Okay, little modification to my last mail: many Android smartphones are still 32 bit, but according to
https://www.androidauthority.com/arm-32-vs-64-bit-explained-1232065/ from 2023 on, all (or at least many) new ARM processors will be 64 bit only. Apple‘s iPhone 64 bit only since quite a while already (September 2017, iOS 11 release). > On 26. Dec 2021, at 17:31, Lev Maximov <lev.maxi...@gmail.com> wrote: > > > Hi Michael, > > > Python on Windows is and is supposed to be, as far as I get it, a dying > > platform. > I would join Matti in thinking that it is a misconception. > > Have you heard of the enormous daily updated unofficial repository of the > binary windows compilations of > almost 600 python libraries by Christoph Gohlke? (numpy and libs depending on > it are built with MKL there) > It is there for a reason. > > If you look at the stats such as this one (Matti already mentioned them while > I was writing this text), > > https://www.jetbrains.com/research/python-developers-survey-2018/ > https://www.jetbrains.com/lp/python-developers-survey-2020/ > > you'll see (in addition to the fact that numpy is the #1 library in data > science ;) ) that in > the recent years the percentage of windows user among the developers is quite > high: > 69% linux - 47% windows - 32% macos (2018) > 68% linux - 48% windows - 29% macos (2020) > So it looks as if it is rather growing than dying. > > This is due to the popularity of the above mentioned data science and AI, > which have skyrocketed in the > last 10 years. And the vast majority of data scientists work on windows. > > Windows as a platform for developers as a whole is also quite flourishing > today. > According to the stackoverflow 2021 developer survey 45% of the respondents > use Windows (25% linux, 25% macos). > Among the professional developers the numbers are 41% for windows, 30% macos, > 26% linux. > > Also the primary audience of the tutorials like mine (as well as of > stackoverflow?) are windows users. > Linux users can easily figure things described there on their own, through > the docstrings, source code > or, as a last resort, through the docs ) > > >The more experienced the Python developers are, the more likely they are to > >use Linux and macOS as development > > environments, and the less likely they are to choose Windows. > (from the same jetbrains survey of 2018) > > I wouldn't like to go into holy wars, though. I'm equally literate in both > unix and windows (somewhat less in macos) > and in my opinion the interests of all the users of the the three operating > systems should be taken into account > in both the code of the library and the docs. > > The documentation is sometimes pretty ignorant of mac/windows users, btw: > > Alias on this platform (Linux x86_64) > https://numpy.org/doc/stable/reference/arrays.scalars.html#numpy.int_ > And what about the other platforms? > > As for the particular issue of the difference in the default integer types, > in my opinion the default choice of int32 on windows for > array [1,2,3] fits the description > > >" If not given, then the type will be determined as the minimum type > >required to hold the objects in the sequence." > https://numpy.org/doc/stable/reference/generated/numpy.array.html > > better than int64 on linux/macos. > > Best regards, > Lev > > >> On Sun, Dec 26, 2021 at 8:45 PM Michael Siebert >> <michael.sieber...@gmail.com> wrote: >> Hey Lev, >> >> I‘ve forgotten to mention my MacBook M1, >> it‘s also int64 there. >> >> Python on Windows is and is supposed to be, as far as I get it, a dying >> platform. A billion things are broken there (HDF comes to my mind) and it >> seems even Microsoft wants developers to move away from native Windows with >> their introduction of WSL (Windows Subsystem for Linux). Its latest version, >> WSL2 even comes with an actual Linux kernel and since Windows 11, it has >> support for graphical applications (Xorg) out of the box. With Visual Studio >> Code (also Microsoft) and it’s remote capabilities, one does not even feel a >> difference between developing in an Ubuntu in a WSL in Windows and an actual >> Ubuntu. >> >> Considering the „traditional“ C datatypes, fixed types and prioritizing them >> in Numpy documentation, that‘s what my issue (see below) is about. I think >> they have summarized it nicely in >> >> https://matt.sh/howto-c >> >> Best regards, Michael >> >>>> On 26. Dec 2021, at 13:49, Lev Maximov <lev.maxi...