+</gexf>
+"""
+        cls.simple_directed_graph = nx.DiGraph()
+        cls.simple_directed_graph.add_node("0", label="Hello")
+        cls.simple_directed_graph.add_node("1", label="World")
+        cls.simple_directed_graph.add_edge("0", "1", id="0")
+
+        cls.simple_directed_fh = io.BytesIO(cls.simple_directed_data.encode("UTF-8"))
+
+        cls.attribute_data = """<?xml version="1.0" encoding="UTF-8"?>\
+<gexf xmlns="http://www.gexf.net/1.2draft" xmlns:xsi="http://www.w3.\
+org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.gexf.net/\
+1.2draft http://www.gexf.net/1.2draft/gexf.xsd" version="1.2">
+  <meta lastmodifieddate="2009-03-20">
+    <creator>Gephi.org</creator>
+    <description>A Web network</description>
+  </meta>
+  <graph defaultedgetype="directed">
+    <attributes class="node">
+      <attribute id="0" title="url" type="string"/>
+      <attribute id="1" title="indegree" type="integer"/>
+      <attribute id="2" title="frog" type="boolean">
+        <default>true</default>
+      </attribute>
+    </attributes>
+    <nodes>
+      <node id="0" label="Gephi">
+        <attvalues>
+          <attvalue for="0" value="https://gephi.org"/>
+          <attvalue for="1" value="1"/>
+          <attvalue for="2" value="false"/>
+        </attvalues>
+      </node>
+      <node id="1" label="Webatlas">
+        <attvalues>
+          <attvalue for="0" value="http://webatlas.fr"/>
+          <attvalue for="1" value="2"/>
+          <attvalue for="2" value="false"/>
+        </attvalues>
+      </node>
+      <node id="2" label="RTGI">
+        <attvalues>
+          <attvalue for="0" value="http://rtgi.fr"/>
+          <attvalue for="1" value="1"/>
+          <attvalue for="2" value="true"/>
+        </attvalues>
+      </node>
+      <node id="3" label="BarabasiLab">
+        <attvalues>
+          <attvalue for="0" value="http://barabasilab.com"/>
+          <attvalue for="1" value="1"/>
+          <attvalue for="2" value="true"/>
+        </attvalues>
+      </node>
+    </nodes>
+    <edges>
+      <edge id="0" source="0" target="1" label="foo"/>
+      <edge id="1" source="0" target="2"/>
+      <edge id="2" source="1" target="0"/>
+      <edge id="3" source="2" target="1"/>
+      <edge id="4" source="0" target="3"/>
+    </edges>
+  </graph>
+</gexf>
+"""
+        cls.attribute_graph = nx.DiGraph()
+        cls.attribute_graph.graph["node_default"] = {"frog": True}
+        cls.attribute_graph.add_node(
+            "0", label="Gephi", url="https://gephi.org", indegree=1, frog=False
+        )
+        cls.attribute_graph.add_node(
+            "1", label="Webatlas", url="http://webatlas.fr", indegree=2, frog=False
+        )
+        cls.attribute_graph.add_node(
+            "2", label="RTGI", url="http://rtgi.fr", indegree=1, frog=True
+        )
+        cls.attribute_graph.add_node(
+            "3",
+            label="BarabasiLab",
+            url="http://barabasilab.com",
+            indegree=1,
+            frog=True,
+        )
+        cls.attribute_graph.add_edge("0", "1", id="0", label="foo")
+        cls.attribute_graph.add_edge("0", "2", id="1")
+        cls.attribute_graph.add_edge("1", "0", id="2")
+        cls.attribute_graph.add_edge("2", "1", id="3")
+        cls.attribute_graph.add_edge("0", "3", id="4")
+        cls.attribute_fh = io.BytesIO(cls.attribute_data.encode("UTF-8"))
+
+        cls.simple_undirected_data = """<?xml version="1.0" encoding="UTF-8"?>
+<gexf xmlns="http://www.gexf.net/1.2draft" version="1.2">
+    <graph mode="static" defaultedgetype="undirected">
+        <nodes>
+            <node id="0" label="Hello" />
+            <node id="1" label="Word" />
+        </nodes>
+        <edges>
+            <edge id="0" source="0" target="1" />
+        </edges>
+    </graph>
+</gexf>
+"""
+        cls.simple_undirected_graph = nx.Graph()
+        cls.simple_undirected_graph.add_node("0", label="Hello")
+        cls.simple_undirected_graph.add_node("1", label="World")
+        cls.simple_undirected_graph.add_edge("0", "1", id="0")
+
+        cls.simple_undirected_fh = io.BytesIO(
+            cls.simple_undirected_data.encode("UTF-8")
+        )
+
+    def test_read_simple_directed_graphml(self):
+        G = self.simple_directed_graph
+        H = nx.read_gexf(self.simple_directed_fh)
+        assert sorted(G.nodes()) == sorted(H.nodes())
+        assert sorted(G.edges()) == sorted(H.edges())
+        assert sorted(G.edges(data=True)) == sorted(H.edges(data=True))
+        self.simple_directed_fh.seek(0)
+
+    def test_write_read_simple_directed_graphml(self):
+        G = self.simple_directed_graph
+        fh = io.BytesIO()
