On 4/6/20, Ralf Gommers <ralf.gomm...@gmail.com> wrote: > On Mon, Apr 6, 2020 at 3:31 PM Eric Wieser <wieser.eric+nu...@gmail.com> > wrote: > >> When I added this function, it was always my intent for it to be consumed >> by downstream packages, but as Sebastian remarks, it wasn't really >> desirable to put it in the top-level namespace. >> > > This is a nice function indeed, +1 for making it public. > > Regarding namespace, it would be nice to decouple the `numpy` and > `numpy.lib` namespaces, so we can put this in `numpy.lib` and say that's > where library author functions go from now on. That'd be better than making > all `numpy.lib.*` submodules public. > > Cheers, > Ralf >
Thanks all. So far, it looks like folks are in favor of ensuring that `normalize_axis_index` is public. So I'll remove the implementation from the scipy PR, and use the one in numpy. For the current and older releases of numpy, scipy can import the function `numpy.core.multiarray`. If a newer version of numpy is found, scipy can grab it from wherever it is decided its public home should be. Can we also make `normalize_axis_tuple` public? Currently it resides in `numpy.core.numeric`. Warren > > >> >> I think I would be reasonably happy to make the guarantee that it would >> not be removed (or more likely, moved) without a lengthy deprecation >> cycle. >> >> Perhaps worth opening a github issue, so we can keep track of how many >> downstream projects are already using it. >> >> Eric >> >> On Sun, 5 Apr 2020 at 15:06, Sebastian Berg <sebast...@sipsolutions.net> >> wrote: >> >>> On Sun, 2020-04-05 at 00:43 -0400, Warren Weckesser wrote: >>> > On 4/4/20, Warren Weckesser <warren.weckes...@gmail.com> wrote: >>> > > It would be handy if in scipy we can use the function >>> > > `numpy.lib.shape_base.normalize_axis_index` as a consistent method >>> > > for >>> > > validating an `axis` argument. Is this function considered part of >>> > > the public API? >>> > > >>> > > There are modules in numpy that do not have leading underscores but >>> > > are still usually considered private. I'm not sure if >>> > > `numpy.lib.shape_base` is one of those. `normalize_axis_index` is >>> > > not >>> > > in the top-level `numpy` namespace, and it is not included in the >>> > > API >>> > > reference >>> > > ( >>> > > >>> https://numpy.org/devdocs/search.html?q=normalize_axis_index&check_keywords=yes&area=default >>> > > ), >>> > > so I'm not sure if we can safely consider this function to be >>> > > public. >>> > > >>> >>> I do not see a reason why we should not make those functions public. >>> The only thing I see is that they are maybe not really required in the >>> main namespace, i.e. you can be expected to use:: >>> >>> from numpy.something import normalize_axis_tuple >>> >>> I think, since this is a function for library authors more than end- >>> users. And we do not have much prior art around where to put something >>> like that. >>> >>> Cheers, >>> >>> Sebastian >>> >>> >>> >>> > > Warren >>> > > >>> > >>> > Answering my own question: >>> > >>> > "shape_base.py" is not where `normalize_axis_index` is originally >>> > defined, so that module can be ignored. >>> > >>> > The function is actually defined in `numpy.core.multiarray`. The >>> > pull >>> > request in which the function was created is >>> > https://github.com/numpy/numpy/pull/8584. Whether or not the function >>> > was to be public is discussed starting here: >>> > https://github.com/numpy/numpy/pull/8584#issuecomment-281179399. A >>> > leading underscore was discussed and intentionally not added to the >>> > function. On the other hand, it was not added to the top-level >>> > namespace, and Eric Wieser wrote "Right now, it is only accessible >>> > via >>> > np.core.multiarray.normalize_axis_index, so yes, an internal >>> > function". >>> > >>> > There is another potentially useful function, `normalize_axis_tuple`, >>> > defined in `numpy.core.numeric`. This function is also not in the >>> > top-level numpy namespace. >>> > >>> > So it looks like neither of these functions is currently intended to >>> > be public. For the moment, I think we'll create our own utility >>> > functions in scipy. We can switch to using the numpy functions if >>> > those functions are ever intentionally made public. >>> > >>> > Warren >>> > _______________________________________________ >>> > NumPy-Discussion mailing list >>> > NumPy-Discussion@python.org >>> > https://mail.python.org/mailman/listinfo/numpy-discussion >>> > >>> >>> _______________________________________________ >>> NumPy-Discussion mailing list >>> NumPy-Discussion@python.org >>> https://mail.python.org/mailman/listinfo/numpy-discussion >>> >> _______________________________________________ >> NumPy-Discussion mailing list >> NumPy-Discussion@python.org >> https://mail.python.org/mailman/listinfo/numpy-discussion >> > _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
