Charles R Harris
Sat, Oct 14, 3:03 PM
to numpy-discussion, SciPy, bcc: python-announce-list
Hi All,
On behalf of the NumPy team, I'm pleased to announce the release of NumPy
1.26.2. NumPy 1.26.2 is a maintenance release that fixes bugs and
regressions discovered after the 1.26.1 release. The
.
Highlights are:
- Improved detection of BLAS and LAPACK libraries for meson builds
- Pickle compatibility with the upcoming NumPy 2.0.
The Python versions supported by this release are 3.9-3.12. Wheels can be
downloaded from PyPI <https://pypi.org/project/numpy/1.26.1/>; source
archives, r
Hi All,
On behalf of the NumPy team, I'm pleased to announce the release of NumPy
1.26.0. The NumPy 1.26.0 release is a continuation of the 1.25.x release
cycle with the addition of Python 3.12.0 support. Python 3.12 dropped
distutils, consequently supporting it required finding a replacement for
Hi All,
On behalf of the NumPy team, I'm pleased to announce the release of NumPy
1.26.0rc1. The NumPy 1.26.0 release is a continuation of the 1.25.x release
cycle with the addition of Python 3.12.0 support. Python 3.12 dropped
distutils, consequently supporting it required finding a replacement
Hi All,
On behalf of the NumPy team, I'm pleased to announce the release of NumPy
1.26.0b1. The NumPy 1.26.0 release is a continuation of the 1.25.x release
cycle with the addition of Python 3.12.0 support. Python 3.12 dropped
distutils, consequently supporting it required finding a replacement
Hi All,
On behalf of the NumPy team, I'm pleased to announce the release of NumPy
1.25.2. NumPy 1.25.2 is a maintenance release that fixes bugs and
regressions discovered after the 1.25.1 release. This is the last planned
release in the 1.25.x series, the next final release will be 1.26.0, which
Hi All,
On behalf of the NumPy team, I'm pleased to announce the release of NumPy
1.25.1. NumPy 1.25.1 is a maintenance release that fixes bugs discovered
after the 1.24.3 release and updates the build infrastructure to stay
current with upstream changes.
The Python versions supported by this
. That is needed because distutils has been dropped by Python
12 and we will be switching to using meson for future builds. The next
mainline release will be NumPy 2.0.0. We plan that the 2.0 series will
still support downstream projects built against earlier
versions of NumPy.
The Python versions
. That is needed because distutils has been dropped by Python
12 and we will be switching to using meson for future builds. The next
mainline release will be NumPy 2.0.0. We plan that the 2.0 series will
still support downstream projects built against earlier
versions of NumPy.
The Python versions
Hi All,
On behalf of the NumPy team, I'm pleased to announce the release of NumPy
1.24.3. NumPy 1.24.3 is a maintenance release that fixes bugs and
regressions discovered after the 1.24.2 release.
The Python versions supported by this release are 3.8-3.11 Note that 32 bit
wheels are only
Hi All,
On behalf of the NumPy team, I'm pleased to announce the release of NumPy
1.24.2. NumPy 1.24.2 is a maintenance release that fixes bugs and
regressions discovered after the 1.24.1 release.
The Python versions supported by this release are 3.8-3.11 Note that 32 bit
wheels are only
Hi All,
On behalf of the NumPy team, I'm pleased to announce the release of NumPy
1.24.1. NumPy 1.24.1 is a maintenance release that fixes bugs and
regressions discovered after the 1.24.0 release.