+        nx.write_gexf(G, fh)
+        fh.seek(0)
+        H = nx.read_gexf(fh)
+        assert sorted(G.nodes()) == sorted(H.nodes())
+        assert sorted(G.edges()) == sorted(H.edges())
+        assert sorted(G.edges(data=True)) == sorted(H.edges(data=True))
+        self.simple_directed_fh.seek(0)
+
+    def test_read_simple_undirected_graphml(self):
+        G = self.simple_undirected_graph
+        H = nx.read_gexf(self.simple_undirected_fh)
+        assert sorted(G.nodes()) == sorted(H.nodes())
+        assert sorted(sorted(e) for e in G.edges()) == sorted(
+            sorted(e) for e in H.edges()
+        )
+        self.simple_undirected_fh.seek(0)
+
+    def test_read_attribute_graphml(self):
+        G = self.attribute_graph
+        H = nx.read_gexf(self.attribute_fh)
+        assert sorted(G.nodes(True)) == sorted(H.nodes(data=True))
+        ge = sorted(G.edges(data=True))
+        he = sorted(H.edges(data=True))
+        for a, b in zip(ge, he):
+            assert a == b
+        self.attribute_fh.seek(0)
+
+    def test_directed_edge_in_undirected(self):
+        s = """<?xml version="1.0" encoding="UTF-8"?>
+<gexf xmlns="http://www.gexf.net/1.2draft" version='1.2'>
+    <graph mode="static" defaultedgetype="undirected" name="">
+        <nodes>
+            <node id="0" label="Hello" />
+            <node id="1" label="Word" />
+        </nodes>
+        <edges>
+            <edge id="0" source="0" target="1" type="directed"/>
+        </edges>
+    </graph>
+</gexf>
+"""
+        fh = io.BytesIO(s.encode("UTF-8"))
+        pytest.raises(nx.NetworkXError, nx.read_gexf, fh)
+
+    def test_undirected_edge_in_directed(self):
+        s = """<?xml version="1.0" encoding="UTF-8"?>
+<gexf xmlns="http://www.gexf.net/1.2draft" version='1.2'>
+    <graph mode="static" defaultedgetype="directed" name="">
+        <nodes>
+            <node id="0" label="Hello" />
+            <node id="1" label="Word" />
+        </nodes>
+        <edges>
+            <edge id="0" source="0" target="1" type="undirected"/>
+        </edges>
+    </graph>
+</gexf>
+"""
+        fh = io.BytesIO(s.encode("UTF-8"))
+        pytest.raises(nx.NetworkXError, nx.read_gexf, fh)
+
+    def test_key_raises(self):
+        s = """<?xml version="1.0" encoding="UTF-8"?>
+<gexf xmlns="http://www.gexf.net/1.2draft" version='1.2'>
+    <graph mode="static" defaultedgetype="directed" name="">
+        <nodes>
+            <node id="0" label="Hello">
+              <attvalues>
+                <attvalue for='0' value='1'/>
+              </attvalues>
+            </node>
+            <node id="1" label="Word" />
+        </nodes>
+        <edges>
+            <edge id="0" source="0" target="1" type="undirected"/>
+        </edges>
+    </graph>
+</gexf>
+"""
+        fh = io.BytesIO(s.encode("UTF-8"))
+        pytest.raises(nx.NetworkXError, nx.read_gexf, fh)
+
+    def test_relabel(self):
+        s = """<?xml version="1.0" encoding="UTF-8"?>
+<gexf xmlns="http://www.gexf.net/1.2draft" version='1.2'>
+    <graph mode="static" defaultedgetype="directed" name="">
+        <nodes>
+            <node id="0" label="Hello" />
+            <node id="1" label="Word" />
+        </nodes>
+        <edges>
+            <edge id="0" source="0" target="1"/>
+        </edges>
+    </graph>
+</gexf>
+"""
+        fh = io.BytesIO(s.encode("UTF-8"))
+        G = nx.read_gexf(fh, relabel=True)
+        assert sorted(G.nodes()) == ["Hello", "Word"]
+
+    def test_default_attribute(self):
+        G = nx.Graph()
+        G.add_node(1, label="1", color="green")
+        nx.add_path(G, [0, 1, 2, 3])
+        G.add_edge(1, 2, foo=3)
+        G.graph["node_default"] = {"color": "yellow"}
+        G.graph["edge_default"] = {"foo": 7}
+        fh = io.BytesIO()
+        nx.write_gexf(G, fh)
+        fh.seek(0)
+        H = nx.read_gexf(fh, node_type=int)
+        assert sorted(G.nodes()) == sorted(H.nodes())
+        assert sorted(sorted(e) for e in G.edges()) == sorted(
+            sorted(e) for e in H.edges()
+        )
+        # Reading a gexf graph always sets mode attribute to either
+        # 'static' or 'dynamic'. Remove the mode attribute from the
+        # read graph for the sake of comparing remaining attributes.
+        del H.graph["mode"]
+        assert G.graph == H.graph
+
+    def test_serialize_ints_to_strings(self):
+        G = nx.Graph()
+        G.add_node(1, id=7, label=77)
+        fh = io.BytesIO()
+        nx.write_gexf(G, fh)
+        fh.seek(0)
+        H = nx.read_gexf(fh, node_type=int)
+        assert list(H) == [7]
+        assert H.nodes[7]["label"] == "77"
+
+    def test_write_with_node_attributes(self):
+        # Addresses #673.
