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Releases: numpy/numpy
v2.3.1 (Jun 21, 2025)
4d833e5Compare
NumPy 2.3.1 Release Notes
The NumPy 2.3.1 release is a patch release with several bug fixes,
annotation improvements, and better support for OpenBSD. Highlights are:
- Fix bug in
matmulfor non-contiguous out kwarg parameter - Fix for Accelerate runtime warnings on M4 hardware
- Fix new in NumPy 2.3.0
np.vectorizecasting errors - Improved support of cpu features for FreeBSD and OpenBSD
This release supports Python versions 3.11-3.13, Python 3.14 will be
supported when it is released.
Contributors
A total of 9 people contributed to this release. People with a "+" by
their names contributed a patch for the first time.
- Brad Smith +
- Charles Harris
- Developer-Ecosystem-Engineering
- François Rozet
- Joren Hammudoglu
- Matti Picus
- Mugundan Selvanayagam
- Nathan Goldbaum
- Sebastian Berg
Pull requests merged
A total of 12 pull requests were merged for this release.
- #29140: MAINT: Prepare 2.3.x for further development
- #29191: BUG: fix matmul with transposed out arg (#29179)
- #29192: TYP: Backport typing fixes and improvements.
- #29205: BUG: Revert
np.vectorizecasting to legacy behavior (#29196) - #29222: TYP: Backport typing fixes
- #29233: BUG: avoid negating unsigned integers in resize implementation...
- #29234: TST: Fix test that uses uninitialized memory (#29232)
- #29235: BUG: Address interaction between SME and FPSR (#29223)
- #29237: BUG: Enforce integer limitation in concatenate (#29231)
- #29238: CI: Add support for building NumPy with LLVM for Win-ARM64
- #29241: ENH: Detect CPU features on OpenBSD ARM and PowerPC64
- #29242: ENH: Detect CPU features on FreeBSD / OpenBSD RISC-V64.
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v2.3.0 (June 7, 2025)
0532af4Compare
NumPy 2.3.0 Release Notes
The NumPy 2.3.0 release continues the work to improve free threaded
Python support and annotations together with the usual set of bug fixes.
It is unusual in the number of expired deprecations, code
modernizations, and style cleanups. The latter may not be visible to
users, but is important for code maintenance over the long term. Note
that we have also upgraded from manylinux2014 to manylinux_2_28.
Users running on a Mac having an M4 cpu might see various warnings about
invalid values and such. The warnings are a known problem with
Accelerate. They are annoying, but otherwise harmless. Apple promises to
fix them.
This release supports Python versions 3.11-3.13, Python 3.14 will be
supported when it is released.
Highlights
- Interactive examples in the NumPy documentation.
- Building NumPy with OpenMP Parallelization.
- Preliminary support for Windows on ARM.
- Improved support for free threaded Python.
- Improved annotations.
New functions
New functionnumpy.strings.slice
The new functionnumpy.strings.slice was added, which implements fast
native slicing of string arrays. It supports the full slicing API
including negative slice offsets and steps.
(gh-27789)
Deprecations
The
numpy.typing.mypy_pluginhas been deprecated in favor of
platform-agnostic static type inference. Please removenumpy.typing.mypy_pluginfrom thepluginssection of your mypy
configuration. If this change results in new errors being reported,
kindly open an issue.(gh-28129)
The
numpy.typing.NBitBasetype has been deprecated and will be
removed in a future version.This type was previously intended to be used as a generic upper
bound for type-parameters, for example:importnumpyasnpimportnumpy.typingasnptdeff[NT:npt.NBitBase](x:np.complexfloating[NT])->np.floating[NT]: ...
But in NumPy 2.2.0,
float64andcomplex128were changed to
concrete subtypes, causing static type-checkers to rejectx: np.float64 = f(np.complex128(42j)).So instead, the better approach is to use
typing.overload:importnumpyasnpfromtypingimportoverload@overloaddeff(x:np.complex64)->np.float32: ...@overloaddeff(x:np.complex128)->np.float64: ...@overloaddeff(x:np.clongdouble)->np.longdouble: ...
