[Numpy-discussion] Revised NEP-18, array_function protocol (original) (raw)

Marten van Kerkwijk m.h.vankerkwijk at gmail.com
Sat Jun 30 12:52:19 EDT 2018

Hi Hameer,

I think the override on dtype would work - after all, the override is checked before anything is done, so one can just pass in self if one wishes (or some helper class that contains both self and any desired further information.

But, as you note, it would not cover everything, and your array_reference idea definitely makes things more uniform. Indeed, it would allow one to implement things like np.zeros_like using np.zero, which seems quite nice.

Still, I'm not sure whether this should be included in the present NEP or is best done separately after, with a few concrete examples of where it would be useful.

All the best,

Marten

On Sat, Jun 30, 2018 at 10:40 AM, Hameer Abbasi <einstein.edison at gmail.com> wrote:

Hi Marten,

Sorry, I had clearly misunderstood. It would indeed be nice for overrides to work on functions like zeros or arange as well, but it seems strange to change the signature just for that. As a possible alternative, should we perhaps generally check for overrides on dtype?

While this very clearly makes sense for something like astropy, it has a few drawbacks: - Other duck arrays such as Dask need more information than just the dtype. For example, Dask needs chunk sizes, XArray needs axis labels, and pydata/sparse needs to know the type of the reference array in order to make one of the same type. The information in a reference array is a strict superset of information in the dtype. - There’s a need for a separate protocol, which might be a lot harder to work with for both NumPy and library authors. - Some things, like numpy.random.RandomState, don’t accept a dtype argument. As for your concern about changing the signature, it’s easy enough with a decorator. We’ll need a separate decorator for array generation functions. Something like: def arraygenerationfunction(func): @functools.wraps(func) def wrapped(*args, **kwargs, arrayreference=np.NoValue): if arrayreference is not np.NoValue: success, result = tryarrayfunctionoverride(wrapped, [arrayreference], args, kwargs) if success: return result return func(*args, **kwargs) return wrapped Hameer Abbasi

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