+        G = nx.Graph()
+        G.add_edges_from([(0, 1), (1, 2), (2, 3)])
+        for i in range(4):
+            G.nodes[i]["id"] = i
+            G.nodes[i]["label"] = i
+            G.nodes[i]["pid"] = i
+            G.nodes[i]["start"] = i
+            G.nodes[i]["end"] = i + 1
+
+        expected = f"""<gexf xmlns="http://www.gexf.net/1.2draft" xmlns:xsi\
+="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation=\
+"http://www.gexf.net/1.2draft http://www.gexf.net/1.2draft/\
+gexf.xsd" version="1.2">
+  <meta lastmodifieddate="{time.strftime("%Y-%m-%d")}">
+    <creator>NetworkX {nx.__version__}</creator>
+  </meta>
+  <graph defaultedgetype="undirected" mode="dynamic" name="" timeformat="long">
+    <nodes>
+      <node id="0" label="0" pid="0" start="0" end="1" />
+      <node id="1" label="1" pid="1" start="1" end="2" />
+      <node id="2" label="2" pid="2" start="2" end="3" />
+      <node id="3" label="3" pid="3" start="3" end="4" />
+    </nodes>
+    <edges>
+      <edge source="0" target="1" id="0" />
+      <edge source="1" target="2" id="1" />
+      <edge source="2" target="3" id="2" />
+    </edges>
+  </graph>
+</gexf>"""
+        obtained = "\n".join(nx.generate_gexf(G))
+        assert expected == obtained
+
+    def test_edge_id_construct(self):
+        G = nx.Graph()
+        G.add_edges_from([(0, 1, {"id": 0}), (1, 2, {"id": 2}), (2, 3)])
+
+        expected = f"""<gexf xmlns="http://www.gexf.net/1.2draft" xmlns:xsi\
+="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.\
+gexf.net/1.2draft http://www.gexf.net/1.2draft/gexf.xsd" version="1.2">
+  <meta lastmodifieddate="{time.strftime("%Y-%m-%d")}">
+    <creator>NetworkX {nx.__version__}</creator>
+  </meta>
+  <graph defaultedgetype="undirected" mode="static" name="">
+    <nodes>
+      <node id="0" label="0" />
+      <node id="1" label="1" />
+      <node id="2" label="2" />
+      <node id="3" label="3" />
+    </nodes>
+    <edges>
+      <edge source="0" target="1" id="0" />
+      <edge source="1" target="2" id="2" />
+      <edge source="2" target="3" id="1" />
+    </edges>
+  </graph>
+</gexf>"""
+
+        obtained = "\n".join(nx.generate_gexf(G))
+        assert expected == obtained
+
+    def test_numpy_type(self):
+        np = pytest.importorskip("numpy")
+        G = nx.path_graph(4)
+        nx.set_node_attributes(G, {n: n for n in np.arange(4)}, "number")
+        G[0][1]["edge-number"] = np.float64(1.1)
+
+        expected = f"""<gexf xmlns="http://www.gexf.net/1.2draft"\
+ xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation\
+="http://www.gexf.net/1.2draft http://www.gexf.net/1.2draft/gexf.xsd"\
+ version="1.2">
+  <meta lastmodifieddate="{time.strftime("%Y-%m-%d")}">
+    <creator>NetworkX {nx.__version__}</creator>
+  </meta>
+  <graph defaultedgetype="undirected" mode="static" name="">
+    <attributes mode="static" class="edge">
+      <attribute id="1" title="edge-number" type="float" />
+    </attributes>
+    <attributes mode="static" class="node">
+      <attribute id="0" title="number" type="int" />
+    </attributes>
+    <nodes>
+      <node id="0" label="0">
+        <attvalues>
+          <attvalue for="0" value="0" />
+        </attvalues>
+      </node>
+      <node id="1" label="1">
+        <attvalues>
+          <attvalue for="0" value="1" />
+        </attvalues>
+      </node>
+      <node id="2" label="2">
+        <attvalues>
+          <attvalue for="0" value="2" />
+        </attvalues>
+      </node>
+      <node id="3" label="3">
+        <attvalues>
+          <attvalue for="0" value="3" />
+        </attvalues>
+      </node>
+    </nodes>
+    <edges>
+      <edge source="0" target="1" id="0">
+        <attvalues>
+          <attvalue for="1" value="1.1" />
+        </attvalues>
+      </edge>
+      <edge source="1" target="2" id="1" />
+      <edge source="2" target="3" id="2" />
+    </edges>
+  </graph>
+</gexf>"""
+        obtained = "\n".join(nx.generate_gexf(G))
+        assert expected == obtained
+
+    def test_bool(self):
+        G = nx.Graph()
+        G.add_node(1, testattr=True)
+        fh = io.BytesIO()
+        nx.write_gexf(G, fh)
+        fh.seek(0)
+        H = nx.read_gexf(fh, node_type=int)
+        assert H.nodes[1]["testattr"]
+
+    # Test for NaN, INF and -INF
+    def test_specials(self):
+        from math import isnan
+
+        inf, nan = float("inf"), float("nan")
+        G = nx.Graph()
+        G.add_node(1, testattr=inf, strdata="inf", key="a")
+        G.add_node(2, testattr=nan, strdata="nan", key="b")
+        G.add_node(3, testattr=-inf, strdata="-inf", key="c")
+
+        fh = io.BytesIO()
+        nx.write_gexf(G, fh)
+        fh.seek(0)
+        filetext = fh.read()
+        fh.seek(0)
+        H = nx.read_gexf(fh, node_type=int)
+
+        assert b"INF" in filetext
+        assert b"NaN" in filetext
+        assert b"-INF" in filetext
+
+        assert H.nodes[1]["testattr"] == inf
+        assert isnan(H.nodes[2]["testattr"])
+        assert H.nodes[3]["testattr"] == -inf
+
+        assert H.nodes[1]["strdata"] == "inf"
+        assert H.nodes[2]["strdata"] == "nan"
+        assert H.nodes[3]["strdata"] == "-inf"
+