(gh-28884)
Expired deprecations
Remove deprecated macros like
NPY_OWNDATAfrom Cython interfaces
in favor ofNPY_ARRAY_OWNDATA(deprecated since 1.7)(gh-28254)
Remove
numpy/npy_1_7_deprecated_api.hand C macros likeNPY_OWNDATAin favor ofNPY_ARRAY_OWNDATA(deprecated since 1.7)(gh-28254)
Remove alias
generate_divbyzero_errortonpy_set_floatstatus_divbyzeroandgenerate_overflow_errortonpy_set_floatstatus_overflow(deprecated since 1.10)(gh-28254)
Remove
np.tostring(deprecated since 1.19)(gh-28254)
Raise on
np.conjugateof non-numeric types (deprecated since 1.13)(gh-28254)
Raise when using
np.bincount(...minlength=None), use 0 instead
(deprecated since 1.14)(gh-28254)
Passing
shape=Noneto functions with a non-optional shape argument
errors, use()instead (deprecated since 1.20)(gh-28254)
Inexact matches for
modeandsearchsideraise (deprecated since
1.20)(gh-28254)
Setting
__array_finalize__ = Noneerrors (deprecated since 1.23)(gh-28254)
np.fromfileandnp.fromstringerror on bad data, previously they
would guess (deprecated since 1.18)(gh-28254)
datetime64andtimedelta64construction with a tuple no longer
accepts aneventvalue, either use a two-tuple of (unit, num) or a
4-tuple of (unit, num, den, 1) (deprecated since 1.14)(gh-28254)
When constructing a
dtypefrom a class with adtypeattribute,
that attribute must be a dtype-instance rather than a thing that can
be parsed as a dtype instance (deprecated in 1.19). At some point
the whole construct of using a dtype attribute will be deprecated
(see#25306)(gh-28254)
Passing booleans as partition index errors (deprecated since 1.23)
(gh-28254)
Out-of-bounds indexes error even on empty arrays (deprecated since
1.20)(gh-28254)
np.tostringhas been removed, usetobytesinstead (deprecated
since 1.19)(gh-28254)
Disallow make a non-writeable array writeable for arrays with a base
that do not own their data (deprecated since 1.17)(gh-28254)
concatenate()withaxis=Noneusessame-kindcasting by
default, notunsafe(deprecated since 1.20)(gh-28254)
Unpickling a scalar with object dtype errors (deprecated since 1.20)
(gh-28254)
The binary mode of
fromstringnow errors, usefrombufferinstead
(deprecated since 1.14)(gh-28254)
Converting
np.inexactornp.floatingto a dtype errors
(deprecated since 1.19)(gh-28254)
Converting
np.complex,np.integer,np.signedinteger,np.unsignedinteger,np.genericto a dtype errors (deprecated
since 1.19)(gh-28254)
The Python built-in
rounderrors for complex scalars. Usenp.roundorscalar.roundinstead (deprecated since 1.19)(gh-28254)
'np.bool' scalars can no longer be interpreted as an index
(deprecated since 1.19)(gh-28254)
Parsing an integer via a float string is no longer supported.
(deprecated since 1.23) To avoid this error you can- make sure the original data is stored as integers.
- use the
converters=floatkeyword argument. - Use
np.loadtxt(...).astype(np.int64)
(gh-28254)
The use of a length 1 tuple for the ufunc
signatureerrors. Usedtypeor fill the tuple withNone(deprecated since 1.19)(gh-28254)
Special handling of matrix is in np.outer is removed. Convert to a
ndarray viamatrix.A(deprecated since 1.20)(gh-28254)
Removed the
np.compatpackage source code (removed in 2.0)(gh-28961)
C API changes
NpyIter_GetTransferFlagsis now available to check if the iterator
needs the Python API or if casts may cause floating point errors
(FPE). FPEs can for example be set when castingfloat64(1e300)tofloat32(overflow to infinity) or a NaN to an integer (invalid
value).(gh-27883)
NpyIternow has no limit on the number of operands it supports.(gh-28080)
NewNpyIter_GetTransferFlags andNpyIter_IterationNeedsAPI change
NumPy now has the newNpyIter_GetTransferFlags function as a more
precise way checking of iterator/buffering needs. I.e. whether the
Python API/GIL is required or floating point errors may occur. This
function is also faster if you already know your needs without
buffering.
TheNpyIter_IterationNeedsAPI function now performs all the checks
that were previously performed at setup time. While it was never
necessary to call it multiple times, doing so will now have a larger
cost.
(gh-27998)
New Features
The type parameter of
np.dtypenow defaults totyping.Any. This
way, static type-checkers will inferdtype: np.dtypeasdtype: np.dtype[Any], without reporting an error.(gh-28669)
Static type-checkers now interpret:
_: np.ndarrayas_: npt.NDArray[typing.Any]._: np.flatiteras_: np.flatiter[np.ndarray].
