dynamical.org reformatters

Reformat weather datasets into zarr.

Local development

We use

• uv to manage dependencies and python environments
• ruff for linting and formatting
• mypy for type checking
• pre-commit to automatically lint and format as you git commit (type checking on commit is TODO)

Setup

1. Install uv
2. Run uv run pre-commit install to setup the git hooks
3. If you use VSCode, you may want to install the extensions (ruff, mypy) it will recommend when you open this folder

Running locally

• uv run main.py --help
• uv run main.py noaa-gefs-forecast update-template
• uv run main.py noaa-gefs-forecast reformat-local 2024-01-02T00:00

Development commands

• Add dependency: uv add <package> [--dev]. Use --dev to add a development only dependency.
• Lint: uv run ruff check
• Type check: uv run mypy
• Format: uv run ruff format

Deploying to the cloud

To reformat a large archive we parallelize work across multiple cloud servers.

We use

• docker to containerize the code
• kubernetes indexed jobs to run work in parallel

Setup

1. Install docker and kubectl. Make sure docker can be found at /usr/bin/docker and kubectl at /usr/bin/kubectl.
2. Setup a docker image repository and export the DOCKER_REPOSITORY environment variable in your local shell. eg. export DOCKER_REPOSITORY=us-central1-docker.pkg.dev/<project-id>/reformatters/main
3. Setup a kubernetes cluster and configure kubectl to point to your cluster. eg gcloud container clusters get-credentials <cluster-name> --region <region> --project <project>
4. Create a kubectl secret containing your Source Coop S3 credentials kubectl create secret generic source-coop-key --from-literal='AWS_ACCESS_KEY_ID=XXX' --from-literal='AWS_SECRET_ACCESS_KEY=XXX'

Development commands

1. uv run main.py noaa-gefs-forecast reformat-kubernetes <INIT_TIME_END> [--jobs-per-pod <int>] [--max-parallelism <int>]