NumPy 2.2.5 Release Notes

NumPy 2.2.5 is a patch release that fixes bugs found after the 2.2.4
release. It has a large number of typing fixes/improvements as well as
the normal bug fixes and some CI maintenance.

This release supports Python versions 3.10-3.13.

Contributors

A total of 7 people contributed to this release. People with a "+" by
their names contributed a patch for the first time.

Charles Harris
Joren Hammudoglu
Baskar Gopinath +
Nathan Goldbaum
Nicholas Christensen +
Sayed Adel
karl +

Pull requests merged

A total of 19 pull requests were merged for this release.

#28545: MAINT: Prepare 2.2.x for further development
#28582: BUG: Fix return type of NpyIter_GetIterNext in Cython declarations
#28583: BUG: avoid deadlocks with C++ shared mutex in dispatch cache
#28585: TYP: fix typing errors in _core.strings
#28631: MAINT, CI: Update Ubuntu to 22.04 in azure-pipelines
#28632: BUG: Set writeable flag for writeable dlpacks.
#28633: BUG: Fix crackfortran parsing error when a division occurs within...
#28650: TYP: fix ndarray.tolist() and .item() for unknown dtype
#28654: BUG: fix deepcopying StringDType arrays (#28643)
#28661: TYP: Accept objects that write() to str in savetxt
#28663: CI: Replace QEMU armhf with native (32-bit compatibility mode)
#28682: SIMD: Resolve Highway QSort symbol linking error on aarch32/ASIMD
#28683: TYP: add missing "b1" literals for dtype[bool]
#28705: TYP: Fix false rejection of NDArray[object_].__abs__()
#28706: TYP: Fix inconsistent NDArray[float64].__[r]truediv__ return...
#28723: TYP: fix string-like ndarray rich comparison operators
#28758: TYP: some [arg]partition fixes
#28772: TYP: fix incorrect random.Generator.integers return type
#28774: TYP: fix count_nonzero signature

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f5045039100ed58fa817a6227a356240...

NumPy 2.2.4 Release Notes

NumPy 2.2.4 is a patch release that fixes bugs found after the 2.2.3
release. There are a large number of typing improvements, the rest of
the changes are the usual mix of bugfixes and platform maintenace.

This release supports Python versions 3.10-3.13.

Contributors

A total of 15 people contributed to this release. People with a "+" by
their names contributed a patch for the first time.

Abhishek Kumar
Andrej Zhilenkov
Andrew Nelson
Charles Harris
Giovanni Del Monte
Guan Ming(Wesley) Chiu +
Jonathan Albrecht +
Joren Hammudoglu
Mark Harfouche
Matthieu Darbois
Nathan Goldbaum
Pieter Eendebak
Sebastian Berg
Tyler Reddy
lvllvl +

Pull requests merged

A total of 17 pull requests were merged for this release.

#28333: MAINT: Prepare 2.2.x for further development.
#28348: TYP: fix positional- and keyword-only params in astype, cross...
#28377: MAINT: Update FreeBSD version and fix test failure
#28379: BUG: numpy.loadtxt reads only 50000 lines when skip_rows >= max_rows
#28385: BUG: Make np.nonzero threading safe
#28420: BUG: safer bincount casting (backport to 2.2.x)
#28422: BUG: Fix building on s390x with clang
#28423: CI: use QEMU 9.2.2 for Linux Qemu tests
#28424: BUG: skip legacy dtype multithreaded test on 32 bit runners
#28435: BUG: Fix searchsorted and CheckFromAny byte-swapping logic
#28449: BUG: sanity check __array_interface__ number of dimensions
#28510: MAINT: Hide decorator from pytest traceback
#28512: TYP: Typing fixes backported from #28452, #28491, #28494
#28521: TYP: Backport fixes from #28505, #28506, #28508, and #28511
#28533: TYP: Backport typing fixes from main (2)
#28534: TYP: Backport typing fixes from main (3)
#28542: TYP: Backport typing fixes from main (4)

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56232f4a69b03dd7a87a55fffc5f2ebc  numpy-2.2.4.tar.gz

SHA256

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f7de08cbe5551911886d1ab60de...

