NumPy 2.4.0 Release Notes

The NumPy 2.4.0 release continues the work to improve free threaded Python
support, user dtypes implementation, and annotations. There are many expired
deprecations and bug fixes as well.

This release supports Python versions 3.11-3.14

Highlights

Apart from annotations and same_value kwarg, the 2.4 highlights are mostly
of interest to downstream developers. They should help in implementing new user
dtypes.

• Many annotation improvements. In particular, runtime signature introspection.
• New casting kwarg 'same_value' for casting by value.
• New PyUFunc_AddLoopsFromSpec function that can be used to add user sort
  loops using the ArrayMethod API.
• New __numpy_dtype__ protocol.

Deprecations

Setting the strides attribute is deprecated

Setting the strides attribute is now deprecated since mutating
an array is unsafe if an array is shared, especially by multiple
threads. As an alternative, you can create a new view (no copy) via:

• np.lib.stride_tricks.strided_window_view if applicable,
• np.lib.stride_tricks.as_strided for the general case,
• or the np.ndarray constructor (buffer is the original array) for a
  light-weight version.

(gh-28925)

Positional out argument to np.maximum, np.minimum is deprecated

Passing the output array out positionally to numpy.maximum and
numpy.minimum is deprecated. For example, np.maximum(a, b, c) will emit
a deprecation warning, since c is treated as the output buffer rather than
a third input.

Always pass the output with the keyword form, e.g. np.maximum(a, b, out=c).
This makes intent clear and simplifies type annotations.

(gh-29052)

align= must be passed as boolean to np.dtype()

When creating a new dtype a VisibleDeprecationWarning will be given if
align= is not a boolean. This is mainly to prevent accidentally passing a
subarray align flag where it has no effect, such as np.dtype("f8", 3)
instead of np.dtype(("f8", 3)). We strongly suggest to always pass
align= as a keyword argument.

(gh-29301)

Assertion and warning control utilities are deprecated

np.testing.assert_warns and np.testing.suppress_warnings are
deprecated. Use warnings.catch_warnings, warnings.filterwarnings,
pytest.warns, or pytest.filterwarnings instead.

(gh-29550)

np.fix is pending deprecation

The numpy.fix function will be deprecated in a future release. It is
recommended to use numpy.trunc instead, as it provides the same
functionality of truncating decimal values to their integer parts. Static type
checkers might already report a warning for the use of numpy.fix.

(gh-30168)

in-place modification of ndarray.shape is pending deprecation

Setting the ndarray.shape attribute directly will be deprecated in a future
release. Instead of modifying the shape in place, it is recommended to use the
numpy.reshape function. Static type checkers might already report a
warning for assignments to ndarray.shape.

(gh-30282)

Deprecation of numpy.lib.user_array.container

The numpy.lib.user_array.container class is deprecated and will be removed
in a future version.

(gh-30284)

Expired deprecations

Removed deprecated MachAr runtime discovery mechanism.

(gh-29836)

Raise TypeError on attempt to convert array with ndim > 0 to scalar

Conversion of an array with ndim > 0 to a scalar was deprecated in NumPy
1.25. Now, attempting to do so raises TypeError. Ensure you extract a
single element from your array before performing this operation.

(gh-29841)

Removed numpy.linalg.linalg and numpy.fft.helper

The following were deprecated in NumPy 2.0 and have been moved to private
modules:

• numpy.linalg.linalg
  Use numpy.linalg instead.
• numpy.fft.helper
  Use numpy.fft instead.

(gh-29909)

Removed interpolation parameter from quantile and percentile functions

The interpolation parameter was deprecated in NumPy 1.22.0 and has been
removed from the following functions:

• numpy.percentile
• numpy.nanpercentile
• numpy.quantile
• numpy.nanquantile

Use the method parameter instead.

(gh-29973)

Removed numpy.in1d

numpy.in1d has been deprecated since NumPy 2.0 and is now removed in favor of numpy.isin.

(gh-29978)

Removed numpy.ndindex.ndincr()

The ndindex.ndincr() method has been deprecated since NumPy 1.20 and is now
removed; use next(ndindex) instead.

(gh-29980)

Removed fix_imports parameter from numpy.save

The fix_imports parameter was deprecated in NumPy 2.1.0 and is now removed.
This flag has been ignored since NumPy 1.17 and was only needed to support
loading files in Python 2 that were written in Python 3.

