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Hironsan / HateSonar

Hate Speech Detection Library for Python.
https://hatesonar.herokuapp.com/
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Update numpy to 1.26.0 #281

Closed pyup-bot closed 1 year ago

pyup-bot commented 1 year ago

This PR updates numpy from 1.22.2 to 1.26.0.

Changelog ### 1.26.0 ``` The NumPy 1.26.0 release is a continuation of the 1.25.x release cycle with the addition of Python 3.12.0 support. Python 3.12 dropped distutils, consequently supporting it required finding a replacement for the setup.py/distutils based build system NumPy was using. We have chosen to use the Meson build system instead, and this is the first NumPy release supporting it. This is also the first release that supports Cython 3.0 in addition to retaining 0.29.X compatibility. Supporting those two upgrades was a large project, over 100 files have been touched in this release. The changelog doesn\'t capture the full extent of the work, special thanks to Ralf Gommers, Sayed Adel, Stéfan van der Walt, and Matti Picus who did much of the work in the main development branch. The highlights of this release are: - Python 3.12.0 support. - Cython 3.0.0 compatibility. - Use of the Meson build system - Updated SIMD support The Python versions supported in this release are 3.9-3.12. Build system changes In this release, NumPy has switched to Meson as the build system and meson-python as the build backend. Installing NumPy or building a wheel can be done with standard tools like `pip` and `pypa/build`. The following are supported: - Regular installs: `pip install numpy` or (in a cloned repo) `pip install .` - Building a wheel: `python -m build` (preferred), or `pip wheel .` - Editable installs: `pip install -e . --no-build-isolation` - Development builds through the custom CLI implemented with [spin](https://github.com/scientific-python/spin): `spin build`. All the regular `pip` and `pypa/build` flags (e.g., `--no-build-isolation`) should work as expected. NumPy-specific build customization Many of the NumPy-specific ways of customizing builds have changed. The `NPY_*` environment variables which control BLAS/LAPACK, SIMD, threading, and other such options are no longer supported, nor is a `site.cfg` file to select BLAS and LAPACK. Instead, there are command-line flags that can be passed to the build via `pip`/`build`\'s config-settings interface. These flags are all listed in the `meson_options.txt` file in the root of the repo. Detailed documented will be available before the final 1.26.0 release; for now please see [the SciPy \"building from source\"docs](http://scipy.github.io/devdocs/building/index.html) since most build customization works in an almost identical way in SciPy as it does in NumPy. Build dependencies While the runtime dependencies of NumPy have not changed, the build dependencies have. Because we temporarily vendor Meson and meson-python, there are several new dependencies - please see the `[build-system]` section of `pyproject.toml` for details. Troubleshooting This build system change is quite large. In case of unexpected issues, it is still possible to use a `setup.py`-based build as a temporary workaround (on Python 3.9-3.11, not 3.12), by copying `pyproject.toml.setuppy` to `pyproject.toml`. However, please open an issue with details on the NumPy issue tracker. We aim to phase out `setup.py` builds as soon as possible, and therefore would like to see all potential blockers surfaced early on in the 1.26.0 release cycle. Contributors A total of 11 people contributed to this release. People with a \"+\" by their names contributed a patch for the first time. - Bas van Beek - Charles Harris - Matti Picus - Melissa Weber Mendonça - Ralf Gommers - Sayed Adel - Sebastian Berg - Stefan van der Walt - Tyler Reddy - Warren Weckesser Pull requests merged A total of 18 pull requests were merged for this release. - [24305](https://github.com/numpy/numpy/pull/24305): MAINT: Prepare 1.26.x branch for development - [24308](https://github.com/numpy/numpy/pull/24308): MAINT: Massive update of files from main for numpy 1.26 - [24322](https://github.com/numpy/numpy/pull/24322): CI: fix wheel builds on the 1.26.x branch - [24326](https://github.com/numpy/numpy/pull/24326): BLD: update openblas to newer version - [24327](https://github.com/numpy/numpy/pull/24327): TYP: Trim down the `_NestedSequence.