From b3cd8eb975e850ba600cf4b233423ff2c0df9cd4 Mon Sep 17 00:00:00 2001
From: Tom White <tom.e.white@gmail.com>
Date: Mon, 2 Oct 2023 15:17:35 +0100
Subject: [PATCH] Duck array ops for `all` and `any`

---
 xarray/core/duck_array_ops.py | 18 +++++++++++++-----
 xarray/core/weighted.py       |  2 +-
 2 files changed, 14 insertions(+), 6 deletions(-)

diff --git a/xarray/core/duck_array_ops.py b/xarray/core/duck_array_ops.py
index 7e7333fd8ea..bbf358ff48b 100644
--- a/xarray/core/duck_array_ops.py
+++ b/xarray/core/duck_array_ops.py
@@ -16,8 +16,6 @@
 
 import numpy as np
 import pandas as pd
-from numpy import all as array_all  # noqa: F401
-from numpy import any as array_any  # noqa: F401
 from numpy import (  # noqa: F401
     isclose,
     isnat,
@@ -319,7 +317,7 @@ def allclose_or_equiv(arr1, arr2, rtol=1e-5, atol=1e-8):
     if lazy_equiv is None:
         with warnings.catch_warnings():
             warnings.filterwarnings("ignore", r"All-NaN (slice|axis) encountered")
-            return bool(isclose(arr1, arr2, rtol=rtol, atol=atol, equal_nan=True).all())
+            return bool(array_all(isclose(arr1, arr2, rtol=rtol, atol=atol, equal_nan=True)))
     else:
         return lazy_equiv
 
@@ -333,7 +331,7 @@ def array_equiv(arr1, arr2):
         with warnings.catch_warnings():
             warnings.filterwarnings("ignore", "In the future, 'NAT == x'")
             flag_array = (arr1 == arr2) | (isnull(arr1) & isnull(arr2))
-            return bool(flag_array.all())
+            return bool(array_all(flag_array))
     else:
         return lazy_equiv
 
@@ -349,7 +347,7 @@ def array_notnull_equiv(arr1, arr2):
         with warnings.catch_warnings():
             warnings.filterwarnings("ignore", "In the future, 'NAT == x'")
             flag_array = (arr1 == arr2) | isnull(arr1) | isnull(arr2)
-            return bool(flag_array.all())
+            return bool(array_all(flag_array))
     else:
         return lazy_equiv
 
@@ -536,6 +534,16 @@ def f(values, axis=None, skipna=None, **kwargs):
 cumsum_1d.numeric_only = True
 
 
+def array_all(array, axis=None, keepdims=False):
+    xp = get_array_namespace(array)
+    return xp.all(array, axis=axis, keepdims=keepdims)
+
+
+def array_any(array, axis=None, keepdims=False):
+    xp = get_array_namespace(array)
+    return xp.any(array, axis=axis, keepdims=keepdims)
+
+
 _mean = _create_nan_agg_method("mean", invariant_0d=True)
 
 
diff --git a/xarray/core/weighted.py b/xarray/core/weighted.py
index 269cb49a2c1..cd24091b18e 100644
--- a/xarray/core/weighted.py
+++ b/xarray/core/weighted.py
@@ -171,7 +171,7 @@ def __init__(self, obj: T_Xarray, weights: T_DataArray) -> None:
 
         def _weight_check(w):
             # Ref https://github.com/pydata/xarray/pull/4559/files#r515968670
-            if duck_array_ops.isnull(w).any():
+            if duck_array_ops.array_any(duck_array_ops.isnull(w)):
                 raise ValueError(
                     "`weights` cannot contain missing values. "
                     "Missing values can be replaced by `weights.fillna(0)`."