Evaluation of the carbon sequestration for the canton of Vaud

Preparing the environment

1. Create the conda environment

# the environment's name will be `carbonseq_vaud`
conda env create -f environment.yml

2. Follow this instructions to set the environment variables AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY for the fresh floodreg_vaud conda environment (in order for boto3 to find your S3-like credentials for DigitalOcean Spaces). They correspond to the DigitalOcean Spaces access and secret key respectively. Important note: the command jupyter-notebook must be launched from within the floodreg_vaud environment so the access keys can be extracted from the environment variables

3. Enter the fresh environment

conda activate carbonseq_vaud

4. Already within the environment, make it available as a jupyter kernel as in:

python -m ipykernel install --user --name carbonseq_vaud --display-name "Python (carbonseq_vaud)"