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Diffstat (limited to 'doc/source/reference/arrays.classes.rst')
| -rw-r--r-- | doc/source/reference/arrays.classes.rst | 8 |
1 files changed, 6 insertions, 2 deletions
diff --git a/doc/source/reference/arrays.classes.rst b/doc/source/reference/arrays.classes.rst index b3f24439f..76d77a6a5 100644 --- a/doc/source/reference/arrays.classes.rst +++ b/doc/source/reference/arrays.classes.rst @@ -8,8 +8,12 @@ Standard array subclasses The :class:`ndarray` in NumPy is a "new-style" Python built-in-type. Therefore, it can be inherited from (in Python or in C) -if desired. Therefore, it can form a foundation for many useful -classes. Often whether to sub-class the array object or to simply use +if desired. If your goal is to create an array with *modified* behavior, +as do dask arrays for distributed computation and cupy arrays for GPU-based +computation, subclassing is discouraged. Instead, using numpy's +:ref:`dispatch mechanism <dispatch_mechanism>`_ is recommended. + +Often whether to sub-class the array object or to simply use the core array component as an internal part of a new class is a difficult decision, and can be simply a matter of choice. NumPy has several tools for simplifying how your new object interacts with other |