NumPy 2.2.3 Release Notes

NumPy 2.2.3 is a patch release that fixes bugs found after the 2.2.2
release. The majority of the changes are typing improvements and fixes
for free threaded Python. Both of those areas are still under
development, so if you discover new problems, please report them.

This release supports Python versions 3.10-3.13.

Contributors

A total of 9 people contributed to this release. People with a "+" by
their names contributed a patch for the first time.

!amotzop
Charles Harris
Chris Sidebottom
Joren Hammudoglu
Matthew Brett
Nathan Goldbaum
Raghuveer Devulapalli
Sebastian Berg
Yakov Danishevsky +

Pull requests merged

A total of 21 pull requests were merged for this release.

#28185: MAINT: Prepare 2.2.x for further development
#28201: BUG: fix data race in a more minimal way on stable branch
#28208: BUG: Fix from_float_positional errors for huge pads
#28209: BUG: fix data race in np.repeat
#28212: MAINT: Use VQSORT_COMPILER_COMPATIBLE to determine if we should...
#28224: MAINT: update highway to latest
#28236: BUG: Add cpp atomic support (#28234)
#28237: BLD: Compile fix for clang-cl on WoA
#28243: TYP: Avoid upcasting float64 in the set-ops
#28249: BLD: better fix for clang / ARM compiles
#28266: TYP: Fix timedelta64.__divmod__ and timedelta64.__mod__...
#28274: TYP: Fixed missing typing information of set_printoptions
#28278: BUG: backport resource cleanup bugfix from gh-28273
#28282: BUG: fix incorrect bytes to stringdtype coercion
#28283: TYP: Fix scalar constructors
#28284: TYP: stub numpy.matlib
#28285: TYP: stub the missing numpy.testing modules
#28286: CI: Fix the github label for TYP: PR's and issues
#28305: TYP: Backport typing updates from main
#28321: BUG: fix race initializing legacy dtype casts
#28324: CI: update test_moderately_small_alpha

Checksums

MD5

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SHA256

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NumPy 2.2.2 Release Notes

NumPy 2.2.2 is a patch release that fixes bugs found after the 2.2.1
release. The number of typing fixes/updates is notable. This release
supports Python versions 3.10-3.13.

Contributors

A total of 8 people contributed to this release. People with a "+" by
their names contributed a patch for the first time.

Alicia Boya García +
Charles Harris
Joren Hammudoglu
Kai Germaschewski +
Nathan Goldbaum
PTUsumit +
Rohit Goswami
Sebastian Berg

Pull requests merged

A total of 16 pull requests were merged for this release.

#28050: MAINT: Prepare 2.2.x for further development
#28055: TYP: fix void arrays not accepting str keys in __setitem__
#28066: TYP: fix unnecessarily broad integer binop return types (#28065)
#28112: TYP: Better ndarray binop return types for float64 &...
#28113: TYP: Return the correct bool from issubdtype
#28114: TYP: Always accept date[time] in the datetime64 constructor
#28120: BUG: Fix auxdata initialization in ufunc slow path
#28131: BUG: move reduction initialization to ufunc initialization
#28132: TYP: Fix interp to accept and return scalars
#28137: BUG: call PyType_Ready in f2py to avoid data races
#28145: BUG: remove unnecessary call to PyArray_UpdateFlags
#28160: BUG: Avoid data race in PyArray_CheckFromAny_int
#28175: BUG: Fix f2py directives and --lower casing
#28176: TYP: Fix overlapping overloads issue in 2->1 ufuncs
#28177: TYP: preserve shape-type in ndarray.astype()
#28178: TYP: Fix missing and spurious top-level exports

Checksums

MD5

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NumPy 2.2.1 Release Notes

NumPy 2.2.1 is a patch release following 2.2.0. It fixes bugs found
after the 2.2.0 release and has several maintenance pins to work around
upstream changes.

There was some breakage in downstream projects following the 2.2.0
release due to updates to NumPy typing. Because of problems due to MyPy
defects, we recommend using basedpyright for type checking, it can be
installed from PyPI. The Pylance extension for Visual Studio Code is
also based on Pyright. Problems that persist when using basedpyright
should be reported as issues on the NumPy github site.

This release supports Python 3.10-3.13.

Contributors

A total of 9 people contributed to this release. People with a "+" by
their names contributed a patch for the first time.