(gh-29984)

Removal of four undocumented ndarray.ctypes methods

Four undocumented methods of the ndarray.ctypes object have been removed:

• _ctypes.get_data() (use _ctypes.data instead)
• _ctypes.get_shape() (use _ctypes.shape instead)
• _ctypes.get_strides() (use _ctypes.strides instead)
• _ctypes.get_as_parameter() (use _ctypes._as_parameter_ instead)

These methods have been deprecated since NumPy 1.21.

(gh-29986)

Removed newshape parameter from numpy.reshape

The newshape parameter was deprecated in NumPy 2.1.0 and has been
removed from numpy.reshape. Pass it positionally or use shape=
on newer NumPy versions.

(gh-29994)

Removal of deprecated functions and arguments

The following long-deprecated APIs have been removed:

• numpy.trapz --- deprecated since NumPy 2.0 (2023-08-18). Use numpy.trapezoid or
  scipy.integrate functions instead.
• disp function --- deprecated from 2.0 release and no longer functional. Use
  your own printing function instead.
• bias and ddof arguments in numpy.corrcoef --- these had no effect
  since NumPy 1.10.

(gh-29997)

Removed delimitor parameter from numpy.ma.mrecords.fromtextfile()

The delimitor parameter was deprecated in NumPy 1.22.0 and has been
removed from numpy.ma.mrecords.fromtextfile(). Use delimiter instead.

(gh-30021)

numpy.array2string and numpy.sum deprecations finalized

The following long-deprecated APIs have been removed or converted to errors:

• The style parameter has been removed from numpy.array2string.
  This argument had no effect since Numpy 1.14.0. Any arguments following
  it, such as formatter have now been made keyword-only.
• Calling np.sum(generator) directly on a generator object now raises a
  TypeError. This behavior was deprecated in NumPy 1.15.0. Use
  np.sum(np.fromiter(generator)) or the python sum builtin instead.

(gh-30068)

Compatibility notes

• NumPy's C extension modules have begun to use multi-phase initialisation, as
  defined by PEP 489. As part of this, a new explicit check has been added that
  each such module is only imported once per Python process. This comes with
  the side-effect that deleting numpy from sys.modules and re-importing
  it will now fail with an ImportError. This has always been unsafe, with
  unexpected side-effects, though did not previously raise an error.

  (gh-29030)

• numpy.round now always returns a copy. Previously, it returned a view
  for integer inputs for decimals >= 0 and a copy in all other cases.
  This change brings round in line with ceil, floor and trunc.

  (gh-29137)

• Type-checkers will no longer accept calls to numpy.arange with
  start as a keyword argument. This was done for compatibility with
  the Array API standard. At runtime it is still possible to use
  numpy.arange with start as a keyword argument.

  (gh-30147)

• The Macro NPY_ALIGNMENT_REQUIRED has been removed The macro was defined in
  the npy_cpu.h file, so might be regarded as semi public. As it turns out,
  with modern compilers and hardware it is almost always the case that
  alignment is required, so numpy no longer uses the macro. It is unlikely
  anyone uses it, but you might want to compile with the -Wundef flag or
  equivalent to be sure.

  (gh-29094)

C API changes

The NPY_SORTKIND enum has been enhanced with new variables

This is of interest if you are using PyArray_Sort or PyArray_ArgSort.
We have changed the semantics of the old names in the NPY_SORTKIND enum and
added new ones. The changes are backward compatible, and no recompilation is
needed. The new names of interest are:

• NPY_SORT_DEFAULT -- default sort (same value as NPY_QUICKSORT)
• NPY_SORT_STABLE -- the sort must be stable (same value as NPY_MERGESORT)
• NPY_SORT_DESCENDING -- the sort must be descending

The semantic change is that NPY_HEAPSORT is mapped to `NPY_QUICK...

NumPy 2.4.0 Release Notes

The NumPy 2.4.0 release continues the work to improve free threaded Python
support, user dtypes implementation, and annotations. There are many expired
deprecations and bug fixes as well.

This release supports Python versions 3.11-3.14

Highlights

Apart from annotations and same_value kwarg, the 2.4 highlights are mostly
of interest to downstream developers. They should help in implementing new user
dtypes.

