Re: [Numpy-discussion] NEP: array API standard adoption (NEP 47)

2021-03-15 Thread Ralf Gommers
On Thu, Mar 11, 2021 at 6:08 PM Sebastian Berg wrote: > On Thu, 2021-03-11 at 12:37 +0100, Ralf Gommers wrote: > > On Wed, Mar 10, 2021 at 6:41 PM Sebastian Berg < > > sebast...@sipsolutions.net> > > wrote: > > > > > Top Posting, to discuss post specific questions about NEP 47 and > > > partially

Re: [Numpy-discussion] Perf regression with Pythran between Numpy 0.19.5 and 0.20 (commit 4cd6e4b336fbc68d88c0e9bc45a435ce7b721f1f, ENH: implement NEP-35's `like=` argument)

2021-03-15 Thread Sebastian Berg
On Mon, 2021-03-15 at 14:59 +0100, Peter Andreas Entschev wrote: > Hi Pierre, > > Thanks for pinging me. To put it in the simplest way possible, that > PR > adds a new `like` kwarg that will dispatch to downstream libraries > using `__array_function__` when specified, otherwise fallback to the > d

Re: [Numpy-discussion] Perf regression with Pythran between Numpy 0.19.5 and 0.20 (commit 4cd6e4b336fbc68d88c0e9bc45a435ce7b721f1f, ENH: implement NEP-35's `like=` argument)

2021-03-15 Thread Peter Andreas Entschev
Hi Pierre, Thanks for pinging me. To put it in the simplest way possible, that PR adds a new `like` kwarg that will dispatch to downstream libraries using `__array_function__` when specified, otherwise fallback to the default behavior of NumPy. While that introduces an extra check on the C side, t

Re: [Numpy-discussion] Perf regression with Pythran between Numpy 0.19.5 and 0.20 (commit 4cd6e4b336fbc68d88c0e9bc45a435ce7b721f1f, ENH: implement NEP-35's `like=` argument)

2021-03-15 Thread PIERRE AUGIER
- Mail original - > De: "Juan Nunez-Iglesias" > À: "numpy-discussion" > Envoyé: Dimanche 14 Mars 2021 07:15:39 > Objet: Re: [Numpy-discussion] Looking for a difference between Numpy 0.19.5 > and 0.20 explaining a perf regression with > Pythran > Hi Pierre, > > If you’re able to compil

Re: [Numpy-discussion] Numpy 1.20.1 availability

2021-03-15 Thread Jerome Kieffer
On Sun, 14 Mar 2021 10:14:13 + Peter Cock wrote: > I'm impressed to see 17 million conda-forge numpy downloads, vs > 'just' 2.5 million downloads of the default channel's package: I doubt the download figures from conda are correct ... A couple of days after my software package has entered