Status of numpy.distutils
and migration advice#
numpy.distutils
has been deprecated in NumPy 1.23.0
. It will be removed
for Python 3.12; for Python <= 3.11 it will not be removed until 2 years after
the Python 3.12 release (Oct 2025).
Warning
numpy.distutils
is only tested with setuptools < 60.0
, newer
versions may break. See Interaction of numpy.distutils with setuptools for details.
Migration advice#
It is not necessary to migrate immediately - the release date for Python 3.12 is October 2023. It may be beneficial to wait with migrating until there are examples from other projects to follow (see below).
There are several build systems which are good options to migrate to. Assuming you have compiled code in your package (if not, we recommend using Flit) and you want to be using a well-designed, modern and reliable build system, we recommend:
CMake (or scikit-build as an interface to CMake)
If you have modest needs (only simple Cython/C extensions, and perhaps nested
setup.py
files) and have been happy with numpy.distutils
so far, you
can also consider switching to setuptools
. Note that most functionality of
numpy.distutils
is unlikely to be ported to setuptools
.
Moving to Meson#
SciPy is moving to Meson for its 1.9.0 release, planned for July 2022. During
this process, any remaining issues with Meson’s Python support and achieving
feature parity with numpy.distutils
will be resolved. Note: parity means a
large superset, but right now some BLAS/LAPACK support is missing and there are
a few open issues related to Cython. SciPy uses almost all functionality that
numpy.distutils
offers, so if SciPy has successfully made a release with
Meson as the build system, there should be no blockers left to migrate, and
SciPy will be a good reference for other packages who are migrating.
For more details about the SciPy migration, see:
NumPy itself will very likely migrate to Meson as well, once the SciPy migration is done.
Moving to CMake / scikit-build#
See the scikit-build documentation
for how to use scikit-build. Please note that as of Feb 2022, scikit-build
still relies on setuptools, so it’s probably not quite ready yet for a
post-distutils world. How quickly this changes depends on funding, the current
(Feb 2022) estimate is that if funding arrives then a viable numpy.distutils
replacement will be ready at the end of 2022, and a very polished replacement
mid-2023. For more details on this, see
this blog post by Henry Schreiner.
Moving to setuptools
#
For projects that only use numpy.distutils
for historical reasons, and do
not actually use features beyond those that setuptools
also supports,
moving to setuptools
is likely the solution which costs the least effort.
To assess that, there are the numpy.distutils
features that are not
present in setuptools
:
Nested
setup.py
filesFortran build support
BLAS/LAPACK library support (OpenBLAS, MKL, ATLAS, Netlib LAPACK/BLAS, BLIS, 64-bit ILP interface, etc.)
Support for a few other scientific libraries, like FFTW and UMFPACK
Better MinGW support
Per-compiler build flag customization (e.g. -O3 and SSE2 flags are default)
a simple user build config system, see [site.cfg.example](https://github.com/numpy/numpy/blob/master/site.cfg.example)
SIMD intrinsics support
The most widely used feature is nested setup.py
files. This feature will
likely be ported to setuptools
(see
gh-18588 for status).
Projects only using that feature could move to setuptools
after that is
done. In case a project uses only a couple of setup.py
files, it also could
make sense to simply aggregate all the content of those files into a single
setup.py
file and then move to setuptools
. This involves dropping all
Configuration
instances, and using Extension
instead. E.g.,:
from distutils.core import setup
from distutils.extension import Extension
setup(name='foobar',
version='1.0',
ext_modules=[
Extension('foopkg.foo', ['foo.c']),
Extension('barpkg.bar', ['bar.c']),
],
)
For more details, see the setuptools documentation
Interaction of numpy.distutils
with setuptools
#
It is recommended to use setuptools < 60.0
. Newer versions may work, but
are not guaranteed to. The reason for this is that setuptools
60.0 enabled
a vendored copy of distutils
, including backwards incompatible changes that
affect some functionality in numpy.distutils
.
If you are using only simple Cython or C extensions with minimal use of
numpy.distutils
functionality beyond nested setup.py
files (its most
popular feature, see Configuration
),
then latest setuptools
is likely to continue working. In case of problems,
you can also try SETUPTOOLS_USE_DISTUTILS=stdlib
to avoid the backwards
incompatible changes in setuptools
.
Whatever you do, it is recommended to put an upper bound on your setuptools
build requirement in pyproject.toml
to avoid future breakage - see
For downstream package authors.