__getitem__` signature - [24328](https://github.com/numpy/numpy/pull/24328): BUG: fix choose refcount leak - [24337](https://github.com/numpy/numpy/pull/24337): TST: fix running the test suite in builds without BLAS/LAPACK - [24338](https://github.com/numpy/numpy/pull/24338): BUG: random: Fix generation of nan by dirichlet. - [24340](https://github.com/numpy/numpy/pull/24340): MAINT: Dependabot updates from main - [24342](https://github.com/numpy/numpy/pull/24342): MAINT: Add back NPY_RUN_MYPY_IN_TESTSUITE=1 - [24353](https://github.com/numpy/numpy/pull/24353): MAINT: Update `extbuild.py` from main. - [24356](https://github.com/numpy/numpy/pull/24356): TST: fix distutils tests for deprecations in recent setuptools\... - [24375](https://github.com/numpy/numpy/pull/24375): MAINT: Update cibuildwheel to version 2.15.0 - [24381](https://github.com/numpy/numpy/pull/24381): MAINT: Fix codespaces setup.sh script - [24403](https://github.com/numpy/numpy/pull/24403): ENH: Vendor meson for multi-target build support - [24404](https://github.com/numpy/numpy/pull/24404): BLD: vendor meson-python to make the Windows builds with SIMD\... - [24405](https://github.com/numpy/numpy/pull/24405): BLD, SIMD: The meson CPU dispatcher implementation - [24406](https://github.com/numpy/numpy/pull/24406): MAINT: Remove versioneer Checksums MD5 875d02016f215f8ce2513453393f0089 numpy-1.26.0b1-cp310-cp310-macosx_10_9_x86_64.whl 7df1856729096fbbbbb82b58c1695810 numpy-1.26.0b1-cp310-cp310-macosx_11_0_arm64.whl 928037510906572ecadb154b8089853f numpy-1.26.0b1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl 93fb7c8a0e7af169c9bf42d8bfa17c2c numpy-1.26.0b1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl a865069d224bf3830671de8e1f374344 numpy-1.26.0b1-cp310-cp310-musllinux_1_1_x86_64.whl c53d1d8cb653fc08bd3f931e4c965430 numpy-1.26.0b1-cp310-cp310-win_amd64.whl c7e212fbb7e64231747c6c8aac0f8678 numpy-1.26.0b1-cp311-cp311-macosx_10_9_x86_64.whl f2df03cdaee283c1f7486d2f66e497dd numpy-1.26.0b1-cp311-cp311-macosx_11_0_arm64.whl 8af359b78166474b7a621a482f3073fd 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This is the last planned release in the 1.25.x series, the next release will be 1.26.0, which will use the meson build system and support Python 3.12. The Python versions supported by this release are 3.9-3.11. Contributors A total of 13 people contributed to this release. People with a \"+\" by their names contributed a patch for the first time. - Aaron Meurer - Andrew Nelson - Charles Harris - Kevin Sheppard - Matti Picus - Nathan Goldbaum - Peter Hawkins - Ralf Gommers - Randy Eckenrode + - Sam James + - Sebastian Berg - Tyler Reddy - dependabot\[bot\] Pull requests merged A total of 19 pull requests were merged for this release. - [24148](https://github.com/numpy/numpy/pull/24148): MAINT: prepare 1.25.x for further development - [24174](https://github.com/numpy/numpy/pull/24174): ENH: Improve clang-cl compliance - [24179](https://github.com/numpy/numpy/pull/24179): MAINT: Upgrade various build dependencies. - [24182](https://github.com/numpy/numpy/pull/24182): BLD: use `-ftrapping-math` with Clang on macOS - [24183](https://github.com/numpy/numpy/pull/24183): BUG: properly handle negative indexes in ufunc_at fast path - [24184](https://github.com/numpy/numpy/pull/24184): BUG: PyObject_IsTrue and PyObject_Not error handling in setflags - [24185](https://github.com/numpy/numpy/pull/24185): BUG: histogram small range robust - [24186](https://github.com/numpy/numpy/pull/24186): MAINT: Update meson.build files from main branch - [24234](https://github.com/numpy/numpy/pull/24234): MAINT: exclude min, max and round from `np.