[Numpy-discussion] Re: Policy on AI-generated code

2024-07-04 Thread Stefan Krah
ating the obvious, but BSD code also requires attribution either in the code itself or in the docs. I'm told that Bing Copilot often displays links to the origin of the generated code like Stackoverflow. So some tools do "know" where the code came from and recognize the general c

[Numpy-discussion] Re: Policy on AI-generated code

2024-07-04 Thread Stefan Krah
egulations on the uploader, no matter where the uploader was from. I was told in no uncertain terms that this policy was just and that it would protect the PSF (protection of uploaders was not a concern). Stefan Krah ___ NumPy-Discussion mailin

Re: [Numpy-discussion] A little about XND

2018-06-18 Thread Stefan Krah
ot; as the inner dimensions. Sorry for the long mail, I hope this clears up a bit what function signatures generally look like. Stefan Krah ___ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion

Re: [Numpy-discussion] A little about XND

2018-06-18 Thread Stefan Krah
nt64". > I realize that this is no longer about describing precisely what the > function doing the calculation expects, but rather what an upper level is > allowed to do before calling the function (i.e., take a dimension of 1 and > broadcast it). Yes, for datashape the proble

[Numpy-discussion] Re: Better compatibility of the Python scientific/data stack with fast Python interpreters

2025-04-29 Thread Stefan Krah
sonable. The only garbage collected language that achieves the _same_ extension speed that I know of is OCaml (which is quite an achievement). SBCL Lisp, which has a great compiler for pure Lisp, also does not have really fast extensions. Does the Graal VM solve this iss

[Numpy-discussion] Re: Better compatibility of the Python scientific/data stack with fast Python interpreters

2025-05-07 Thread Stefan Krah
n CPython C-API. All of that under the assumption that there are many API calls. Stefan Krah > Is there a proper reproducible benchmark? Here are the benchmarks for _decimal: bench.py import time import platform if p

[Numpy-discussion] Re: Better compatibility of the Python scientific/data stack with fast Python interpreters

2025-05-07 Thread Stefan Krah
ersion 3.9, _decimal has been slowed down significantly since I left.) _decimal of course operates on scalars and has many API calls, so maybe for NumPy this is not relevant except for small arrays. Or perhaps HPy has evolved in the meantime (the above GitHub thread i

[Numpy-discussion] Re: Better compatibility of the Python scientific/data stack with fast Python interpreters

2025-05-18 Thread Stefan Krah
= y print(y) # In case optimizing compilers have gotten smart and eliminate the loop. === Stefan Krah ___ NumPy-Discussion mailing list -- numpy-discussion@python.org To unsubscribe send an e