improve warning messages

osmnx/_osm_xml.py

@@ -96,14 +96,14 @@ def _opener(filepath: Path, encoding: str) -> TextIO:
     with _opener(Path(filepath), encoding) as f:
         root_attrs = ET.parse(f).getroot().attrib
         if "generator" in root_attrs and "OSMnx" in root_attrs["generator"]:
-            warn(
+            msg = (
                 "The XML file you are loading appears to have been generated "
                 "by OSMnx: this use case is not supported and may not behave "
                 "as expected. To save/load graphs to/from disk for later use "
                 "in OSMnx, use the `io.save_graphml` and `io.load_graphml` "
-                "functions instead. Refer to the documentation for details.",
-                stacklevel=2,
+                "functions instead. Refer to the documentation for details."
             )
+            warn(msg, stacklevel=2)
 
     # parse the XML to Overpass-like JSON
     with _opener(Path(filepath), encoding) as f:
@@ -175,11 +175,11 @@ def _save_graph_xml(
     filepath.parent.mkdir(parents=True, exist_ok=True)
 
     if not settings.all_oneway:  # pragma: no cover
-        warn(
+        msg = (
             "For the `save_graph_xml` function to behave properly, the graph "
-            "must have been created with `ox.settings.all_oneway=True`.",
-            stacklevel=2,
+            "must have been created with `ox.settings.all_oneway=True`."
         )
+        warn(msg, stacklevel=2)
 
     if isinstance(data, nx.MultiDiGraph):
         gdf_nodes, gdf_edges = utils_graph.graph_to_gdfs(

osmnx/routing.py

@@ -256,25 +256,25 @@ def _verify_edge_attribute(G: nx.MultiDiGraph, attr: str) -> None:
     """
     Verify attribute values are numeric and non-null across graph edges.
 
-    Raises a `ValueError` if attribute contains non-numeric values and raises
-    a warning if attribute is missing or null on any edges.
+    Raises a ValueError if this attribute contains non-numeric values, and
+    issues a UserWarning if this attribute is missing or null on any edges.
 
     Parameters
     ----------
     G : networkx.MultiDiGraph
         input graph
     attr : string
-        edge attribute to verify
+        name of the edge attribute to verify
 
     Returns
     -------
     None
     """
     try:
-        values = np.array(tuple(G.edges(data=attr)))[:, 2]
-        values_float = values.astype(float)
+        values_float = (np.array(tuple(G.edges(data=attr)))[:, 2]).astype(float)
         if np.isnan(values_float).any():
-            warn(f"The attribute {attr!r} is missing or null on some edges.", stacklevel=2)
+            msg = f"The attribute {attr!r} is missing or null on some edges."
+            warn(msg, stacklevel=2)
     except ValueError as e:
         msg = f"The edge attribute {attr!r} contains non-numeric values."
         raise ValueError(msg) from e

osmnx/utils_geo.py

@@ -47,7 +47,8 @@ def sample_points(G: nx.MultiGraph, n: int) -> gpd.GeoSeries:
         which each point was drawn
     """
     if nx.is_directed(G):  # pragma: no cover
-        warn("graph should be undirected to avoid oversampling bidirectional edges", stacklevel=2)
+        msg = "`G` should be undirected to avoid oversampling bidirectional edges."
+        warn(msg, stacklevel=2)
     gdf_edges = utils_graph.graph_to_gdfs(G, nodes=False)[["geometry", "length"]]
     weights = gdf_edges["length"] / gdf_edges["length"].sum()
     idx = np.random.default_rng().choice(gdf_edges.index, size=n, p=weights)

osmnx/utils_graph.py

@@ -274,11 +274,11 @@ def graph_from_gdfs(
     except (AssertionError, ValueError):  # pragma: no cover
         # AssertionError if x/y coords don't match geometry column
         # ValueError if geometry column contains non-point geometry types
-        warn(
-            "discarding the gdf_nodes geometry column, though its "
-            "values differ from the coordinates in the x and y columns",
-            stacklevel=2,
+        msg = (
+            "Discarding the `gdf_nodes` geometry column, though its values "
+            "differ from the coordinates in the x and y columns."
         )
+        warn(msg, stacklevel=2)
     df_nodes = gdf_nodes.drop(columns=gdf_nodes.geometry.name)
 
     # create graph and add graph-level attribute dict