Talk:NumPy

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Would some knowledgeable person please explain in the article the version of Python for which NumPy works? As far as I can discover NumPy is for the tenaciously non-obsolete Python version 2.7 and not for the shiny and spanking new Python 3.x. Help please!! — Preceding unsigned comment added by Hawden (talk • contribs) 14:16, 8 March 2014 (UTC)[reply]

Numpy works for Python 3.x, Python 2 isn't really supported anymore

Since numarray and numeric are deprecated, that info is no longer relevant to most people. I would like to move alot of that info to a new section, e.g. History of Numerical Python. Chrike 04:42, 25 June 2007 (UTC)[reply]

Um, which info? The info in the heading section is relevant, as it tells who originally created it. The other info is already in the 'History' section. Please clarify so we can work together to improve the article. peterl (talk) 10:15, 19 October 2011 (UTC)[reply]

I suggest we look into renaming this article from Numerical Python to NumPy because nowhere else (except in very old documents) is the term Numerical Python used much. See http://numpy.scipy.org or Travis Oliphant's "Guide to NumPy" Chrike 17:21, 15 October 2007 (UTC)[reply]

This page has been moved from "Numerical Python" to NumPy as the result of a move request listed at Wikipedia:Requested moves. Dekimasuよ! 11:56, 22 October 2007 (UTC) [reply]

The intro reads "Since Python is an interpreted language, mathematical algorithms often run much slower than they do in compiled languages like C or even Java."

Isn't Python compiled? (pyc files) See http://www.network-theory.co.uk/docs/pytut/CompiledPythonfiles.html 202.78.240.7 (talk) 04:43, 11 June 2008 (UTC)[reply]

"A program doesn't run any faster when it is read from a .pyc or .pyo file than when it is read from a .py file; the only thing that's faster about .pyc or .pyo files is the speed with which they are loaded." Python Tutorial Hawryluka (talk) 14:54, 22 July 2008 (UTC)[reply]

Python source code (.py files) is compiled into byte code (.pyc or .pyo files) the first time it is successfully imported. If possible the compiled byte code file is saved for future use but this is just an optimisation. The byte code itself is interpreted, so Python is regarded an interpreted language.

The article used to justify that the numpy implementation is about the same as an equivalent ("nothing fancy") C++ program does not, in fact, support the claim. According to the article, the numpy based implementation was more than 10 times slower than the naive C++ version -- to me that's very far from being close to the same speed. A naive C++ implementation of a vector or matrix library will also be far from optimal; considerable effort has to be made to make full use of a CPUs theoretical performance -- hence BLAS and similar libraries exist. A naive matrix-matrix multiplication, for example, will not use more than 20 % (at best!) of a processors potential.

Due to this exaggeration I'm removing the claim. — Preceding unsigned comment added by 212.130.79.38 (talk) 11:23, 6 May 2016 (UTC)[reply]

I could not find this information. The closest was this thread in the mail-list https://groups.google.com/forum/#!topic/comp.lang.python/Ej8x3hP3wlc%5B1-25%5D

Nicoguaro (talk) 16:11, 2 February 2017 (UTC)[reply]

Added. peterl (talk) 21:26, 5 February 2017 (UTC)[reply]

In the page is indicated a BSD license, but on NumPy site (https://numpy.org/license.html) BSD is not explicitly mentioned (the text is almost the same of the BSD3).

Paolo Gibellini (talk) 11:22, 31 January 2020 (UTC)[reply]

Thanks for pointing that out. BSD is mentioned on the main NumPy page, toward the top of the page. I have added a citation. --{{u|Mark viking}} {Talk} 11:41, 31 January 2020 (UTC)[reply]

Where it mentions BSD, it links to this: https://github.com/numpy/numpy/blob/main/LICENSE.txt, which indicates that it's BSD-3. 70.50.71.2 (talk) 17:41, 8 June 2023 (UTC)[reply]

The article does not explain what basic types are supported as the elements of the array. Is there an expert able to add this information ? -- Juergen 217.61.203.35 (talk) 09:37, 23 August 2020 (UTC)[reply]

It can be anything.

https://numpy.org/devdocs/user/basics.types.html and https://numpy.org/devdocs/user/basics.rec.html#structured-arrays

peterl (talk) 17:37, 23 August 2020 (UTC)[reply]

https://doi.org/10.1038/s41586-020-2649-2 It's open access, thus accessible to everyone. I added it to the further reading list, but I think we could use the paper to improve the article:

• check if we can exchange some existing references by the paper, after all there is nothing more solid than a open access Nature publication
• maybe add some of the included images, same as the paper they are CC-BY-4.0 licensed
• extend the text: The paper emphasizes NumPy being at the foundation of the scientific python ecosystem and that it's role of providing an API that is also used by other scientific computing packages. The importance of NumPy now extends beyond the package itself. — Preceding unsigned comment added by Elimik31 (talk • contribs) 01:29, 15 October 2020 (UTC)[reply]

I now implemented the last point that I suggested, using the paper as a reference and mentioning python's role for providing an array API for other array implementation in the limitations section, since numpy's limitations are what those array packages usually aim at solving. Elimik31 (talk) 23:05, 15 October 2020 (UTC)[reply]

Gui 45.251.232.185 (talk) 23:31, 19 June 2022 (UTC)[reply]

Could someone fix the release version reference to Wikidata? I gave it a go but no luck. The latest release version should show as v1.23.5. Wikidata does have this value marked as the preferred rank, but I am not sure how to make this page refer to it. Thanks!

--Toastpaint (talk) 02:01, 28 November 2022 (UTC)[reply]