Installation

If not using a conda/mamba environment it is recommended to pip install the wfsai package inside a python virtual environment. e.g.

python -m venv <path-of-your-venv>
source activate <path-of-your-venv>   

pip

pip install git+https://github.com/antarctica/wfsai.git@main

conda/mamba

conda/mamba create -n <environment-name> -c conda-forge git pip
conda/mamba activate <environment-name>
pip install git+https://github.com/antarctica/wfsai.git@main

GDAL

The 'imagery' module within the wfsai package makes use of the gdal python implementation, including it's underlying dependencies. We found that the best way to handle gdal and it's dependencies is to use a mamba environment with the mamba dependency solver. If you are using a conda/mamba environment in your project then simply include gdal as a dependency in your environment.yaml or use the command:

conda install -n <environment-name> -c conda-forge gdal

If not using the 'imagery' module then gdal installation is not required.

Environment Variables

If retrieving a configuration from a remote repository then specify the REMOTE_CONFIG_REPO environment variable.

REMOTE_CONFIG_REPO=<url>

With either remote or local config files, you should specify the CONFIG_FILE environment variable.

CONFIG_FILE=<config filename>