Supported Platforms

SfePy is known to work on various flavors of recent Linux, Intel-based MacOS and Windows. SfePy requires Python 3. The release 2019.4 was the last with Python 2.7 support.

Note: Depending on Python installation and OS used, replacing python by python3 might be required in all the commands below (e.g. in Compilation of C Extension Modules) in order to use Python 3.


Installation prerequisites, required to build SfePy:

Python packages required for using SfePy:

Make sure the dependencies of those packages are also installed (e.g igakit reguires FORTRAN compiler, scikit-umfpack does not work without UMFPACK, petsc4py without PETSc etc.). All dependencies of meshio need to be installed for full mesh file format support (when using pip: pip install meshio[all]).

SfePy should work both with bleeding edge (Git) and last released versions of NumPy and SciPy. Please, submit an issue at Issues page in case this does not hold.

Other dependencies/suggestions:

  • To be able to (re)generate the documentation Sphinx, numpydoc and LaTeX are needed (see How to Regenerate Documentation).

  • If doxygen is installed, the documentation of data structures and functions can be automatically generated by running:

    python doxygendocs
  • Mesh generation tools use pexpect and gmsh or tetgen.

  • IPython is recommended over the regular Python shell to fluently follow some parts of primer/tutorial (see Using IPython).

  • MUMPS library for using MUMPS linear direct solver (real and complex arithmetic, parallel factorization)

Notes on selecting Python Distribution

SfePy should work with any recent Python 3.x (in long-term view Python 3.6+ is recommended). It is only matter of taste to use either native OS Python installation or any other suitable distribution. We could recommend the following distributions to use:

On any supported platform we could recommend Anaconda distribution as easy-to-use, stable and up-to-date Python distribution with all the required dependencies (including pre-built sfepy package).

Note: all SfePy releases are regularly tested on recent Linux distributions (Debian and (K)Ubuntu) using OS Python installation and Anaconda, macOS 10.12+ using Anaconda and Windows 8.1+ using Anaconda.

Installing SfePy

For Anaconda and .deb based Linux distributions (Debian, (K)Ubuntu), pre-built SfePy packages are available. You may directly install them with:

  • Anaconda distribution: install sfepy from conda-forge channel:

    conda install -c conda-forge sfepy
  • Debian/(K)Ubuntu: install python-sfepy:

    sudo apt-get install python-sfepy

There are no further steps required to install/configure SfePy (see Notes on Multi-platform Python Distributions for additional notes).

Using SfePy Docker Images

Besides the classical installation we also provide experimental Docker images with ready-to-run Anaconda and Sfepy installation.

Before you start using SfePy images, you need to first install and configure Docker on your computer. To do this follow official Docker documentation.

Currently available images are:

  • sfepy/sfepy-notebook - basic command line interface and web browser access to Jupyter notebook/JupyterLab interface,

  • sfepy/sfepy-x11vnc-desktop - optimized Ubuntu desktop environment accessible via standard web browser or VNC client.

For available runtime options and further information see sfepy-docker project on Github.

Installing SfePy from Sources

The latest stable release can be obtained from the download page. Otherwise, download the development version of the code from SfePy git repository:

git clone git://

In case you wish to use a specific release instead of the latest master version, use:

git tag -l

to see the available releases - the release tags have form release_<year>.<int>.

See the download page for additional download options.

Compilation of C Extension Modules

In the SfePy top-level directory:

  1. Look at and follow the instructions therein. Usually no changes are necessary.

  2. Compile the extension modules

    • for in-place use:

      python build_ext --inplace
    • for installation:

      python build

We recommend starting with the in-place build.


SfePy can be used without any installation by running its main scripts and examples from the top-level directory of the distribution or can be installed locally or system-wide:

  • system-wide (may require root privileges):

    python install
  • local (requires write access to <installation prefix>):

    python install --root=<installation prefix>

If all went well, proceed with Testing Installation.

Testing Installation

After building and/or installing SfePy you should check if all the functions are working properly by running the automated tests.

Running Automated Test Suite

Depending on type of your build run following tests:

  • in-place build:

    python ./


    python ./sfepy-run run_tests

    or (on Unix-based systems) directly by

    ./sfepy-run run_tests
  • installed (local or system-wide) build:

    sfepy-run run_tests

    (This command creates a directory called 'output' in the current directory as well as some other auxiliary files. Use the in-place build testing if you do not want to care about this.)

