Hi All, For 1.17, there has been a big effort, especially by Stephan, to make __array_function__ sufficiently usable that it can be exposed. I think this is great, and still like the idea very much, but its impact on the numpy code base has gotten so big in the most recent PR (gh-13585) that I wonder if we shouldn't reconsider the approach, and at least for 1.17 stick with the status quo. Since that seems to be a bigger question than can be usefully addressed in the PR, I thought I would raise it here.
Specifically, now not only does every numpy function have its dispatcher function, but also internally all numpy function calls are being done via the new `__skip_array_function__` attribute, to avoid further overrides. I think both changes make the code significantly less readable, thus, e.g., making it even harder than it is already to attract new contributors. I think with this it is probably time to step back and check whether the implementation is in fact the right one. For instance, among the alternatives we originally considered was one that had the overridable versions of functions in the regular `numpy` namespace, and the once that would not themselves check in a different one. Alternatively, for some of the benefits provided by `__skip_array_function__`, there was a different suggestion to have a special return value, of `NotImplementedButCoercible`. Might these be better after all? More generally, I think we're suffering from the fact that several of us seem to have rather different final goals in mind In particular, I'd like to move to a state where as much of the code as possible makes use of the simplest possible implementation, with only a few true base functions, so that all but those simplest functions will generally work on any type of array. Others, however, worry much more about making implementations (even more) part of the API. All the best, Marten
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