+        assert H.nodes[1]["networkx_key"] == "a"
+        assert H.nodes[2]["networkx_key"] == "b"
+        assert H.nodes[3]["networkx_key"] == "c"
+
+    def test_simple_list(self):
+        G = nx.Graph()
+        list_value = [(1, 2, 3), (9, 1, 2)]
+        G.add_node(1, key=list_value)
+        fh = io.BytesIO()
+        nx.write_gexf(G, fh)
+        fh.seek(0)
+        H = nx.read_gexf(fh, node_type=int)
+        assert H.nodes[1]["networkx_key"] == list_value
+
+    def test_dynamic_mode(self):
+        G = nx.Graph()
+        G.add_node(1, label="1", color="green")
+        G.graph["mode"] = "dynamic"
+        fh = io.BytesIO()
+        nx.write_gexf(G, fh)
+        fh.seek(0)
+        H = nx.read_gexf(fh, node_type=int)
+        assert sorted(G.nodes()) == sorted(H.nodes())
+        assert sorted(sorted(e) for e in G.edges()) == sorted(
+            sorted(e) for e in H.edges()
+        )
+
+    def test_multigraph_with_missing_attributes(self):
+        G = nx.MultiGraph()
+        G.add_node(0, label="1", color="green")
+        G.add_node(1, label="2", color="green")
+        G.add_edge(0, 1, id="0", weight=3, type="undirected", start=0, end=1)
+        G.add_edge(0, 1, id="1", label="foo", start=0, end=1)
+        G.add_edge(0, 1)
+        fh = io.BytesIO()
+        nx.write_gexf(G, fh)
+        fh.seek(0)
+        H = nx.read_gexf(fh, node_type=int)
+        assert sorted(G.nodes()) == sorted(H.nodes())
+        assert sorted(sorted(e) for e in G.edges()) == sorted(
+            sorted(e) for e in H.edges()
+        )
+
+    def test_missing_viz_attributes(self):
+        G = nx.Graph()
+        G.add_node(0, label="1", color="green")
+        G.nodes[0]["viz"] = {"size": 54}
+        G.nodes[0]["viz"]["position"] = {"x": 0, "y": 1, "z": 0}
+        G.nodes[0]["viz"]["color"] = {"r": 0, "g": 0, "b": 256}
+        G.nodes[0]["viz"]["shape"] = "http://random.url"
+        G.nodes[0]["viz"]["thickness"] = 2
+        fh = io.BytesIO()
+        nx.write_gexf(G, fh, version="1.1draft")
+        fh.seek(0)
+        H = nx.read_gexf(fh, node_type=int)
+        assert sorted(G.nodes()) == sorted(H.nodes())
+        assert sorted(sorted(e) for e in G.edges()) == sorted(
+            sorted(e) for e in H.edges()
+        )
+
+        # Test missing alpha value for version >draft1.1 - set default alpha value
+        # to 1.0 instead of `None` when writing for better general compatibility
+        fh = io.BytesIO()
+        # G.nodes[0]["viz"]["color"] does not have an alpha value explicitly defined
+        # so the default is used instead
+        nx.write_gexf(G, fh, version="1.2draft")
+        fh.seek(0)
+        H = nx.read_gexf(fh, node_type=int)
+        assert H.nodes[0]["viz"]["color"]["a"] == 1.0
+
+        # Second graph for the other branch
+        G = nx.Graph()
+        G.add_node(0, label="1", color="green")
+        G.nodes[0]["viz"] = {"size": 54}
+        G.nodes[0]["viz"]["position"] = {"x": 0, "y": 1, "z": 0}
+        G.nodes[0]["viz"]["color"] = {"r": 0, "g": 0, "b": 256, "a": 0.5}
+        G.nodes[0]["viz"]["shape"] = "ftp://random.url"
+        G.nodes[0]["viz"]["thickness"] = 2
+        fh = io.BytesIO()
+        nx.write_gexf(G, fh)
+        fh.seek(0)
+        H = nx.read_gexf(fh, node_type=int)
+        assert sorted(G.nodes()) == sorted(H.nodes())
+        assert sorted(sorted(e) for e in G.edges()) == sorted(
+            sorted(e) for e in H.edges()
+        )
+
+    def test_slice_and_spell(self):
+        # Test spell first, so version = 1.2
+        G = nx.Graph()
+        G.add_node(0, label="1", color="green")
+        G.nodes[0]["spells"] = [(1, 2)]
+        fh = io.BytesIO()
+        nx.write_gexf(G, fh)
+        fh.seek(0)
+        H = nx.read_gexf(fh, node_type=int)
+        assert sorted(G.nodes()) == sorted(H.nodes())
+        assert sorted(sorted(e) for e in G.edges()) == sorted(
+            sorted(e) for e in H.edges()
+        )
+
+        G = nx.Graph()
+        G.add_node(0, label="1", color="green")
+        G.nodes[0]["slices"] = [(1, 2)]
+        fh = io.BytesIO()
+        nx.write_gexf(G, fh, version="1.1draft")
+        fh.seek(0)
+        H = nx.read_gexf(fh, node_type=int)
+        assert sorted(G.nodes()) == sorted(H.nodes())
+        assert sorted(sorted(e) for e in G.edges()) == sorted(
+            sorted(e) for e in H.edges()
+        )
+
+    def test_add_parent(self):
+        G = nx.Graph()
+        G.add_node(0, label="1", color="green", parents=[1, 2])
+        fh = io.BytesIO()
+        nx.write_gexf(G, fh)
+        fh.seek(0)
+        H = nx.read_gexf(fh, node_type=int)
+        assert sorted(G.nodes()) == sorted(H.nodes())
+        assert sorted(sorted(e) for e in G.edges()) == sorted(
+            sorted(e) for e in H.edges()
+        )

.venv/lib/python3.12/site-packages/networkx/readwrite/tests/test_gml.py

@@ -0,0 +1,744 @@
+import codecs
+import io
+import math
+from ast import literal_eval
+from contextlib import contextmanager
+from textwrap import dedent
+
+import pytest
+
+import networkx as nx
+from networkx.readwrite.gml import literal_destringizer, literal_stringizer
+
+
+class TestGraph:
+    @classmethod
+    def setup_class(cls):
