Installation

In order to best make use of the pynuml package, it is strongly encouraged to install the provided numl Anaconda environment. Parallel processing functionality requires an MPI installation, which will be automatically configured when you install the numl conda environment.

Installing the numl conda environment

Installing pynuml requires an Anaconda installation that utilises conda-forge. If you need to install Anaconda, we recommend using the Mambaforge variant.

A conda environment for numl is available via the anaconda client, and can be installed using:

mamba install -y anaconda-client
mamba env create numl/numl

Once installed, this environment will need to be activated at the start of each terminal session:

mamba activate numl

This environment contains the most recent version of pynuml published to conda.

Installing with Anaconda

It is also possible to install pynuml on its own via Anaconda, using the numl channel:

mamba install -c numl pynuml

Installing with pip

pynuml is also available on PyPi, although this installation method is not recommended, as pynuml has non-python dependencies that cannot be installed by pip. If the user has installed those dependencies manually, then the package can be installed using:

pip install pynuml

Installing for development

If you’re installing pynuml for development, you can install the numl Anaconda environment as outlined above, and then clone the repository directly and install it in editable mode:

git clone https://github.com/vhewes/pynuml
pip install --no-deps -e ./pynuml

This will uninstall the conda release of pynuml installed by default as part of the numl environment, and override it with your local repository. If installed in editable mode, any changes made to the package will instantaneously be reflected when the module is imported in Python.