Charles Harris
Joren Hammudoglu
Matti Picus
Nathan Goldbaum
Peter Hawkins
Simon Altrogge
Thomas A Caswell
Warren Weckesser
Yang Wang +

Pull requests merged

A total of 12 pull requests were merged for this release.

#27935: MAINT: Prepare 2.2.x for further development
#27950: TEST: cleanups
#27958: BUG: fix use-after-free error in npy_hashtable.cpp (#27955)
#27959: BLD: add missing include
#27982: BUG:fix compile error libatomic link test to meson.build
#27990: TYP: Fix falsely rejected value types in ndarray.__setitem__
#27991: MAINT: Don't wrap #include <Python.h> with extern "C"
#27993: BUG: Fix segfault in stringdtype lexsort
#28006: MAINT: random: Tweak module code in mtrand.pyx to fix a Cython...
#28007: BUG: Cython API was missing NPY_UINTP.
#28021: CI: pin scipy-doctest to 1.5.1
#28044: TYP: allow None in operand sequence of nditer

Checksums

MD5

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780077d95eafc2ccc3ced969db22377b3864e5b9a0ea5eb347cc93b3ea900315...

NumPy 2.2.0 Release Notes

The NumPy 2.2.0 release is quick release that brings us back into sync
with the usual twice yearly release cycle. There have been an number of
small cleanups, as well as work bringing the new StringDType to
completion and improving support for free threaded Python. Highlights
are:

New functions matvec and vecmat, see below.
Many improved annotations.
Improved support for the new StringDType.
Improved support for free threaded Python
Fixes for f2py

This release supports Python versions 3.10-3.13.

Deprecations

_add_newdoc_ufunc is now deprecated. ufunc.__doc__ = newdoc
should be used instead.

(gh-27735)

Expired deprecations

bool(np.array([])) and other empty arrays will now raise an error.
Use arr.size > 0 instead to check whether an array has no
elements.

(gh-27160)

Compatibility notes

numpy.cov now properly transposes single-row (2d
array) design matrices when rowvar=False. Previously, single-row
design matrices would return a scalar in this scenario, which is not
correct, so this is a behavior change and an array of the
appropriate shape will now be returned.

(gh-27661)

New Features

New functions for matrix-vector and vector-matrix products

Two new generalized ufuncs were defined:
- numpy.matvec - matrix-vector product, treating the
  arguments as stacks of matrices and column vectors,
  respectively.
- numpy.vecmat - vector-matrix product, treating the
  arguments as stacks of column vectors and matrices,
  respectively. For complex vectors, the conjugate is taken.
These add to the existing numpy.matmul as well as to
numpy.vecdot, which was added in numpy 2.0.

Note that numpy.matmul never takes a complex
conjugate, also not when its left input is a vector, while both
numpy.vecdot and numpy.vecmat do take
the conjugate for complex vectors on the left-hand side (which are
taken to be the ones that are transposed, following the physics
convention).

(gh-25675)
np.complexfloating[T, T] can now also be written as
np.complexfloating[T]

(gh-27420)
UFuncs now support __dict__ attribute and allow overriding
__doc__ (either directly or via ufunc.__dict__["__doc__"]).
__dict__ can be used to also override other properties, such as
__module__ or __qualname__.

(gh-27735)
The "nbit" type parameter of np.number and its subtypes now
defaults to typing.Any. This way, type-checkers will infer
annotations such as x: np.floating as x: np.floating[Any], even
in strict mode.

(gh-27736)

Improvements

The datetime64 and timedelta64 hashes now correctly match the
Pythons builtin datetime and timedelta ones. The hashes now
evaluated equal even for equal values with different time units.

(gh-14622)
Fixed a number of issues around promotion for string ufuncs with
StringDType arguments. Mixing StringDType and the fixed-width DTypes
using the string ufuncs should now generate much more uniform
results.

(gh-27636)
Improved support for empty memmap. Previously an empty
memmap would fail unless a non-zero offset was set.
Now a zero-size memmap is supported even if
offset=0. To achieve this, if a memmap is mapped to
an empty file that file is padded with a single byte.

(gh-27723)
A regression has been fixed which allows F2PY users to expose variables
to Python in modules with only assignments, and also fixes situations
where multiple modules are present within a single source file.

