Installation ============ smmregrid is a lightweight python package, but it depends on ``cdo`` for weights installation, thus both installation options requires conda/mamba. We recommend to use `mamba `_ since it provides a lighter and deal in a better way with dependencies. Using PyPi ---------- .. warning:: Please note that although smmregrid is distributed via PyPi, it depends on packages that currently are available only on conda-forge and on configuration files available from the GitHub repository. Therefore, the installation via pip requires the creation of a conda environment as well as the clone from the repository. It will bring you the last version available on PyPi. You can create a conda/mamba environment which incudes the python, `eccodes `_ and `cdo `_ dependencies, and then install smmregrid. However, you should start by cloning the repository from GitHub, since the configuration files used for running ECmean4 are placed there :: > git clone https://github.com/jvonhard/smmregrid.git > mamba create -n smmregrid "python>=3.8" cdo eccodes > mamba activate smmregrid > pip install smmregrid Using GitHub ------------ This method will allow you to have access at the most recent ECmean4 version but it requires a bit more of effort. As before, should clone from the Github Repository :: > git clone https://github.com/jvonhard/smmregrid.git .. note :: Please note that if you clone with HTTPS you will not be able to contribute to the code, even if you are listed as collaborator. If you want to be a developer you should clone with SSH and you should add your own SSH key on the GitHub portal: please check the `procedure on the Github website `_ . Then you can through the ECmean4 folder :: > cd smmregrid and then you can set up the conda/mamba environment :: > mamba env create --name smmregrid -f environment.yml Then you should activate the environment :: > mamba activate smmregrid Requirements ------------ The required packages are listed in ``environment.yml`` and in ``pyproject.toml``. A secondary environment available in ``dev-environment.yml`` can be used for development, including testing capabilities and jupyter notebooks. .. note:: Both Unix and MacOS are supported. Python >=3.8 is requested.