The Python versions supported by this release are 3.8-3.11 Note that 32 bit
wheels are only
Hi All,
On behalf of the NumPy team, I'm pleased to announce the release of NumPy
1.24.0. The NumPy 1.24.0 release continues the ongoing work to improve the
handling and promotion of dtypes, increase execution speed, and
clarify the documentation. There are also a large number of new and expired
Hi All,
On behalf of the NumPy team, I'm pleased to announce the release of NumPy
1.24.0rc1. The NumPy 1.24.0 release continues the ongoing work to improve
the handling and promotion of dtypes, increase execution speed, and
clarify the documentation. There are also a large number of new and
Hi All,
On behalf of the NumPy team, I'm pleased to announce the release of NumPy
1.24.0rc1. The NumPy 1.24.0 release continues the ongoing work to improve
the handling and promotion of dtypes, increase execution speed, and
clarify the documentation. There are also a large number of new and
Hi All,
On behalf of the NumPy team, I am pleased to announce the release of
NumPy 1.23.4. NumPy 1.23.4 is a maintenance release that fixes bugs
discovered after the 1.23.3 release and keeps the build infrastructure
current. The main improvements are fixes for some annotation corner cases,
a fix
Hi All,
On behalf of the NumPy team, I am pleased to announce the release of
NumPy 1.23.3. NumPy 1.23.3 is a maintenance release that fixes bugs
discovered after the 1.23.2 release. There is no major theme for this
release, the main improvements are for some downstream builds and some
annotation
Hi All,
On behalf of the NumPy team, I am pleased to announce the release of
NumPy 1.23.2. NumPy 1.23.2 is a maintenance release that fixes bugs
discovered after the 1.23.1 release. Notable features are:
- Typing changes needed for Python 3.11
- Wheels for Python 3.11.0rc1
The Python
Hi All,
On behalf of the NumPy team, I'm pleased to announce the release of NumPy
1.23.1. NumPy 1.23.1 is a maintenance release that fixes bugs discovered
after the 1.23.0 release. Notable fixes are:
- Fix searchsorted for float16 NaNs
- Fix compilation on Apple M1
- Fix KeyError in
Hi All,
On behalf of the NumPy team, I'm pleased to announce the release of NumPy
1.23.0. The NumPy 1.23.0 release continues the ongoing work to improve the
handling and promotion of dtypes, increase the execution speed, clarify the
documentation, and expire old deprecations. The highlights are:
Hi All,
On behalf of the NumPy team, I'm pleased to announce the release of NumPy
1.23.0rc2. The NumPy 1.23.0 release continues the ongoing work to improve
the handling and promotion of dtypes, increase the execution speed, clarify
the documentation, and expire old deprecations. The highlights
Hi All,
On behalf of the NumPy team, I'm pleased to announce the release of NumPy
1.23.0rc2. The NumPy 1.23.0 release continues the ongoing work to improve
the handling and promotion of dtypes, increase the execution speed, clarify
the documentation, and expire old deprecations. The highlights
Hi All,
On behalf of the NumPy team, I'm pleased to announce the release of NumPy
1.23.0rc1. The NumPy 1.23.0 release continues the ongoing work to improve
the handling and promotion of dtypes, increase the execution speed, clarify
the documentation, and expire old deprecations. The highlights
Hi All,
On behalf of the NumPy team, I'm pleased to announce the release of NumPy
1.22.4. NumPy 1.22.4 is a maintenance release that fixes bugs discovered
after the 1.22.3 release. In addition, the wheels for this release are
built using the recently released Cython 0.29.30, which should fix the
bit wheel is intended to make life easier for
oldest-supported-numpy.
The Python versions supported in this release are 3.7-3.10. If you want to
compile your own version using gcc-11 you will need to use gcc-11.2+ to
avoid problems. Wheels can be downloaded from PyPI
<https://pypi.org/project/nu
Hi All,
On behalf of the NumPy team, I'm pleased to announce the release of NumPy
1.22.3. NumPy 1.22.3 is a maintenance release that fixes bugs discovered
after the 1.22.2 release. The most noticeable fixes may be those for
DLPack. One that may cause some problems is disallowing strings as inputs
Hi All,
On behalf of the NumPy team, I'm pleased to announce the release of NumPy
1.22.2. NumPy 1.22.2 fixes several bugs discovered after the 1.22.1
release. Notable fixes are:
- Build related fixes for downstream projects and other platforms.
- Various annotation fixes/additions.
