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This PR contains the following updates:
2.23.1->2.26.03.3.0->3.4.11.25.2->1.26.10.28.0->0.28.12.1.0->2.1.27.4.1->7.4.33.11.1->3.12.0Release Notes
aws-powertools/powertools-lambda-python (aws-lambda-powertools)
v2.26.0Compare Source
[v2.26.0] - 2023-10-13
v2.25.1Compare Source
[v2.25.1] - 2023-09-22
v2.25.0Compare Source
[v2.25.0] - 2023-09-15
v2.24.0Compare Source
[v2.24.0] - 2023-09-08
aws/aws-sdk-pandas (awswrangler)
v3.4.1: AWS SDK for pandas 3.4.1Compare Source
Features/Enhancements 🚀
athena.to_icebergby @LeonLuttenberger in https://github.com/aws/aws-sdk-pandas/pull/2465client_request_tokenby @kukushking in https://github.com/aws/aws-sdk-pandas/pull/2474Bug fixes 🐛
sanitize_column_nameincreate_*_tableby @LeonLuttenberger in https://github.com/aws/aws-sdk-pandas/pull/2464requests_aws4authnot being treated as an optional dependency by @LeonLuttenberger in https://github.com/aws/aws-sdk-pandas/pull/2471Documentation 📚
New Contributors
Full Changelog: aws/aws-sdk-pandas@3.4.0...3.4.1
v3.4.0: AWS SDK for pandas 3.4.0Compare Source
Features/Enhancements 🚀
wr.cloudwatchqueries by @LeonLuttenberger in #2430Bug fixes 🐛
athena.to_icebergwait_query by @jaidisido in #2428athena.to_icebergby @jaidisido in #2446wr.s3.to_parquetby @kukushking in #2455Tests 🧪
New Contributors
Full Changelog: aws/aws-sdk-pandas@3.3.0...3.4.0
numpy/numpy (numpy)
v1.26.1Compare Source
NumPy 1.26.1 Release Notes
NumPy 1.26.1 is a maintenance release that fixes bugs and regressions
discovered after the 1.26.0 release. In addition, it adds new
functionality for detecting BLAS and LAPACK when building from source.
Highlights are:
The 1.26.release series is the last planned minor release series before
NumPy 2.0. The Python versions supported by this release are 3.9-3.12.
Build system changes
Improved BLAS/LAPACK detection and control
Auto-detection for a number of BLAS and LAPACK is now implemented for
Meson. By default, the build system will try to detect MKL, Accelerate
(on macOS >=13.3), OpenBLAS, FlexiBLAS, BLIS and reference BLAS/LAPACK.
Support for MKL was significantly improved, and support for FlexiBLAS
was added.
New command-line flags are available to further control the selection of
the BLAS and LAPACK libraries to build against.
To select a specific library, use the config-settings interface via
piporpypa/build. E.g., to selectlibblas/liblapack, use:This works not only for the libraries named above, but for any library
that Meson is able to detect with the given name through
pkg-configorCMake.
Besides
-Dblasand-Dlapack, a number of other new flags areavailable to control BLAS/LAPACK selection and behavior:
-Dblas-orderand-Dlapack-order: a list of library names tosearch for in order, overriding the default search order.
-Duse-ilp64: if set totrue, use ILP64 (64-bit integer) BLAS andLAPACK. Note that with this release, ILP64 support has been extended
to include MKL and FlexiBLAS. OpenBLAS and Accelerate were supported
in previous releases.
-Dallow-noblas: if set totrue, allow NumPy to build with itsinternal (very slow) fallback routines instead of linking against an
external BLAS/LAPACK library. The default for this flag may be
changed to ``true`` in a future 1.26.x release, however for
1.26.1 we'd prefer to keep it as ``false`` because if failures
to detect an installed library are happening, we'd like a bug
report for that, so we can quickly assess whether the new
auto-detection machinery needs further improvements.
-Dmkl-threading: to select the threading layer for MKL. There arefour options:
seq,iomp,gompandtbb. The default isauto, which selects from those four as appropriate given theversion of MKL selected.
-Dblas-symbol-suffix: manually select the symbol suffix to use forthe library - should only be needed for linking against libraries
built in a non-standard way.
New features
numpy._coresubmodule stubsnumpy._coresubmodule stubs were added to provide compatibility withpickled arrays created using NumPy 2.0 when running Numpy 1.26.
Contributors
A total of 13 people contributed to this release. People with a "+" by
their names contributed a patch for the first time.
Pull requests merged
A total of 20 pull requests were merged for this release.
-march=native...use-compute-creditsfor Cirrus.NumpyUnpicklerfor backportingnumpy._corestubs. RemoveNumpyUnpicklerChecksums
MD5
SHA256
v1.26.0Compare Source
NumPy 1.26.0 Release Notes
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:
The Python versions supported in this release are 3.9-3.12.
New Features
Array API v2022.12 support in
numpy.array_apinumpy.array_apinow full supports thev2022.12 version of the array API standard. Note that this does not
yet include the optional
fftextension in the standard.(gh-23789)
Support for the updated Accelerate BLAS/LAPACK library
Support for the updated Accelerate BLAS/LAPACK library, including ILP64
(64-bit integer) support, in macOS 13.3 has been added. This brings
arm64 support, and significant performance improvements of up to 10x for
commonly used linear algebra operations. When Accelerate is selected at
build time, the 13.3+ version will automatically be used if available.
