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# Installation
The main way to install `io4dolfinx` is through [PYPI](https://pypi.org/project/io4dolfinx/), which provides pre-built binary wheels for most platforms. This is the recommended method for most users.
```bash
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):
```bash
python3 -m pip install "io4dolfinx[test]"
```
- Documentation dependencies (for building the docs):
```bash
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:
```bash
python3 -m pip install --no-binary=h5py h5py
```
- For pyvista support, you can install the `pyvista` package:
```bash
python3 -m pip install pyvista
```
or equivalently
```bash
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](https://github.com/FEniCS/spack-fenics) to be possible to maintain and keep up to date.
We do the same for the [packages](https://github.com/scientificcomputing/spack_repos.git) 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:
```bash
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](https://packages.spack.io/package.html?name=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
```bash
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
```bash
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](https://pypi.org/project/io4dolfinx/) with
```bash
python3 -m pip install io4dolfinx[test]
```
This docker container can be opened with
```bash
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.
```bash
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](https://github.com/scientificcomputing/io4dolfinx/releases)
```
To run the test suite, you should also install `ipyparallel`, `pytest` and `coverage`, which can all be installed with conda
```bash
conda install -c conda-forge ipyparallel pytest coverage
```
|
