Hi Kai,
I am not using numpy financial, but from what I know:
Given numpy 2.0 has a support for MPFD types I think it is very reasonable to
drop Decimal support and remove unnecessary complexity.
Regards,
dgpb
> On 30 Mar 2024, at 02:20, kaistri...@gmail.com wrote:
>
> Hi all,
>
> I'm
Hi all,
I'm currently working NumPy-Financial (npf) and would like to ask for comments
on dropping decimal.Decimal support in npf. I'm proposing to drop Decimal
support for npf. There are a few reasons for this:
1. No one appears to use decimal types. Since it's release in 2019, not a
single
On Fri, Mar 29, 2024 at 2:07 PM Peter Hawkins
wrote:
> It looks like the pybind11 release is now done (
> https://github.com/pybind/pybind11/releases/tag/v2.12.0)? Any more
> blockers?
>
No more blockers - CI is running on the last backport that we need I
believe, so it's very close. Hours to
On Fri, Mar 29, 2024 at 8:39 AM Jim Pivarski wrote:
> On Fri, Mar 29, 2024 at 8:07 AM Steven G. Johnson wrote:
>
>> Should a dtype=object array be treated more like Python lists for type
>> detection/coercion reasons? Currently, they are treated quite differently:
>> >>> np.isfinite([1,2,3])
On Fri, Mar 29, 2024 at 9:11 AM Steven G. Johnson wrote:
> Should a dtype=object array be treated more like Python lists for type
> detection/coercion reasons? Currently, they are treated quite differently:
>
> >>> import numpy as np
> >>> np.isfinite([1,2,3])
> array([ True, True, True])
>
On Fri, Mar 29, 2024 at 8:07 AM Steven G. Johnson wrote:
> Should a dtype=object array be treated more like Python lists for type
> detection/coercion reasons? Currently, they are treated quite differently:
> >>> np.isfinite([1,2,3])
> array([ True, True, True])
>
In this case, the `[1, 2,
Should a dtype=object array be treated more like Python lists for type
detection/coercion reasons? Currently, they are treated quite differently:
>>> import numpy as np
>>> np.isfinite([1,2,3])
array([ True, True, True])
>>> np.isfinite(np.asarray([1,2,3], dtype=object))
Traceback (most
It looks like the pybind11 release is now done
(https://github.com/pybind/pybind11/releases/tag/v2.12.0)? Any more blockers?
(We're eagerly awaiting -rc1 so we can release new wheels for our project...)
___
NumPy-Discussion mailing list --