-
Hi All,
On behalf of the NumPy team, I'm pleased to announce the release of NumPy
1.22.1. NumPy 1.22.1 fixes several bugs discovered after the 1.22.0
release. Notable fixes are:
- Fix for f2PY docstring problems (SciPy)
- Fix for reduction type problems (AstroPy)
- Fixes for various
Hi All,
On behalf of the NumPy team, I'm pleased to announce the release of NumPy
1.22.0. NumPy 1.22.0 is a big release featuring the work of 153
contributors spread over 609 pull requests. There have been many
improvements,
highlights are:
- Annotations of the main namespace are essentially
Hi All,
On behalf of the NumPy team I am pleased to announce the release of NumPy
1.21.5. NumPy 1.21.5 is a maintenance release that fixes a few bugs
discovered after the 1.21.4 release and does some maintenance to extend the
1.21.x lifetime. The Python versions supported in this release are
Hi All,
On behalf of the NumPy team, I'm pleased to announce the release of NumPy
1.22.0rc3. NumPy 1.22.0rc3 is a big release featuring the work of 152
contributors spread over 602 pull requests. There have been many
improvements,
highlights are:
- Annotations of the main namespace are
Hi All,
On behalf of the NumPy team, I'm pleased to announce the release of NumPy
1.22.0rc1. NumPy 1.22.0rc1 is a big release featuring the work of 151
contributers spread over 589 pull requests. There have been many
improvements,
highlights are:
- Annotations of the main namespace are
Hi All,
On behalf of the NumPy team, I'm pleased to announce the release of NumPy
1.22.0rc1. NumPy 1.22.0rc1 is a big release featuring the work of 150
contributers spread over 575 pull requests. There have been many
improvements,
highlights are:
- Annotations of the main namespace are
Hi All,
On behalf of the NumPy team I am pleased to announce the release of NumPy
1.21.4. NumPy 1.21.4 is a maintenance release that fixes a few bugs
discovered after 1.21.3. The most important fix here is for the NumPy
header files to make them work for both x86_64 and M1 hardware when
included
Hi All,
On behalf of the NumPy team I am pleased to announce the release of NumPy
1.21.3. NumPy 1.21.3 is a maintenance release that fixes a few bugs
discovered after the 1.21.2 release. It also provides 64 bit Python 3.10.0
wheels. Note a few oddities about the Python 3.10 wheels:
- There
Hi All,
On behalf of the NumPy team I am pleased to announce the release of NumPy
1.21.2. NumPy 1.21.2 is a maintenance release that fixes bugs discovered
after 1.21.1. It also provides 64 bit manylinux Python 3.10.0rc1 wheels for
downstream testing. Note that Python 3.10 is not yet final. There
Il giorno martedì 21 aprile 2020 21:04:17 UTC+2, Derek Vladescu ha scritto:
> I’ve just begun a serious study of using Python as an aspiring
> programmer/data scientist.
> Can someone please walk me through how to download Python, SO THAT I will be
> able to import numpy?
>
> Thanks,
> Derek
>
FWIW, I installed Anaconda on Windows 10. Then besides Python you also get
SPIDER, Jupyter and more, all out of the box.
Am Mittwoch, 22. April 2020 schrieb Souvik Dutta :
> First head over to the official python download page. Then choose the
> version and type of installer you want. After you
First head over to the official python download page. Then choose the
version and type of installer you want. After you download it click on the
installer to install it. Don't forget to click on the check boxes that says
add python to path and download pip. Then search for idle in the search
menu.
I’ve just begun a serious study of using Python as an aspiring programmer/data
scientist.
Can someone please walk me through how to download Python, SO THAT I will be
able to import numpy?
Thanks,
Derek
Sent from Mail for Windows 10
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On Wed, 29 May 2019 at 9:38 PM Shakti Kumar
wrote:
>
>
> On Wed, 29 May 2019 at 9:29 PM Contreras, Brian J
> wrote:
>
>> Good Morning,
>>
>> I am a research student at the Georgia Institute of Technology. I have
>> made multiple attempts to download
On Wed, 29 May 2019 at 9:29 PM Contreras, Brian J
wrote:
> Good Morning,
>
> I am a research student at the Georgia Institute of Technology. I have
> made multiple attempts to download different versions of Python with Numpy
> on my Microsoft Surface Book with no success.
>
Si
Good Morning,
I am a research student at the Georgia Institute of Technology. I have made
multiple attempts to download different versions of Python with Numpy on my
Microsoft Surface Book with no success.
I ensured that I have space for the program and the latest windows 10 update, I
still
Hello!
I wanted to announce here a "new" iOS app for coding Python: Pyto. It's
available on the App Store and is open source.
Features
=
The app has a file browser with scripts, a code editor with syntax coloring and
smart code completion and a console that supports input.
On 2015-03-01 20:32, fl wrote:
Hi,
It is difficult to install numpy package for my PC Windows 7, 64-bit OS. In
the end, I install Enthought Canopy, which is recommended on line because it
does install numpy automatically. Now, I can test it with
import numpy
it succeeds. On
On 2015-03-01 20:32:34 +, fl said:
import numpy
it succeeds. On http://wiki.scipy.org/Cookbook, it shows some interesting
code example snippet, such as Cookbook / ParticleFilter, Markov chain etc.
I don't know how I can access these code examples, because I don't know where
Enthought
On Sunday, March 1, 2015 at 1:25:59 PM UTC-8, Andrea D'Amore wrote:
On 2015-03-01 20:32:34 +, fl said:
import numpy
it succeeds. On http://wiki.scipy.org/Cookbook, it shows some interesting
code example snippet, such as Cookbook / ParticleFilter, Markov chain etc.
