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DHIDB

dhidb

PyPI version CI and release

dhidb provides read-only Python access to the global 300 m Dynamic Habitat Indices database stored as a dense TileDB array on public S3-compatible object storage. It supports point, bounding-box, and polygon queries without first downloading the complete database.

Installation

pip install dhidb

For development:

python -m pip install -e ".[test]"

Requirements and optional dependencies

DHIDB requires Python 3.10 or newer. The runtime dependencies and the compatibility ranges published by the package are:

Dependency Supported version range
affine >=2.4
numpy >=1.26,<3
pandas >=2.1
pyproj >=3.6
rasterio >=1.3
shapely >=2.0
tiledb >=0.35,<0.38
xarray >=2024.1

Optional features are installed with package extras. There is no generic dhidb[dependency] extra; use the feature-specific extra you need:

Extra Install command Adds
netcdf pip install "dhidb[netcdf]" scipy>=1.11 for NetCDF export
zarr pip install "dhidb[zarr]" zarr>=2.18 for Zarr export
test pip install "dhidb[test]" build, pytest, coverage, Ruff, and SciPy tooling

For local development and testing:

python -m pip install -e ".[test,netcdf,zarr]"

The documentation website has its own Node.js dependencies in website/package.json; they are not part of the Python package extras.

Quick start

from dhidb import DHIProvider

with DHIProvider() as db:
    print(db.years)
    print(db.variables)

    germany = db.query_bbox(
        bounds=(5.8, 47.2, 15.1, 55.1),
        years=[2020, 2021, 2022],
        variables=["dhi_cum", "dhi_min", "dhi_var", "valid_count"],
    )

Documentation

The Docusaurus website source is in website/. Build it locally with:

npm --prefix website install
npm --prefix website run start

Data variables

Variable Meaning Unit
dhi_cum Cumulative productivity from LSP TPROD PPI integral (m2 m-2 day)
dhi_min Minimum seasonal productivity baseline from LSP MINV PPI (m2 m-2)
dhi_var Inter-period GPP coefficient of variation dimensionless
dhi_combined Normalized combined DHI, where available dimensionless
observed_count Number of available 10-day observations scenes
valid_count Number of accepted 10-day observations scenes
qflag_any_count Observations carrying any source quality flag scenes
qflag_rejected_count Observations rejected by quality filtering scenes

License

MIT

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