This is because their type parameters now have default values.
(gh-28940)
NumPy now registers its pkg-config paths with thepkgconf PyPI package
Thepkgconf PyPI
package provides an interface for projects like NumPy to register their
own paths to be added to the pkg-config search path. This means that
when usingpkgconf
from PyPI, NumPy will be discoverable without needin...
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v2.3.0rc1 (May 25, 2025)
3abd587Compare
NumPy 2.3.0 Release Notes
The NumPy 2.3.0 release continues the work to improve free threaded
Python support and annotations together with the usual set of bug fixes.
It is unusual in the number of expired deprecations and the number of
code modernizations and style cleanups. The latter may not be visible to
users, but is important for code maintenance over the long term. Note
that we have also upgraded from manylinux2014 to manylinux_2_28.
There are known test failures in the rc1 release involving MyPy and
PyPy. The cause of both has been determined and fixes will be applied
before the final release. The current Windows on ARM wheels also lack
OpenBLAS, but they should suffice for initial downstream testing.
OpenBLAS will be incorporated in those wheels when it becomes available.
This release supports Python versions 3.11-3.13, Python 3.14 will be
supported when it is released.
Highlights
- Interactive examples in the NumPy documentation.
- Building NumPy with OpenMP Parallelization.
- Preliminary support for Windows on ARM.
- Improved support for free threaded Python.
- Improved annotations.
New functions
New functionnumpy.strings.slice
The new functionnumpy.strings.slice was added, which implements fast
native slicing of string arrays. It supports the full slicing API
including negative slice offsets and steps.
(gh-27789)
Deprecations
The
numpy.typing.mypy_pluginhas been deprecated in favor of
platform-agnostic static type inference. Please removenumpy.typing.mypy_pluginfrom thepluginssection of your mypy
configuration. If this change results in new errors being reported,
kindly open an issue.(gh-28129)
The
numpy.typing.NBitBasetype has been deprecated and will be
removed in a future version.This type was previously intended to be used as a generic upper
bound for type-parameters, for example:importnumpyasnpimportnumpy.typingasnptdeff[NT:npt.NBitBase](x:np.complexfloating[NT])->np.floating[NT]: ...
But in NumPy 2.2.0,
float64andcomplex128were changed to
concrete subtypes, causing static type-checkers to rejectx: np.float64 = f(np.complex128(42j)).So instead, the better approach is to use
typing.overload:importnumpyasnpfromtypingimportoverload@overloaddeff(x:np.complex64)->np.float32: ...@overloaddeff(x:np.complex128)->np.float64: ...@overloaddeff(x:np.clongdouble)->np.longdouble: ...
(gh-28884)
Expired deprecations
Remove deprecated macros like
NPY_OWNDATAfrom Cython interfaces
in favor ofNPY_ARRAY_OWNDATA(deprecated since 1.7)(gh-28254)
Remove
numpy/npy_1_7_deprecated_api.hand C macros likeNPY_OWNDATAin favor ofNPY_ARRAY_OWNDATA(deprecated since 1.7)(gh-28254)
Remove alias
generate_divbyzero_errortonpy_set_floatstatus_divbyzeroandgenerate_overflow_errortonpy_set_floatstatus_overflow(deprecated since 1.10)(gh-28254)
Remove
np.tostring(deprecated since 1.19)(gh-28254)
Raise on
np.conjugateof non-numeric types (deprecated since 1.13)(gh-28254)
Raise when using
np.bincount(...minlength=None), use 0 instead
(deprecated since 1.14)(gh-28254)
Passing
shape=Noneto functions with a non-optional shape argument
errors, use()instead (deprecated since 1.20)(gh-28254)
Inexact matches for
modeandsearchsideraise (deprecated since
1.20)(gh-28254)
Setting
__array_finalize__ = Noneerrors (deprecated since 1.23)(gh-28254)
np.fromfileandnp.fromstringerror on bad data, previously they
would guess (deprecated since 1.18)(gh-28254)
datetime64andtimedelta64construction with a tuple no longer
accepts aneventvalue, either use a two-tuple of (unit, num) or a
4-tuple of (unit, num, den, 1) (deprecated since 1.14)(gh-28254)
When constructing a
dtypefrom a class with adtypeattribute,
that attribute must be a dtype-instance rather than a thing that can
be parsed as a dtype instance (deprecated in 1.19). At some point
the whole construct of using a dtype attribute will be deprecated
(see#25306)(gh-28254)
Passing booleans as partition index errors (deprecated since 1.23)
(gh-28254)
Out-of-bounds indexes error even on empty arrays (deprecated since
1.20)(gh-28254)
np.tostringhas been removed, usetobytesinstead (deprecated
since 1.19)(gh-28254)
Disallow make a non-writeable array writeable for arrays with a base
that do not own their data (deprecated since 1.17)(gh-28254)
concatenate()withaxis=Noneusessame-kindcasting by
default, notunsafe(deprecated since 1.20)(gh-28254)
Unpickling a scalar with object dtype errors (deprecated since 1.20)
(gh-28254)
The binary mode of
fromstringnow errors, usefrombufferinstead
(deprecated since 1.14)(gh-28254)
Converting
np.inexactornp.floatingto a dtype errors
(deprecated since 1.19)(gh-28254)
Converting
np.complex,np.integer,np.signedinteger,np.unsignedinteger,np.genericto a dtype errors (deprecated
since 1.19)(gh-28254)
The Python built-in
rounderrors for complex scalars. Usenp.roundorscalar.roundinstead (deprecated since 1.19)(gh-28254)
'np.bool' scalars can no longer be interpreted as an index
(deprecated since 1.19)(gh-28254)
Parsing an integer via a float string is no longer supported.