• Many annotation improvements. In particular, runtime signature introspection.
• New casting kwarg 'same_value' for casting by value.
• New PyUFunc_AddLoopsFromSpec function that can be used to add user sort
  loops using the ArrayMethod API.
• New __numpy_dtype__ protocol.

Deprecations

Setting the strides attribute is deprecated

Setting the strides attribute is now deprecated since mutating
an array is unsafe if an array is shared, especially by multiple
threads. As an alternative, you can create a new view (no copy) via:

• np.lib.stride_tricks.strided_window_view if applicable,
• np.lib.stride_tricks.as_strided for the general case,
• or the np.ndarray constructor (buffer is the original array) for a
  light-weight version.

(gh-28925)

Positional out argument to np.maximum, np.minimum is deprecated

Passing the output array out positionally to numpy.maximum and
numpy.minimum is deprecated. For example, np.maximum(a, b, c) will emit
a deprecation warning, since c is treated as the output buffer rather than
a third input.

Always pass the output with the keyword form, e.g. np.maximum(a, b, out=c).
This makes intent clear and simplifies type annotations.

(gh-29052)

align= must be passed as boolean to np.dtype()

When creating a new dtype a VisibleDeprecationWarning will be given if
align= is not a boolean. This is mainly to prevent accidentally passing a
subarray align flag where it has no effect, such as np.dtype("f8", 3)
instead of np.dtype(("f8", 3)). We strongly suggest to always pass
align= as a keyword argument.

(gh-29301)

Assertion and warning control utilities are deprecated

np.testing.assert_warns and np.testing.suppress_warnings are
deprecated. Use warnings.catch_warnings, warnings.filterwarnings,
pytest.warns, or pytest.filterwarnings instead.

(gh-29550)

np.fix is pending deprecation

The numpy.fix function will be deprecated in a future release. It is
recommended to use numpy.trunc instead, as it provides the same
functionality of truncating decimal values to their integer parts. Static type
checkers might already report a warning for the use of numpy.fix.

(gh-30168)

in-place modification of ndarray.shape is pending deprecation

Setting the ndarray.shape attribute directly will be deprecated in a future
release. Instead of modifying the shape in place, it is recommended to use the
numpy.reshape function. Static type checkers might already report a
warning for assignments to ndarray.shape.

(gh-30282)

Deprecation of numpy.lib.user_array.container

The numpy.lib.user_array.container class is deprecated and will be removed
in a future version.

(gh-30284)

Expired deprecations

Removed deprecated MachAr runtime discovery mechanism.

(gh-29836)

Raise TypeError on attempt to convert array with ndim > 0 to scalar

Conversion of an array with ndim > 0 to a scalar was deprecated in NumPy
1.25. Now, attempting to do so raises TypeError. Ensure you extract a
single element from your array before performing this operation.

(gh-29841)

Removed numpy.linalg.linalg and numpy.fft.helper

The following were deprecated in NumPy 2.0 and have been moved to private
modules:

• numpy.linalg.linalg
  Use numpy.linalg instead.
• numpy.fft.helper
  Use numpy.fft instead.

(gh-29909)

Removed interpolation parameter from quantile and percentile functions

The interpolation parameter was deprecated in NumPy 1.22.0 and has been
removed from the following functions:

• numpy.percentile
• numpy.nanpercentile
• numpy.quantile
• numpy.nanquantile

Use the method parameter instead.

(gh-29973)

Removed numpy.in1d

numpy.in1d has been deprecated since NumPy 2.0 and is now removed in favor of numpy.isin.

(gh-29978)

Removed numpy.ndindex.ndincr()

The ndindex.ndincr() method has been deprecated since NumPy 1.20 and is now
removed; use next(ndindex) instead.

(gh-29980)

Removed fix_imports parameter from numpy.save

The fix_imports parameter was deprecated in NumPy 2.1.0 and is now removed.
This flag has been ignored since NumPy 1.17 and was only needed to support
loading files in Python 2 that were written in Python 3.

(gh-29984)

Removal of four undocumented ndarray.ctypes methods

Four undocumented methods of the ndarray.ctypes object have been removed:

• _ctypes.get_data() (use _ctypes.data instead)
• _ctypes.get_shape() (use _ctypes.shape instead)
• _ctypes.get_strides() (use _ctypes.strides instead)
• _ctypes.get_as_parameter() (use _ctypes._as_parameter_ instead)

These methods have been deprecated since NumPy 1.21.

