Building redistributable binaries#
The intended audience for this section is anyone who wants to build SciPy and deploy it anywhere else than their own machine - from distro packagers to users who want to build wheels to deploy to their production environment
When python -m build
or pip wheel
is used to build a SciPy wheel,
that wheel will rely on external shared libraries (at least for BLAS/LAPACK and
a Fortran compiler runtime library, perhaps other libraries). Such wheels
therefore will only run on the system on which they are built. See
the pypackaging-native content under “Building and installing or uploading
artifacts” for more context on that.
A wheel like that is therefore an intermediate stage to producing a binary that
can be distributed. That final binary may be a wheel - in that case, run
auditwheel
(Linux), delocate
(macOS), delvewheel
(Windows) or
repairwheel
(platform-independent) to vendor the required shared libraries
into the wheel.
The final binary may also be in another packaging format (e.g., a .rpm
,
.deb
or .conda
package). In that case, there are packaging
ecosystem-specific tools to first install the wheel into a staging area, then
making the extension modules in that install location relocatable (e.g., by
rewriting RPATHs), and then repackaging it into the final package format.
Build and runtime dependencies#
The Python build and runtime dependencies that are needed to build SciPy can
be found in the pyproject.toml
metadata. Note that for released versions of
SciPy, dependencies will likely have upper bounds. Each upper bound has
comments above it; packagers are free to remove or loosen those upper bound in
most cases (except for numpy
). E.g.:
# The upper bound on pybind11 is preemptive only
"pybind11>=2.12.0,<2.13.0",
# ...
# 3. The <2.3 upper bound is for matching the numpy deprecation policy,
# it should not be loosened.
"numpy>=2.0.0rc1,<2.3",
Non-Python build requirements are:
C, C++ and Fortran compilers
BLAS and LAPACK libraries
ninja
pkg-config
Minimum versions of common compilers are enforced in the top-level
meson.build
file. The minimum LAPACK version is currently 3.7.1.
More detailed information on these build dependencies can be found in
Toolchain Roadmap.
Using system dependencies instead of vendored sources#
SciPy contains a lot of code that has been vendored from libraries written in
C, C++ and Fortran. This is done for a mix of historical and robustness
reasons. Distro packagers sometimes have reasons to want to unvendor this
code, ensuring that they only have a single version of a particular library in
use. We offer a build option, -Duse-system-libraries
, to allow them to do
so in a much easier fashion than can be done by manually patching SciPy.
$ python -m build -wnx -Duse-system-libraries=boost.math
This build option causes a dependency lookup for the exact same version as is bundled in SciPy only. A different system version will not be accepted, the build will then fall back to the vendored sources or error out. This is because different versions can easily cause failures at build time or at runtime, and SciPy’s CI does not test with any other versions. This may change in the future, however as of now, using a different version requires patching out the relevant version check and is strongly discouraged.
Advice for packagers:
You should think about this build option as “if I’m already unbundling a library for some compelling reason, this option makes that quite a bit easier”.
You should not default to unbundling everything, this will cause diamond dependencies and more build complexity for little gain. Most of these libraries are not maintained as well as SciPy and/or known to not offer a stable API; effectively you’d be adding an extra
==
dependency for each library you unbundle. Only do that for a good reason. E.g., it allows you to drop patches, you consider both SciPy and the vendored library in question security-critical, or it’s a large gain in binary size.
The build option takes the following values:
none
: Use the source code shipped as part of SciPy, do not look for external dependencies (default).all
: Use external libraries for all components controlled byuse-system-libraries
, and error out if they are not found. Detecting is done by Meson, typically first through thepkg-config
and then thecmake
method of thedependency()
function.auto
: Try detecting external libraries, and if they are not found then fall back onto vendored sources.A comma-separated list of dependency names (e.g.,
boost.math,qhull
). If given, uses theall
behavior for the named dependencies (andnone
for the rest). Supported options are:boost.math
(since 1.16.0)qhull
(since 1.16.0)
It’s also valid to combine the generic and named-library options above, for
example boost.math,auto
will apply the auto
behavior to all
dependencies other than boost.math
.
Stripping the test suite from a wheel or installed package#
By default, an installed version of scipy
includes the full test suite.
That test suite, including data files and compiled extension modules that are
test-only, takes up about 4.5 MB in a wheel (for x86-64, as of v1.14.0), and
more than that on disk. In cases where binary size matters, packagers may want
to remove the test suite. As of SciPy 1.14.0, there is a convenient way of
doing this, making use of
Meson’s install tags
functionality. It is a one-liner:
$ python -m build -wnx -Cinstall-args=--tags=runtime,python-runtime,devel
Note
Note that in the above command -wnx
means --wheel --no-isolation
--skip-dependency-check
. It assumes that the packager has already set up
the build environment, which is usually the case for distro packaging. The
install tags feature works equally well with isolated builds (e.g. pip
install scipy --no-binary -Cinstall-args=--tags=runtime,python-runtime,devel
).
If you want to produce a separate package for the tests themselves, say under
the name scipy-tests
, then edit pyproject.toml
to change the project
name:
[project]
name = "scipy-tests"
And then build with:
$ python -m build -wnx -Cinstall-args=--tags=tests
The above would build the whole package twice; in order to rebuild in a cached
fashion, use the -Cbuild-dir=build
build option:
$ $ # apply patch to change the project name in pyproject.toml
$ python -m build -wnx -Cbuild-dir=build -Cinstall-args=--tags=tests
The end result will look something like:
$ ls -lh dist/*.whl
... 20M ... dist/scipy-1.14.0-cp311-cp311-linux_x86_64.whl
... 4,5M ... dist/scipy_tests-1.14.0-cp311-cp311-linux_x86_64.whl