Move DeprecationWarning suppression to equivalent function

Rather than suppressing the warning in merge_attrs, handle it at the
source in equivalent() where the 'or' operation happens. This is cleaner
and includes a clear comment about when the suppression can be removed
(when minimum numpy version >= 2.0).

The warning only occurs in numpy < 2.0; numpy 2.0+ raises ValueError
directly, which we already handle properly in merge_attrs.

Author: max-sixty

xarray/core/utils.py

@@ -249,7 +249,14 @@ def equivalent(first: T, second: T) -> bool:
         return duck_array_ops.array_equiv(first, second)
     if isinstance(first, list) or isinstance(second, list):
         return list_equiv(first, second)  # type: ignore[arg-type]
-    return (first == second) or (pd.isnull(first) and pd.isnull(second))  # type: ignore[call-overload]
+
+    # Suppress DeprecationWarning about ambiguous truth values from numpy < 2.0
+    # In numpy 2.0+, this will raise ValueError directly, which we handle in callers
+    # Can remove this suppression when minimum numpy version >= 2.0
+    import warnings
+    with warnings.catch_warnings():
+        warnings.filterwarnings("ignore", category=DeprecationWarning)
+        return (first == second) or (pd.isnull(first) and pd.isnull(second))  # type: ignore[call-overload]
 
 
 def list_equiv(first: Sequence[T], second: Sequence[T]) -> bool:

xarray/structure/merge.py

@@ -650,18 +650,10 @@ def merge_attrs(variable_attrs, combine_attrs, context=None):
                 else:
                     # Check if values are equivalent
                     try:
-                        import warnings
-
-                        # Suppress DeprecationWarning about ambiguous truth values
-                        # since we handle the resulting ValueError appropriately
-                        with warnings.catch_warnings():
-                            warnings.filterwarnings(
-                                "ignore", category=DeprecationWarning
-                            )
-                            if equivalent(attrs[key], value):
-                                # Values are equivalent, keep the attribute
-                                filtered_result[key] = value
-                            # else: Values differ, drop the attribute (don't add to filtered_result)
+                        if equivalent(attrs[key], value):
+                            # Values are equivalent, keep the attribute
+                            filtered_result[key] = value
+                        # else: Values differ, drop the attribute (don't add to filtered_result)
                     except ValueError:
                         # Likely an ambiguous truth value from numpy array comparison
                         # Treat as non-equivalent and drop the attribute