(gh-29986)

Removed newshape parameter from numpy.reshape

The newshape parameter was deprecated in NumPy 2.1.0 and has been
removed from numpy.reshape. Pass it positionally or use shape=
on newer NumPy versions.

(gh-29994)

Removal of deprecated functions and arguments

The following long-deprecated APIs have been removed:

• numpy.trapz --- deprecated since NumPy 2.0 (2023-08-18). Use numpy.trapezoid or
  scipy.integrate functions instead.
• disp function --- deprecated from 2.0 release and no longer functional. Use
  your own printing function instead.
• bias and ddof arguments in numpy.corrcoef --- these had no effect
  since NumPy 1.10.

(gh-29997)

Removed delimitor parameter from numpy.ma.mrecords.fromtextfile()

The delimitor parameter was deprecated in NumPy 1.22.0 and has been
removed from numpy.ma.mrecords.fromtextfile(). Use delimiter instead.

(gh-30021)

numpy.array2string and numpy.sum deprecations finalized

The following long-deprecated APIs have been removed or converted to errors:

• The style parameter has been removed from numpy.array2string.
  This argument had no effect since Numpy 1.14.0. Any arguments following
  it, such as formatter have now been made keyword-only.
• Calling np.sum(generator) directly on a generator object now raises a
  TypeError. This behavior was deprecated in NumPy 1.15.0. Use
  np.sum(np.fromiter(generator)) or the python sum builtin instead.

(gh-30068)

Compatibility notes

• NumPy's C extension modules have begun to use multi-phase initialisation, as
  defined by PEP 489. As part of this, a new explicit check has been added that
  each such module is only imported once per Python process. This comes with
  the side-effect that deleting numpy from sys.modules and re-importing
  it will now fail with an ImportError. This has always been unsafe, with
  unexpected side-effects, though did not previously raise an error.

  (gh-29030)

• numpy.round now always returns a copy. Previously, it returned a view
  for integer inputs for decimals >= 0 and a copy in all other cases.
  This change brings round in line with ceil, floor and trunc.

  (gh-29137)

• Type-checkers will no longer accept calls to numpy.arange with
  start as a keyword argument. This was done for compatibility with
  the Array API standard. At runtime it is still possible to use
  numpy.arange with start as a keyword argument.

  (gh-30147)

• The Macro NPY_ALIGNMENT_REQUIRED has been removed The macro was defined in
  the npy_cpu.h file, so might be regarded as semi public. As it turns out,
  with modern compilers and hardware it is almost always the case that
  alignment is required, so numpy no longer uses the macro. It is unlikely
  anyone uses it, but you might want to compile with the -Wundef flag or
  equivalent to be sure.

  (gh-29094)

C API changes

The NPY_SORTKIND enum has been enhanced with new variables

This is of interest if you are using PyArray_Sort or PyArray_ArgSort.
We have changed the semantics of the old names in the NPY_SORTKIND enum and
added new ones. The changes are backward compatible, and no recompilation is
needed. The new names of interest are:

• NPY_SORT_DEFAULT -- default sort (same value as NPY_QUICKSORT)
• NPY_SORT_STABLE -- the sort must be stable (same value as NPY_MERGESORT)
• NPY_SORT_DESCENDING -- the sort must be descending

The semantic change is that NPY_HEAPSORT is mapped to `NPY_QUICK...

NumPy 2.3.5 Release Notes

The NumPy 2.3.5 release is a patch release split between a number of maintenance
updates and bug fixes. This release supports Python versions 3.11-3.14.

Contributors

A total of 10 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.

• Aaron Kollasch +
• Charles Harris
• Joren Hammudoglu
• Matti Picus
• Nathan Goldbaum
• Rafael Laboissière +
• Sayed Awad
• Sebastian Berg
• Warren Weckesser
• Yasir Ashfaq +

