For some context on why this matters, if you're writing a library (like sklearn) and you want to support multiple array types, you might need to do stuff like

For some context on why this matters, if you're writing a library (like sklearn) and you want to support multiple array types, you might need to do stuff like if isinstance(x, ndarray): ... elif isinstance(x, other_array): ... In the most ideal case having the standard means that scientific libraries can support all conforming implementations by default. Then sklearn would automatically support cupy/numpy/dask/jax/mxnet/pytorch/tensorflow arrays. Multiply that by all the scientific libraries and the effect is pretty profound.