__all__` - [24241](https://github.com/numpy/numpy/pull/24241): MAINT: Dependabot updates - [24242](https://github.com/numpy/numpy/pull/24242): BUG: Fix the signature for np.array_api.take - [24243](https://github.com/numpy/numpy/pull/24243): BLD: update OpenBLAS to an intermeidate commit - [24244](https://github.com/numpy/numpy/pull/24244): BUG: Fix reference count leak in str(scalar). - [24245](https://github.com/numpy/numpy/pull/24245): BUG: fix invalid function pointer conversion error - [24255](https://github.com/numpy/numpy/pull/24255): BUG: Factor out slow `getenv` call used for memory policy warning - [24292](https://github.com/numpy/numpy/pull/24292): CI: correct URL in cirrus.star - 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1a1329e26f46230bf77b02cc19e900db9b52f398d6722ca853349a782d4cff55 numpy-1.25.2-pp39-pypy39_pp73-macosx_10_9_x86_64.whl 4c3abc71e8b6edba80a01a52e66d83c5d14433cbcd26a40c329ec7ed09f37901 numpy-1.25.2-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 1b9735c27cea5d995496f46a8b1cd7b408b3f34b6d50459d9ac8fe3a20cc17bf numpy-1.25.2-pp39-pypy39_pp73-win_amd64.whl fd608e19c8d7c55021dffd43bfe5492fab8cc105cc8986f813f8c3c048b38760 numpy-1.25.2.tar.gz ``` ### 1.25.1 ``` discovered after the 1.25.0 release. The Python versions supported by this release are 3.9-3.11. Contributors A total of 10 people contributed to this release. People with a \"+\" by their names contributed a patch for the first time. - Andrew Nelson - Charles Harris - Developer-Ecosystem-Engineering - Hood Chatham - Nathan Goldbaum - Rohit Goswami - Sebastian Berg - Tim Paine + - dependabot\[bot\] - matoro + Pull requests merged A total of 14 pull requests were merged for this release. - [23968](https://github.com/numpy/numpy/pull/23968): MAINT: prepare 1.25.x for further development - [24036](https://github.com/numpy/numpy/pull/24036): BLD: Port long double identification to C for meson - [24037](https://github.com/numpy/numpy/pull/24037): BUG: Fix reduction `return NULL` to be `goto fail` - [24038](https://github.com/numpy/numpy/pull/24038): BUG: Avoid undefined behavior in array.astype() - [24039](https://github.com/numpy/numpy/pull/24039): BUG: Ensure `__array_ufunc__` works without any kwargs passed - [24117](https://github.com/numpy/numpy/pull/24117): MAINT: Pin urllib3 to avoid anaconda-client bug. - [24118](https://github.com/numpy/numpy/pull/24118): TST: Pin pydantic\<2 in Pyodide workflow - [24119](https://github.com/numpy/numpy/pull/24119): MAINT: Bump pypa/cibuildwheel from 2.13.0 to 2.13.1 - [24120](https://github.com/numpy/numpy/pull/24120): MAINT: Bump actions/checkout from 3.5.2 to 3.5.3 - [24122](https://github.com/numpy/numpy/pull/24122): BUG: Multiply or Divides using SIMD without a full vector can\... - [24127](https://github.com/numpy/numpy/pull/24127): MAINT: testing for IS_MUSL closes #24074 - [24128](https://github.com/numpy/numpy/pull/24128): BUG: Only replace dtype temporarily if dimensions changed - [24129](https://github.com/numpy/numpy/pull/24129): MAINT: Bump actions/setup-node from 3.6.0 to 3.7.0 - [24134](https://github.com/numpy/numpy/pull/24134): BUG: Fix private procedures in f2py modules Checksums MD5 d09d98643db31e892fad11b8c2b7af22 numpy-1.25.1-cp310-cp310-macosx_10_9_x86_64.whl d5b8d3b0424e2af41018f35a087c4500 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NumPy 1.25.0 release continues the ongoing work to improve the handling and promotion of dtypes, increase the execution speed, and clarify the documentation. There has also been work to prepare for the future NumPy 2.0.0 release, resulting in a large number of new and expired deprecation. Highlights are: - Support for MUSL, there are now MUSL wheels. - Support the Fujitsu C/C++ compiler. - Object arrays are now supported in einsum - Support for inplace matrix multiplication (`=`). We will be releasing a NumPy 1.26 when Python 3.12 comes out. That is needed because distutils has been dropped by Python 3.12 and we will be switching to using meson for future builds. The next