+        cls.simple_data = """Creator "me"
+Version "xx"
+graph [
+ comment "This is a sample graph"
+ directed 1
+ IsPlanar 1
+ pos  [ x 0 y 1 ]
+ node [
+   id 1
+   label "Node 1"
+   pos [ x 1 y 1 ]
+ ]
+ node [
+    id 2
+    pos [ x 1 y 2 ]
+    label "Node 2"
+    ]
+  node [
+    id 3
+    label "Node 3"
+    pos [ x 1 y 3 ]
+  ]
+  edge [
+    source 1
+    target 2
+    label "Edge from node 1 to node 2"
+    color [line "blue" thickness 3]
+
+  ]
+  edge [
+    source 2
+    target 3
+    label "Edge from node 2 to node 3"
+  ]
+  edge [
+    source 3
+    target 1
+    label "Edge from node 3 to node 1"
+  ]
+]
+"""
+
+    def test_parse_gml_cytoscape_bug(self):
+        # example from issue #321, originally #324 in trac
+        cytoscape_example = """
+Creator "Cytoscape"
+Version 1.0
+graph   [
+    node    [
+        root_index  -3
+        id  -3
+        graphics    [
+            x   -96.0
+            y   -67.0
+            w   40.0
+            h   40.0
+            fill    "#ff9999"
+            type    "ellipse"
+            outline "#666666"
+            outline_width   1.5
+        ]
+        label   "node2"
+    ]
+    node    [
+        root_index  -2
+        id  -2
+        graphics    [
+            x   63.0
+            y   37.0
+            w   40.0
+            h   40.0
+            fill    "#ff9999"
+            type    "ellipse"
+            outline "#666666"
+            outline_width   1.5
+        ]
+        label   "node1"
+    ]
+    node    [
+        root_index  -1
+        id  -1
+        graphics    [
+            x   -31.0
+            y   -17.0
+            w   40.0
+            h   40.0
+            fill    "#ff9999"
+            type    "ellipse"
+            outline "#666666"
+            outline_width   1.5
+        ]
+        label   "node0"
+    ]
+    edge    [
+        root_index  -2
+        target  -2
+        source  -1
+        graphics    [
+            width   1.5
+            fill    "#0000ff"
+            type    "line"
+            Line    [
+            ]
+            source_arrow    0
+            target_arrow    3
+        ]
+        label   "DirectedEdge"
+    ]
+    edge    [
+        root_index  -1
+        target  -1
+        source  -3
+        graphics    [
+            width   1.5
+            fill    "#0000ff"
+            type    "line"
+            Line    [
+            ]
+            source_arrow    0
+            target_arrow    3
+        ]
+        label   "DirectedEdge"
+    ]
+]
+"""
+        nx.parse_gml(cytoscape_example)
+
+    def test_parse_gml(self):
+        G = nx.parse_gml(self.simple_data, label="label")
+        assert sorted(G.nodes()) == ["Node 1", "Node 2", "Node 3"]
+        assert sorted(G.edges()) == [
+            ("Node 1", "Node 2"),
+            ("Node 2", "Node 3"),
+            ("Node 3", "Node 1"),
+        ]
+
+        assert sorted(G.edges(data=True)) == [
+            (
+                "Node 1",
+                "Node 2",
+                {
+                    "color": {"line": "blue", "thickness": 3},
+                    "label": "Edge from node 1 to node 2",
+                },
+            ),
+            ("Node 2", "Node 3", {"label": "Edge from node 2 to node 3"}),
+            ("Node 3", "Node 1", {"label": "Edge from node 3 to node 1"}),
+        ]
+
+    def test_read_gml(self, tmp_path):
+        fname = tmp_path / "test.gml"
+        with open(fname, "w") as fh:
+            fh.write(self.simple_data)
+        Gin = nx.read_gml(fname, label="label")
+        G = nx.parse_gml(self.simple_data, label="label")
+        assert sorted(G.nodes(data=True)) == sorted(Gin.nodes(data=True))
+        assert sorted(G.edges(data=True)) == sorted(Gin.edges(data=True))
+
+    def test_labels_are_strings(self):
+        # GML requires labels to be strings (i.e., in quotes)
+        answer = """graph [
+  node [
+    id 0
+    label "1203"
+  ]
+]"""
+        G = nx.Graph()
+        G.add_node(1203)
+        data = "\n".join(nx.generate_gml(G, stringizer=literal_stringizer))
+        assert data == answer
+
+    def test_relabel_duplicate(self):
+        data = """
+graph
+[
+        label   ""
+        directed        1
+        node
+        [
+                id      0
+                label   "same"
+        ]
+        node
+        [
+                id      1
+                label   "same"
+        ]
+]
+"""
+        fh = io.BytesIO(data.encode("UTF-8"))
+        fh.seek(0)
+        pytest.raises(nx.NetworkXError, nx.read_gml, fh, label="label")
+
+    @pytest.mark.parametrize("stringizer", (None, literal_stringizer))
+    def test_tuplelabels(self, stringizer):
+        # https://github.com/networkx/networkx/pull/1048
+        # Writing tuple labels to GML failed.
+        G = nx.Graph()
+        G.add_edge((0, 1), (1, 0))
+        data = "\n".join(nx.generate_gml(G, stringizer=stringizer))
+        answer = """graph [
+  node [
+    id 0
+    label "(0,1)"
+  ]
+  node [
+    id 1
+    label "(1,0)"
+  ]
+  edge [
+    source 0
+    target 1
+  ]
+]"""
+        assert data == answer
+
+    def test_quotes(self, tmp_path):
+        # https://github.com/networkx/networkx/issues/1061
+        # Encoding quotes as HTML entities.
