Thanks for clarifying! In that case I think endorsing SPEC 7 makes sense.
On Tue, Oct 8, 2024 at 3:08 PM Robert Kern wrote:
> On Tue, Oct 8, 2024 at 8:36 AM Nathan via NumPy-Discussion <
> numpy-discussion@python.org> wrote:
>
>>
>> Since the legacy RNG interface
Regarding thread safety - that's not a problem. At least for Python 3.13,
the GIL is temporarily re-enabled during imports. That won't necessarily be
true in the future, but separately CPython also uses per-module locks on
import, so there shouldn't be any issues with threads simultaneously
importi
Here's a github code search for the string "np.matrix":
https://github.com/search?q=%22np.matrix%22&type=code
First, if you narrow down to just Python code, there are almost 60 thousand
results, which is quite high, much higher than we we're comfortable with
for outright removals for NumPy 2.0.
Improvements to the promoters for some of the string ufuncs:
https://github.com/numpy/numpy/pull/27636
Support for stringdtype arrays in the type hints and typing support for the
string ufuncs:
https://github.com/numpy/numpy/pull/27470
If you have a particular improvement you’re looking for I’d l
Hi all,
GitHub is rolling out the new UI for issues, which includes a lot of new
opportunities to reorganize our backlog. More detail on the changelog blog:
https://github.blog/changelog/2025-01-13-evolving-github-issues-public-preview/
In particular, there is now much richer support for tracking
If a NumPy array is shared between two threads, NumPy doesn’t do anything
to synchronize array access. This is true in all Python versions and build
configurations - since NumPy releases the GIL during most array operations
whether or not you’re using free-threaded Python doesn’t change much except
I think we can just upload 2.3.1 wheels for 3.14 and 3.14t. I’m planning to
poke at the wheel-building configuration tomorrow to set that up if no one
else gets to it first. We already set up nightlies a while back so it
should be straightforward.
On Tue, Jul 22, 2025 at 5:40 PM Charles R Harris v
NumPy probably isn’t the right spot for this - we’re very conservative
about adding new functionality to NumPy that might also live in SciPy.
SciPy has convolution functionality but I’m not sure if they would want
greenfield code for this. Definitely worth asking the SciPy developers.
That said, h
If functionality is available in SciPy we usually don’t consider adding it
to NumPy. That rules out adding eig.
Is there any reason why polyeig doesn’t make sense to add to SciPy instead
of NumPy? Generally if functionality makes sense to add to SciPy that’s
where we point people to.
On Thu, Jun
On Wed, Sep 10, 2025 at 7:02 AM Ralf Gommers via NumPy-Discussion <
numpy-discussion@python.org> wrote:
>
>
> On Wed, Sep 10, 2025 at 2:06 PM Hugo van Kemenade wrote:
>
>> I believe Azure Pipelines and GitHub Actions essentially use the same
>> infra, and Azure Pipelines is also dropping macOS In
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