Download

The latest stable release of FEniCS is version 2019.1.0, which was released in April 2019.

FEniCS on Docker

To use our prebuilt, high-performance Docker images, first install Docker CE for your platform (Windows, Mac or Linux) and then run the following command:

curl -s https://get.fenicsproject.org | bash

To run the FEniCS Docker image, use the command fenicsproject run. For more options and features, see fenicsproject help.

Alternatively, you can start a container with the following docker command:

docker run -ti -p 127.0.0.1:8000:8000 -v $(pwd):/home/fenics/shared -w /home/fenics/shared quay.io/fenicsproject/stable:current

For detailed instructions, see the FEniCS Reference Manual.

FEniCS on Windows 10

To install FEniCS on Windows 10, enable the Windows Subsystem for Linux and install the Ubuntu distribution. Then follow the instructions for Ubuntu below.

Ubuntu FEniCS on Ubuntu

To install FEniCS on Ubuntu, run the following commands:

sudo apt-get install software-properties-common
sudo add-apt-repository ppa:fenics-packages/fenics
sudo apt-get update
sudo apt-get install fenics

For detailed instructions, see the FEniCS Reference Manual.

FEniCS on Anaconda

To use our prebuilt Anaconda Python packages (Linux and Mac only), first install Anaconda, then run following commands in your terminal:

conda create -n fenicsproject -c conda-forge fenics
source activate fenicsproject

For further information on using Anaconda, see the documentation.

Installing FEniCS via Anaconda is also supported in Microsoft Azure Notebooks. In the first cell of a new Jupyter notebook, type:

!conda config --add channels conda-forge
!conda install fenics

Warning: FEniCS Anaconda recipes are maintained by the community and distributed binary packages do not have a full feature set yet, especially regarding sparse direct solvers and input/output facilities.

Update. 2017.2.0 release on conda-forge features MUMPS direct solver, but lacks SuperLU_dist and MPI-enabled HDF5.

Building FEniCS from source

For installation in high performance computing clusters we recommend always building from source. For detailed instructions, see the FEniCS Reference Manual.