On Fri, Jan 23, 2026 at 8:28 AM Swayam Singh via NumPy-Discussion < [email protected]> wrote:
> Hi everyone, > > I'm happy to announce the release of *NumPy-QuadDType-v1.0.0*, a > cross-platform > 128-bit (quadruple precision) floating-point data type for NumPy. > Release notes are available on GitHub: > https://github.com/numpy/numpy-quaddtype/releases/tag/v1.0.0 > > *Highlights* > > - *Platform support*: > Linux, macOS (Intel & Apple Silicon), and Windows; > Python 3.11–3.14 including free-threading (GIL-free) builds; > Big-endian architecture support; > FMA-disable option for older x86-64 CPUs (Sandy Bridge era) > > - *New ufuncs*: > `logaddexp2`, `floor_divide`, `float_power`, `fmod`, `divmod`, > `fabs`, `heaviside`, `conj`/`conjugate`, `expm1`, `cbrt`, > `hypot`, `degrees`/`rad2deg`, `radians`/`deg2rad`, > `nextafter`, `spacing`, `modf`, `ldexp`, `frexp`, > and all logical ufuncs > > - *Enhanced scalar support*: > `is_integer`, `as_integer_ratio`, `imag`/`real` getters, > buffer protocol, `__version__` attribute, > and support for `np.bool`, arbitrary-length Python ints, > bytes, and sequences > > - *Casting improvements*: > `same_value` casting rule; > `StringDType` array casting; > fixed-length string casting; > bytes array casting; > improved inter-backend quad-to-quad fixes > > - *Type stubs*: Full static typing support > - *Serialization*: Pickle and hash support > - *Array functions*: `argmax`/`argmin` slots, `nonzero`, > `scanfunc`/`fromstr`, and comparison promoter registration > > *Links* > > - *Repo*: https://github.com/numpy/numpy-quaddtype > - *Documentation*: https://numpy.org/numpy-quaddtype/ > - *PyPI*: https://pypi.org/project/numpy-quaddtype/ > - *Conda-Forge*: https://anaconda.org/conda-forge/numpy_quaddtype > > *Contributors* > > GitHub usernames of contributors to this release: > > - @SwayamInSync > - @juntyr > - @ngoldbaum > - @jorenham > - @melissawm > - @mhvk > > Congratulations! Chuck
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