Pull requests merged

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

• #29979: MAINT: Prepare 2.3.x for further development
• #30026: SIMD, BLD: Backport FPMATH mode on x86-32 and filter successor...
• #30029: MAINT: Backport write_release.py
• #30041: TYP: Various typing updates
• #30059: BUG: Fix np.strings.slice if stop=None or start and stop >= len...
• #30063: BUG: Fix np.strings.slice if start > stop
• #30076: BUG: avoid negating INT_MIN in PyArray_Round implementation (#30071)
• #30090: BUG: Fix resize when it contains references (#29970)
• #30129: BLD: update scipy-openblas, use -Dpkg_config_path (#30049)
• #30130: BUG: Avoid compilation error of wrapper file generated with SWIG...
• #30157: BLD: use scipy-openblas 0.3.30.7 (#30132)
• #30158: DOC: Remove nonexistent order parameter docs of ma.asanyarray...
• #30185: BUG: Fix check of PyMem_Calloc return value. (#30176)
• #30217: DOC: fix links for newly rebuilt numpy-tutorials site
• #30218: BUG: Fix build on s390x with clang (#30214)
• #30237: ENH: Make FPE blas check a runtime check for all apple arm systems

NumPy 2.3.4 Release Notes

The NumPy 2.3.4 release is a patch release split between a number of maintenance
updates and bug fixes. This release supports Python versions 3.11-3.14. This
release is based on Python 3.14.0 final.

Changes

The npymath and npyrandom libraries now have a .lib rather than a
.a file extension on win-arm64, for compatibility for building with MSVC and
setuptools. Please note that using these static libraries is discouraged
and for existing projects using it, it's best to use it with a matching
compiler toolchain, which is clang-cl on Windows on Arm.

(gh-29750)

Contributors

A total of 17 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.

• !DWesl
• Charles Harris
• Christian Barbia +
• Evgeni Burovski
• Joren Hammudoglu
• Maaz +
• Mateusz Sokół
• Matti Picus
• Nathan Goldbaum
• Ralf Gommers
• Riku Sakamoto +
• Sandeep Gupta +
• Sayed Awad
• Sebastian Berg
• Sergey Fedorov +
• Warren Weckesser
• dependabot[bot]

Pull requests merged

A total of 30 pull requests were merged for this release.

• #29725: MAINT: Prepare 2.3.x for further development
• #29781: MAINT: Pin some upstream dependences
• #29782: BLD: enable x86-simd-sort to build on KNL with -mavx512f
• #29783: BUG: Include python-including headers first (#29281)
• #29784: TYP: fix np.number and np.*integer method declaration
• #29785: TYP: mypy 1.18.1
• #29788: TYP: replace scalar type __init__ with __new__
• #29790: BUG: Fix dtype refcount in __array__ (#29715)
• #29791: TYP: fix method declarations in floating, timedelta64, and datetime64Backport
• #29792: MAINT: delete unused variables in unary logical dispatch
• #29797: BUG: Fix pocketfft umath strides for AIX compatibility (#29768)
• #29798: BUG: np.setbufsize should raise ValueError for negative input
• #29799: BUG: Fix assert in nditer buffer setup
• #29800: BUG: Stable ScalarType ordering
• #29838: TST: Pin pyparsing to avoid matplotlib errors.
• #29839: BUG: linalg: emit a MemoryError on a malloc failure (#29811)
• #29840: BLD: change file extension for libnpymath on win-arm64 from .a...
• #29864: CI: Fix loongarch64 CI (#29856)
• #29865: TYP: Various typing fixes
• #29910: BUG: Fix float16-sort failures on 32-bit x86 MSVC (#29908)
• #29911: TYP: add missing __slots__ (#29901)
• #29913: TYP: wrong argument defaults in testing._private (#29902)
• #29920: BUG: avoid segmentation fault in string_expandtabs_length_promoter
• #29921: BUG: Fix INT_MIN % -1 to return 0 for all signed integer types...
• #29922: TYP: minor fixes related to errstate (#29914)
• #29923: TST: use requirements/test_requirements across CI (#29919)
• #29926: BUG: fix negative samples generated by Wald distribution (#29609)
• #29940: MAINT: Bump pypa/cibuildwheel from 3.1.4 to 3.2.1
• #29949: STY: rename @classmethod arg to cls
• #29950: MAINT: Simplify string arena growth strategy (#29885)

NumPy 2.3.3 Release Notes

The NumPy 2.3.3 release is a patch release split between a number of maintenance
updates and bug fixes. This release supports Python versions 3.11-3.14. Note
that the 3.14.0 final is currently expected in Oct, 2025. This release is based
on 3.14.0rc2.

Contributors

A total of 13 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.

