Hi Chuck, and thanks for putting this together!
It seems the release has broken existing uses of dask array with `np.min` (I presume among other functions):
Perhaps `__array_function__` should be switched off for one more release cycle? I imagine that scikit-image [1] are not the only ones using this construct, which worked fine before `__array_function__`.
Thank goodness (and you!) for pre-releases! ;)
Juan.
On Mon, 1 Jul 2019, at 8:48 AM, Charles R Harris wrote:
Hi All,
On behalf of the NumPy team I am pleased to announce the release of NumPy 1.17.0rc1. The 1.17 release contains a number of new features that should substantially improve its performance and usefulness. The Python versions supported are 3.5-3.7, note that Python 2.7 has been dropped. Python 3.8b1 should work with the released source packages, but there are no guarantees about future releases. Highlights of this release are:
- A new extensible random module along with four selectable random numbe5 generators and improved seeding designed for use in parallel processes has been added. The currently available bit generators are MT19937, PCG64, Philox, and SFC64.
- NumPy's FFT implementation was changed from fftpack to pocketfft, resulting in faster, more accurate transforms and better handling of datasets of prime length.
- New radix sort and timsort sorting methods. It is currently not possible to choose which will be used, but they are hardwired to the datatype and used when either ``stable`` or ``mergesort`` is passed as the method.
- Overriding numpy functions is now possible by default
Downstream developers should use Cython >= 0.29.10 for Python 3.8 support and OpenBLAS >= 3.7 (not currently out) to avoid problems on the Skylake architecture. The NumPy wheels on PyPI are built from the OpenBLAS development branch in order to avoid those problems. Wheels for this release can be downloaded from
PyPI, source archives and release notes are available from
Github.
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