Add support for automatic dict and set attributes in module io

osmnx/io.py

@@ -421,6 +421,16 @@ def _convert_node_attr_types(G, dtypes=None):
     G : networkx.MultiDiGraph
     """
     for _, data in G.nodes(data=True):
+        # first, eval stringified lists, dicts or sets to convert them to objects
+        # node attributes might have a single value, or a list if simplified
+        for attr, value in data.items():
+            # check for stringified lists
+            if (value.startswith("[") and value.endswith("]")) or (
+                value.startswith("{") and value.endswith("}")
+            ):
+                with contextlib.suppress(SyntaxError, ValueError):
+                    data[attr] = ast.literal_eval(value)
+
         for attr in data.keys() & dtypes.keys():
             data[attr] = dtypes[attr](data[attr])
     return G
@@ -446,10 +456,12 @@ def _convert_edge_attr_types(G, dtypes=None):
         # remove extraneous "id" attribute added by graphml saving
         data.pop("id", None)
 
-        # first, eval stringified lists to convert them to list objects
+        # first, eval stringified lists, dicts or sets to convert them to objects
         # edge attributes might have a single value, or a list if simplified
         for attr, value in data.items():
-            if value.startswith("[") and value.endswith("]"):
+            if (value.startswith("[") and value.endswith("]")) or (
+                value.startswith("{") and value.endswith("}")
+            ):
                 with contextlib.suppress(SyntaxError, ValueError):
                     data[attr] = ast.literal_eval(value)
 

tests/test_osmnx.py

@@ -474,6 +474,25 @@ def test_graph_save_load():
     edge_attrs = {n: bool(b) for n, b in zip(G.edges, bools)}
     nx.set_edge_attributes(G, edge_attrs, attr_name)
 
+    # create list, set, and dict attributes for nodes and edges
+    rand_ints_nodes = np.random.randint(0, 10, len(G.nodes))
+    rand_ints_edges = np.random.randint(0, 10, len(G.edges))
+    list_name = "test_list"
+    list_node_attrs = {n: [n, r] for n, r in zip(G.nodes, rand_ints_nodes)}
+    nx.set_node_attributes(G, list_node_attrs, list_name)
+    list_edge_attrs = {e: [e, r] for e, r in zip(G.edges, rand_ints_edges)}
+    nx.set_edge_attributes(G, list_edge_attrs, list_name)
+    set_name = "test_set"
+    set_node_attrs = {n: {n, r} for n, r in zip(G.nodes, rand_ints_nodes)}
+    nx.set_node_attributes(G, set_node_attrs, set_name)
+    set_edge_attrs = {e: {e, r} for e, r in zip(G.edges, rand_ints_edges)}
+    nx.set_edge_attributes(G, set_edge_attrs, set_name)
+    dict_name = "test_dict"
+    dict_node_attrs = {n: {n: r} for n, r in zip(G.nodes, rand_ints_nodes)}
+    nx.set_node_attributes(G, dict_node_attrs, dict_name)
+    dict_edge_attrs = {e: {e: r} for e, r in zip(G.edges, rand_ints_edges)}
+    nx.set_edge_attributes(G, dict_edge_attrs, dict_name)
+
     # save/load graph as graphml file
     ox.save_graphml(G, gephi=True)
     ox.save_graphml(G, gephi=False)