• Aleksandr A. Voyt +
• Bernard Roesler +
• Charles Harris
• Hunter Hogan +
• Joren Hammudoglu
• Maanas Arora
• Matti Picus
• Nathan Goldbaum
• Raghuveer Devulapalli
• Sanjay Kumar Sakamuri Kamalakar +
• Tobias Markus +
• Warren Weckesser
• Zebreus +

Pull requests merged

A total of 23 pull requests were merged for this release.

• #29440: MAINT: Prepare 2.3.x for further development.
• #29446: BUG: Fix test_configtool_pkgconfigdir to resolve PKG_CONFIG_DIR...
• #29447: BLD: allow targeting webassembly without emscripten
• #29460: MAINT: Backport write_release.py
• #29473: MAINT: Bump pypa/cibuildwheel from 3.1.0 to 3.1.2
• #29500: BUG: Always return a real dtype from linalg.cond (gh-18304) (#29333)
• #29501: MAINT: Add .file entry to all .s SVML files
• #29556: BUG: Casting from one timedelta64 to another didn't handle NAT.
• #29562: BLD: update vendored Meson to 1.8.3 [wheel build]
• #29563: BUG: Fix metadata not roundtripping when pickling datetime (#29555)
• #29587: TST: update link and version for Intel SDE download
• #29593: TYP: add sorted kwarg to unique
• #29672: MAINT: Update pythoncapi-compat from main.
• #29673: MAINT: Update cibuildwheel.
• #29674: MAINT: Fix typo in wheels.yml
• #29683: BUG, BLD: Correct regex for ppc64 VSX3/VSX4 feature detection
• #29684: TYP: ndarray.fill() takes no keyword arguments
• #29685: BUG: avoid thread-unsafe refcount check in temp elision
• #29687: CI: replace comment-hider action in mypy_primer workflow
• #29689: BLD: Add missing <unordered_map> include
• #29691: BUG: use correct input dtype in flatiter assignment
• #29700: TYP: fix np.bool method declarations
• #29701: BUG: Correct ambiguous logic for s390x CPU feature detection

NumPy 2.3.2 Release Notes

The NumPy 2.3.2 release is a patch release with a number of bug fixes
and maintenance updates. The highlights are:

• Wheels for Python 3.14.0rc1
• PyPy updated to the latest stable release
• OpenBLAS updated to 0.3.30

This release supports Python versions 3.11-3.14

Contributors

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

• !DWesl
• Charles Harris
• Joren Hammudoglu
• Maanas Arora
• Marco Edward Gorelli
• Matti Picus
• Nathan Goldbaum
• Sebastian Berg
• kostayScr +

Pull requests merged

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

• #29256: MAINT: Prepare 2.3.x for further development
• #29283: TYP: Work around a mypy issue with bool arrays (#29248)
• #29284: BUG: fix fencepost error in StringDType internals
• #29287: BUG: handle case in mapiter where descriptors might get replaced...
• #29350: BUG: Fix shape error path in array-interface
• #29412: BUG: Allow reading non-npy files in npz and add test
• #29413: TST: Avoid uninitialized values in test (#29341)
• #29414: BUG: Fix reference leakage for output arrays in reduction functions
• #29415: BUG: fix casting issue in center, ljust, rjust, and zfill (#29369)
• #29416: TYP: Fix overloads in np.char.array and np.char.asarray...
• #29417: BUG: Any dtype should call square on arr \*\* 2 (#29392)
• #29424: MAINT: use a stable pypy release in CI
• #29425: MAINT: Support python 314rc1
• #29429: MAINT: Update highway to match main.
• #29430: BLD: use github to build macos-arm64 wheels with OpenBLAS and...
• #29437: BUG: fix datetime/timedelta hash memory leak (#29411)

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SHA256

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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 matmul for non-contiguous out kwarg parameter
• Fix for Accelerate runtime warnings on M4 hardware
• Fix new in NumPy 2.3.0 np.vectorize casting 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.vectorize casting 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.

Checksums

MD5

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SHA256

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36890eb9e9d2081137bd78d29050ba63b8dab95dff7912eadf1185e80074b2a0 ...

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 function numpy.strings.slice

The new function numpy.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_plugin has been deprecated in favor of
  platform-agnostic static type inference. Please remove
  numpy.typing.mypy_plugin from the plugins section of your mypy
  configuration. If this change results in new errors being reported,
  kindly open an issue.

  (gh-28129)

• The numpy.typing.NBitBase type 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:

  import numpy as np
  import numpy.typing as npt
  
  def f[NT: npt.NBitBase](x: np.complexfloating[NT]) -> np.floating[NT]: ...

