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).


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:

  1. Meson

  2. CMake (or scikit-build as an interface to CMake)

If you have modest needs (only simple Cython/C extensions, and perhaps nested 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 files

  • Fortran 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](

  • SIMD intrinsics support

The most widely used feature is nested 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 files, it also could make sense to simply aggregate all the content of those files into a single 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
          Extension('', ['foo.c']),
          Extension('', ['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 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.