+        G = nx.path_graph(1)
+        G.name = "path_graph(1)"
+        attr = 'This is "quoted" and this is a copyright: ' + chr(169)
+        G.nodes[0]["demo"] = attr
+        with open(tmp_path / "test.gml", "w+b") as fobj:
+            nx.write_gml(G, fobj)
+            fobj.seek(0)
+            # Should be bytes in 2.x and 3.x
+            data = fobj.read().strip().decode("ascii")
+        answer = """graph [
+  name "path_graph(1)"
+  node [
+    id 0
+    label "0"
+    demo "This is "quoted" and this is a copyright: ©"
+  ]
+]"""
+        assert data == answer
+
+    def test_unicode_node(self, tmp_path):
+        node = "node" + chr(169)
+        G = nx.Graph()
+        G.add_node(node)
+        with open(tmp_path / "test.gml", "w+b") as fobj:
+            nx.write_gml(G, fobj)
+            fobj.seek(0)
+            # Should be bytes in 2.x and 3.x
+            data = fobj.read().strip().decode("ascii")
+        answer = """graph [
+  node [
+    id 0
+    label "node©"
+  ]
+]"""
+        assert data == answer
+
+    def test_float_label(self, tmp_path):
+        node = 1.0
+        G = nx.Graph()
+        G.add_node(node)
+        with open(tmp_path / "test.gml", "w+b") as fobj:
+            nx.write_gml(G, fobj)
+            fobj.seek(0)
+            # Should be bytes in 2.x and 3.x
+            data = fobj.read().strip().decode("ascii")
+        answer = """graph [
+  node [
+    id 0
+    label "1.0"
+  ]
+]"""
+        assert data == answer
+
+    def test_special_float_label(self, tmp_path):
+        special_floats = [float("nan"), float("+inf"), float("-inf")]
+        try:
+            import numpy as np
+
+            special_floats += [np.nan, np.inf, np.inf * -1]
+        except ImportError:
+            special_floats += special_floats
+
+        G = nx.cycle_graph(len(special_floats))
+        attrs = dict(enumerate(special_floats))
+        nx.set_node_attributes(G, attrs, "nodefloat")
+        edges = list(G.edges)
+        attrs = {edges[i]: value for i, value in enumerate(special_floats)}
+        nx.set_edge_attributes(G, attrs, "edgefloat")
+
+        with open(tmp_path / "test.gml", "w+b") as fobj:
+            nx.write_gml(G, fobj)
+            fobj.seek(0)
+            # Should be bytes in 2.x and 3.x
+            data = fobj.read().strip().decode("ascii")
+            answer = """graph [
+  node [
+    id 0
+    label "0"
+    nodefloat NAN
+  ]
+  node [
+    id 1
+    label "1"
+    nodefloat +INF
+  ]
+  node [
+    id 2
+    label "2"
+    nodefloat -INF
+  ]
+  node [
+    id 3
+    label "3"
+    nodefloat NAN
+  ]
+  node [
+    id 4
+    label "4"
+    nodefloat +INF
+  ]
+  node [
+    id 5
+    label "5"
+    nodefloat -INF
+  ]
+  edge [
+    source 0
+    target 1
+    edgefloat NAN
+  ]
+  edge [
+    source 0
+    target 5
+    edgefloat +INF
+  ]
+  edge [
+    source 1
+    target 2
+    edgefloat -INF
+  ]
+  edge [
+    source 2
+    target 3
+    edgefloat NAN
+  ]
+  edge [
+    source 3
+    target 4
+    edgefloat +INF
+  ]
+  edge [
+    source 4
+    target 5
+    edgefloat -INF
+  ]
+]"""
+            assert data == answer
+
+            fobj.seek(0)
+            graph = nx.read_gml(fobj)
+            for indx, value in enumerate(special_floats):
+                node_value = graph.nodes[str(indx)]["nodefloat"]
+                if math.isnan(value):
+                    assert math.isnan(node_value)
+                else:
+                    assert node_value == value
+
+                edge = edges[indx]
+                string_edge = (str(edge[0]), str(edge[1]))
+                edge_value = graph.edges[string_edge]["edgefloat"]
+                if math.isnan(value):
+                    assert math.isnan(edge_value)
+                else:
+                    assert edge_value == value
+
+    def test_name(self):
+        G = nx.parse_gml('graph [ name "x" node [ id 0 label "x" ] ]')
+        assert "x" == G.graph["name"]
+        G = nx.parse_gml('graph [ node [ id 0 label "x" ] ]')
+        assert "" == G.name
+        assert "name" not in G.graph
+
+    def test_graph_types(self):
+        for directed in [None, False, True]:
+            for multigraph in [None, False, True]:
+                gml = "graph ["
+                if directed is not None:
+                    gml += " directed " + str(int(directed))
+                if multigraph is not None:
+                    gml += " multigraph " + str(int(multigraph))
+                gml += ' node [ id 0 label "0" ]'
+                gml += " edge [ source 0 target 0 ]"
+                gml += " ]"
+                G = nx.parse_gml(gml)
+                assert bool(directed) == G.is_directed()
+                assert bool(multigraph) == G.is_multigraph()
+                gml = "graph [\n"
+                if directed is True:
+                    gml += "  directed 1\n"
+                if multigraph is True:
+                    gml += "  multigraph 1\n"
+                gml += """  node [
+    id 0
+    label "0"
+  ]
+  edge [
+    source 0
+    target 0
+"""
+                if multigraph:
+                    gml += "    key 0\n"
+                gml += "  ]\n]"
+                assert gml == "\n".join(nx.generate_gml(G))
+
+    def test_data_types(self):
+        data = [
+            True,
+            False,
+            10**20,
+            -2e33,
+            "'",
+            '"&&&""',
+            [{(b"\xfd",): "\x7f", chr(0x4444): (1, 2)}, (2, "3")],
+        ]
+        data.append(chr(0x14444))
+        data.append(literal_eval("{2.3j, 1 - 2.3j, ()}"))
+        G = nx.Graph()
+        G.name = data
+        G.graph["data"] = data
+        G.add_node(0, int=-1, data={"data": data})
+        G.add_edge(0, 0, float=-2.5, data=data)
+        gml = "\n".join(nx.generate_gml(G, stringizer=literal_stringizer))