(gh-24053)
mesonbackend forf2pyf2pyin compile mode (i.e.f2py -c) now accepts the--backend mesonoption. This is the default option for Python3.12on-wards. Older versions will still default to
--backend distutils.To support this in realistic use-cases, in compile mode
f2pytakes a--depflag one or many times which maps todependency()calls in themesonbackend, and does nothing in thedistutilsbackend.There are no changes for users of
f2pyonly as a code generator, i.e.without
-c.(gh-24532)
bind(c)support forf2pyBoth functions and subroutines can be annotated with
bind(c).f2pywill handle both the correct type mapping, and preserve the unique label
for other
Cinterfaces.Note:
bind(c, name = 'routine_name_other_than_fortran_routine')isnot honored by the
f2pybindings by design, sincebind(c)with thenameis meant to guarantee only the same name inCandFortran,not in
PythonandFortran.(gh-24555)
Improvements
iso_c_bindingsupport forf2pyPreviously, users would have to define their own custom
f2cmapfile touse type mappings defined by the Fortran2003
iso_c_bindingintrinsicmodule. These type maps are now natively supported by
f2py(gh-24555)
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
pipandpypa/build. Thefollowing are supported:
pip install numpyor (in a cloned repo)pip install .python -m build(preferred), orpip wheel .pip install -e . --no-build-isolationspin:
spin build.All the regular
pipandpypa/buildflags (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.cfgfile to select BLAS and LAPACK. Instead, there arecommand-line flags that can be passed to the build via
pip/build'sconfig-settings interface. These flags are all listed in the
meson_options.txtfile in the root of the repo. Detailed documentedwill be available before the final 1.26.0 release; for now please see
the SciPy "building from source" docs
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.tomlfor 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 temporaryworkaround (on Python 3.9-3.11, not 3.12), by copying
pyproject.toml.setuppytopyproject.toml. However, please open anissue with details on the NumPy issue tracker. We aim to phase out
setup.pybuilds as soon as possible, and therefore would like to seeall potential blockers surfaced early on in the 1.26.0 release cycle.
Contributors
A total of 20 people contributed to this release. People with a "+" by
their names contributed a patch for the first time.
Pull requests merged
A total of 59 pull requests were merged for this release.
_NestedSequence.__getitem__signatureextbuild.pyfrom main.asv devhas been removed, useasv run._umath_linalgdependenciesbindingdirective to "False".castingkeyword tonp.clipfromnumeric.pyiiso_c_bindingtype maps and fixbind(c)...binary_reprto accept any object implementing...dtypeandgenerichashabletyping.assert_typemesonbackend forf2pyspin docs...Checksums
MD5
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openai/openai-python (openai)
v0.28.1Compare Source
What's Changed
New Contributors
Full Changelog: openai/openai-python@v0.27.10...v0.28.1
pandas-dev/pandas (pandas)
v2.1.2: Pandas 2.1.2Compare Source
This is a patch release in the 2.1.x series and includes some regression and bug fixes. We recommend that all users upgrade to this version.
See the full whatsnew for a list of all the changes.
The release will be available on the defaults and conda-forge channels:
Or via PyPI:
Please report any issues with the release on the pandas issue tracker.
Thanks to all the contributors who made this release possible.
v2.1.1: Pandas 2.1.1Compare Source
This is a patch release in the 2.1.x series and includes some regression and bug fixes. We recommend that all users upgrade to this version.
See the full whatsnew for a list of all the changes.
The release will be available on the defaults and conda-forge channels:
Or via PyPI:
Please report any issues with the release on the pandas issue tracker.
Thanks to all the contributors who made this release possible.
pytest-dev/pytest (pytest)
v7.4.3: pytest 7.4.3 (2023-10-24)Compare Source
Bug Fixes
#10447: Markers are now considered in the reverse mro order to ensure base class markers are considered first -- this resolves a regression.
#11239: Fixed
:=in asserts impacting unrelated test cases.#11439: Handled an edge case where :data:
sys.stderrmight already be closed when :ref:faulthandleris tearing down.v7.4.2: pytest 7.4.2 (2023-09-07)Compare Source
Bug Fixes
#11237: Fix doctest collection of
functools.cached_propertyobjects.#11306: Fixed bug using
--importmode=importlibwhich would cause package__init__.pyfiles to be imported more than once in some cases.#11367: Fixed bug where
user_propertieswhere not being saved in the JUnit XML file if a fixture failed during teardown.#11394: Fixed crash when parsing long command line arguments that might be interpreted as files.
Improved Documentation
pytest-dev/pytest-mock (pytest-mock)
v3.12.0Compare Source
mocker.resetall()now also resets mocks created bymocker.create_autospec(#390_)... _#390:https://github.com/pytest-dev/pytest-mock/pull/3900
Configuration
📅 Schedule: Branch creation - "before 4am on the first day of the month" (UTC), Automerge - At any time (no schedule defined).
🚦 Automerge: Disabled by config. Please merge this manually once you are satisfied.
♻ Rebasing: Whenever PR becomes conflicted, or you tick the rebase/retry checkbox.
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