Load Kerchunked dataset with Xarray

Overview

Within this notebook, we will cover:

How to load a Kerchunk pre-generated reference file into Xarray as if it were a Zarr store.

Prerequisites

Concepts	Importance	Notes
Kerchunk Basics	Required	Core
Xarray Tutorial	Required	Core

Time to learn: 45 minutes

Opening Reference Dataset with Fsspec and Xarray

One way of using our reference dataset is opening it with Xarray. To do this, we will create an fsspec filesystem and pass it to Xarray.

# create an fsspec reference filesystem from the Kerchunk output
import fsspec
import xarray as xr

fs = fsspec.filesystem(
    "reference",
    fo="references/ARG_combined.json",
    remote_protocol="s3",
    remote_options={"anon": True},
    skip_instance_cache=True,
)
m = fs.get_mapper("")
ds = xr.open_dataset(m, engine="zarr", backend_kwargs={"consolidated": False})

Opening Reference Dataset with Xarray and the `Kerchunk` Engine

As of writing, the latest version of Kerchunk supports opening an reference dataset with Xarray without specifically creating an fsspec filesystem. This is the same behavior as the example above, just a few less lines of code.

storage_options = {
    "remote_protocol": "s3",
    "skip_instance_cache": True,
    "remote_options": {"anon": True}
}  # options passed to fsspec
open_dataset_options = {"chunks": {}}  # opens passed to xarray

ds = xr.open_dataset(
    "references/ARG_combined.json",
    engine="kerchunk",
    storage_options=storage_options,
    open_dataset_options=open_dataset_options,
)