open-climate-service 0.1.0a1

Climate and Earth Observation data API

DHIS2 Open Climate Service

Climate and Earth Observation data is distributed across dozens of providers — each with different APIs, data formats, and access mechanisms. The Open Climate Service unifies this fragmented landscape behind a single, consistent interface.

Each instance is configured for a specific country or region, and all data extraction, processing, and storage is scoped to that spatial extent. It abstracts data access across heterogeneous sources (CHIRPS, ERA5, WorldPop, and others), stores outputs as GeoZarr, and exposes them through standards-based endpoints.

The platform is designed to operate independently of DHIS2 and can be deployed on local, cloud-hosted, or sovereign country infrastructure. See docs/setup_guide.md for a step-by-step setup walkthrough, docs/user_guide.md for data access examples, docs/managed_data_api_guide.md for the full API reference, and docs/roadmap.md for the planned development steps.

Status: active development. Current focus is on dataset ingestion, sync workflows, and GeoZarr storage. APIs and data models may change without notice.

Setup

Using uv (recommended)

Install dependencies (requires uv):

uv sync

Copy .env.example to .env and adjust values as needed. Environment variables are loaded automatically from .env at runtime. See .env.example for the full list of available options.

Start the app:

uv run uvicorn open_climate_service.main:app --reload

Using pip

If you cannot use uv (e.g. mixed conda/forge environments):

python -m venv .venv
source .venv/bin/activate
pip install -e .
python -m uvicorn open_climate_service.main:app --reload

Using conda

conda create -n dhis2-climate-service python=3.13
conda activate dhis2-climate-service
pip install -e .
python -m uvicorn open_climate_service.main:app --reload

Development

Common Makefile targets:

Target	Description
make sync	Install dependencies with uv
make run	Start the app with uvicorn (hot reload)
make lint	Check linting, formatting, and types
make fix	Autofix ruff lint and format issues
make test	Run the test suite with pytest
make openapi	Regenerate the pygeoapi OpenAPI spec
make start	Build and start the Docker stack
make restart	Tear down, rebuild, and restart the Docker stack

Endpoints

Once running, the API is available at:

Endpoint	Description
http://localhost:8000/	Navigation document
http://localhost:8000/health	Health check
http://localhost:8000/docs	Interactive API documentation (Swagger UI)
http://localhost:8000/extent	Configured spatial extent
http://localhost:8000/datasets	Managed dataset catalogue
http://localhost:8000/stac/catalog.json	STAC catalog for published GeoZarr data
http://localhost:8000/zarr/{dataset_id}	GeoZarr store for a managed dataset
http://localhost:8000/ogcapi	OGC API root

STAC

Published GeoZarr datasets are discoverable under /stac as one STAC Collection per dataset. Each collection includes a zarr asset with direct xarray-compatible access metadata derived from the live Zarr store.

Discover available datasets and open one with xarray:

The catalog is populated once at least one dataset has been ingested and published (see docs/setup_guide.md).

import httpx
import xarray as xr

catalog = httpx.get("http://127.0.0.1:8000/stac/catalog.json").json()
children = [link for link in catalog["links"] if link["rel"] == "child"]

if not children:
    print("No published datasets found. Run an ingestion first.")
else:
    for link in children:
        print(link["title"], "—", link["href"])

    collection = httpx.get(children[0]["href"]).json()
    asset = collection["assets"]["zarr"]
    ds = xr.open_zarr(
        asset["href"],
        consolidated=asset["xarray:open_kwargs"]["consolidated"],
    )
    print(ds)

pygeoapi

The OGC API is served by pygeoapi, mounted at /ogcapi. Its configuration is generated dynamically from published artifacts and written to the resolved runtime data directory (for Docker: /app/data/pygeoapi/pygeoapi-config.yml).

The base configuration is bundled with the package at open_climate_service/data/pygeoapi/base.yml and does not need to be copied or managed separately.

To validate the configuration manually:

PYTHONPATH="$(pwd)/src" uv run pygeoapi config validate -c data/pygeoapi/pygeoapi-config.yml

Regenerate after changes to publication logic:

make openapi