mainline release will be NumPy 2.0.0. We plan that the 2.0 series will still support downstream projects built against earlier versions of NumPy. The Python versions supported in this release are 3.9-3.11. Deprecations - `np.core.MachAr` is deprecated. It is private API. In names defined in `np.core` should generally be considered private. ([gh-22638](https://github.com/numpy/numpy/pull/22638)) - `np.finfo(None)` is deprecated. ([gh-23011](https://github.com/numpy/numpy/pull/23011)) - `np.round_` is deprecated. Use `np.round` instead. ([gh-23302](https://github.com/numpy/numpy/pull/23302)) - `np.product` is deprecated. Use `np.prod` instead. ([gh-23314](https://github.com/numpy/numpy/pull/23314)) - `np.cumproduct` is deprecated. Use `np.cumprod` instead. ([gh-23314](https://github.com/numpy/numpy/pull/23314)) - `np.sometrue` is deprecated. Use `np.any` instead. ([gh-23314](https://github.com/numpy/numpy/pull/23314)) - `np.alltrue` is deprecated. Use `np.all` instead. ([gh-23314](https://github.com/numpy/numpy/pull/23314)) - Only ndim-0 arrays are treated as scalars. NumPy used to treat all arrays of size 1 (e.g., `np.array([3.14])`) as scalars. In the future, this will be limited to arrays of ndim 0 (e.g., `np.array(3.14)`). The following expressions will report a deprecation warning: python a = np.array([3.14]) float(a) better: a[0] to get the numpy.float or a.item() b = np.array([[3.14]]) c = numpy.random.rand(10) c[0] = b better: c[0] = b[0, 0] ([gh-10615](https://github.com/numpy/numpy/pull/10615)) - `numpy.find_common_type` is now deprecated and its use should be replaced with either `numpy.result_type` or `numpy.promote_types`. Most users leave the second `scalar_types` argument to `find_common_type` as `[]` in which case `np.result_type` and `np.promote_types` are both faster and more robust. When not using `scalar_types` the main difference is that the replacement intentionally converts non-native byte-order to native byte order. Further, `find_common_type` returns `object` dtype rather than failing promotion. This leads to differences when the inputs are not all numeric. Importantly, this also happens for e.g. timedelta/datetime for which NumPy promotion rules are currently sometimes surprising. When the `scalar_types` argument is not `[]` things are more complicated. In most cases, using `np.result_type` and passing the Python values `0`, `0.0`, or `0j` has the same result as using `int`, `float`, or `complex` in `scalar_types`. When `scalar_types` is constructed, `np.result_type` is the correct replacement and it may be passed scalar values like `np.float32(0.0)`. Passing values other than 0, may lead to value-inspecting behavior (which `np.find_common_type` never used and NEP 50 may change in the future). The main possible change in behavior in this case, is when the array types are signed integers and scalar types are unsigned. If you are unsure about how to replace a use of `scalar_types` or when non-numeric dtypes are likely, please do not hesitate to open a NumPy issue to ask for help. ([gh-22539](https://github.com/numpy/numpy/pull/22539)) Expired deprecations - `np.core.machar` and `np.finfo.machar` have been removed. ([gh-22638](https://github.com/numpy/numpy/pull/22638)) - `+arr` will now raise an error when the dtype is not numeric (and positive is undefined). ([gh-22998](https://github.com/numpy/numpy/pull/22998)) - A sequence must now be passed into the stacking family of functions (`stack`, `vstack`, `hstack`, `dstack` and `column_stack`). ([gh-23019](https://github.com/numpy/numpy/pull/23019)) - `np.clip` now defaults to same-kind casting. Falling back to unsafe casting was deprecated in NumPy 1.17. ([gh-23403](https://github.com/numpy/numpy/pull/23403)) - `np.clip` will now propagate `np.nan` values passed as `min` or `max`. Previously, a scalar NaN was usually ignored. This was deprecated in NumPy 1.17. ([gh-23403](https://github.com/numpy/numpy/pull/23403)) - The `np.dual` submodule has been removed. ([gh-23480](https://github.com/numpy/numpy/pull/23480)) - NumPy now always ignores sequence behavior for an array-like (defining one of the array protocols). (Deprecation started NumPy 1.20) ([gh-23660](https://github.com/numpy/numpy/pull/23660)) - The niche `FutureWarning` when casting to a subarray dtype in `astype` or the array creation functions such as `asarray` is now finalized. The behavior is now always the same as if the subarray dtype was wrapped into a single field (which was the workaround, previously). (FutureWarning since NumPy 1.20) ([gh-23666](https://github.com/numpy/numpy/pull/23666)) - `==` and `!