(deprecated since 1.23) To avoid this error you can- make sure the original data is stored as integers.
- use the
converters=floatkeyword argument. - Use
np.loadtxt(...).astype(np.int64)
(gh-28254)
The use of a length 1 tuple for the ufunc
signatureerrors. Usedtypeor fill the tuple withNone(deprecated since 1.19)(gh-28254)
Special handling of matrix is in np.outer is removed. Convert to a
ndarray viamatrix.A(deprecated since 1.20)(gh-28254)
Removed the
np.compatpackage source code (removed in 2.0)(gh-28961)
C API changes
NpyIter_GetTransferFlagsis now available to check if the iterator
needs the Python API or if casts may cause floating point errors
(FPE). FPEs can for example be set when castingfloat64(1e300)tofloat32(overflow to infinity) or a NaN to an integer (invalid
value).(gh-27883)
NpyIternow has no limit on the number of operands it supports.(gh-28080)
NewNpyIter_GetTransferFlags andNpyIter_IterationNeedsAPI change
NumPy now has the newNpyIter_GetTransferFlags function as a more
precise way checking of iterator/buffering needs. I.e. whether the
Python API/GIL is required or floating point errors may occur. This
function is also faster if you already know your needs without
buffering.
TheNpyIter_IterationNeedsAPI function now performs all the checks
that were previously performed at setup time. While it was never
necessary to call it multiple times, doing so will now have a larger
cost.
(gh-27998)
New Features
The type parameter of
np.dtypenow defaults totyping.Any. This
way, static type-checkers will inferdtype: np.dtypeasdtype: np.dtype[Any], without reporting an error.(gh-28669)
Static type-checkers now interpret:
_: np.ndarrayas_: npt.NDArray[typing.Any]._: np.flatiteras_: np.flatiter[np.ndarray].
This is because their type parameters now have default values.
(gh-28940)
NumPy now registers its pkg-config paths with thepkgconf PyPI package
Thepkgconf PyPI
package provides an interface for projects like NumPy to register their
own paths to be added to the pkg-config search path...
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v2.2.6 (May 17, 2025)
2b686f6Compare
NumPy 2.2.6 Release Notes
NumPy 2.2.6 is a patch release that fixes bugs found after the 2.2.5
release. It is a mix 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 8 people contributed to this release. People with a "+" by
their names contributed a patch for the first time.
- Charles Harris
- Ilhan Polat
- Joren Hammudoglu
- Marco Gorelli +
- Matti Picus
- Nathan Goldbaum
- Peter Hawkins
- Sayed Adel
Pull requests merged
A total of 11 pull requests were merged for this release.
- #28778: MAINT: Prepare 2.2.x for further development
- #28851: BLD: Update vendor-meson to fix module_feature conflicts arguments...
- #28852: BUG: fix heap buffer overflow in np.strings.find
- #28853: TYP: fix
NDArray[floating] + floatreturn type - #28864: BUG: fix stringdtype singleton thread safety
- #28865: MAINT: use OpenBLAS 0.3.29
- #28889: MAINT: from_dlpack thread safety fixes
- #28913: TYP: Fix non-existent
CanIndexannotation inndarray.setfield - #28915: MAINT: Avoid dereferencing/strict aliasing warnings
- #28916: BUG: Fix missing check for PyErr_Occurred() in _pyarray_correlate.
