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This PR contains the following updates:
==1.26.0
->==1.26.4
Warning
Some dependencies could not be looked up. Check the Dependency Dashboard for more information.
Release Notes
numpy/numpy (numpy)
v1.26.4
Compare Source
NumPy 1.26.4 Release Notes
NumPy 1.26.4 is a maintenance release that fixes bugs and regressions
discovered after the 1.26.3 release. The Python versions supported by
this release are 3.9-3.12. This is the last planned release in the
1.26.x series.
Contributors
A total of 13 people contributed to this release. People with a "+" by
their names contributed a patch for the first time.
Pull requests merged
A total of 19 pull requests were merged for this release.
numpy.array_api
: fixlinalg.cholesky
upper decomp...newaxis
to__all__
innumpy.array_api
__config__.py
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v1.26.3
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NumPy 1.26.3 Release Notes
NumPy 1.26.3 is a maintenance release that fixes bugs and regressions
discovered after the 1.26.2 release. The most notable changes are the
f2py bug fixes. The Python versions supported by this release are
3.9-3.12.
Compatibility
f2py
will no longer accept ambiguous-m
and.pyf
CLI combinations.When more than one
.pyf
file is passed, an error is raised. When both-m
and a.pyf
is passed, a warning is emitted and the-m
providedname is ignored.
Improvements
f2py
now handlescommon
blocks which havekind
specifications frommodules. This further expands the usability of intrinsics like
iso_fortran_env
andiso_c_binding
.Contributors
A total of 18 people contributed to this release. People with a "+" by
their names contributed a patch for the first time.
Pull requests merged
A total of 42 pull requests were merged for this release.
__getitem__
innumpy.array_api
newaxis
andlinalg.solve
innumpy.array_api
long
typebase
in cpu_avx512_knf2py
wrappers when modules and subroutines...iso_c_type
mappings more consistentlyf2py
rewrite withmeson
detailsnumpy/f2py/_backends
from main.f2py/*.py
from main.Checksums
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v1.26.2
: 1.26.2 releaseCompare Source
NumPy 1.26.2 Release Notes
NumPy 1.26.2 is a maintenance release that fixes bugs and regressions
discovered after the 1.26.1 release. The 1.26.release series is the last
planned minor release series before NumPy 2.0. The Python versions
supported by this release are 3.9-3.12.
Contributors
A total of 13 people contributed to this release. People with a "+" by
their names contributed a patch for the first time.
Pull requests merged
A total of 25 pull requests were merged for this release.
import_array()
noexcept
to shuffle helpersallow-noblas
option to true.np.dtype
to itself doesn't crashChecksums
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v1.26.1
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NumPy 1.26.1 Release Notes
NumPy 1.26.1 is a maintenance release that fixes bugs and regressions
discovered after the 1.26.0 release. In addition, it adds new
functionality for detecting BLAS and LAPACK when building from source.
Highlights are:
The 1.26.release series is the last planned minor release series before
NumPy 2.0. The Python versions supported by this release are 3.9-3.12.
Build system changes
Improved BLAS/LAPACK detection and control
Auto-detection for a number of BLAS and LAPACK is now implemented for
Meson. By default, the build system will try to detect MKL, Accelerate
(on macOS >=13.3), OpenBLAS, FlexiBLAS, BLIS and reference BLAS/LAPACK.
Support for MKL was significantly improved, and support for FlexiBLAS
was added.
New command-line flags are available to further control the selection of
the BLAS and LAPACK libraries to build against.
To select a specific library, use the config-settings interface via
pip
orpypa/build
. E.g., to selectlibblas
/liblapack
, use:This works not only for the libraries named above, but for any library
that Meson is able to detect with the given name through
pkg-config
orCMake.
Besides
-Dblas
and-Dlapack
, a number of other new flags areavailable to control BLAS/LAPACK selection and behavior:
-Dblas-order
and-Dlapack-order
: a list of library names tosearch for in order, overriding the default search order.
-Duse-ilp64
: if set totrue
, use ILP64 (64-bit integer) BLAS andLAPACK. Note that with this release, ILP64 support has been extended
to include MKL and FlexiBLAS. OpenBLAS and Accelerate were supported
in previous releases.
-Dallow-noblas
: if set totrue
, allow NumPy to build with itsinternal (very slow) fallback routines instead of linking against an
external BLAS/LAPACK library. The default for this flag may be
changed to ``true`` in a future 1.26.x release, however for
1.26.1 we'd prefer to keep it as ``false`` because if failures
to detect an installed library are happening, we'd like a bug
report for that, so we can quickly assess whether the new
auto-detection machinery needs further improvements.
-Dmkl-threading
: to select the threading layer for MKL. There arefour options:
seq
,iomp
,gomp
andtbb
. The default isauto
, which selects from those four as appropriate given theversion of MKL selected.
-Dblas-symbol-suffix
: manually select the symbol suffix to use forthe library - should only be needed for linking against libraries
built in a non-standard way.
New features
numpy._core
submodule stubsnumpy._core
submodule stubs were added to provide compatibility withpickled arrays created using NumPy 2.0 when running Numpy 1.26.
Contributors
A total of 13 people contributed to this release. People with a "+" by
their names contributed a patch for the first time.
Pull requests merged
A total of 20 pull requests were merged for this release.
-march=native
...use-compute-credits
for Cirrus.NumpyUnpickler
for backportingnumpy._core
stubs. RemoveNumpyUnpickler
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