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Xarray specifications via type hints

Project description

Xarrayspecs

Release Python Downloads DOI Tests

Xarray specifications via type hints

Installation

pip install xarrayspecs

Basic Usage

Xarray DataArray Specifications

import numpy as np
import xarrayspecs as xs
from dataclasses import dataclass
from numpy.typing import NDArray
from typing import Annotated, Any


@dataclass
class Temp(xs.AsDataArray):
    temp: Annotated[
        NDArray[Any],
        xs.use("data"),
        xs.dims("lon", "lat"),
        xs.dtype(np.float64),
        xs.attrs(long_name="Temperature", units="K"),
    ]
    lat: Annotated[
        NDArray[Any],
        xs.use("coord"),
        xs.dims("lat"),
        xs.dtype(np.float64),
        xs.attrs(long_name="Latitude", units="deg"),
    ]
    lon: Annotated[
        NDArray[Any],
        xs.use("coord"),
        xs.dims("lon"),
        xs.dtype(np.float64),
        xs.attrs(long_name="Longitude", units="deg"),
    ]
    date: Annotated[str, xs.use("attr")]


Temp.new(
    np.random.uniform(273, 293, size=(2, 2)),
    np.array([0, 1]),
    np.array([2, 3]),
    "2026-03-01",
)
<xarray.DataArray 'temp' (lon: 2, lat: 2)> Size: 32B
array([[283.97627008, 287.30378733],
       [285.05526752, 283.89766366]])
Coordinates:
  * lon      (lon) float64 16B 2.0 3.0
  * lat      (lat) float64 16B 0.0 1.0
Attributes:
    long_name:  Temperature
    units:      K
    date:       2026-03-01

Xarray Dataset Specifications

@dataclass
class Weather(xs.AsDataset):
    temp: Annotated[
        NDArray[Any],
        xs.use("data"),
        xs.dims("lon", "lat"),
        xs.dtype(np.float64),
        xs.attrs(long_name="Temperature", units="K"),
    ]
    humid: Annotated[
        NDArray[Any],
        xs.use("data"),
        xs.dims("lon", "lat"),
        xs.dtype(np.float64),
        xs.attrs(long_name="Humidity", units="%"),
    ]
    lat: Annotated[
        NDArray[Any],
        xs.use("coord"),
        xs.dims("lat"),
        xs.dtype(np.float64),
        xs.attrs(long_name="Latitude", units="deg"),
    ]
    lon: Annotated[
        NDArray[Any],
        xs.use("coord"),
        xs.dims("lon"),
        xs.dtype(np.float64),
        xs.attrs(long_name="Longitude", units="deg"),
    ]
    date: Annotated[str, xs.use("attr")]


Weather.new(
    np.random.uniform(273, 293, size=(2, 2)),
    np.random.uniform(0, 100, size=(2, 2)),
    np.array([0, 1]),
    np.array([2, 3]),
    "2026-03-01",
)
<xarray.Dataset> Size: 96B
Dimensions:  (lat: 2, lon: 2)
Coordinates:
  * lat      (lat) float64 16B 0.0 1.0
  * lon      (lon) float64 16B 2.0 3.0
Data variables:
    temp     (lon, lat) float64 32B 284.0 287.3 285.1 283.9
    humid    (lon, lat) float64 32B 42.37 64.59 43.76 89.18
Attributes:
    date:     2026-03-01

Xarray DataTree Specifications

Temp = Annotated[
    NDArray[Any],
    xs.use("data"),
    xs.name("temp"),
    xs.dims("lon", "lat"),
    xs.dtype(np.float64),
    xs.attrs(long_name="Temperature", units="K"),
]
Humid = Annotated[
    NDArray[Any],
    xs.use("data"),
    xs.name("humid"),
    xs.dims("lon", "lat"),
    xs.dtype(np.float64),
    xs.attrs(long_name="Humidity", units="%"),
]
Lat = Annotated[
    NDArray[Any],
    xs.use("coord"),
    xs.name("lat"),
    xs.dims("lat"),
    xs.dtype(np.float64),
    xs.attrs(long_name="Latitude", units="deg"),
]
Lon = Annotated[
    NDArray[Any],
    xs.use("coord"),
    xs.name("lon"),
    xs.dims("lon"),
    xs.dtype(np.float64),
    xs.attrs(long_name="Longitude", units="deg"),
]
Date = Annotated[str, xs.use("attr"), xs.name("date")]


@dataclass
class Weathers(xs.AsDataTree):
    temp_0: Annotated[Temp, xs.node("/0")]
    temp_1: Annotated[Temp, xs.node("/1")]
    humid_0: Annotated[Humid, xs.node("/0")]
    humid_1: Annotated[Humid, xs.node("/1")]
    lat_0: Annotated[Lat, xs.node("/0")]
    lat_1: Annotated[Lat, xs.node("/1")]
    lon_0: Annotated[Lon, xs.node("/0")]
    lon_1: Annotated[Lon, xs.node("/1")]
    date_0: Annotated[Date, xs.node("/0")]
    date_1: Annotated[Date, xs.node("/1")]


Weathers.new(
    np.random.uniform(273, 293, size=(2, 2)),
    np.random.uniform(273, 293, size=(2, 2)),
    np.random.uniform(0, 100, size=(2, 2)),
    np.random.uniform(0, 100, size=(2, 2)),
    np.array([0, 1]),
    np.array([0, 1]),
    np.array([2, 3]),
    np.array([2, 3]),
    "2026-03-01",
    "2026-03-01",
)
<xarray.DataTree>
Group: /
├── Group: /0
│       Dimensions:  (lat: 2, lon: 2)
│       Coordinates:
│         * lat      (lat) float64 16B 0.0 1.0
│         * lon      (lon) float64 16B 2.0 3.0
│       Data variables:
│           temp     (lon, lat) float64 32B 284.0 287.3 285.1 283.9
│           humid    (lon, lat) float64 32B 96.37 38.34 79.17 52.89
│       Attributes:
│           date:     2026-03-01
└── Group: /1
        Dimensions:  (lat: 2, lon: 2)
        Coordinates:
          * lat      (lat) float64 16B 0.0 1.0
          * lon      (lon) float64 16B 2.0 3.0
        Data variables:
            temp     (lon, lat) float64 32B 281.5 285.9 281.8 290.8
            humid    (lon, lat) float64 32B 56.8 92.56 7.104 8.713
        Attributes:
            date:     2026-03-01

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