- #28966: TYP: reject complex scalar types in ndarray.__ifloordiv__
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v2.2.5 (Apr 19, 2025)
7be8c1fCompare
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()tostrinsavetxt - #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 fordtype[bool] - #28705: TYP: Fix false rejection of
NDArray[object_].__abs__() - #28706: TYP: Fix inconsistent
NDArray[float64].__[r]truediv__return... - #28723: TYP: fix string-like
ndarrayrich comparison operators - #28758: TYP: some
[arg]partitionfixes - #28772: TYP: fix incorrect
random.Generator.integersreturn type - #28774: TYP: fix
count_nonzerosignature
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2.2.4 (Mar 16, 2025)
3b37785Compare
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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2.2.3 (Feb 13, 2025)
a274561Compare
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_positionalerrors 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
float64in the set-ops - #28249: BLD: better fix for clang / ARM compiles
- #28266: TYP: Fix
timedelta64.__divmod__andtimedelta64.__mod__... - #28274: TYP: Fixed missing typing information of set_printoptions
- #28278: BUG: backport resource cleanup bugfix fromgh-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.testingmodules - #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
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2.2.2 (Jan 18, 2025)
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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
voidarrays not acceptingstrkeys in__setitem__ - #28066: TYP: fix unnecessarily broad
integerbinop return types (#28065) - #28112: TYP: Better
ndarraybinop return types forfloat64&... - #28113: TYP: Return the correct
boolfromissubdtype - #28114: TYP: Always accept
date[time]in thedatetime64constructor - #28120: BUG: Fix auxdata initialization in ufunc slow path
- #28131: BUG: move reduction initialization to ufunc initialization
- #28132: TYP: Fix
interpto 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
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2.2.1 (DEC 21, 2024)
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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>withextern "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
Nonein operand sequence of nditer
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2.2.0 (Dec 8, 2024)
e7a123bCompare
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
matvecandvecmat, 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_ufuncis 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.
Usearr.size > 0instead to check whether an array has no
elements.(gh-27160)
Compatibility notes
numpy.covnow properly transposes single-row (2d
array) design matrices whenrowvar=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.matmulas well as tonumpy.vecdot, which was added in numpy 2.0.Note that
numpy.matmulnever takes a complex
conjugate, also not when its left input is a vector, while bothnumpy.vecdotandnumpy.vecmatdo 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 asnp.complexfloating[T](gh-27420)
UFuncs now support
__dict__attribute and allow overriding__doc__(either directly or viaufunc.__dict__["__doc__"]).__dict__can be used to also override other properties, such as__module__or__qualname__.(gh-27735)
The "nbit" type parameter of
np.numberand its subtypes now
defaults totyping.Any. This way, type-checkers will infer
annotations such asx: np.floatingasx: np.floating[Any], even
in strict mode.(gh-27736)
Improvements
The
datetime64andtimedelta64hashes now correctly match the
Pythons builtindatetimeandtimedeltaones. 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 emptymemmapwould fail unless a non-zerooffsetwas set.
Now a zero-sizememmapis supported even ifoffset=0. To achieve this, if amemmapis 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
licensingDue 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.zerosallocations
on linux. Thus should generally improve performance.(gh-27808)
Changes
numpy.fixnow won't perform casting to a floating
data-type for integer and boolean data-type input arrays.(gh-26766)
The type annotations of
numpy.float64andnumpy.complex128now
reflect that they are also subtypes of the built-infloatandcomplextypes, respectively. This update prevents static
type-checkers from reporting errors in cases such as:x:float=numpy.float64(6.28)# validz:complex=numpy.complex128(-1j)# valid
(gh-27334)
The
reprof arrays large enough to be summarized (i.e., where
elements are replaced with...) now includes theshapeof 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 asshape=..., this argument cannot actually be passed in
to thenp.arrayconstructor. If you encounter problems, e.g., due
to failing doctests, you can use the print optionlegacy=2.1to
get the old behaviour.(gh-27482)
Calling
__array_wrap__directly on NumPy arrays or scalars now
does the right thing whenreturn_scalaris 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 isend 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 butNPY_PROMOTION_STATE=weak
while_set_promotion_stateand_get_promotion_stateare removed. In
case code used_no_nep50_warning, acontextlib.nullcontextcould be
used to replace it when not available.(gh-27156)
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