Building from source¶
Note
If you are only trying to install SciPy, we recommend using binaries - see Installation for details on that.
Building SciPy from source requires setting up system-level dependencies (compilers, BLAS/LAPACK libraries, etc.) first, and then invoking a build. The build may be done in order to install SciPy for local usage, develop SciPy itself, or build redistributable binary packages. And it may be desired to customize aspects of how the build is done. This guide will cover all these aspects. In addition, it provides background information on how the SciPy build works, and links to up-to-date guides for generic Python build & packaging documentation that is relevant.
System-level dependencies¶
SciPy uses compiled code for speed, which means you need compilers and some other system-level (i.e, non-Python / non-PyPI) dependencies to build it on your system.
Note
If you are using Conda, you can skip the steps in this section - with the
exception of installing compilers for Windows or the Apple Developer Tools
for macOS. All other dependencies will be installed automatically by the
mamba env create -f environment.yml
command.
Building SciPy from source¶
If you want to only install SciPy from source once and not do any development
work, then the recommended way to build and install is to use pip
.
Otherwise, conda is recommended.
Note
If you don’t have a conda installation yet, we recommend using Mambaforge; any conda flavor will work though.
Building from source to use SciPy¶
Building from source for SciPy development¶
If you want to build from source in order to work on SciPy itself, first clone the SciPy repository:
git clone https://github.com/scipy/scipy.git
cd scipy
git submodule update --init
Then you want to do the following:
Create a dedicated development environment (virtual environment or conda environment),
Install all needed dependencies (build, and also test, doc and optional dependencies),
Build SciPy with our
dev.py
developer interface.
Step (3) is always the same, steps (1) and (2) are different between conda and virtual environments:
To build SciPy in an activated development environment, run:
python dev.py build
This will install SciPy inside the repository (by default in a
build-install
directory). You can then run tests (python dev.py test
),
drop into IPython (python dev.py ipython
), or take other development steps
like build the html documentation or running benchmarks. The dev.py
interface is self-documenting, so please see python dev.py --help
and
python dev.py <subcommand> --help
for detailed guidance.
IDE support & editable installs
While the dev.py
interface is our recommended way of working on SciPy,
it has one limitation: because of the custom install location, SciPy
installed using dev.py
will not be recognized automatically within an
IDE (e.g., for running a script via a “run” button, or setting breakpoints
visually). This will work better with an in-place build (or “editable
install”).
Editable installs are supported. It is important to understand that you
may use either an editable install or dev.py in a given repository clone,
but not both. If you use editable installs, you have to use pytest
and other development tools directly instead of using dev.py
.
To use an editable install, ensure you start from a clean repository (run
git clean -xdf
if you’ve built with dev.py
before) and have all
dependencies set up correctly as described higher up on this page. Then
do:
# Note: the --no-build-isolation is important! meson-python will
# auto-rebuild each time SciPy is imported by the Python interpreter.
pip install -e . --no-build-isolation
# To run the tests for, e.g., the `scipy.linalg` module:
pytest scipy/linalg
When making changes to SciPy code, including to compiled code, there is no
need to manually rebuild or reinstall. When you run git clean -xdf
,
which removes the built extension modules, remember to also uninstall SciPy
with pip uninstall scipy
.
See the meson-python documentation on editable installs for more details on how things work under the hood.