(gh-27695)

Performance improvements and changes

Improved multithreaded scaling on the free-threaded build when many
threads simultaneously call the same ufunc operations.

(gh-27896)
NumPy now uses fast-on-failure attribute lookups for protocols. This
can greatly reduce overheads of function calls or array creation
especially with custom Python objects. The largest improvements will
be seen on Python 3.12 or newer.

(gh-27119)
OpenBLAS on x86_64 and i686 is built with fewer kernels. Based on
benchmarking, there are 5 clusters of performance around these
kernels: PRESCOTT NEHALEM SANDYBRIDGE HASWELL SKYLAKEX.
OpenBLAS on windows is linked without quadmath, simplifying
licensing
Due to a regression in OpenBLAS on windows, the performance
improvements when using multiple threads for OpenBLAS 0.3.26 were
reverted.

(gh-27147)
NumPy now indicates hugepages also for large np.zeros allocations
on linux. Thus should generally improve performance.

(gh-27808)

Changes

numpy.fix now won't perform casting to a floating
data-type for integer and boolean data-type input arrays.

(gh-26766)
The type annotations of numpy.float64 and numpy.complex128 now
reflect that they are also subtypes of the built-in float and
complex types, respectively. This update prevents static
type-checkers from reporting errors in cases such as:
```
x: float = numpy.float64(6.28)  # valid
z: complex = numpy.complex128(-1j)  # valid
```
(gh-27334)
The repr of arrays large enough to be summarized (i.e., where
elements are replaced with ...) now includes the shape of the
array, similar to what already was the case for arrays with zero
size and non-obvious shape. With this change, the shape is always
given when it cannot be inferred from the values. Note that while
written as shape=..., this argument cannot actually be passed in
to the np.array constructor. If you encounter problems, e.g., due
to failing doctests, you can use the print option legacy=2.1 to
get the old behaviour.

(gh-27482)
Calling __array_wrap__ directly on NumPy arrays or scalars now
does the right thing when return_scalar is passed (Added in NumPy
2). It is further safe now to call the scalar __array_wrap__ on a
non-scalar result.

(gh-27807)
Bump the musllinux CI image and wheels to 1_2 from 1_1. This is because
1_1 is end of life.

(gh-27088)
The NEP 50 promotion state settings are now removed. They were always
meant as temporary means for testing. A warning will be given if the
environment variable is set to anything but NPY_PROMOTION_STATE=weak
while _set_promotion_state and _get_promotion_state are removed. In
case code used _no_nep50_warning, a contextlib.nullcontext could be
used to replace it when not available.

(gh-27156)

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NumPy 2.2.0 Release Notes

The NumPy 2.2.0 release is a quick release that brings us back into sync
with the usual twice yearly release cycle. There have been an number of
small cleanups, as well as work bringing the new StringDType to
completion and improving support for free threaded Python. Highlights
are:

New functions matvec and vecmat, see below.
Many improved annotations.
Improved support for the new StringDType.
Improved support for free threaded Python
Fixes for f2py

This release supports Python versions 3.10-3.13.

Deprecations

_add_newdoc_ufunc is now deprecated. ufunc.__doc__ = newdoc
should be used instead.

(gh-27735)

Expired deprecations

bool(np.array([])) and other empty arrays will now raise an error.
Use arr.size > 0 instead to check whether an array has no
elements.

(gh-27160)

Compatibility notes

numpy.cov now properly transposes single-row (2d array) design matrices
when rowvar=False. Previously, single-row design matrices would return a
scalar in this scenario, which is not correct, so this is a behavior change
and an array of the appropriate shape will now be returned.

(gh-27661)

New Features

New functions for matrix-vector and vector-matrix products

Two new generalized ufuncs were defined:
- numpy.matvec - matrix-vector product, treating the
  arguments as stacks of matrices and column vectors,
  respectively.
- numpy.vecmat - vector-matrix product, treating the
  arguments as stacks of column vectors and matrices,
  respectively. For complex vectors, the conjugate is taken.
These add to the existing numpy.matmul as well as to
numpy.vecdot, which was added in numpy 2.0.

Note that numpy.matmul never takes a complex conjugate, also not when its
left input is a vector, while both numpy.vecdot and numpy.vecmat do
take the conjugate for complex vectors on the left-hand side (which are
taken to be the ones that are transposed, following the physics
convention).