    Please note this method is not fully supported on Windows systems yet. It can be currently used only with pre-compiled sfepy packages (see Installing SfePy).

Running Failing Tests in Raise Mode

If a particular test fails, run it in the raise mode

python sfepy-run run_tests --raise tests/<>

and, please, report the output to the SfePy mailing list.

It is also possible to automatically start a debugger when/if an exception is raised by running a test in the debug mode:

python sfepy-run run_tests --debug tests/


If something goes wrong, edit the config file and set debug_flags = '-DDEBUG_FMF' to turn on bound checks in the low level C functions, and recompile the code:

python clean
python build_ext --inplace

Then re-run your code and report the output to the SfePy mailing list.

Using IPython

We generally recommend to use (a customized) IPython interactive shell over the regular Python interpreter when following Tutorial or Primer (or even for any regular interactive work with SfePy).

Install IPython (as a generic part of your selected distribution) and then customize it to your choice.

Depending on your IPython usage, you can customize your default profile or create a SfePy specific new one as follows:

  1. Create a new SfePy profile:

    ipython profile create sfepy
  2. Open the ~/.ipython/profile_sfepy/ file in a text editor and add/edit after the c = get_config() line:

    exec_lines = [
        'import numpy as nm',
        'import matplotlib as mpl',
    # Add your preferred SfePy customization here...
    c.InteractiveShellApp.exec_lines = exec_lines
    c.TerminalIPythonApp.gui = 'wx'
    c.TerminalInteractiveShell.colors = 'Linux' # NoColor, Linux, or LightBG

    Please note, that generally it is not recommended to use star (*) imports here.

  3. Run the customized IPython shell:

    ipython --profile=sfepy

Notes on Multi-platform Python Distributions


We highly recommend this scientific-oriented Python distribution.

(Currently regularly tested by developers on SfePy releases with Python 3.6 64-bit on Ubuntu 16.04 LTS, Windows 8.1+ and macOS 10.12+.)

Download appropriate Anaconda Python 3.x installer package and follow install instructions. We recommend to choose user-level install option (no admin privileges required).

Anaconda can be used for:

  1. installing the latest release of SfePy directly from the conda-forge channel (see sfepy-feedstock). In this case, follow the instructions in Installing SfePy.

    Installing/upgrading SfePy from the conda-forge channel can also be achieved by adding conda-forge to your channels with:

    conda config --add channels conda-forge

    Once the conda-forge channel has been enabled, SfePy can be installed with:

    conda install sfepy

    It is possible to list all of the versions of SfePy available on your platform with:

    conda search sfepy --channel conda-forge
  2. installing the SfePy dependencies only - then proceed with the Installing SfePy from Sources instructions.

    In this case, install the missing/required packages using built-in conda package manager:

    conda install mayavi wxpython

    See conda help for further information.

Occasionally, you should check for distribution and/or installed packages updates (there is no built-in automatic update mechanism available):

conda update conda
conda update anaconda
conda update <package>

or try:

conda update --all

Compilation of C Extension Modules on Windows

To build SfePy extension modules, included mingw-w32/64 compiler tools should work fine. If you encounter any problems, we recommend to install and use Microsoft Visual C++ Build Tools instead (see Anaconda FAQ).

Notes on Installing SfePy Dependencies on Various Platforms

The following information has been provided by users of the listed platforms and may become obsolete over time. The generic installation instructions above should work in any case, provided the required dependencies are installed.


emerge -va pytables pyparsing numpy scipy matplotlib ipython mayavi


pacman -S python2-numpy python2-scipy python2-matplotlib ipython2 python2-sympy
yaourt -S python-pytables python2-mayavi


Edit Makefile and change all references from python to python2. Edit scripts and change shebangs to point to python2.


(Old instructions, check also (K)Ubuntu below.)

First, you have to install the dependencies packages:

apt-get install python-tables python-pyparsing python-matplotlib python-scipy

Than SfePy can be installed with:

apt-get install python-sfepy


(Tested on Kubuntu 16.04 LTS.)

First, you have to install the dependencies packages (if apt-get is not installed, install it or try apt-get install instead):

sudo apt-get install python-scipy python-matplotlib python-tables python-pyparsing libsuitesparse-dev python-setuptools mayavi2 python-dev ipython python-sympy cython python-sparse

Than SfePy can be installed with:

apt-get install python-sfepy