=` warnings have been finalized. The `==` and `!=` operators on arrays now always: - raise errors that occur during comparisons such as when the arrays have incompatible shapes (`np.array([1, 2]) == np.array([1, 2, 3])`). - return an array of all `True` or all `False` when values are fundamentally not comparable (e.g. have different dtypes). An example is `np.array(["a"]) == np.array([1])`. This mimics the Python behavior of returning `False` and `True` when comparing incompatible types like `"a" == 1` and `"a" != 1`. For a long time these gave `DeprecationWarning` or `FutureWarning`. ([gh-22707](https://github.com/numpy/numpy/pull/22707)) - Nose support has been removed. NumPy switched to using pytest in 2018 and nose has been unmaintained for many years. We have kept NumPy\'s nose support to avoid breaking downstream projects who might have been using it and not yet switched to pytest or some other testing framework. With the arrival of Python 3.12, unpatched nose will raise an error. It is time to move on. *Decorators removed*: - raises - slow - setastest - skipif - knownfailif - deprecated - parametrize - \_needs_refcount These are not to be confused with pytest versions with similar names, e.g., pytest.mark.slow, pytest.mark.skipif, pytest.mark.parametrize. *Functions removed*: - Tester - import_nose - run_module_suite ([gh-23041](https://github.com/numpy/numpy/pull/23041)) - The `numpy.testing.utils` shim has been removed. Importing from the `numpy.testing.utils` shim has been deprecated since 2019, the shim has now been removed. All imports should be made directly from `numpy.testing`. ([gh-23060](https://github.com/numpy/numpy/pull/23060)) - The environment variable to disable dispatching has been removed. Support for the `NUMPY_EXPERIMENTAL_ARRAY_FUNCTION` environment variable has been removed. This variable disabled dispatching with `__array_function__`. ([gh-23376](https://github.com/numpy/numpy/pull/23376)) - Support for `y=` as an alias of `out=` has been removed. The `fix`, `isposinf` and `isneginf` functions allowed using `y=` as a (deprecated) alias for `out=`. This is no longer supported. ([gh-23376](https://github.com/numpy/numpy/pull/23376)) Compatibility notes - The `busday_count` method now correctly handles cases where the `begindates` is later in time than the `enddates`. Previously, the `enddates` was included, even though the documentation states it is always excluded. ([gh-23229](https://github.com/numpy/numpy/pull/23229)) - When comparing datetimes and timedelta using `np.equal` or `np.not_equal` numpy previously allowed the comparison with `casting="unsafe"`. This operation now fails. Forcing the output dtype using the `dtype` kwarg can make the operation succeed, but we do not recommend it. ([gh-22707](https://github.com/numpy/numpy/pull/22707)) - When loading data from a file handle using `np.load`, if the handle is at the end of file, as can happen when reading multiple arrays by calling `np.load` repeatedly, numpy previously raised `ValueError` if `allow_pickle=False`, and `OSError` if `allow_pickle=True`. Now it raises `EOFError` instead, in both cases. ([gh-23105](https://github.com/numpy/numpy/pull/23105)) `np.pad` with `mode=wrap` pads with strict multiples of original data Code based on earlier version of `pad` that uses `mode="wrap"` will return different results when the padding size is larger than initial array. `np.pad` with `mode=wrap` now always fills the space