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.

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#

Conda env

If you are using a conda environment, pip is still the tool you use to invoke a from-source build of SciPy. It is important to always use the --no-build-isolation flag to the pip install command, to avoid building against a numpy wheel from PyPI. In order for that to work you must first install the remaining build dependencies into the conda environment:

# Either install all SciPy dev dependencies into a fresh conda environment
mamba env create -f environment.yml

# Or, install only the required build dependencies
mamba install python numpy cython pythran pybind11 compilers openblas meson-python pkg-config

# To build the latest stable release:
pip install scipy --no-build-isolation --no-binary scipy

# To build a development version, you need a local clone of the SciPy git repository:
git clone https://github.com/scipy/scipy.git
cd scipy
git submodule update --init
pip install . --no-build-isolation

Virtual env or system Python

# To build the latest stable release:
pip install scipy --no-binary scipy

# To build a development version, you need a local clone of the SciPy git repository:
git clone https://github.com/scipy/scipy.git
cd scipy
git submodule update --init
pip install .

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:

Conda env

To create a scipy-dev development environment with every required and optional dependency installed, run:

mamba env create -f environment.yml
mamba activate scipy-dev

Virtual env or system Python

Note

There are many tools to manage virtual environments, like venv, virtualenv/virtualenvwrapper, pyenv/pyenv-virtualenv, Poetry, PDM, Hatch, and more. Here we use the basic venv tool that is part of the Python stdlib. You can use any other tool; all we need is an activated Python environment.

Create and activate a virtual environment in a new directory named venv ( note that the exact activation command may be different based on your OS and shell - see “How venvs work” in the venv docs).

Linux

python -m venv venv
source venv/bin/activate

macOS

python -m venv venv
source venv/bin/activate

Windows

python -m venv venv
.\venv\Scripts\activate

Then install the Python-level dependencies (see pyproject.toml) from PyPI with:

# Build dependencies
python -m pip install numpy cython pythran pybind11 meson-python ninja pydevtool rich-click

# Test and optional runtime dependencies
python -m pip install pytest pytest-xdist pytest-timeout pooch threadpoolctl asv gmpy2 mpmath hypothesis

# Doc build dependencies
python -m pip install sphinx "pydata-sphinx-theme==0.9.0" sphinx-design matplotlib numpydoc jupytext myst-nb

# Dev dependencies (static typing and linting)
python -m pip install mypy typing_extensions types-psutil pycodestyle ruff cython-lint

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.

Building from source#

System-level dependencies#

Building SciPy from source#

Building from source to use SciPy#

Building from source for SciPy development#

Customizing builds#

Background information#