From 96d8f683ca99d7d4258944553f1cce7f43ec24fc Mon Sep 17 00:00:00 2001
From: mgunyho <20118130+mgunyho@users.noreply.github.com>
Date: Sat, 19 Aug 2023 14:02:40 +0300
Subject: [PATCH] Show list of dimensions in error messages of Rolling and
 Coarsen, update tests

---
 xarray/core/rolling.py       | 18 +++++++++++++-----
 xarray/tests/test_coarsen.py |  5 ++++-
 xarray/tests/test_rolling.py | 11 +++++++++++
 3 files changed, 28 insertions(+), 6 deletions(-)

diff --git a/xarray/core/rolling.py b/xarray/core/rolling.py
index 916fabe42ac..dcd01a0e0f1 100644
--- a/xarray/core/rolling.py
+++ b/xarray/core/rolling.py
@@ -102,6 +102,14 @@ def __init__(
         self.center = self._mapping_to_list(center, default=False)
         self.obj: T_Xarray = obj
 
+        missing_dims = tuple(dim for dim in self.dim if dim not in self.obj.dims)
+        if missing_dims:
+            # NOTE: we raise KeyError here but ValueError in Coarsen.
+            raise KeyError(
+                f"Window dimensions {missing_dims} not found in {self.obj.__class__.__name__} "
+                f"dimensions {tuple(self.obj.dims)}"
+            )
+
         # attributes
         if min_periods is not None and min_periods <= 0:
             raise ValueError("min_periods must be greater than zero or None")
@@ -624,8 +632,7 @@ def __init__(
         xarray.DataArray.groupby
         """
         super().__init__(obj, windows, min_periods, center)
-        if any(d not in self.obj.dims for d in self.dim):
-            raise KeyError(self.dim)
+
         # Keep each Rolling object as a dictionary
         self.rollings = {}
         for key, da in self.obj.data_vars.items():
@@ -839,10 +846,11 @@ def __init__(
         self.side = side
         self.boundary = boundary
 
-        absent_dims = [dim for dim in windows.keys() if dim not in self.obj.dims]
-        if absent_dims:
+        missing_dims = tuple(dim for dim in windows.keys() if dim not in self.obj.dims)
+        if missing_dims:
             raise ValueError(
-                f"Dimensions {absent_dims!r} not found in {self.obj.__class__.__name__}."
+                f"Window dimensions {missing_dims} not found in {self.obj.__class__.__name__} "
+                f"dimensions {tuple(self.obj.dims)}"
             )
         if not utils.is_dict_like(coord_func):
             coord_func = {d: coord_func for d in self.obj.dims}  # type: ignore[misc]
diff --git a/xarray/tests/test_coarsen.py b/xarray/tests/test_coarsen.py
index d58361afdd3..e345ae691ec 100644
--- a/xarray/tests/test_coarsen.py
+++ b/xarray/tests/test_coarsen.py
@@ -17,7 +17,10 @@
 
 
 def test_coarsen_absent_dims_error(ds: Dataset) -> None:
-    with pytest.raises(ValueError, match=r"not found in Dataset."):
+    with pytest.raises(
+        ValueError,
+        match=r"Window dimensions \('foo',\) not found in Dataset dimensions",
+    ):
         ds.coarsen(foo=2)
 
 
diff --git a/xarray/tests/test_rolling.py b/xarray/tests/test_rolling.py
index 73aebc1b1f0..0e3c0874a0a 100644
--- a/xarray/tests/test_rolling.py
+++ b/xarray/tests/test_rolling.py
@@ -77,6 +77,12 @@ def test_rolling_properties(self, da) -> None:
         with pytest.raises(ValueError, match="min_periods must be greater than zero"):
             da.rolling(time=2, min_periods=0)
 
+        with pytest.raises(
+            KeyError,
+            match=r"\('foo',\) not found in DataArray dimensions",
+        ):
+            da.rolling(foo=2)
+
     @pytest.mark.parametrize("name", ("sum", "mean", "std", "min", "max", "median"))
     @pytest.mark.parametrize("center", (True, False, None))
     @pytest.mark.parametrize("min_periods", (1, None))
@@ -540,6 +546,11 @@ def test_rolling_properties(self, ds) -> None:
             ds.rolling(time=2, min_periods=0)
         with pytest.raises(KeyError, match="time2"):
             ds.rolling(time2=2)
+        with pytest.raises(
+            KeyError,
+            match=r"\('foo',\) not found in Dataset dimensions",
+        ):
+            ds.rolling(foo=2)
 
     @pytest.mark.parametrize(
         "name", ("sum", "mean", "std", "var", "min", "max", "median")