with strict multiples of original data even if the padding size is larger than the initial array. ([gh-22575](https://github.com/numpy/numpy/pull/22575)) Cython `long_t` and `ulong_t` removed `long_t` and `ulong_t` were aliases for `longlong_t` and `ulonglong_t` and confusing (a remainder from of Python 2). This change may lead to the errors: 'long_t' is not a type identifier 'ulong_t' is not a type identifier We recommend use of bit-sized types such as `cnp.int64_t` or the use of `cnp.intp_t` which is 32 bits on 32 bit systems and 64 bits on 64 bit systems (this is most compatible with indexing). If C `long` is desired, use plain `long` or `npy_long`. `cnp.int_t` is also `long` (NumPy\'s default integer). However, `long` is 32 bit on 64 bit windows and we may wish to adjust this even in NumPy. (Please do not hesitate to contact NumPy developers if you are curious about this.) ([gh-22637](https://github.com/numpy/numpy/pull/22637)) Changed error message and type for bad `axes` argument to `ufunc` The error message and type when a wrong `axes` value is passed to `ufunc(..., axes=[...])` has changed. The message is now more indicative of the problem, and if the value is mismatched an `AxisError` will be raised. A `TypeError` will still be raised for invalidinput types. ([gh-22675](https://github.com/numpy/numpy/pull/22675)) Array-likes that define `__array_ufunc__` can now override ufuncs if used as `where` If the `where` keyword argument of a `numpy.ufunc`{.interpreted-text role="class"} is a subclass of `numpy.ndarray`{.interpreted-text role="class"} or is a duck type that defines `numpy.class.__array_ufunc__`{.interpreted-text role="func"} it can override the behavior of the ufunc using the same mechanism as the input and output arguments. Note that for this to work properly, the `where.__array_ufunc__` implementation will have to unwrap the `where` argument to pass it into the default implementation of the `ufunc` or, for `numpy.ndarray`{.interpreted-text role="class"} subclasses before using `super().__array_ufunc__`. ([gh-23240](https://github.com/numpy/numpy/pull/23240)) Compiling against the NumPy C API is now backwards compatible by default NumPy now defaults to exposing a backwards compatible subset of the C-API. This makes the use of `oldest-supported-numpy` unnecessary. Libraries can override the default minimal version to be compatible with using: define NPY_TARGET_VERSION NPY_1_22_API_VERSION before including NumPy or by passing the equivalent `-D` option to the compiler. The NumPy 1.25 default is `NPY_1_19_API_VERSION`. Because the ``` ### 1.24.4 ``` discovered after the 1.24.3 release. It is the last planned release in the 1.24.x cycle. The Python versions supported by this release are 3.8-3.11. Contributors A total of 4 people contributed to this release. 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6620c0acd41dbcb368610bb2f4d83145674040025e5536954782467100aa8835 numpy-1.24.4-cp39-cp39-win32.whl befe2bf740fd8373cf56149a5c23a0f601e82869598d41f8e188a0e9869926f8 numpy-1.24.4-cp39-cp39-win_amd64.whl 31f13e25b4e304632a4619d0e0777662c2ffea99fcae2029556b17d8ff958aef numpy-1.24.4-pp38-pypy38_pp73-macosx_10_9_x86_64.whl 95f7ac6540e95bc440ad77f56e520da5bf877f87dca58bd095288dce8940532a numpy-1.24.4-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl e98f220aa76ca2a977fe435f5b04d7b3470c0a2e6312907b37ba6068f26787f2 numpy-1.24.4-pp38-pypy38_pp73-win_amd64.whl 80f5e3a4e498641401868df4208b74581206afbee7cf7b8329daae82676d9463 numpy-1.24.4.tar.gz ``` ### 1.24.3 ``` discovered after the 1.24.2 release. The Python versions supported by this release are 3.8-3.11. Contributors A total of 12 people contributed to this release. People with a \"+\" by their names contributed a patch for the first time. - Aleksei Nikiforov + - Alexander Heger - Bas van Beek - Bob Eldering - Brock Mendel - Charles Harris - Kyle Sunden - Peter Hawkins - Rohit Goswami - Sebastian Berg - Warren Weckesser - dependabot\[bot\] Pull requests merged A total of 17 pull requests were merged for this