I don't know how
Hi,
It is difficult to install numpy package for my PC Windows 7, 64-bit OS. In
the end, I install Enthought Canopy, which is recommended on line because it
does install numpy automatically. Now, I can test it with
import numpy
it succeeds. On http://wiki.scipy.org/Cookbook, it shows some
to
upgrade the gnu compilers to install the latest versions) and
where these should be installed (local disks, /share/apps, other?).
A little more background, our students are currently working
with a local installation using
Python-2.7.1
numpy-1.5.1
scipy-0.9.0b1
Mayavi-3.4.0
ATLAS-3.8.3
vtk-5.4
Steven D'Aprano wrote:
It
only becomes your problem if you have advised people that the right way
to use your module is with import *.
And if you're advising people to do that, it would be an
extremely good idea to give your functions different names
so that they don't conflict with the
On 2010-11-14 17:37 , Gregory Ewing wrote:
Steven D'Aprano wrote:
It only becomes your problem if you have advised people that the right way to
use your module is with import *.
And if you're advising people to do that, it would be an
extremely good idea to give your functions different names
(somehow automatically
determine which func should be used - numpy or Python max)? The same
issue with min, but they are equivalent, of course.
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Well, I think I have found an appropriate solution.
Regards, D.
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On 13/11/2010 19:55, dmitrey wrote:
Well, I think I have found an appropriate solution.
Regards, D.
Hi Dmitrey,
Would you mind briefly describing your solution?
Thanks,
Ben
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On 11/13/2010 2:41 PM, dmitrey wrote:
hi all,
I have the following problem:
I have overloaded max function in my module (FuncDesigner); it works
like following:
if some data in arguments is of type oofun then my function works,
elseware numpy.max() is used.
Now the problem:
suppose someone
to get rid of the problem (somehow automatically
determine which func should be used - numpy or Python max)? The same
issue with min, but they are equivalent, of course.
Automatically? No.
--
Steven
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Hi
I am looking for a robust, cross-platform way to determine if I am on a
32 bit or a 64 bit Python and if the numpy installation is also 32 bit
or 64 bit.
I have googled a bit and found some platform specific solutions but
nothing general.
The solution should work with different versions of
I am looking for a robust, cross-platform way to determine if I am on a
32 bit or a 64 bit Python and if the numpy installation is also 32 bit
or 64 bit.
You can find out the size of a pointer with struct.calcsize(P) * 8.
Numpy will have the same configuration if you can import it.
Regards,
On Mon, 25 May 2009 23:54:45 +0200
Martin v. Löwis mar...@v.loewis.de wrote:
I am looking for a robust, cross-platform way to determine if I am
on a 32 bit or a 64 bit Python and if the numpy installation is
also 32 bit or 64 bit.
You can find out the size of a pointer with
?
Python has no array objects in the core language, only lists. The
distinction is important when discussing numarray etc, because Python
lists and NumPy etc arrays are very different.
While you can build a Python list from a subsection of your C array,
changes made in Python won't be pushed back
from existing data?
Python has no array objects in the core language, only lists. The
distinction is important when discussing numarray etc, because Python
lists and NumPy etc arrays are very different.
Thank you very much for the detailed reply!
Sorry if I was not clear enough. I was talking about
On Sat, 2005-01-01 at 10:27 -0600, Bo Peng wrote:
Sorry if I was not clear enough. I was talking about the differece
between python array module
(http://docs.python.org/lib/module-array.html, Modules/arraymodule.c in
the source tree) and NumPy array. They both use C-style memory block
Bo Peng wrote:
Dear list,
I am writing a Python extension module that needs a way to expose pieces
of a big C array to python. Currently, I am using NumPy like the following:
PyObject* res = PyArray_FromDimsAndData(1, int*dim, PyArray_DOUBLE,
char*buf);
Users will get a Numeric Array object
Bo Peng wrote:
Dear list,
I am writing a Python extension module that needs a way to expose pieces
of a big C array to python. Currently, I [use] NumPy Users ... actually
change the underlying C array.
Python's array module is built-in, easy to use, but *without* a
FromLenAndData function!
Bo Peng wrote:
Scott David Daniels wrote:
I wrote blocks and views to overcome this problem.
I was too impatient to wait for your reply. :-)
I call 21-hour turnaround over New Year's Eve pretty good. Clearly I
will never be quick enough for you ;-). Since I presented this at
the Vancouver Python
Dear list,
I am writing a Python extension module that needs a way to expose pieces
of a big C array to python. Currently, I am using NumPy like the following:
PyObject* res = PyArray_FromDimsAndData(1, int*dim, PyArray_DOUBLE,
char*buf);
Users will get a Numeric Array object and can change
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