(gh-25675)
np.complexfloating[T, T] can now also be written as
np.complexfloating[T]

(gh-27420)
UFuncs now support __dict__ attribute and allow overriding
__doc__ (either directly or via ufunc.__dict__["__doc__"]).
__dict__ can be used to also override other properties, such as
__module__ or __qualname__.

(gh-27735)
The "nbit" type parameter of np.number and its subtypes now
defaults to typing.Any. This way, type-checkers will infer
annotations such as x: np.floating as x: np.floating[Any], even
in strict mode.

(gh-27736)

Improvements

The datetime64 and timedelta64 hashes now correctly match the
Pythons builtin datetime and timedelta ones. The hashes now
evaluated equal even for equal values with different time units.

(gh-14622)
Fixed a number of issues around promotion for string ufuncs with
StringDType arguments. Mixing StringDType and the fixed-width DTypes
using the string ufuncs should now generate much more uniform
results.

(gh-27636)
Improved support for empty memmap. Previously an empty memmap would
fail unless a non-zero offset was set. Now a zero-size memmap is
supported even if offset=0. To achieve this, if a memmap is mapped to
an empty file that file is padded with a single byte.

(gh-27723)
f2py handles multiple modules and exposes variables again. A regression
has been fixed which allows F2PY users to expose variables to Python in
modules with only assignments, and also fixes situations where multiple
modules are present within a single source file.

(gh-27695)

Performance improvements and changes

NumPy now uses fast-on-failure attribute lookups for protocols. This
can greatly reduce overheads of function calls or array creation
especially with custom Python objects. The largest improvements will
be seen on Python 3.12 or newer.

(gh-27119)
OpenBLAS on x86_64 and i686 is built with fewer kernels. Based on
benchmarking, there are 5 clusters of performance around these
kernels: PRESCOTT NEHALEM SANDYBRIDGE HASWELL SKYLAKEX.
OpenBLAS on windows is linked without quadmath, simplifying
licensing
Due to a regression in OpenBLAS on windows, the performance
improvements when using multiple threads for OpenBLAS 0.3.26 were
reverted.

(gh-27147)
NumPy now indicates hugepages also for large np.zeros allocations
on linux. Thus should generally improve performance.

(gh-27808)

Changes

numpy.fix now won't perform casting to a floating
data-type for integer and boolean data-type input arrays.

(gh-26766)
The type annotations of numpy.float64 and numpy.complex128 now reflect
that they are also subtypes of the built-in float and complex types,
respe 1E79 ctively. This update prevents static type-checkers from reporting
errors in cases such as:
```
x: float = numpy.float64(6.28)  # valid
z: complex = numpy.complex128(-1j)  # valid
```
(gh-27334)
The repr of arrays large enough to be summarized (i.e., where
elements are replaced with ...) now includes the shape of the
array, similar to what already was the case for arrays with zero
size and non-obvious shape. With this change, the shape is always
given when it cannot be inferred from the values. Note that while
written as shape=..., this argument cannot actually be passed in
to the np.array constructor. If you encounter problems, e.g., due
to failing doctests, you can use the print option legacy=2.1 to
get the old behaviour.

(gh-27482)
Calling __array_wrap__ directly on NumPy arrays or scalars now
does the right thing when return_scalar is passed (Added in NumPy
2). It is further safe now to call the scalar __array_wrap__ on a
non-scalar result.

(gh-27807)
Bump the musllinux CI image and wheels to 1_2 from 1_1. This is because
1_1 is end of life.

(gh-27088)
NEP 50 promotion state option removed

The NEP 50 promotion state settings are now removed. They were always meant as
temporary means for testing. A warning will be given if the environment
variable is set to anything but NPY_PROMOTION_STATE=weak while
_set_promotion_state and _get_promotion_state are removed. In case code
used _no_nep50_warning, a contextlib.nullcontext could be used to replace
it when not available.

(gh-27156)

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1a00dd2343f8e...

NumPy 2.1.3 Release Notes

NumPy 2.1.3 is a maintenance release that fixes bugs and regressions
discovered after the 2.1.2 release. This release also adds support
for free threaded Python 3.13 on Windows.

The Python versions supported by this release are 3.10-3.13.

