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Interface for using cubed with xarray for parallel computation.

Project description

Note: this is a proof-of-concept, and many things are incomplete, untested, or don't work.

cubed-xarray

Interface for using cubed with xarray.

Requirements

Cubed version >v0.6.0

Xarray pull request #7019

Installation

Install via pip.

Importing

You don't need to import this package in user code. Once pip install-ed, xarray should automatically become aware of this package via the magic of entrypoints.

Usage

Xarray objects backed by cubed arrays can be created either by:

  1. Passing existing cubed.Array objects to the data argument of xarray constructors,
  2. Calling .chunk on xarray objects,
  3. Passing a chunks argument to xarray.open_dataset.

In (2) and (3) the choice to use cubed.Array instead of dask.array.Array is made by passing the keyword argument chunked_array_type='cubed'. To pass arguments to the constructor of cubed.Array then pass them via the dictionary from_array_kwargs, e.g. from_array_kwargs={'spec': cubed.Spec(max_mem=2_000_000)}.

If cubed and cubed-xarray are installed but dask is not, then specifying the parallel array type to use is not necessary.

Tests

Integration tests for wrapping cubed with xarray also live in this repository.

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