+        G = nx.parse_gml(gml, destringizer=literal_destringizer)
+        assert data == G.name
+        assert {"name": data, "data": data} == G.graph
+        assert list(G.nodes(data=True)) == [(0, {"int": -1, "data": {"data": data}})]
+        assert list(G.edges(data=True)) == [(0, 0, {"float": -2.5, "data": data})]
+        G = nx.Graph()
+        G.graph["data"] = "frozenset([1, 2, 3])"
+        G = nx.parse_gml(nx.generate_gml(G), destringizer=literal_eval)
+        assert G.graph["data"] == "frozenset([1, 2, 3])"
+
+    def test_escape_unescape(self):
+        gml = """graph [
+  name "&"䑄��&unknown;"
+]"""
+        G = nx.parse_gml(gml)
+        assert (
+            '&"\x0f' + chr(0x4444) + "��&unknown;"
+            == G.name
+        )
+        gml = "\n".join(nx.generate_gml(G))
+        alnu = "#1234567890;&#x1234567890abcdef"
+        answer = (
+            """graph [
+  name "&"䑄&"""
+            + alnu
+            + """;&unknown;"
+]"""
+        )
+        assert answer == gml
+
+    def test_exceptions(self, tmp_path):
+        pytest.raises(ValueError, literal_destringizer, "(")
+        pytest.raises(ValueError, literal_destringizer, "frozenset([1, 2, 3])")
+        pytest.raises(ValueError, literal_destringizer, literal_destringizer)
+        pytest.raises(ValueError, literal_stringizer, frozenset([1, 2, 3]))
+        pytest.raises(ValueError, literal_stringizer, literal_stringizer)
+        with open(tmp_path / "test.gml", "w+b") as f:
+            f.write(codecs.BOM_UTF8 + b"graph[]")
+            f.seek(0)
+            pytest.raises(nx.NetworkXError, nx.read_gml, f)
+
+        def assert_parse_error(gml):
+            pytest.raises(nx.NetworkXError, nx.parse_gml, gml)
+
+        assert_parse_error(["graph [\n\n", "]"])
+        assert_parse_error("")
+        assert_parse_error('Creator ""')
+        assert_parse_error("0")
+        assert_parse_error("graph ]")
+        assert_parse_error("graph [ 1 ]")
+        assert_parse_error("graph [ 1.E+2 ]")
+        assert_parse_error('graph [ "A" ]')
+        assert_parse_error("graph [ ] graph ]")
+        assert_parse_error("graph [ ] graph [ ]")
+        assert_parse_error("graph [ data [1, 2, 3] ]")
+        assert_parse_error("graph [ node [ ] ]")
+        assert_parse_error("graph [ node [ id 0 ] ]")
+        nx.parse_gml('graph [ node [ id "a" ] ]', label="id")
+        assert_parse_error("graph [ node [ id 0 label 0 ] node [ id 0 label 1 ] ]")
+        assert_parse_error("graph [ node [ id 0 label 0 ] node [ id 1 label 0 ] ]")
+        assert_parse_error("graph [ node [ id 0 label 0 ] edge [ ] ]")
+        assert_parse_error("graph [ node [ id 0 label 0 ] edge [ source 0 ] ]")
+        nx.parse_gml("graph [edge [ source 0 target 0 ] node [ id 0 label 0 ] ]")
+        assert_parse_error("graph [ node [ id 0 label 0 ] edge [ source 1 target 0 ] ]")
+        assert_parse_error("graph [ node [ id 0 label 0 ] edge [ source 0 target 1 ] ]")
+        assert_parse_error(
+            "graph [ node [ id 0 label 0 ] node [ id 1 label 1 ] "
+            "edge [ source 0 target 1 ] edge [ source 1 target 0 ] ]"
+        )
+        nx.parse_gml(
+            "graph [ node [ id 0 label 0 ] node [ id 1 label 1 ] "
+            "edge [ source 0 target 1 ] edge [ source 1 target 0 ] "
+            "directed 1 ]"
+        )
+        nx.parse_gml(
+            "graph [ node [ id 0 label 0 ] node [ id 1 label 1 ] "
+            "edge [ source 0 target 1 ] edge [ source 0 target 1 ]"
+            "multigraph 1 ]"
+        )
+        nx.parse_gml(
+            "graph [ node [ id 0 label 0 ] node [ id 1 label 1 ] "
+            "edge [ source 0 target 1 key 0 ] edge [ source 0 target 1 ]"
+            "multigraph 1 ]"
+        )
+        assert_parse_error(
+            "graph [ node [ id 0 label 0 ] node [ id 1 label 1 ] "
+            "edge [ source 0 target 1 key 0 ] edge [ source 0 target 1 key 0 ]"
+            "multigraph 1 ]"
+        )
+        nx.parse_gml(
+            "graph [ node [ id 0 label 0 ] node [ id 1 label 1 ] "
+            "edge [ source 0 target 1 key 0 ] edge [ source 1 target 0 key 0 ]"
+            "directed 1 multigraph 1 ]"
+        )
+
+        # Tests for string convertible alphanumeric id and label values
+        nx.parse_gml("graph [edge [ source a target a ] node [ id a label b ] ]")
+        nx.parse_gml(
+            "graph [ node [ id n42 label 0 ] node [ id x43 label 1 ]"
+            "edge [ source n42 target x43 key 0 ]"
+            "edge [ source x43 target n42 key 0 ]"
+            "directed 1 multigraph 1 ]"
+        )
+        assert_parse_error(
+            "graph [edge [ source '\u4200' target '\u4200' ] "
+            + "node [ id '\u4200' label b ] ]"
+        )
+
+        def assert_generate_error(*args, **kwargs):
+            pytest.raises(
+                nx.NetworkXError, lambda: list(nx.generate_gml(*args, **kwargs))
+            )
+
+        G = nx.Graph()
+        G.graph[3] = 3
+        assert_generate_error(G)
+        G = nx.Graph()
+        G.graph["3"] = 3
+        assert_generate_error(G)
+        G = nx.Graph()
+        G.graph["data"] = frozenset([1, 2, 3])
+        assert_generate_error(G, stringizer=literal_stringizer)
+
+    def test_label_kwarg(self):
+        G = nx.parse_gml(self.simple_data, label="id")
+        assert sorted(G.nodes) == [1, 2, 3]
+        labels = [G.nodes[n]["label"] for n in sorted(G.nodes)]
+        assert labels == ["Node 1", "Node 2", "Node 3"]
+
+        G = nx.parse_gml(self.simple_data, label=None)
+        assert sorted(G.nodes) == [1, 2, 3]
+        labels = [G.nodes[n]["label"] for n in sorted(G.nodes)]
+        assert labels == ["Node 1", "Node 2", "Node 3"]
+
+    def test_outofrange_integers(self, tmp_path):
+        # GML restricts integers to 32 signed bits.
