On 9/8/22, Andrew Nelson <andyf...@gmail.com> wrote:
> On Thu, 8 Sept 2022, 19:42 Sebastian Berg, <sebast...@sipsolutions.net>
> wrote:
>
>>
>> TL;DR:  NumPy scalars representation is e.g. `34.3` instead of
>> `float32(34.3)`.  So the representation is missing the type
>> information.  What are your thoughts on changing that?


I like the idea, but as others have noted, this could result in a lot
of churn in the docs of many projects.


>
>
>> From the Python documentation on repr:
>
>
> From the Python documentation on repr:
>
> "this should look like a valid Python expression that could be used to
> recreate an object with the same value"


To quote from https://docs.python.org/3/library/functions.html#repr:

> For many types, this function makes an attempt to return a string
> that would yield an object with the same value when passed to eval();

Sebastian, is this an explicit goal of the change?  (Personally, I've
gotten used to not taking this too seriously, but my world view is
biased by the long-term use of NumPy, which has never followed this
guideline.)

If that is a goal, than the floating point types with precision
greater than double precision will need to display the argument of the
type as a string.  For example, the following is run on a platform
where numpy.longdouble is extended precision (80 bits):

```
In [161]: longpi = np.longdouble('3.14159265358979323846')

In [162]: longpi
Out[162]: 3.1415926535897932385

In [163]: np.longdouble(3.1415926535897932385)  # Argument is parsed
as 64 bit float
Out[163]: 3.141592653589793116

In [164]: np.longdouble('3.1415926535897932385')  # Correctly
reproduces the longdouble
Out[164]: 3.1415926535897932385
```

Warren

>
> I think it definitely we should definitely have:
>
> repr(np.float32(34.3)) == 'float32(34.3)'
> And
> str(np.float32(34.3)) == '34.3'
>
> It seems buglike not to have that.
>
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