  But in NumPy 2.2.0, float64 and complex128 were changed to
  concrete subtypes, causing static type-checkers to reject
  x: np.float64 = f(np.complex128(42j)).

  So instead, the better approach is to use typing.overload:

  import numpy as np
  from typing import overload
  
  @overload
  def f(x: np.complex64) -> np.float32: ...
  @overload
  def f(x: np.complex128) -> np.float64: ...
  @overload
  def f(x: np.clongdouble) -> np.longdouble: ...

  (gh-28884)

Expired deprecations

• Remove deprecated macros like NPY_OWNDATA from Cython interfaces
  in favor of NPY_ARRAY_OWNDATA (deprecated since 1.7)

  (gh-28254)

• Remove numpy/npy_1_7_deprecated_api.h and C macros like
  NPY_OWNDATA in favor of NPY_ARRAY_OWNDATA (deprecated since 1.7)

  (gh-28254)

• Remove alias generate_divbyzero_error to
  npy_set_floatstatus_divbyzero and generate_overflow_error to
  npy_set_floatstatus_overflow (deprecated since 1.10)

  (gh-28254)

• Remove np.tostring (deprecated since 1.19)

  (gh-28254)

• Raise on np.conjugate of 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=None to functions with a non-optional shape argument
  errors, use () instead (deprecated since 1.20)

  (gh-28254)

• Inexact matches for mode and searchside raise (deprecated since
  1.20)

  (gh-28254)

• Setting __array_finalize__ = None errors (deprecated since 1.23)

  (gh-28254)

• np.fromfile and np.fromstring error on bad data, previously they
  would guess (deprecated since 1.18)

  (gh-28254)

• datetime64 and timedelta64 construction with a tuple no longer
  accepts an event value, 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 dtype from a class with a dtype attribute,
  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.tostring has been removed, use tobytes instead (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() with axis=None uses same-kind casting by
  default, not unsafe (deprecated since 1.20)

  (gh-28254)

• Unpickling a scalar with object dtype errors (deprecated since 1.20)

  (gh-28254)

• The binary mode of fromstring now errors, use frombuffer instead
  (deprecated since 1.14)

  (gh-28254)

• Converting np.inexact or np.floating to a dtype errors
  (deprecated since 1.19)

  (gh-28254)

• Converting np.complex, np.integer, np.signedinteger,
  np.unsignedinteger, np.generic to a dtype errors (deprecated
  since 1.19)

  (gh-28254)

• The Python built-in round errors for complex scalars. Use
  np.round or scalar.round instead (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=float keyword argument.
  • Use np.loadtxt(...).astype(np.int64)

  (gh-28254)

• The use of a length 1 tuple for the ufunc signature errors. Use
  dtype or fill the tuple with None (deprecated since 1.19)

  (gh-28254)

• Special handling of matrix is in np.outer is removed. Convert to a
  ndarray via matrix.A (deprecated since 1.20)

  (gh-28254)

• Removed the np.compat package source code (removed in 2.0)

  (gh-28961)

C API changes

• NpyIter_GetTransferFlags is 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 casting float64(1e300) to
  float32 (overflow to infinity) or a NaN to an integer (invalid
  value).

  (gh-27883)

• NpyIter now has no limit on the number of operands it supports.

  (gh-28080)

New NpyIter_GetTransferFlags and NpyIter_IterationNeedsAPI change

NumPy now has the new NpyIter_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.

The NpyIter_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.dtype now defaults to typing.Any. This
  way, static type-checkers will infer dtype: np.dtype as
  dtype: np.dtype[Any], without reporting an error.

  (gh-28669)

• Static type-checkers now interpret:

  • _: np.ndarray as _: npt.NDArray[typing.Any].
  • _: np.flatiter as _: np.flatiter[np.ndarray].

  This is because their type parameters now have default values.

  (gh-28940)

NumPy now registers its pkg-config paths with the pkgconf PyPI package

The pkgconf 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 using pkgconf
from PyPI, NumPy will be discoverable without needin...

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 function numpy.strings.slice

The new function numpy.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_plugin has been deprecated in favor of
  platform-agnostic static type inference. Please remove
  numpy.typing.mypy_plugin from the plugins section of your mypy
  configuration. If this change results in new errors being reported,
  kindly open an issue.

