[Numpy-discussion] proposed changes to array printing in 1.14
Allan Haldane
allanhaldane at gmail.com
Fri Jun 30 11:11:47 EDT 2017
On 06/30/2017 03:55 AM, Juan Nunez-Iglesias wrote:
> To reiterate my point on a previous thread, I don't think this should
> happen until NumPy 2.0. This *will* break a massive number of doctests,
> and what's worse, it will do so in a way that makes it difficult to
> support doctesting for both 1.13 and 1.14. I don't see a big enough
> benefit to these changes to justify breaking everyone's tests before an
> API-breaking version bump.
I am still on the fence about exactly how annoying this change would be,
and it is is good to hear whether this affects you and how badly.
Yes, someone would have to spend an hour removing a hundred spaces in
doctests, and the 1.13 to 1.14 period is trickier (but virtualenv
helps). But none of your end users are going to have their scripts
break, there are no new warnings or exceptions.
A followup questions is, to what degree can we compromise? Would it be
acceptable to skip the big change #1, but keep the other 3 changes? I
expect they affect far fewer doctests. Or, for instance, I could scale
back #1 so it only affects size-1 (or perhaps, only size-0) arrays. What
amount of change would be OK, and how is changing a small number of
doctests different from changing more?
Also, let me clarify the motivations for the changes. As Marten noted,
change #2 is what motivated all the other changes. Currently 0d arrays
print in their own special way which was making it very hard to
implement fixes to voidtype str/repr, and the datetime and other 0d
reprs are weird. The fix is to make 0d arrays print using the same
code-path as higher-d ndarrays, but then we ended up with reprs like
"array( 1.)" because of the space for the sign position. So I removed
the space from the sign position for all float arrays. But as I noted I
probably could remove it for only size-1 or 0d arrays and still fix my
problem, even though I think it might be pretty hacky to implement in
the numpy code.
Allan
>
> On 30 Jun 2017, 6:42 AM +1000, Marten van Kerkwijk
> <m.h.vankerkwijk at gmail.com>, wrote:
>> To add to Allan's message: point (2), the printing of 0-d arrays, is
>> the one that is the most important in the sense that it rectifies a
>> really strange situation, where the printing cannot be logically
>> controlled by the same mechanism that controls >=1-d arrays (see PR).
>>
>> While point 3 can also be considered a bug fix, 1 & 4 are at some
>> level matters of taste; my own reason for supporting their
>> implementation now is that the 0-d arrays already forces me (or,
>> specifically, astropy) to rewrite quite a few doctests, and I'd rather
>> have everything in one go -- in this respect, it is a pity that this
>> is separate from the earlier change in printing for structured arrays
>> (which was also much for the better, but broke a lot of doctests).
>>
>> -- Marten
>>
>>
>>
>> On Thu, Jun 29, 2017 at 3:38 PM, Allan Haldane
>> <allanhaldane at gmail.com> wrote:
>>> Hello all,
>>>
>>> There are various updates to array printing in preparation for numpy
>>> 1.14. See https://github.com/numpy/numpy/pull/9139/
>>>
>>> Some are quite likely to break other projects' doc-tests which expect a
>>> particular str or repr of arrays, so I'd like to warn the list in case
>>> anyone has opinions.
>>>
>>> The current proposed changes, from most to least painful by my
>>> reckoning, are:
>>>
>>> 1.
>>> For float arrays, an extra space previously used for the sign position
>>> will now be omitted in many cases. Eg, `repr(arange(4.))` will now
>>> return 'array([0., 1., 2., 3.])' instead of 'array([ 0., 1., 2., 3.])'.
>>>
>>> 2.
>>> The printing of 0d arrays is overhauled. This is a bit finicky to
>>> describe, please see the release note in the PR. As an example of the
>>> effect of this, the `repr(np.array(0.))` now prints as 'array(0.)`
>>> instead of 'array(0.0)'. Also the repr of 0d datetime arrays is now like
>>> "array('2005-04-04', dtype='datetime64[D]')" instead of
>>> "array(datetime.date(2005, 4, 4), dtype='datetime64[D]')".
>>>
>>> 3.
>>> User-defined dtypes which did not properly implement their `repr` (and
>>> `str`) should do so now. Otherwise it now falls back to
>>> `object.__repr__`, which will return something ugly like
>>> `<mytype object at 0x7f37f1b4e918>`. (Previously you could depend on
>>> only implementing the `item` method and the repr of that would be
>>> printed. But no longer, because this risks infinite recursions.).
>>>
>>> 4.
>>> Bool arrays of size 1 with a 'True' value will now omit a space, so that
>>> `repr(array([True]))` is now 'array([True])' instead of
>>> 'array([ True])'.
>>>
>>> Allan
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