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Update dependency numpy to v2.2.3 #19

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@renovate renovate bot commented Jan 11, 2025

This PR contains the following updates:

Package Change Age Adoption Passing Confidence
numpy (changelog) ==2.1.3 -> ==2.2.3 age adoption passing confidence

Release Notes

numpy/numpy (numpy)

v2.2.3: 2.2.3 (Feb 13, 2025)

Compare Source

NumPy 2.2.3 Release Notes

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

This release supports Python versions 3.10-3.13.

Contributors

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

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

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

  • #​28185: MAINT: Prepare 2.2.x for further development
  • #​28201: BUG: fix data race in a more minimal way on stable branch
  • #​28208: BUG: Fix from_float_positional errors for huge pads
  • #​28209: BUG: fix data race in np.repeat
  • #​28212: MAINT: Use VQSORT_COMPILER_COMPATIBLE to determine if we should...
  • #​28224: MAINT: update highway to latest
  • #​28236: BUG: Add cpp atomic support (#​28234)
  • #​28237: BLD: Compile fix for clang-cl on WoA
  • #​28243: TYP: Avoid upcasting float64 in the set-ops
  • #​28249: BLD: better fix for clang / ARM compiles
  • #​28266: TYP: Fix timedelta64.__divmod__ and timedelta64.__mod__...
  • #​28274: TYP: Fixed missing typing information of set_printoptions
  • #​28278: BUG: backport resource cleanup bugfix from gh-28273
  • #​28282: BUG: fix incorrect bytes to stringdtype coercion
  • #​28283: TYP: Fix scalar constructors
  • #​28284: TYP: stub numpy.matlib
  • #​28285: TYP: stub the missing numpy.testing modules
  • #​28286: CI: Fix the github label for TYP: PR's and issues
  • #​28305: TYP: Backport typing updates from main
  • #​28321: BUG: fix race initializing legacy dtype casts
  • #​28324: CI: update test_moderately_small_alpha
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v2.2.2: 2.2.2 (Jan 18, 2025)

Compare Source

NumPy 2.2.2 Release Notes

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

Contributors

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

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

Pull requests merged

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

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

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v2.2.1: 2.2.1 (DEC 21, 2024)

Compare Source

NumPy 2.2.1 Release Notes

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

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

This release supports Python 3.10-3.13.

Contributors

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

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

Pull requests merged

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

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

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v2.2.0: 2.2.0 (Dec 8, 2024)

Compare Source

NumPy 2.2.0 Release Notes

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

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

This release supports Python versions 3.10-3.13.

Deprecations

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

    (gh-27735)

Expired deprecations

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

    (gh-27160)

Compatibility notes

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

    (gh-27661)

New Features

  • New functions for matrix-vector and vector-matrix products

    Two new generalized ufuncs were defined:

    • numpy.matvec - matrix-vector product, treating the
      arguments as stacks of matrices and column vectors,
      respectively.
    • numpy.vecmat - vector-matrix product, treating the
      arguments as stacks of column vectors and matrices,
      respectively. For complex vectors, the conjugate is taken.

    These add to the existing numpy.matmul as well as to
    numpy.vecdot, which was added in numpy 2.0.

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

    (gh-25675)

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

    (gh-27420)

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

    (gh-27735)

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

    (gh-27736)

Improvements

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

    (gh-14622)

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

    (gh-27636)

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

    (gh-27723)

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

    (gh-27695)

Performance improvements and changes

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

    (gh-27896)

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

    (gh-27119)

  • OpenBLAS on x86_64 and i686 is built with fewer kernels. Based on
    benchmarking, there are 5 clusters of performance around these
    kernels: PRESCOTT NEHALEM SANDYBRIDGE HASWELL SKYLAKEX.

  • OpenBLAS on windows is linked without quadmath, simplifying
    licensing

  • Due to a regression in OpenBLAS on windows, the performance
    improvements when using multiple threads for OpenBLAS 0.3.26 were
    reverted.

    (gh-27147)

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

    (gh-27808)

Changes

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

    (gh-26766)

  • The type annotations of numpy.float64 and numpy.complex128 now
    reflect that they are also subtypes of the built-in float and
    complex types, respectively. This update prevents static
    type-checkers from reporting errors in cases such as:

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

    (gh-27334)

  • The repr of arrays large enough to be summarized (i.e., where
    elements are replaced with ...) now includes the shape of the
    array, similar to what already was the case for arrays with zero
    size and non-obvious shape. With this change, the shape is always
    given when it cannot be inferred from the values. Note that while
    written as shape=..., this argument cannot actually be passed in
    to the np.array constructor. If you encounter problems, e.g., due
    to failing doctests, you can use the print option legacy=2.1 to
    get the old behaviour.

    (gh-27482)

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

    (gh-27807)

  • Bump the musllinux CI image and wheels to 1_2 from 1_1. This is because
    1_1 is end of life.

    (gh-27088)

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

    (gh-27156)

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@renovate renovate bot force-pushed the renovate/numpy-2.x branch from 9653173 to 6b16c4e Compare January 20, 2025 08:02
@renovate renovate bot changed the title Update dependency numpy to v2.2.1 Update dependency numpy to v2.2.2 Jan 20, 2025
@renovate renovate bot changed the title Update dependency numpy to v2.2.2 Update dependency numpy to v2.2.3 Feb 15, 2025
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