Installation

The main way to install io4dolfinx is through PYPI, which provides pre-built binary wheels for most platforms. This is the recommended method for most users.

python3 -m pip install io4dolfinx

io4dolfinx has some optional dependencies for specific backends (like ADIOS2 or H5PY). If you want to use these backends, you can install the library with the appropriate extras:

• Test dependencies (for running the test suite):

python3 -m pip install "io4dolfinx[test]"

• Documentation dependencies (for building the docs):

python3 -m pip install "io4dolfinx[docs]"

• For HDF5 support with MPI, you need to have an HDF5 library installed with MPI support, and the h5py Python package installed with MPI support. You can install h5py with MPI support using pip:

python3 -m pip install --no-binary=h5py h5py

• For pyvista support, you can install the pyvista package:

python3 -m pip install pyvista

or equivalently

python3 -m pip install "io4dolfinx[pyvista]"

• For ADIOS2 support you should have ADIOS2 installed with Python bindings, see https://adios2.readthedocs.io/en/latest/setting_up/setting_up.html for more info.

Spack

The FEniCS Spack packages uses a separate spack repo to be possible to maintain and keep up to date. We do the same for the packages maintained by Scientific Computing at Simula Research Laboratory. To install py-io4dolfinx, one should first install spack on your system, then use the following commands in a new spack environment:

spack repo add https://github.com/FEniCS/spack-fenics.git
spack repo add https://github.com/scientificcomputing/spack_repos.git
spack add py-io4dolfinx@1.1 ^py-fenics-dolfinx+petsc4py ^adios2+python+hdf5 ^petsc+mumps

to get an installation of io4dolfinx with all backends installed. If you require further petsc packages you should activate them by adding them to ^petsc+..... See Spack PETSc for options.

Docker

An MPI build of ADIOS2 is installed in the official DOLFINx containers, and thus there are no additional dependencies required to install io4dolfinx on top of DOLFINx in these images.

Create a Docker container, named for instance dolfinx-checkpoint. Use the nightly tag to get the main branch of DOLFINx, or stable to get the latest stable release

docker run -ti -v $(pwd):/root/shared -w /root/shared --name=dolfinx-checkpoint ghcr.io/fenics/dolfinx/dolfinx:nightly

For the latest version compatible with nightly (with the ability to run the test suite), use

export HDF5_MPI=ON
export HDF5_DIR=/usr/local
python3 -m pip install --no-binary-h5py --no-build-isolation io4dolfinx[test]@git+https://github.com/scientificcomputing/io4dolfinx@main

If you are using the stable image, you can install io4dolfinx from PYPI with

python3 -m pip install io4dolfinx[test]

This docker container can be opened with

docker container start -i dolfinx-checkpoint

at a later instance

Conda

Note

Conda supports the stable release of DOLFINx, and thus the appropriate version should be installed, see the section above for more details.

Following is a minimal recipe of how to install io4dolfinx, given that you have conda installed on your system.

conda create -n dolfinx-checkpoint python=3.12
conda activate dolfinx-checkpoint
conda install -c conda-forge io4dolfinx

Note

Remember to download the appropriate version of io4dolfinx from Github io4dolfinx: Releases

To run the test suite, you should also install ipyparallel, pytest and coverage, which can all be installed with conda

conda install -c conda-forge ipyparallel pytest coverage