dynamical.org reformatters

Reformat weather datasets into zarr.

Browse the datasets produced by this repo at https://dynamical.org/catalog/.

• See AGENTS.md for an overview of the approach and this repository.
• Integrate a new dataset to be reformatted.
• Add a new variable to an existing dataset.

Local development

We use

• uv to manage dependencies and python environments
• ruff for linting and formatting
• ty for type checking
• pytest for testing
• prek to automatically lint and format as you git commit

Setup

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

Running locally

• uv run main --help - list all datasets
• uv run main <DATASET_ID> update-template
• uv run main <DATASET_ID> backfill-local <APPEND_DIM_END>

Development commands

• Add dependency: uv add <package> [--dev]. Use --dev to add a development only dependency.
• Lint: uv run ruff check [--fix]
• Type check: uv run ty check
• Format: uv run ruff format
• Tests:
  • Run tests in parallel on all available cores: uv run pytest
  • Run tests serially: uv run pytest -n 0

Deploying to the cloud

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

We use

• docker to package the code and dependencies
• 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. e.g. export DOCKER_REPOSITORY=container.registry/<project-id>/reformatters/main. Follow your registry's instructions to allow your docker to authenticate and push images to the registry.
3. Setup a kubernetes cluster and configure kubectl to point to your cluster. e.g. aws eks update-kubeconfig --region <region> --name <cluster-name>, gcloud container clusters get-credentials <cluster-name> --region <region> --project <project>, etc.
4. Create a kubectl secret containing a single json encoded value to be passed to fsspec storage_options or splatted as keyword arguments to an icechunk storage opener kubectl create secret generic your-destination-storage-options-key --from-literal=contents='{"key": "...", "secret": "..."}'. See storage.py.