document the duck array integration status

doc/duckarrays.rst

@@ -0,0 +1,59 @@
+.. currentmodule:: xarray
+
+Working with numpy-like arrays
+==============================
+
+.. warning::
+
+   This feature should be considered experimental. Please report any bug you may find on
+   xarray’s github repository.
+
+Numpy-like arrays (:term:`duck array`) extend the :py:class:`numpy.ndarray` with
+additional features, like propagating physical units or a different layout in memory.
+
+:py:class:`DataArray` and :py:class:`Dataset` objects can wrap these duck arrays, as
+long as they satisfy certain conditions (see :ref:`internals.duck_arrays`).
+
+.. note::
+
+    For ``dask`` support see :ref:`dask`.
+
+
+Missing features
+----------------
+Most of the API does support :term:`duck array` objects, but there are a few areas where
+the code will still cast to ``numpy`` arrays:
+
+- dimension coordinates, and thus all indexing operations:
+
+  * :py:meth:`Dataset.sel` and :py:meth:`DataArray.sel`
+  * :py:meth:`Dataset.loc` and :py:meth:`DataArray.loc`
+  * :py:meth:`Dataset.drop_sel` and :py:meth:`DataArray.drop_sel`
+  * :py:meth:`Dataset.reindex`, :py:meth:`Dataset.reindex_like`,
+    :py:meth:`DataArray.reindex` and :py:meth:`DataArray.reindex_like`: duck arrays in
+    data variables and non-dimension coordinates won't be casted
+
+- functions and methods that depend on external libraries or features of ``numpy`` not
+  covered by ``__array_function__`` / ``__array_ufunc__``:
+
+  * :py:meth:`Dataset.ffill` and :py:meth:`DataArray.ffill` (uses ``bottleneck``)
+  * :py:meth:`Dataset.bfill` and :py:meth:`DataArray.bfill` (uses ``bottleneck``)
+  * :py:meth:`Dataset.interp`, :py:meth:`Dataset.interp_like`,
+    :py:meth:`DataArray.interp` and :py:meth:`DataArray.interp_like` (uses ``scipy``):
+    duck arrays in data variables and non-dimension coordinates will be casted in
+    addition to not supporting duck arrays in dimension coordinates
+  * :py:meth:`Dataset.rolling_exp` and :py:meth:`DataArray.rolling_exp` (uses
+    ``numbagg``)
+  * :py:meth:`Dataset.rolling` and :py:meth:`DataArray.rolling` (uses internal functions
+    of ``numpy``)
+  * :py:meth:`Dataset.interpolate_na` and :py:meth:`DataArray.interpolate_na` (uses
+    :py:class:`numpy.vectorize`)
+  * :py:func:`apply_ufunc` with ``vectorize=True`` (uses :py:class:`numpy.vectorize`)
+
+
+Extensions using duck arrays
+----------------------------
+Here's a list of libraries extending ``xarray`` to make working with wrapped duck arrays
+easier:
+
+- `pint-xarray <https://github.com/xarray-contrib/pint-xarray>`_

doc/index.rst

@@ -60,6 +60,7 @@ Documentation
 * :doc:`io`
 * :doc:`dask`
 * :doc:`plotting`
+* :doc:`duckarrays`
 
 .. toctree::
    :maxdepth: 1
@@ -80,6 +81,7 @@ Documentation
    io
    dask
    plotting
+   duckarrays
 
 **Help & reference**
 

doc/internals.rst

@@ -42,21 +42,24 @@ xarray objects via the (readonly) :py:attr:`Dataset.variables
 <xarray.Dataset.variables>` and
 :py:attr:`DataArray.variable <xarray.DataArray.variable>` attributes.
 
-Duck arrays
------------
+
+.. _internals.duck_arrays:
+
+Integrating with duck arrays
+----------------------------
 
 .. warning::
 
     This is a experimental feature.
 
-xarray can wrap custom `duck array`_ objects as long as they define numpy's
+xarray can wrap custom :term:`duck array` objects as long as they define numpy's
 ``shape``, ``dtype`` and ``ndim`` properties and the ``__array__``,
 ``__array_ufunc__`` and ``__array_function__`` methods.
 
 In certain situations (e.g. when printing the collapsed preview of
-variables of a ``Dataset``), xarray will display the repr of a `duck array`_
+variables of a ``Dataset``), xarray will display the repr of a :term:`duck array`
 in a single line, truncating it to a certain number of characters. If that
-would drop too much information, the `duck array`_ may define a
+would drop too much information, the :term:`duck array` may define a
 ``_repr_inline_`` method that takes ``max_width`` (number of characters) as an
 argument:
 
@@ -71,8 +74,6 @@ argument:
 
         ...
 
-.. _duck array: https://numpy.org/neps/nep-0022-ndarray-duck-typing-overview.html
-
 
 Extending xarray
 ----------------

doc/terminology.rst

@@ -104,3 +104,11 @@ complete examples, please consult the relevant documentation.*
         one, it has 0 dimensions. That means that, e.g., :py:class:`int`,
         :py:class:`float`, and :py:class:`str` objects are "scalar" while
         :py:class:`list` or :py:class:`tuple` are not.
+
+    duck array
+        `Duck arrays <duck array>`_ are array implementations that behave
+        like numpy arrays. They have to define the ``shape``, ``dtype`` and
+        ``ndim`` properties. For integration with ``xarray``, the ``__array__``,
+        ``__array_ufunc__`` and ``__array_function__`` protocols are also required.
+
+        .. _duck array: https://numpy.org/neps/nep-0022-ndarray-duck-typing-overview.html

doc/whats-new.rst

@@ -61,7 +61,8 @@ Bug fixes
 
 Documentation
 ~~~~~~~~~~~~~
-
+- document the API not supported with duck arrays (:pull:`4530`).
+  By `Justus Magin <https://github.com/keewis>`_.
 - Raise a more informative error when :py:meth:`DataArray.to_dataframe` is
   is called on a scalar (:issue:`4228`). By `Pieter Gijsbers <https://github.com/pgijsbers>`_.