Improvements

Fixed a number of issues around promotion for string ufuncs with
StringDType arguments. Mixing StringDType and the fixed-width DTypes
using the string ufuncs should now generate much more uniform
results.

(gh-27636)

Changes

numpy.fix now won't perform casting to a floating
data-type for integer and boolean data-type input arrays.

(gh-26766)

Contributors

A total of 15 people contributed to this release. People with a "+" by
their names contributed a patch for the first time.

Abhishek Kumar +
Austin +
Benjamin A. Beasley +
Charles Harris
Christian Lorentzen
Marcel Telka +
Matti Picus
Michael Davidsaver +
Nathan Goldbaum
Peter Hawkins
Raghuveer Devulapalli
Ralf Gommers
Sebastian Berg
dependabot[bot]
kp2pml30 +

Pull requests merged

A total of 21 pull requests were merged for this release.

#27512: MAINT: prepare 2.1.x for further development
#27537: MAINT: Bump actions/cache from 4.0.2 to 4.1.1
#27538: MAINT: Bump pypa/cibuildwheel from 2.21.2 to 2.21.3
#27539: MAINT: MSVC does not support #warning directive
#27543: BUG: Fix user dtype can-cast with python scalar during promotion
#27561: DEV: bump python to 3.12 in environment.yml
#27562: BLD: update vendored Meson to 1.5.2
#27563: BUG: weighted quantile for some zero weights (#27549)
#27565: MAINT: Use miniforge for macos conda test.
#27566: BUILD: satisfy gcc-13 pendantic errors
#27569: BUG: handle possible error for PyTraceMallocTrack
#27570: BLD: start building Windows free-threaded wheels [wheel build]
#27571: BUILD: vendor tempita from Cython
#27574: BUG: Fix warning "differs in levels of indirection" in npy_atomic.h...
#27592: MAINT: Update Highway to latest
#27593: BUG: Adjust numpy.i for SWIG 4.3 compatibility
#27616: BUG: Fix Linux QEMU CI workflow
#27668: BLD: Do not set __STDC_VERSION__ to zero during build
#27669: ENH: fix wasm32 runtime type error in numpy._core
#27672: BUG: Fix a reference count leak in npy_find_descr_for_scalar.
#27673: BUG: fixes for StringDType/unicode promoters

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117574ee1a645e63a6d69e20c8673665  numpy-2.1.3-cp312-cp312-win_amd64.whl
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b431935148221b79bda9490b1d069e3c  numpy-2.1.3-cp313-cp313-macosx_14_0_arm64.whl
b3ff577c78097b187bd58f20b6e88642  numpy-2.1.3-cp313-cp313-macosx_14_0_x86_64.whl
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85786d12388d60b904c02eb12df55b37  numpy-2.1.3-cp313-cp313-musllinux_1_1_x86_64.whl
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4f0c3f8c81cb6bd43a9f1f7bef7db82d  numpy-2.1.3-cp313-cp313t-macosx_10_13_x86_64.whl
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209f55dc1ed6da23a5ea3e11ca962308  numpy-2.1.3-cp313-cp313t-musllinux_1_1_x86_64.whl
06a1792849b601c7bdd38e39bc5cb5f1  numpy-2.1.3-cp313-cp313t-musllinux_1_2_aarch64.whl
86630bf207e8cbe6933232cb2a47a6c0  numpy-2.1.3-cp313-cp313t-win32.whl
6af9109b82c0acdcf8b0e81dc0e4c517  numpy-2.1.3-cp313-cp313t-win_amd64.whl
c7e821e086346afc0078acb237f30431  numpy-2.1.3-pp310-pypy310_pp73-macosx_10_15_x86_64.whl
5b938b2da78b1c84044df8cdb2e8e63a  numpy-2.1.3-pp310-pypy310_pp73-macosx_14_0_x86_64.whl
ef251f3b6aa022b1c2fac14889d6d9d3  numpy-2.1.3-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
356c7bb6067ae0dccc4a54efc1879e74  numpy-2.1.3-pp310-pypy310_pp73-win_amd64.whl
11096358375945114577a0c82b2c6038  numpy-2.1.3.tar.gz

