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.