From ac9bce13fd73b61580ed51dbfa779ac8a00636c0 Mon Sep 17 00:00:00 2001
From: Deepak Cherian <deepak@cherian.net>
Date: Wed, 12 Jun 2024 15:35:50 -0600
Subject: [PATCH] Updates

---
 doc/user-guide/dask.rst      | 5 +++++
 xarray/core/dataarray.py     | 6 ++++--
 xarray/core/dataset.py       | 7 +++++--
 xarray/tests/test_dataset.py | 3 +++
 4 files changed, 17 insertions(+), 4 deletions(-)

diff --git a/doc/user-guide/dask.rst b/doc/user-guide/dask.rst
index 27e7449b7c3..e56fc49036e 100644
--- a/doc/user-guide/dask.rst
+++ b/doc/user-guide/dask.rst
@@ -296,6 +296,11 @@ loaded into Dask or not:
 Automatic parallelization with ``apply_ufunc`` and ``map_blocks``
 -----------------------------------------------------------------
 
+.. tip::
+
+   Some problems can become embarassingly parallel and thus easy to parallelize automatically
+   by rechunk to a frequency: e.g. ``ds.chunk(time="YE")``. See :py:meth:`Dataset.chunk` for more.
+
 Almost all of xarray's built-in operations work on Dask arrays. If you want to
 use a function that isn't wrapped by xarray, and have it applied in parallel on
 each block of your xarray object, you have three options:
diff --git a/xarray/core/dataarray.py b/xarray/core/dataarray.py
index 4dc897c1878..431ead33246 100644
--- a/xarray/core/dataarray.py
+++ b/xarray/core/dataarray.py
@@ -1356,11 +1356,13 @@ def chunk(
         sizes along that dimension will not be updated; non-dask arrays will be
         converted into dask arrays with a single block.
 
+        Along datetime-like dimensions, a pandas frequency string is also accepted.
+
         Parameters
         ----------
-        chunks : int, "auto", tuple of int or mapping of Hashable to int, optional
+        chunks : int, "auto", tuple of int or mapping of hashable to int or a pandas frequency string, optional
             Chunk sizes along each dimension, e.g., ``5``, ``"auto"``, ``(5, 5)`` or
-            ``{"x": 5, "y": 5}``.
+            ``{"x": 5, "y": 5}`` or ``{"x": 5, "time": "YE"}``.
         name_prefix : str, optional
             Prefix for the name of the new dask array.
         token : str, optional
diff --git a/xarray/core/dataset.py b/xarray/core/dataset.py
index 469ea8f9d5c..282ca671129 100644
--- a/xarray/core/dataset.py
+++ b/xarray/core/dataset.py
@@ -159,6 +159,7 @@
         QueryParserOptions,
         ReindexMethodOptions,
         SideOptions,
+        T_NormalizedChunks,
         T_Xarray,
     )
     from xarray.core.weighted import DatasetWeighted
@@ -2755,9 +2756,11 @@ def _resolve_frequency(name: Hashable, freq: str) -> tuple[int]:
             )
             return chunks
 
-        chunks_mapping_ints = {
+        chunks_mapping_ints: T_NormalizedChunks = {
             name: (
-                _resolve_frequency(name, chunks) if isinstance(chunks, str) else chunks
+                _resolve_frequency(name, chunks)
+                if isinstance(chunks, str) and chunks != "auto"
+                else chunks
             )
             for name, chunks in chunks_mapping.items()
         }
diff --git a/xarray/tests/test_dataset.py b/xarray/tests/test_dataset.py
index eb15d82d5ab..2279118b202 100644
--- a/xarray/tests/test_dataset.py
+++ b/xarray/tests/test_dataset.py
@@ -1229,6 +1229,9 @@ def test_chunk_by_frequecy_errors(self):
         ds["x"] = ("x", [1, 2, 3])
         with pytest.raises(ValueError, match="datetime variables"):
             ds.chunk(x="YE")
+        ds["x"] = ("x", xr.date_range("2001-01-01", periods=3, freq="D"))
+        with pytest.raises(ValueError, match="Invalid frequency"):
+            ds.chunk(x="foo")
 
     @requires_dask
     def test_dask_is_lazy(self) -> None: