I think np.never_copy is really ugly. I’d much rather simply use ‘never’,
I actually think np.never_copy is the better choice of the two. Arguments for it: - It’s consistent with np.newaxis in spelling (modulo the _) - If mistyped, it can be caught easily by IDEs. - It’s typeable with mypy, unlike constant string literals which currently aren’t - If code written against new numpy is run on old numpy, it will error rather than doing the wrong thing - It won’t be possible to miss parts of our existing API that evaluate a copy argument in a boolean context - It won’t be possible for downstream projects to misinterpret by not checking for ‘never’ - an error will be raised instead. Arguments against it: - It’s more characters than "never" - The implementation of np.never_copy is a little verbose / ugly Eric On Thu, Dec 27, 2018, 1:41 AM Ralf Gommers <ralf.gomm...@gmail.com wrote: > > On Wed, Dec 26, 2018 at 3:29 PM Sebastian Berg <sebast...@sipsolutions.net> > wrote: > >> Hi all, >> >> In https://github.com/numpy/numpy/pull/11897 I am looking into the >> addition of a `copy=np.never_copy` argument to: >> * np.array >> * arr.reshape/np.reshape >> * arr.astype >> >> Which would cause an error to be raised when numpy cannot guarantee >> that the returned array is a view of the input array. >> The motivation is to easier avoid accidental copies of large data, or >> ensure that in-place manipulation will be meaningful. >> >> The copy flag API would be: >> * `copy=True` forces a copy >> * `copy=False` allows numpy to copy if necessary >> * `copy=np.never_copy` will error if a copy would be necessary >> * (almost) all other input will be deprecated. >> >> Unfortunately using `copy="never"` is tricky, because currently >> `np.array(..., copy="never")` behaves exactly the same as >> `np.array(..., copy=bool("never"))`. So that the wrong result would be >> given on old numpy versions and it would be a behaviour change. >> > > I think np.never_copy is really ugly. I'd much rather simply use 'never', > and clearly document that if users start using this and they critically > rely on it really being never, then they should ensure that their code is > only used with numpy >= 1.17.0. > > Note also that this would not be a backwards compatibility break, because > `copy` is now clearly documented as bool, and not bool_like or some such > thing. So we do not need to worry about the very improbable case that users > now are using `copy='never'`. > > If others think `copy='never'` isn't acceptable now, there are two other > options: > 1. add code first to catch `copy='never'` in 1.17.x and raise on it, then > in a later numpy version introduce it. > 2. just do nothing. I'd prefer that over `np.never_copy`. > > Cheers, > Ralf > > >> Some things that are a not so nice maybe: >> * adding/using `np.never_copy` is not very nice >> * Scalars need a copy and so will not be allowed >> * For rare array-likes numpy may not be able to guarantee no-copy, >> although it could happen (but should not). >> >> >> The history is that a long while ago I considered adding a copy flag to >> `reshape` so that it is possible to do `copy=np.never_copy` (or >> similar) to ensure that no copy is made. In these, you may want >> something like an assertion: >> >> ``` >> new_arr = arr.reshape(new_shape) >> assert np.may_share_memory(arr, new_arr) >> >> # Which is sometimes -- but should not be -- written as: >> arr.shape = new_shape # unnecessary container modification >> >> # Or: >> view = np.array(arr, order="F") >> assert np.may_share_memory(arr, new_arr) >> ``` >> >> but is more readable and will not cause an intermediate copy on error. >> >> >> So what do you think? Other variants would be to not expose this for >> `np.array` and probably limit `copy="never"` to the reshape method. Or >> just to not do it at all. Or to also accept "never" for `reshape`, >> although I think I would prefer to keep it in sync and wait for a few >> years to consider that. >> >> Best, >> >> Sebastian >> >> _______________________________________________ >> 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 >
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