SHA256

c894b4305373b9c5576d7a12b473702afdf48ce5369c074ba304cc5ad8730dff  numpy-2.1.3-cp310-cp310-macosx_10_9_x86_64.whl
b47fbb433d3260adcd51eb54f92a2ffbc90a4595f8970ee00e064c644ac788f5  numpy-2.1.3-cp310-cp310-macosx_11_0_arm64.whl
825656d0743699c529c5943554d223c021ff0494ff1442152ce887ef4f7561a1  numpy-2.1.3-cp310-cp310-macosx_14_0_arm64.whl
6a4825252fcc430a182ac4dee5a505053d262c807f8a924603d411f6718b88fd  numpy-2.1.3-cp310-cp310-macosx_14_0_x86_64.whl
e711e02f49e176a01d0349d82cb5f05ba4db7d5e7e0defd026328e5cfb3226d3  numpy-2.1.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
78574ac2d1a4a02421f25da9559850d59457bac82f2b8d7a44fe83a64f770098  numpy-2.1.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
c7662f0e3673fe4e832fe07b65c50342ea27d989f92c80355658c7f888fcc83c  numpy-2.1.3-cp310-cp310-musllinux_1_1_x86_64.whl
fa2d1337dc61c8dc417fbccf20f6d1e139896a30721b7f1e832b2bb6ef4eb6c4  numpy-2.1.3-cp310-cp310-musllinux_1_2_aarch64.whl
72dcc4a35a8515d83e76b58fdf8113a5c969ccd505c8a946759b24e3182d1f23  numpy-2.1.3-cp310-cp310-win32.whl
ecc76a9ba2911d8d37ac01de72834d8849e55473457558e12995f4cd53e778e0  numpy-2.1.3-cp310-cp310-win_amd64.whl
4d1167c53b93f1f5d8a139a742b3c6f4d429b54e74e6b57d0eff40045187b15d  numpy-2.1.3-cp311-cp311-macosx_10_9_x86_64.whl
c80e4a09b3d95b4e1cac08643f1152fa71a0a821a2d4277334c88d54b2219a41  numpy-2.1.3-cp311-cp311-macosx_11_0_arm64.whl
576a1c...

NumPy 2.1.2 Release Notes

NumPy 2.1.2 is a maintenance release that fixes bugs and regressions
discovered after the 2.1.1 release.

The Python versions supported by this release are 3.10-3.13.

Contributors

A total of 11 people contributed to this release. People with a "+" by
their names contributed a patch for the first time.

Charles Harris
Chris Sidebottom
Ishan Koradia +
João Eiras +
Katie Rust +
Marten van Kerkwijk
Matti Picus
Nathan Goldbaum
Peter Hawkins
Pieter Eendebak
Slava Gorloff +

Pull requests merged

A total of 14 pull requests were merged for this release.

#27333: MAINT: prepare 2.1.x for further development
#27400: BUG: apply critical sections around populating the dispatch cache
#27406: BUG: Stub out get_build_msvc_version if distutils.msvccompiler...
#27416: BUILD: fix missing include for std::ptrdiff_t for C++23 language...
#27433: BLD: pin setuptools to avoid breaking numpy.distutils
#27437: BUG: Allow unsigned shift argument for np.roll
#27439: BUG: Disable SVE VQSort
#27471: BUG: rfftn axis bug
#27479: BUG: Fix extra decref of PyArray_UInt8DType.
#27480: CI: use PyPI not scientific-python-nightly-wheels for CI doc...
#27481: MAINT: Check for SVE support on demand
#27484: BUG: initialize the promotion state to be weak
#27501: MAINT: Bump pypa/cibuildwheel from 2.20.0 to 2.21.2
#27506: BUG: avoid segfault on bad arguments in ndarray.__array_function__

Checksums

MD5

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172614423a82ef73d8752ad8a59cbafc  numpy-2.1.2-cp310-cp310-macosx_11_0_arm64.whl
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33f4d63f81ad85c1ea873197f2189d89  numpy-2.1.2-cp313-cp313t-musllinux_1_2_aarch64.whl
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e7cf2857582d507dfa3e8644dd3562a6  numpy-2.1.2-pp310-pypy310_pp73-macosx_14_0_x86_64.whl
9e3d44cb302c629c00fde8f25809b04d  numpy-2.1.2-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
3f97ee2d9962cf9d84624f725bdd2a8f  numpy-2.1.2-pp310-pypy310_pp73-win_amd64.whl
3d92e07d34f60dbac6b82a0982a98757  numpy-2.1.2.tar.gz