  (gh-28129)

• The numpy.typing.NBitBase type 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:

  import numpy as np
  import numpy.typing as npt
  
  def f[NT: npt.NBitBase](x: np.complexfloating[NT]) -> np.floating[NT]: ...

  But in NumPy 2.2.0, float64 and complex128 were changed to
  concrete subtypes, causing static type-checkers to reject
  x: np.float64 = f(np.complex128(42j)).

  So instead, the better approach is to use typing.overload:

  import numpy as np
  from typing import overload
  
  @overload
  def f(x: np.complex64) -> np.float32: ...
  @overload
  def f(x: np.complex128) -> np.float64: ...
  @overload
  def f(x: np.clongdouble) -> np.longdouble: ...

  (gh-28884)

Expired deprecations

• Remove deprecated macros like NPY_OWNDATA from Cython interfaces
  in favor of NPY_ARRAY_OWNDATA (deprecated since 1.7)

  (gh-28254)

• Remove numpy/npy_1_7_deprecated_api.h and C macros like
  NPY_OWNDATA in favor of NPY_ARRAY_OWNDATA (deprecated since 1.7)

  (gh-28254)

• Remove alias generate_divbyzero_error to
  npy_set_floatstatus_divbyzero and generate_overflow_error to
  npy_set_floatstatus_overflow (deprecated since 1.10)

  (gh-28254)

• Remove np.tostring (deprecated since 1.19)

  (gh-28254)

• Raise on np.conjugate of 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=None to functions with a non-optional shape argument
  errors, use () instead (deprecated since 1.20)

  (gh-28254)

• Inexact matches for mode and searchside raise (deprecated since
  1.20)

  (gh-28254)

• Setting __array_finalize__ = None errors (deprecated since 1.23)

  (gh-28254)

• np.fromfile and np.fromstring error on bad data, previously they
  would guess (deprecated since 1.18)

  (gh-28254)

• datetime64 and timedelta64 construction with a tuple no longer
  accepts an event value, 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 dtype from a class with a dtype attribute,
  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.tostring has been removed, use tobytes instead (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() with axis=None uses same-kind casting by
  default, not unsafe (deprecated since 1.20)

  (gh-28254)

• Unpickling a scalar with object dtype errors (deprecated since 1.20)

  (gh-28254)

• The binary mode of fromstring now errors, use frombuffer instead
  (deprecated since 1.14)

  (gh-28254)

• Converting np.inexact or np.floating to a dtype errors
  (deprecated since 1.19)

  (gh-28254)

• Converting np.complex, np.integer, np.signedinteger,
  np.unsignedinteger, np.generic to a dtype errors (deprecated
  since 1.19)

  (gh-28254)

• The Python built-in round errors for complex scalars. Use
  np.round or scalar.round instead (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=float keyword argument.
  • Use np.loadtxt(...).astype(np.int64)

  (gh-28254)

• The use of a length 1 tuple for the ufunc signature errors. Use
  dtype or fill the tuple with None (deprecated since 1.19)

  (gh-28254)

• Special handling of matrix is in np.outer is removed. Convert to a
  ndarray via matrix.A (deprecated since 1.20)

  (gh-28254)

• Removed the np.compat package source code (removed in 2.0)

  (gh-28961)

C API changes

• NpyIter_GetTransferFlags is 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 casting float64(1e300) to
  float32 (overflow to infinity) or a NaN to an integer (invalid
  value).

  (gh-27883)

• NpyIter now has no limit on the number of operands it supports.

  (gh-28080)

New NpyIter_GetTransferFlags and NpyIter_IterationNeedsAPI change

NumPy now has the new NpyIter_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.

The NpyIter_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.dtype now defaults to typing.Any. This
  way, static type-checkers will infer dtype: np.dtype as
  dtype: np.dtype[Any], without reporting an error.

  (gh-28669)

• Static type-checkers now interpret:

  • _: np.ndarray as _: npt.NDArray[typing.Any].
  • _: np.flatiter as _: np.flatiter[np.ndarray].

  This is because their type parameters now have default values.

  (gh-28940)

NumPy now registers its pkg-config paths with the pkgconf PyPI package

The pkgconf PyPI
package provides an interface for projects like NumPy to register their
own paths to be added to the pkg-config search path...

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] + float return 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 CanIndex annotation in ndarray.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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SHA256

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