Installation for users

Capytaine is available on Windows, MacOS [1] and Linux.

Capytaine requires Python 3.6 or higher. Thus it is compatible with all currently supported version of Python.

With Conda

The easiest way to install Capytaine is the precompiled package available on Conda. Download and install the Anaconda distribution or its lightweight counterparts Miniconda and Miniforge.

Once Conda has been installed, you might want to create a dedicated environment. Capytaine’s package is available in the conda-forge channel and can be installed with the following command:

conda install -c conda-forge capytaine

The required dependencies should be installed automatically.

You can check which version of Capytaine has been installed by opening a Python shell and running:

import capytaine; print(capytaine.__version__)

Optional dependencies

Optional dependencies can be manually installed. They are nice to have but not necessary for Capytaine’s main features.

Name

Example installation command

Usage

matplotlib

conda install matplotlib

Used in several examples in the documentation and the cookbook

vtk

conda install -c conda-forge vtk

For 3D visualization

joblib

conda install joblib

For parallel resolution

meshio

pip install meshio

To load more mesh formats

quadpy

pip install quadpy

For higher order quadratures (experimental)

With Pip

The package is available on PyPI, although only as a source distribution. That means that you’ll need a Fortran compiler [2] in order to install the package. If you do, you can install Capytaine as:

pip install capytaine

If you can’t install a compiler, it is recommended to use Conda instead.

With Docker

The following command will create a Docker image based on Ubuntu 22.04 with the version v1.5 of Capytaine:

docker build -t capytaine:v1.5 https://github.com/capytaine/capytaine.git#v1.5

Replace v1.5 by master to download instead the latest development version. Use the following command to open an IPython shell in which Capytaine can be imported:

docker run -it capytaine:v1.5 ipython3

Or the following command to make the current directory accessible from the Docker image and run the file my_script.py from the current directory:

docker run -it -v $(pwd):/home/user capytaine:v1.5 python3 my_scipt.py

Note that graphical displays (matplotlib, vtk, …) might require a complex setup to work from the Docker image.