The SOMISANA toolkit CLI (Command Line Interface) is packaged as a Docker image, and can be used without configuring a local dev environment.
Ensure that docker is installed on your system, and install the CLI:
# Download and execute the install script
wget -qO- https://raw.githubusercontent.com/SAEON/somisana/stable/toolkit/install.sh | bash
# Reload your terminal configuration
source ~/.bashrc
# Start Docker if it's not running
sudo service docker start
# Run the CLI
somisana -h
# Update the CLI
somisana update --version latest
Use the CLI to update itself, referencing a newer version. choose the version of the CLI to use from the listed versions https://github.com/SAEON/somisana/pkgs/container/somisana_toolkit_stable (for example, sha-89a5f54
), and then run the update command:
somisana update --version sha-89a5f54
# Or to reset to the original installed version
somisana update --reset
(1) Create a directory workspace
export SOMISANA_DIR="/home/$USER/temp/somisana"
export WORKDIR=$SOMISANA_DIR/local-run
mkdir -p $WORKDIR/{croco/{forcing,forecast,scratch},forcing-inputs}
touch $SOMISANA_DIR/.env
echo COPERNICUS_USERNAME=username >> $SOMISANA_DIR/.env
echo COPERNICUS_PASSWORD=password >> $SOMISANA_DIR/.env
touch $WORKDIR/.env
chmod -R 777 $SOMISANA_DIR
cd $SOMISANA_DIR
(2) Download GFS boundary data
somisana \
download \
--workdir $WORKDIR/forcing-inputs \
--matlab-env $WORKDIR/.env \
--provider gfs \
--domain 22,31,-37,-31
(3) Download Mercator boundary data
somisana \
download \
--workdir $WORKDIR/forcing-inputs \
--matlab-env $WORKDIR/.env \
--provider mercator \
--domain 22,31,-37,-31
(4) Create forcing files
For this step you do need the source code currently. From the root of the repository (and on the SAEON VPN):
docker run \
--rm \
-v $(pwd)/models/algoa-bay-forecast/crocotools:/crocotools/ \
-v $(pwd)/models/algoa-bay-forecast/lib/grd.nc:/crocotools/croco/forcing/grd.nc \
-v $WORKDIR:/tmp/somisana/current \
-e [email protected] \
ghcr.io/saeon/somisana_matlab:r2022a \
-batch "run('/crocotools/run.m')"
(5) Compile and run the CROCO model
For this step you do need the source code currently. From the root of the repository:
export NP_ETA=4
export NP_XI=3
export TODAY=$(date +"%Y%m%d")
export YESTERDAY=$(date -d "yesterday" +"%Y%m%d")
# Build the docker image
docker build \
-t abf_local \
--build-arg NP_ETA=$NP_ETA \
--build-arg NP_XI=$NP_XI \
.
# Run the docker image
docker run \
--rm \
-v $WORKDIR:/algoa-bay-forecast/current \
-v $(pwd)/models/algoa-bay-forecast/lib/grd.nc:/algoa-bay-forecast/current/croco/forcing/grd.nc \
--cpus $(expr $NP_ETA \* $NP_XI) \
abf_local \
./run_croco.bash \
/algoa-bay-forecast/current \
$TODAY \
$YESTERDAY
TODO
You need to be able to specify specific Python versions for the toolkit. Here are instructions for achieving this with pyenv
or conda
Nothing to do here
The pyenv tool adds entries to the beginning of your $PATH variable. So that when you type in the "python" or "pip" commands, you actually run the "pyenv" tool instead of python or pip (since the first entries on $PATH are from pyenv). Pyenv then manages python versions, and you can easily switch between python versions in your terminal. The pyenv tool just redirects the python/pip commands to specific Python versions.
- First Install Python build dependencies. These are required in order for Pyenv to install and build Python (I'm not sure why it's necessary for Pyenv to build Python as opposed to downloading an executable)
- Then Install Pyenv
After installing Pyenv, follow the instructions for configuring your shell environment. Then install the correct Python version (for example 3.10.6
at the time of writing)
PYTHON_VERSION=3.10.6
pyenv install $PYTHON_VERSION
pyenv global $PYTHON_VERSION
Python dependencies are managed as part of the source code. Some of the libraries reuire 3rd party binaries to be installed separately
These are dependencies that should be installed using the OS package manager and don't get bundled with Python libraries
# for both Pyenv and Conda
sudo apt update
sudo apt install -y \
asyncpg \
postgis
# libpq is a binary file required by the PostgreSQL driver (asyncpg)
# postgis is required for the `raster2pgsql` application
Create a new conda environment called 'somisana' with all the dependencies via the Condafile.yml
file
cd toolkit
conda env create -f Condafile.yml
Then activate the environment
conda activate somisana
If Condafile.yml
is updated with new required dependences you can update your environment like this
conda env update -f Condafile.yml --prune
Pipenv is a wrapper over the regular pip package manager, but with a slightly better mechanism for locking dependencies of referenced libraries (I believe). Dependencies are managed via the Pipfile
and the Pipfile.lock
pip install --user pipenv
# And to update pipenv in the future
pip install --upgrade pipenv
Now install the application Python dependencies as defined in Pipfile.lock
cd toolkit
mkdir .venv # This is optional, and will force pipenv to create a venv directory locally
pipenv install
With the somisana
environment activated
cd toolkit
python __main__.py <options>
# for example
python __main__.py --version # Should print out 'development'
python __main__.py -h # This should list all the available commands
In the case of a Pyenv environment, the pipenv run script
command ensures the correct virtual environment is used (see the script called script
in the Pipfile
).
cd toolkit
pipenv run script <options>
# for example
pipenv run script --version # Should print out 'development'
pipenv run script -h # This should list all the available commands
As a shortcut to these cumbersome commands, you can register the toolkit
command on your $PATH
environment variable that will handle the CLI entry point for you. This checks if you're in a Conda or Pyenv environment so that the same toolkit
command can be used in either case. The toolkit
command should then work the same as the somisana
command used to run the CLI via the docker image.
cd toolkit
source env.sh
toolkit --version # Should print out 'development'
toolkit -h # This should list all the available commands
The CLI is configured via flags and environment variables (in the case of passwords/etc.). Copy the example config into you directory as .env
and adjust accordingly. The .env
file is kept out of source control.
cp .env.example .env
NOTE: There is also a env.sh
script in the root of the repo that can be sourced so that you don't have to be in the toolkit directory to run the CLI. All path-argument inputs that are relative paths are treated as relative to <repo root>/toolkit