> I'm surprised no one has mentioned it already: int and uint are reversed in the first table. Not anymore! I know I'm susceptible to this type of blunders )
Thank you for your kind attention! I've made a few more fixes here and there and added a couple of illustrations. Looks more or less finished to me. Giving it away to the editors. Best regards, Lev On Mon, Dec 27, 2021 at 5:17 AM Juan Nunez-Iglesias <j...@fastmail.com> wrote: > I'm surprised no one has mentioned it already: int and uint are reversed > in the first table. > > I do agree with others that this is a great overview page that should be > included in the numpy docs. Thanks Lev! > > Juan. > > On Sun, 26 Dec 2021, at 12:59 PM, Lev Maximov wrote: > > I've tried to take into account all the suggestions from this thread. > > https://axil.github.io/numpy-data-types.html shows new version now and > > > https://github.com/axil/numpy-data-types/commit/14d9da053fd67e5569436faa1f58599c0cc8b380#diff-ed7002b439e9ac845f22357d822bac1444730fbdb6016d3ec9432297b9ec9f73 > displays most of the changes. > > As for the inheritance diagram, I think it is perfectly fine to add it to > the documentation as is, > except that I'd put back the 'void' type I've originally omitted to keep > it simple. > > Btw is anyone aware why 'U' is missing from the np.typecode['Character']? > > On Sun, Dec 26, 2021 at 11:57 PM Lev Maximov <lev.maxi...@gmail.com> > wrote: > > Python 3.9.7 (tags/v3.9.7:1016ef3, Aug 30 2021, 20:19:38) [MSC v.1929 64 > bit (AMD64)] on win32 > > ^^ this is relevant ^^^^ this > is not > Type "help", "copyright", "credits" or "license" for more information. > >>> import numpy as np > >>> np.int_ > <class 'numpy.int32'> > > On Sun, Dec 26, 2021 at 11:42 PM Michael Siebert < > michael.sieber...@gmail.com> wrote: > > > 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 > <https://www.lfd.uci.edu/~gohlke/pythonlibs/> 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 > <https://insights.stackoverflow.com/survey/2021#most-popular-technologies-op-sys> > 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 > > _______________________________________________ > 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: j...@fastmail.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 >
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