rok commented on code in PR #34957:
URL: https://github.com/apache/arrow/pull/34957#discussion_r1163012303
##########
docs/source/python/extending_types.rst:
##########
@@ -357,3 +357,116 @@ pandas ``ExtensionArray``. This method should have the
following signature::
This way, you can control the conversion of a pyarrow ``Array`` of your pyarrow
extension type to a pandas ``ExtensionArray`` that can be stored in a
DataFrame.
+
+
+Canonical extension types
+~~~~~~~~~~~~~~~~~~~~~~~~~
+
+In the :ref:`format_canonical_extensions` under the section **Official List**
+there is a list of canonical extension types. Here you can find an example of
how
+to implement and how to use the listed canonical extension types.
Review Comment:
Implement seems too strong here? :D
```suggestion
there is a list of canonical extension types. Here we list examples of how to
use the listed canonical extension types.
```
##########
docs/source/python/extending_types.rst:
##########
@@ -357,3 +357,116 @@ pandas ``ExtensionArray``. This method should have the
following signature::
This way, you can control the conversion of a pyarrow ``Array`` of your pyarrow
extension type to a pandas ``ExtensionArray`` that can be stored in a
DataFrame.
+
+
+Canonical extension types
+~~~~~~~~~~~~~~~~~~~~~~~~~
+
+In the :ref:`format_canonical_extensions` under the section **Official List**
+there is a list of canonical extension types. Here you can find an example of
how
+to implement and how to use the listed canonical extension types.
+
+Fixed size tensor
+"""""""""""""""""
+
+Define fixed shape tensor extension type:
+
+.. code-block:: python
+
+ >>> tensor_type = pa.fixed_shape_tensor(pa.int32(), (2, 2))
+
+Create an array of tensors with storage array and defined fixed shape tensor
+extension type:
+
+.. code-block:: python
+
+ >>> arr = [[1, 2, 3, 4], [10, 20, 30, 40], [100, 200, 300, 400]]
+ >>> storage = pa.array(arr, pa.list_(pa.int32(), 4))
+ >>> tensor = pa.ExtensionArray.from_storage(tensor_type, storage)
Review Comment:
Maybe call these `tensor_array` to not confuse them with actual `Tensor`
objects?
```suggestion
>>> arr = [[1, 2, 3, 4], [10, 20, 30, 40], [100, 200, 300, 400]]
>>> storage = pa.array(arr, pa.list_(pa.int32(), 4))
>>> tensor_array = pa.ExtensionArray.from_storage(tensor_type, storage)
```
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