release. - [23206](https://github.com/numpy/numpy/pull/23206): BUG: fix for f2py string scalars (#23194) - [23207](https://github.com/numpy/numpy/pull/23207): BUG: datetime64/timedelta64 comparisons return NotImplemented - [23208](https://github.com/numpy/numpy/pull/23208): MAINT: Pin matplotlib to version 3.6.3 for refguide checks - [23221](https://github.com/numpy/numpy/pull/23221): DOC: Fix matplotlib error in documentation - [23226](https://github.com/numpy/numpy/pull/23226): CI: Ensure submodules are initialized in gitpod. - [23341](https://github.com/numpy/numpy/pull/23341): TYP: Replace duplicate reduce in ufunc type signature with reduceat. - [23342](https://github.com/numpy/numpy/pull/23342): TYP: Remove duplicate CLIP/WRAP/RAISE in `__init__.pyi`. - [23343](https://github.com/numpy/numpy/pull/23343): TYP: Mark `d` argument to fftfreq and rfftfreq as optional\... - [23344](https://github.com/numpy/numpy/pull/23344): TYP: Add type annotations for comparison operators to MaskedArray. - [23345](https://github.com/numpy/numpy/pull/23345): TYP: Remove some stray type-check-only imports of `msort` - [23370](https://github.com/numpy/numpy/pull/23370): BUG: Ensure like is only stripped for `like=` dispatched functions - [23543](https://github.com/numpy/numpy/pull/23543): BUG: fix loading and storing big arrays on s390x - [23544](https://github.com/numpy/numpy/pull/23544): MAINT: Bump larsoner/circleci-artifacts-redirector-action - [23634](https://github.com/numpy/numpy/pull/23634): BUG: Ignore invalid and overflow warnings in masked setitem - [23635](https://github.com/numpy/numpy/pull/23635): BUG: Fix masked array raveling when `order="A"` or `order="K"` - [23636](https://github.com/numpy/numpy/pull/23636): MAINT: Update conftest for newer hypothesis versions - [23637](https://github.com/numpy/numpy/pull/23637): BUG: Fix bug in parsing F77 style string arrays. 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210461d87fb02a84ef243cac5e814aad2b7f4be953b32cb53327bb49fd77fbb4 numpy-1.24.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 784c6da1a07818491b0ffd63c6bbe5a33deaa0e25a20e1b3ea20cf0e43f8046c numpy-1.24.3-cp39-cp39-win32.whl d5036197ecae68d7f491fcdb4df90082b0d4960ca6599ba2659957aafced7c17 numpy-1.24.3-cp39-cp39-win_amd64.whl 352ee00c7f8387b44d19f4cada524586f07379c0d49270f87233983bc5087ca0 numpy-1.24.3-pp38-pypy38_pp73-macosx_10_9_x86_64.whl 1a7d6acc2e7524c9955e5c903160aa4ea083736fde7e91276b0e5d98e6332812 numpy-1.24.3-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 35400e6a8d102fd07c71ed7dcadd9eb62ee9a6e84ec159bd48c28235bbb0f8e4 numpy-1.24.3-pp38-pypy38_pp73-win_amd64.whl ab344f1bf21f140adab8e47fdbc7c35a477dc01408791f8ba00d018dd0bc5155 numpy-1.24.3.tar.gz ``` ### 1.24.2 ``` discovered after the 1.24.1 release. The Python versions supported by this release are 3.8-3.11. Contributors A total of 14 people contributed to this release. People with a \"+\" by their names contributed a patch for the first time. - Bas van Beek - Charles Harris - Khem Raj + - Mark Harfouche - Matti Picus - Panagiotis Zestanakis + - Peter Hawkins - Pradipta Ghosh - Ross Barnowski - Sayed Adel - Sebastian Berg - Syam Gadde + - dmbelov + - pkubaj + Pull requests merged A total of 17 pull requests were merged for this release. - [22965](https://github.com/numpy/numpy/pull/22965): MAINT: Update python 3.11-dev to 3.11. - [22966](https://github.com/numpy/numpy/pull/22966): DOC: Remove dangling deprecation warning - [22967](https://github.com/numpy/numpy/pull/22967): ENH: Detect CPU features on FreeBSD/powerpc64\* - [22968](https://github.com/numpy/numpy/pull/22968): BUG: np.loadtxt cannot load text file with quoted fields separated\... - [22969](https://github.com/numpy/numpy/pull/22969): TST: Add fixture to avoid issue with randomizing test order. - [22970](https://github.com/numpy/numpy/pull/22970): BUG: Fix fill violating read-only flag. (#22959) - [22971](https://github.com/numpy/numpy/pull/22971): MAINT: Add additional information to missing scalar AttributeError - [22972](https://github.com/numpy/numpy/pull/22972): MAINT: Move export for scipy arm64 helper into main module - [22976](https://github.com/numpy/numpy/pull/22976): BUG, SIMD: Fix spurious invalid exception for sin/cos on arm64/clang - [22989](https://github.com/numpy/numpy/pull/22989): BUG: Ensure correct loop order in sin, cos, and arctan2 - [23030](https://github.com/numpy/numpy/pull/23030): DOC: Add version added information for the strict parameter in\... - [23031](https://github.com/numpy/numpy/pull/23031): BUG: use `_Alignof` rather than `offsetof()` on most compilers - [23147](https://github.com/numpy/numpy/pull/23147): BUG: Fix for npyv\_\_trunc_s32_f32 (VXE) - [23148](https://github.com/numpy/numpy/pull/23148): BUG: Fix integer / float scalar promotion - [23149](https://github.com/numpy/numpy/pull/23149): BUG: Add missing \<type_traits> header. - [23150](https://github.com/numpy/numpy/pull/23150): TYP, MAINT: Add a missing explicit `Any` parameter to the `npt.ArrayLike`\... - [23161](https://github.com/numpy/numpy/pull/23161): BLD: remove redundant definition of npy_nextafter \[wheel build\] Checksums MD5 73fe0b507f56c0baf43171a76ad2003f numpy-1.24.2-cp310-cp310-macosx_10_9_x86_64.whl 2dbbe6f8a14e14978d24de9fcc8b49fe numpy-1.24.2-cp310-cp310-macosx_11_0_arm64.whl 9ddadbf9cac2742318d8b292cb9ca579 numpy-1.24.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl 969f4f33baaff53dbbbaf1a146c43534 numpy-1.24.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 6df575dff02feac835d22debb15d190e numpy-1.24.2-cp310-cp310-win32.whl 2f939228a8c33265f2a8a1fce349d6f1 numpy-1.24.2-cp310-cp310-win_amd64.whl c093e61421be01ffff435387839949f1 numpy-1.24.2-cp311-cp311-macosx_10_9_x86_64.whl 03d71e3d9a086b56837c461fd7c9188b numpy-1.24.2-cp311-cp311-macosx_11_0_arm64.whl c0dc33697d156e2b9a029095efeb1b10 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003a9f530e880cb2cd177cba1af7220b9aa42def9c4afc2a2fc3ee6be7eb2b22 numpy-1.24.2.tar.gz ``` ### 1.24.1 ``` discovered after the 1.24.0 release. The Python versions supported by this release are 3.8-3.11. Contributors A total of 12 people contributed to this release. People with a \"+\" by their names contributed a patch for the first time. - Andrew Nelson - Ben Greiner + - Charles Harris - Clément Robert - Matteo Raso - Matti Picus - Melissa Weber Mendonça - Miles Cranmer - Ralf Gommers - Rohit Goswami - Sayed Adel - Sebastian Berg Pull requests merged A total of 18 pull requests were merged for this release. - [22820](https://github.com/numpy/numpy/pull/22820): BLD: add workaround in setup.py for newer setuptools - [22830](https://github.com/numpy/numpy/pull/22830): BLD: CIRRUS_TAG redux - [22831](https://github.com/numpy/numpy/pull/22831): DOC: fix a couple typos in 1.23 notes - [22832](https://github.com/numpy/numpy/pull/22832): BUG: Fix refcounting errors found using pytest-leaks - [22834](https://github.com/numpy/numpy/pull/22834): BUG, SIMD: Fix invalid value encountered in several ufuncs - [22837](https://github.com/numpy/numpy/pull/22837): TST: ignore more np.distutils.log imports - [22839](https://github.com/numpy/numpy/pull/22839): BUG: Do not use getdata() in np.ma.masked_invalid - [22847](https://github.com/numpy/numpy/pull/22847): BUG: Ensure correct behavior for rows ending in delimiter in\... - [22848](https://github.com/numpy/numpy/pull/22848): BUG, SIMD: Fix the bitmask of the boolean comparison - [22857](https://github.com/numpy/numpy/pull/22857): BLD: Help raspian arm + clang 13 about \_\_builtin_mul_overflow - [22858](https://github.com/numpy/numpy/pull/22858): API: Ensure a full mask is returned for masked_invalid - [22866](https://github.com/numpy/numpy/pull/22866): BUG: Polynomials now copy properly (#22669) - [22867](https://github.com/numpy/numpy/pull/22867): BUG, SIMD: Fix memory overlap in ufunc comparison loops - [22868](https://github.com/numpy/numpy/pull/22868): BUG: Fortify string casts against floating point warnings - [22875](https://github.com/numpy/nu
pyup-bot commented 1 year ago

Closing this in favor of #286