DRY

networkx/utils/backends.py

@@ -1024,6 +1024,24 @@ def _convert_graph(
                 preserve_graph_attrs,
             )
             if cache:
+                warning_message = (
+                    f"Using cached graph for {backend_name!r} backend in "
+                    f"call to {self.name}.\n\nFor the cache to be consistent "
+                    "(i.e., correct), the input graph must not have been "
+                    "manually mutated since the cached graph was created. "
+                    "Examples of manually mutating the graph data structures "
+                    "resulting in an inconsistent cache include:\n\n"
+                    "    >>> G[u][v][key] = val\n\n"
+                    "and\n\n"
+                    "    >>> for u, v, d in G.edges(data=True):\n"
+                    "    ...     d[key] = val\n\n"
+                    "Using methods such as `G.add_edge(u, v, weight=val)` "
+                    "will correctly clear the cache to keep it consistent. "
+                    "You may also use `G.__networkx_cache__.clear()` to "
+                    "manually clear the cache, or set `G.__networkx_cache__` "
+                    "to None to disable caching for G. Enable or disable "
+                    "caching via `nx.config.cache_converted_graphs` config."
+                )
                 # Do a simple search for a cached graph with compatible data.
                 # For example, if we need a single attribute, then it's okay
                 # to use a cached graph that preserved all attributes.
@@ -1034,24 +1052,7 @@ def _convert_graph(
                     (graph_key, True) if graph_key is not True else (True,),
                 ):
                     if (rv := cache.get(compat_key)) is not None:
-                        warnings.warn(
-                            f"Using cached graph for {backend_name!r} backend in "
-                            f"call to {self.name}.\n\nFor the cache to be consistent "
-                            "(i.e., correct), the input graph must not have been "
-                            "manually mutated since the cached graph was created. "
-                            "Examples of manually mutating the graph data structures "
-                            "resulting in an inconsistent cache include:\n\n"
-                            "    >>> G[u][v][key] = val\n\n"
-                            "and\n\n"
-                            "    >>> for u, v, d in G.edges(data=True):\n"
-                            "    ...     d[key] = val\n\n"
-                            "Using methods such as `G.add_edge(u, v, weight=val)` "
-                            "will correctly clear the cache to keep it consistent. "
-                            "You may also use `G.__networkx_cache__.clear()` to "
-                            "manually clear the cache, or set `G.__networkx_cache__` "
-                            "to None to disable caching for G. Enable or disable "
-                            "caching via `nx.config.cache_converted_graphs` config."
-                        )
+                        warnings.warn(warning_message)
                         return rv
                 if edge_key is not True and node_key is not True:
                     # Iterate over the items in `cache` to see if any are compatible.
@@ -1078,24 +1079,7 @@ def _convert_graph(
                             continue
                         if graph_key and not gkey:
                             continue
-                        warnings.warn(
-                            f"Using cached graph for {backend_name!r} backend in "
-                            f"call to {self.name}.\n\nFor the cache to be consistent "
-                            "(i.e., correct), the input graph must not have been "
-                            "manually mutated since the cached graph was created. "
-                            "Examples of manually mutating the graph data structures "
-                            "resulting in an inconsistent cache include:\n\n"
-                            "    >>> G[u][v][key] = val\n\n"
-                            "and\n\n"
-                            "    >>> for u, v, d in G.edges(data=True):\n"
-                            "    ...     d[key] = val\n\n"
-                            "Using methods such as `G.add_edge(u, v, weight=val)` "
-                            "will correctly clear the cache to keep it consistent. "
-                            "You may also use `G.__networkx_cache__.clear()` to "
-                            "manually clear the cache, or set `G.__networkx_cache__` "
-                            "to None to disable caching for G. Enable or disable "
-                            "caching via `nx.config.cache_converted_graphs` config."
-                        )
+                        warnings.warn(warning_message)
                         return val
 
         backend = _load_backend(backend_name)