@gmail.com> wrote: >>>> >>> >>> Dear Michael, >>> >>> Thank you for your feedback! >>> >>> I've fixed the x86_64 typo. >>> >>> I'll think how to reformulate the int32 part. I work on debian x86_64 and >>> windows 10 64bit. Constructing an array with np.array([1,2,3]) as well as >>> np.array([1,2,3], dtype=np.int_) gives me int64 dtype on linux, and int32 >>> on windows. >>> >>> As suggested by Matti, I've put the rst source (and images) into a separate >>> github repository >>> >>> https://github.com/axil/numpy-data-types >>> >>> PRs are welcome. My primary concern is to exclude serious typos/mistakes >>> that might mislead/harm the readers if used. >>> >>> My personal preference is towards explicit width types like np.int32, but >>> from reading the docs I have a feeling there's a trend of migrating towards >>> the c-style notation. >>> >>> Best regards, >>> Lev >>> >>>> On Sun, Dec 26, 2021 at 7:05 PM Michael Siebert >>>> <michael.sieber...@gmail.com> wrote: >>>> Dear Lev, >>>> >>>> thank you a lot! Something like this should be part of the Numpy >>>> documentation. I like the diagram, looks very nice! Also, I’ve opened an >>>> issue regarding data types >>>> >>>> https://github.com/numpy/numpy/issues/20662 >>>> >>>> Some feedback from my side: >>>> >>>> 1. When calling numpy.array([1,2,3,4]) it gives me an int64 data type most >>>> of the time (two x86_64 systems, one arm64 system). The only time I’ve got >>>> int32 was on a Raspberry Pi, which is a software limitation, since the CPU >>>> is 64 bit and they have even replaced their so-far 32bit only Raspberry Pi >>>> Zero with a 64bit version (yes, one day Raspberry OS with 64 bit might >>>> actually become the default!). I don’t know what machine you are working >>>> on, but int64 should be the default. >>>> 2. x64 refers to the obsolete Intel Itanium architecture (mentioned once). >>>> Should be x86_64. >>>> 3. np.errstate looks nice, I could use that for my pull request as well. >>>> >>>> Many thanks & best regards, Michael >>>> >>>> >>>>> On 25. Dec 2021, at 10:02, Lev Maximov <lev.maxi...@gmail.com> wrote: >>>>> >>>>> Hi everyone, >>>>> >>>>> I'm almost done with the article about numpy types – something I haven't >>>>> covered in Numpy Illustrated. >>>>> >>>>> Would someone please have a look to confirm I haven't written anything >>>>> anti-climatic there? >>>>> >>>>> https://axil.github.io/numpy-data-types.html >>>>> >>>>> -- >>>>> Best regards, >>>>> Lev >>>>> >>>>> PS Earlier today I've mistakenly sent an email with the wrong link. >>>>> _______________________________________________ >>>>> NumPy-Discussion mailing list -- numpy-discussion@python.org >>>>> To unsubscribe send an email to numpy-discussion-le...@python.org >>>>> https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ >>>>> Member address: michael.sieber...@gmail.com >>>> >>>> _______________________________________________ >>>> NumPy-Discussion mailing list -- numpy-discussion@python.org >>>> To unsubscribe send an email to numpy-discussion-le...@python.org >>>> https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ >>>> Member address: lev.maxi...@gmail.com >>> _______________________________________________ >>> NumPy-Discussion mailing list -- numpy-discussion@python.org >>> To unsubscribe send an email to numpy-discussion-le...@python.org >>> https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ >>> Member address: michael.sieber...@gmail.com >> _______________________________________________ >> NumPy-Discussion mailing list -- numpy-discussion@python.org >> To unsubscribe send an email to numpy-discussion-le...@python.org >> https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ >> Member address: lev.maxi...@gmail.com > _______________________________________________ > NumPy-Discussion mailing list -- numpy-discussion@python.org > To unsubscribe send an email to numpy-discussion-le...@python.org > https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ > Member address: michael.sieber...@gmail.com
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