Numpy

NPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION` to avoid C compiler warnings
about deprecated API usage.

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
- Matti Picus
- Pauli Virtanen
- Philippe Ombredanne +
- Sebastian Berg
- Stefan Behnel +
- Stephan Loyd +
- Zac Hatfield-Dodds

Pull requests merged
--------------------

A total of 9 pull requests were merged for this release.

- [\16959](https://github.com/numpy/numpy/pull/16959): TST: Change aarch64 to arm64 in travis.yml.
- [\16998](https://github.com/numpy/numpy/pull/16998): MAINT: Configure hypothesis in `np.test()` for determinism,\...
- [\17000](https://github.com/numpy/numpy/pull/17000): BLD: pin setuptools \< 49.2.0
- [\17015](https://github.com/numpy/numpy/pull/17015): ENH: Add NumPy declarations to be used by Cython 3.0+
- [\17125](https://github.com/numpy/numpy/pull/17125): BUG: Remove non-threadsafe sigint handling from fft calculation
- [\17243](https://github.com/numpy/numpy/pull/17243): BUG: core: fix ilp64 blas dot/vdot/\... for strides \> int32 max
- [\17244](https://github.com/numpy/numpy/pull/17244): DOC: Use SPDX license expressions with correct license
- [\17245](https://github.com/numpy/numpy/pull/17245): DOC: Fix the link to the quick-start in the old API functions
- [\17272](https://github.com/numpy/numpy/pull/17272): BUG: fix pickling of arrays larger than 2GiB

Checksums
---------

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SHA256

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

Checksums

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SHA256

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

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dbdc15f0c81611925f382dfa97b3bd0bc2c1ce19d4fe50482cb0ddc12ba30020 numpy-2.2.3.tar.gz

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

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

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45681fd7128c8ad1c379f0ca0776a8b0c6583d2f69889ddac01559dfe4390918 numpy-2.2.1.tar.gz

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](https://github.com/numpy/numpy/pull/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](https://github.com/numpy/numpy/pull/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](https://github.com/numpy/numpy/pull/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](https://github.com/numpy/numpy/pull/25675))

- `np.complexfloating[T, T]` can now also be written as
`np.complexfloating[T]`

([gh-27420](https://github.com/numpy/numpy/pull/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](https://github.com/numpy/numpy/pull/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](https://github.com/numpy/numpy/pull/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](https://github.com/numpy/numpy/pull/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](https://github.com/numpy/numpy/pull/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](https://github.com/numpy/numpy/pull/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](https://github.com/numpy/numpy/pull/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](https://github.com/numpy/numpy/pull/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](https://github.com/numpy/numpy/pull/27147))

- NumPy now indicates hugepages also for large `np.zeros` allocations
on linux. Thus should generally improve performance.

([gh-27808](https://github.com/numpy/numpy/pull/27808))

Changes

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

([gh-26766](https://github.com/numpy/numpy/pull/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:

python
x: float = numpy.float64(6.28) valid
z: complex = numpy.complex128(-1j) valid


([gh-27334](https://github.com/numpy/numpy/pull/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](https://github.com/numpy/numpy/pull/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](https://github.com/numpy/numpy/pull/27807))

- Bump the musllinux CI image and wheels to 1_2 from 1_1. This is because
1_1 is [end of life](https://github.com/pypa/manylinux/issues/1629).

([gh-27088](https://github.com/numpy/numpy/pull/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](https://github.com/numpy/numpy/pull/27156))

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