====================== Installation for users ====================== Capytaine is available on Windows, MacOS [#]_ and Linux. .. [#] For the latest informations on the Apple arm64 architectures, see https://github.com/capytaine/capytaine/issues/190 Capytaine requires Python 3.7 or higher. It is compatible with `all currently supported version of Python `_. On a cloud platform ------------------- For a quick try of Capytaine without installing anything on your computer, you can use an online Python-based computing environment such as `CoCalc `_, on which Capytaine is already installed by default, or `Google Colab `_. On such a `Jupyter `_-based environment, Capytaine can be installed by running the following command in a cell:: %pip install capytaine Then run the following line to check that the latest version of Capytaine has been installed:: import capytaine as cpt; print(cpt.__version__) You may need to restart the computing environment (kernel) of the notebook for the installation to be effective. All the core feature of Capytaine are accessible from such a Jupyter-based environment, except for some 3D visualization tools. As a standalone executable -------------------------- An experimental distribution of Capytaine bundled with a full Python distribution in a single executable file can be found at `https://github.com/capytaine/capytaine-standalone`_. Please refer to the instruction on that page for download and usage. The standalone executable is the simplest way to use Capytaine locally, although it has some limitations, such a longer startup time and the current lack of interactive Matplotlib figures. You can check the bundled version of Capytaine with the following command:: .\ipython-with-capytaine-windows.exe -c 'print(cpt.__version__)' (or the corresponding file name on other platforms than Windows). Installing with pip package manager ----------------------------------- Since version 2.0, Capytaine is available as precompiled package on all platform on `PyPI `_, the package registry used by the ``pip`` command. After installing a Python interpreter, run the following command line in a terminal to install Capytaine and its dependencies:: python -m pip install capytaine Then run the following line to check that the latest version of Capytaine has been installed:: python -c 'import capytaine as cpt; print(cpt.__version__)' You might want to use a `virtual environment `_ to install Capytaine independently of your other Python packages and avoid any risk of dependency conflict. The package can also be installed by other modern PyPI-based Python package managers, such as PDM_ or poetry_. .. _PDM: https://pdm.fming.dev .. _poetry: https://python-poetry.org Installing with Conda package manager ------------------------------------- Capytaine is also available in the Anaconda package repository, that can be accessed with the `Anaconda distribution`_ or one of its lightweight counterparts Miniconda_ and Miniforge_. .. _Conda: https://conda.io .. _`Anaconda distribution`: https://www.anaconda.com/download/ .. _Miniconda: https://conda.io/miniconda.html .. _Miniforge: https://github.com/conda-forge/miniforge .. _Mamba: https://mamba.readthedocs.io/en/latest/ .. note:: If you experience very long processing time when installing a package with ``conda``, you might want to `install the libmamba solver with ``conda`` `_ or `fully replace ``conda`` with Mamba_. Once Conda has been installed, you can install Capytaine from the `conda-forge` channel. It is recommended to do the installation into a `dedicated virtual environment `_ (here arbitrarily named ``capytaine_env``):: conda create --name capytaine_env --channel conda-forge capytaine Then activate the environment to use it on the command line with:: conda activate capytaine_env or set it in the project configuration of your IDE (for instance see `the documentation of PyCharm `_, `the documentation of VSCode `_ or the `documentation of Spyder `_). Alternatively, Capytaine can be installed in an existing environment with the following command:: conda install --channel conda-forge capytaine You can check which version of Capytaine has been installed by running the following command line:: python -c 'import capytaine as cpt; print(cpt.__version__)' The latest version is currently |version|. Optional dependencies --------------------- All the required dependencies should be installed automatically when installing with ``pip`` or ``conda``. More 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 | :code:`conda install matplotlib` | Used in several examples | | | | in the documentation and | | | | the cookbook | +------------+------------------------------------------+------------------------------+ | vtk | :code:`conda install -c conda-forge vtk` | For 3D visualization | +------------+------------------------------------------+------------------------------+ | joblib | :code:`conda install joblib` | For parallel resolution | +------------+------------------------------------------+------------------------------+ | meshio | :code:`pip install meshio` | To load more mesh formats | +------------+------------------------------------------+------------------------------+ | quadpy | :code:`pip install quadpy` | For higher order quadratures | | | | (experimental) | +------------+------------------------------------------+------------------------------+ After creating the Conda environment containing Capytaine, you can add more packages to this environment by activating it with ``conda activate`` and then using the ``conda install`` or ``pip install`` commands. However, it is often more efficient to specify the packages you'd like in your environment from the start when creating it, such as in the following example:: conda create --name capy_and_other_env --channel conda-forge capytaine jupyter matplotlib vtk With Docker ----------- The following command will create a Docker image based on Ubuntu 22.04 with the version v2.0 of Capytaine:: docker build -t capytaine:v2.0 https://github.com/capytaine/capytaine.git#v2.0 Replace :code:`v2.0` by :code:`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:v2.0 ipython3 Or the following command to make the current directory accessible from the Docker image and run the file :code:`my_script.py` from the current directory:: docker run -it -v $(pwd):/home/user capytaine:v2.0 python3 my_scipt.py Note that graphical displays (matplotlib, vtk, ...) might require a complex setup to work from the Docker image. With Guix --------- For advanced users, `Guix `_ package definitions are available at the root of the repository:: curl -o capytaine.scm https://raw.githubusercontent.com/capytaine/capytaine/master/capytaine.scm guix shell -f capytaine.scm python -- python3 -c 'import capytaine; print(capytaine.__version__)'