Table of Contents
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
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:
meshio for reading and writing mesh files,
Matplotlib for various plots, GTKAgg for live plotting via log.py,
PyTables for storing results in HDF5 files,
SymPy for some tests and functions,
Mayavi for postproc.py,
igakit for script/gen_iga_patch.py - simple IGA domain generator,
psutil for memory requirements checking
PyVista for post-processing via resview.py
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:
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.
If doxygen is installed, the documentation of data structures and functions can be automatically generated by running:
python setup.py doxygendocs
Mesh generation tools use pexpect and gmsh or tetgen.
MUMPS library for using MUMPS linear direct solver (real and complex arithmetic, parallel factorization)
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:
Linux: OS native installation (See Notes on Installing SfePy Dependencies on Various Platforms for further details.)
Windows: use free versions of commercial multi-platform scientific Python distributions Anaconda or Enthought Canopy (see Notes on Multi-platform Python Distributions for further details). In addition a completely free open-source portable distribution WinPython can be used.
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.
For Anaconda and .deb based Linux distributions (Debian, (K)Ubuntu), pre-built SfePy packages are available. You may directly install them with:
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).
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.
git clone git://github.com/sfepy/sfepy.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.
In the SfePy top-level directory:
site_cfg_template.pyand follow the instructions therein. Usually no changes are necessary.
Compile the extension modules
for in-place use:
python setup.py build_ext --inplace
python setup.py 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 setup.py install
local (requires write access to
python setup.py install --root=<installation prefix>
If all went well, proceed with Testing Installation.
After building and/or installing SfePy you should check if all the functions are working properly by running the automated tests.
Depending on type of your build run following tests:
python ./sfepy-run run_tests
or (on Unix-based systems) directly by
installed (local or system-wide) build:
(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).
If a particular test fails, run it in the raise mode
python sfepy-run run_tests --raise tests/<failing_test_name.py>
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/failing_test_name.py
If something goes wrong, edit the
site_cfg.py config file and set
debug_flags = '-DDEBUG_FMF'
to turn on bound checks in the low level C functions, and recompile the code:
python setup.py clean python setup.py build_ext --inplace
Then re-run your code and report the output to the SfePy mailing list.
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:
Create a new SfePy profile:
ipython profile create sfepy
~/.ipython/profile_sfepy/ipython_config.pyfile in a text editor and add/edit after the
c = get_config()line:
exec_lines = [ 'import numpy as nm', 'import matplotlib as mpl', 'mpl.use("WXAgg")', # # 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.
Run the customized IPython shell:
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:
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
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>
conda update --all
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).
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