SHA256

30d53720b726ec36a7f88dc873f0eec8447fbc93d93a8f079dfac2629598d6ee  numpy-2.1.2-cp310-cp310-macosx_10_9_x86_64.whl
e8d3ca0a72dd8846eb6f7dfe8f19088060fcb76931ed592d29128e0219652884  numpy-2.1.2-cp310-cp310-macosx_11_0_arm64.whl
fc44e3c68ff00fd991b59092a54350e6e4911152682b4782f68070985aa9e648  numpy-2.1.2-cp310-cp310-macosx_14_0_arm64.whl
7c1c60328bd964b53f8b835df69ae8198659e2b9302ff9ebb7de4e5a5994db3d  numpy-2.1.2-cp310-cp310-macosx_14_0_x86_64.whl
6cdb606a7478f9ad91c6283e238544451e3a95f30fb5467fbf715964341a8a86  numpy-2.1.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
d666cb72687559689e9906197e3bec7b736764df6a2e58ee265e360663e9baf7  numpy-2.1.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
c6eef7a2dbd0abfb0d9eaf78b73017dbfd0b54051102ff4e6a7b2980d5ac1a03  numpy-2.1.2-cp310-cp310-musllinux_1_1_x86_64.whl
12edb90831ff481f7ef5f6bc6431a9d74dc0e5ff401559a71e5e4611d4f2d466  numpy-2.1.2-cp310-cp310-musllinux_1_2_aarch64.whl
a65acfdb9c6ebb8368490dbafe83c03c7e277b37e6857f0caeadbbc56e12f4fb  numpy-2.1.2-cp310-cp310-win32.whl
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8e00ea6fc82e8a804433d3e9cedaa1051a1422cb6e443011590c14d2dea59146  numpy-2.1.2-cp311-cp311-musllinux_1_2_aarch64.whl
5006b13a06e0b38d561fab5ccc37581f23c9511879be7693bd33c7cd15ca227c  numpy-2.1.2-cp311-cp311-win32.whl
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d7bf0a4f9f15b32b5ba53147369e94296f5fffb783db5aacc1be15b4bf72f43b  numpy-2.1.2-cp312-cp312-macosx_10_13_x86_64.whl
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f751ed0a2f250541e19dfca9f1eafa31a392c71c832b6bb9e113b10d050cb0f1  numpy-2.1.2-cp312-cp312-macosx_14_0_arm64.whl
bd33f82e95ba7ad632bc57837ee99dba3d7e006536200c4e9124089e1bf42426  numpy-2.1.2-cp312-cp312-macosx_14_0_x86_64.whl
1b8cde4f11f0a975d1fd59373b32e2f5a562ade7cde4f85b7137f3de8fbb29a0  numpy-2.1.2-cp312-cp312-manylinux_2_17_...

NumPy 2.1.1 Release Notes

NumPy 2.1.1 is a maintenance release that fixes bugs and regressions
discovered after the 2.1.0 release.

The Python versions supported by this release are 3.10-3.13.

Contributors

A total of 7 people contributed to this release. People with a "+" by
their names contributed a patch for the first time.

Andrew Nelson
Charles Harris
Mateusz Sokół
Maximilian Weigand +
Nathan Goldbaum
Pieter Eendebak
Sebastian Berg

Pull requests merged

A total of 10 pull requests were merged for this release.

#27236: REL: Prepare for the NumPy 2.1.0 release [wheel build]
#27252: MAINT: prepare 2.1.x for further development
#27259: BUG: revert unintended change in the return value of set_printoptions
#27266: BUG: fix reference counting bug in __array_interface__ implementation...
#27267: TST: Add regression test for missing descr in array-interface
#27276: BUG: Fix #27256 and #27257
#27278: BUG: Fix array_equal for numeric and non-numeric scalar types
#27287: MAINT: Update maintenance/2.1.x after the 2.0.2 release
#27303: BLD: cp311- macosx_arm64 wheels [wheel build]
#27304: BUG: f2py: better handle filtering of public/private subroutines

Checksums

MD5

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SHA256

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950802d17a33c07cba7fd7c3dcfa7d64...

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