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https://github.com/pydata/xarray/pull/1528#issuecomment-345619509 https://api.github.com/repos/pydata/xarray/issues/1528 345619509 MDEyOklzc3VlQ29tbWVudDM0NTYxOTUwOQ== 703554 2017-11-20T08:07:44Z 2017-11-20T08:07:44Z CONTRIBUTOR

Fantastic!

On Monday, November 20, 2017, Matthew Rocklin notifications@github.com wrote:

That is, indeed, quite exciting. Also exciting is that I was able to look at and compute on your data easily.

In [1]: import zarr

In [2]: import gcsfs

In [3]: fs = gcsfs.GCSFileSystem(project='pangeo-181919')

In [4]: gcsmap = gcsfs.mapping.GCSMap('zarr_store_test', gcs=fs, check=True, create=False)

In [5]: import xarray as xr

In [6]: ds_gcs = xr.open_zarr(gcsmap, mode='r')

In [7]: ds_gcs Out[7]: <xarray.Dataset> Dimensions: (x: 200, y: 100) Coordinates: * x (x) int64 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 ... * y (y) int64 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 ... Data variables: bar (x) float64 dask.array<shape=(200,), chunksize=(40,)> foo (y, x) float32 dask.array<shape=(100, 200), chunksize=(50, 40)> Attributes: array_atr: [1, 2] some_attr: copana

In [8]: ds_gcs.sum() Out[8]: <xarray.Dataset> Dimensions: () Data variables: bar float64 dask.array<shape=(), chunksize=()> foo float32 dask.array<shape=(), chunksize=()>

In [9]: ds_gcs.sum().compute() Out[9]: <xarray.Dataset> Dimensions: () Data variables: bar float64 0.0 foo float32 20000.0

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