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 Cheers, Swayam Singh _______________________________________________ NumPy-Discussion mailing list -- [email protected] To unsubscribe send an email to [email protected] https://mail.python.org/mailman3//lists/numpy-discussion.python.org Member address: [email protected]
