xarray-annotated enables run-time validation of xarray.DataArray properties declared in function signatures via typing.Annotated.
The main idea is that annotations serve as a single source of truth for
- structural schema (dims, coords, dtype),
- physical units,
- frequency (and phase) of a time axis,
from which
- static checkers and run-time validation can derive expected properties,
- documentation can be generated automatically,
- automated tools (coding agents) receive steering.
For validating and automatically converting physical units we lean on the excellent pint and pint-xarray. (cf-xarray is an optional dependency for CF/UDUNITS unit strings.)
For full user documentation please visit https://jmarshrossney.github.io/xarray-annotated/.
Either using uv (recommended) or pip:
uv add xarray-annotated
# or
pip install xarray-annotatedCF-convention / UDUNITS unit strings (e.g. "umol m-2 s-1") need the optional cf extra, which pulls in cf-xarray.
uv add "xarray-annotated[cf]"
# or
pip install "xarray-annotated[cf]"Here is a function that converts barometric pressure to altitude. It assumes a unit (pascals) and says so in the docstring but doesn't check or enforce it.
import xarray as xr
def altitude(p: xr.DataArray) -> xr.DataArray:
"""Barometric altitude. Assumes p is in Pa."""
return 44330.0 * (1.0 - (p / 101325.0) ** 0.1903)
p = xr.DataArray([1013.0, 1000.0], dims=["time"], attrs={"units": "hPa"})
altitude(p)<xarray.DataArray (time: 2)> Size: 16B
array([25876.55998663, 25921.86206292])
Dimensions without coordinates: time
Attributes:
units: hPa
The input units are wrong (hPa vs Pa) but the onus is on the user to check, and in reality we all know that such bugs can go unnoticed for a terrifyingly long time.
The returned altitude is numerically wrong and carries a completely bogus hPa units in attrs.
Here we use xarray-annotated to declare expected properties in the signature and enforce them at run-time with minimal boilerplate (just decorators).
from typing import Annotated
import xarray as xr
from xarray_annotated.schema import declare_schema, Dims
from xarray_annotated.units import declare_units, Unit
@declare_units
@declare_schema
def altitude(
p: Annotated[xr.DataArray, Dims("time"), Unit("Pa")],
) -> Annotated[xr.DataArray, Dims("time"), Unit("m")]:
"""Barometric altitude."""
return 44330.0 * (1.0 - (p / 101325.0) ** 0.1903)
p = xr.DataArray([1013.0, 1000.0], dims=["time"], attrs={"units": "hPa"})
altitude(p)<xarray.DataArray (time: 2)> Size: 16B
array([ 2.08162886, 110.90398059])
Dimensions without coordinates: time
Attributes:
units: m
Now the outputs are physical and carry the correct units attribute.
The hPa input was converted to Pa before the body ran, and the result was stamped with the unit the signature promised.
The docstring no longer needs to say "assumes Pa", because the signature does --- and unlike the docstring, it is actually enforced.
If we had handed the function an array whose units were dimensionally wrong, or with an extra dimension, this would have failed gracefully:
altitude(xr.DataArray([1.0, 2.0], dims=["time"], attrs={"units": "kg"}))
# DimensionalityError: Cannot convert from 'kilogram' ([mass])
# to 'pascal' ([mass] / [length] / [time] ** 2)
altitude(xr.DataArray([[1013.0, 1000.0]], dims=["run", "time"], attrs={"units": "hPa"}))
# SchemaError: [altitude] 'p' dims mismatch: expected ('time',) in any order, got ('run', 'time')uv sync # install the package + dev dependencies into .venv
just # lint, typecheck, test, build docsSee the justfile for individual targets (just lint, just test, just test-cov, ...).
A .pre-commit-config.yaml is included to run the same linting (ruff) and type-checking (pyright) steps on every commit. Install the hooks with:
uv run pre-commit installContributions are welcome --- open an issue or pull request on GitHub.