xpystac provides the glue that allows xarray.open_dataset to accept pystac objects.
The goal is that as long as this library is in your env, you should never need to think about it.
Search collection of COGs:
import pystac_client
import xarray as xr
catalog = pystac_client.Client.open(
"https://earth-search.aws.element84.com/v0"
)
search = catalog.search(
intersects=dict(type="Point", coordinates=[-105.78, 35.79]),
collections=['sentinel-s2-l2a-cogs'],
datetime="2020-04-01/2020-05-01",
)
xr.open_dataset(search, engine="stac")Here are a few examples from the Planetary Computer Docs
import planetary_computer
import pystac_client
import xarray as xr
catalog = pystac_client.Client.open(
"https://planetarycomputer.microsoft.com/api/stac/v1",
modifier=planetary_computer.sign_inplace,
)Read from a reference file:
collection = catalog.get_collection("nasa-nex-gddp-cmip6")
asset = collection.assets["ACCESS-CM2.historical"]
xr.open_dataset(asset)ref: https://planetarycomputer.microsoft.com/dataset/nasa-nex-gddp-cmip6#Example-Notebook
Read from a zarr file:
collection = catalog.get_collection("daymet-daily-hi")
asset = collection.assets["zarr-abfs"]
xr.open_dataset(asset)ref: https://planetarycomputer.microsoft.com/docs/quickstarts/reading-zarr-data/
pip install git+https://github.com/stac-utils/xpystacWhen you call xarray.open_dataset(object, engine="stac") this library maps that open call to the correct library.
Depending on the type of object that might be stackstac
or back to xarray.open_dataset itself but with the engine and other options pulled from the pystac object.
This work is inspired by https://github.com/TomAugspurger/staccontainers and the discussion in stac-utils/pystac#846