+        # Check that we honor this restriction on export
+        G = nx.Graph()
+        # Test export for numbers that barely fit or don't fit into 32 bits,
+        # and 3 numbers in the middle
+        numbers = {
+            "toosmall": (-(2**31)) - 1,
+            "small": -(2**31),
+            "med1": -4,
+            "med2": 0,
+            "med3": 17,
+            "big": (2**31) - 1,
+            "toobig": 2**31,
+        }
+        G.add_node("Node", **numbers)
+
+        fname = tmp_path / "test.gml"
+        nx.write_gml(G, fname)
+        # Check that the export wrote the nonfitting numbers as strings
+        G2 = nx.read_gml(fname)
+        for attr, value in G2.nodes["Node"].items():
+            if attr == "toosmall" or attr == "toobig":
+                assert isinstance(value, str)
+            else:
+                assert isinstance(value, int)
+
+    def test_multiline(self):
+        # example from issue #6836
+        multiline_example = """
+graph
+[
+    node
+    [
+	    id 0
+	    label "multiline node"
+	    label2 "multiline1
+    multiline2
+    multiline3"
+	    alt_name "id 0"
+    ]
+]
+"""
+        G = nx.parse_gml(multiline_example)
+        assert G.nodes["multiline node"] == {
+            "label2": "multiline1 multiline2 multiline3",
+            "alt_name": "id 0",
+        }
+
+
+@contextmanager
+def byte_file():
+    _file_handle = io.BytesIO()
+    yield _file_handle
+    _file_handle.seek(0)
+
+
+class TestPropertyLists:
+    def test_writing_graph_with_multi_element_property_list(self):
+        g = nx.Graph()
+        g.add_node("n1", properties=["element", 0, 1, 2.5, True, False])
+        with byte_file() as f:
+            nx.write_gml(g, f)
+        result = f.read().decode()
+
+        assert result == dedent(
+            """\
+            graph [
+              node [
+                id 0
+                label "n1"
+                properties "element"
+                properties 0
+                properties 1
+                properties 2.5
+                properties 1
+                properties 0
+              ]
+            ]
+        """
+        )
+
+    def test_writing_graph_with_one_element_property_list(self):
+        g = nx.Graph()
+        g.add_node("n1", properties=["element"])
+        with byte_file() as f:
+            nx.write_gml(g, f)
+        result = f.read().decode()
+
+        assert result == dedent(
+            """\
+            graph [
+              node [
+                id 0
+                label "n1"
+                properties "_networkx_list_start"
+                properties "element"
+              ]
+            ]
+        """
+        )
+
+    def test_reading_graph_with_list_property(self):
+        with byte_file() as f:
+            f.write(
+                dedent(
+                    """
+              graph [
+                node [
+                  id 0
+                  label "n1"
+                  properties "element"
+                  properties 0
+                  properties 1
+                  properties 2.5
+                ]
+              ]
+            """
+                ).encode("ascii")
+            )
+            f.seek(0)
+            graph = nx.read_gml(f)
+        assert graph.nodes(data=True)["n1"] == {"properties": ["element", 0, 1, 2.5]}
+
+    def test_reading_graph_with_single_element_list_property(self):
+        with byte_file() as f:
+            f.write(
+                dedent(
+                    """
+              graph [
+                node [
+                  id 0
+                  label "n1"
+                  properties "_networkx_list_start"
+                  properties "element"
+                ]
+              ]
+            """
+                ).encode("ascii")
+            )
+            f.seek(0)
+            graph = nx.read_gml(f)
+        assert graph.nodes(data=True)["n1"] == {"properties": ["element"]}
+
+
+@pytest.mark.parametrize("coll", ([], ()))
+def test_stringize_empty_list_tuple(coll):
+    G = nx.path_graph(2)
+    G.nodes[0]["test"] = coll  # test serializing an empty collection
+    f = io.BytesIO()
+    nx.write_gml(G, f)  # Smoke test - should not raise
+    f.seek(0)
+    H = nx.read_gml(f)
+    assert H.nodes["0"]["test"] == coll  # Check empty list round-trips properly
+    # Check full round-tripping. Note that nodes are loaded as strings by
+    # default, so there needs to be some remapping prior to comparison
+    H = nx.relabel_nodes(H, {"0": 0, "1": 1})
+    assert nx.utils.graphs_equal(G, H)
+    # Same as above, but use destringizer for node remapping. Should have no
+    # effect on node attr
+    f.seek(0)
+    H = nx.read_gml(f, destringizer=int)
+    assert nx.utils.graphs_equal(G, H)