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id node_id number title user state locked assignee milestone comments created_at updated_at ▲ closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
1845508562 I_kwDOAMm_X85uADnS 8065 .mfdataset fail to open a kerchunked zarr file from an object-store bucket pl-marasco 22492773 closed 0     4 2023-08-10T16:22:05Z 2023-08-14T14:18:17Z 2023-08-14T14:13:58Z NONE      

What happened?

Trying to open a kerchunk .json through the open_mfdata a ValueError is raised.

What did you expect to happen?

should be open a Dataset as described here below: <xarray.Dataset> Dimensions: (lat: 15680, lon: 40320, time: 36) Coordinates: * lat (lat) float64 80.0 79.99 79.98 79.97 ... -59.97 -59.98 -59.99 * lon (lon) float64 -180.0 -180.0 -180.0 -180.0 ... 180.0 180.0 180.0 * time (time) float64 nan 1.0 2.0 3.0 4.0 5.0 ... 31.0 32.0 33.0 34.0 35.0 Data variables: crs object ... max (time, lat, lon) float32 dask.array<chunksize=(1, 1207, 3102), meta=np.ndarray> mean (time, lat, lon) float32 dask.array<chunksize=(1, 1207, 3102), meta=np.ndarray> median (time, lat, lon) float32 dask.array<chunksize=(1, 1207, 3102), meta=np.ndarray> min (time, lat, lon) float32 dask.array<chunksize=(1, 1207, 3102), meta=np.ndarray> nobs (time, lat, lon) float32 dask.array<chunksize=(1, 1207, 3102), meta=np.ndarray> stdev (time, lat, lon) float32 dask.array<chunksize=(1, 1207, 3102), meta=np.ndarray> Attributes: (12/19) Conventions: CF-1.6 archive_facility: VITO copyright: Copernicus Service information 2021 history: 2021-03-01 - Processing line NDVI LTS identifier: urn:cgls:global:ndvi_stats_all:NDVI-LTS_1999-2019-0... institution: VITO NV ... ... references: https://land.copernicus.eu/global/products/ndvi sensor: VEGETATION-1, VEGETATION-2, VEGETATION source: Derived from EO satellite imagery time_coverage_end: 2019-12-31T23:59:59Z time_coverage_start: 1999-01-01T00:00:00Z title: Normalized Difference Vegetation Index: Long Term S...

Minimal Complete Verifiable Example

python import xarray as xr catalogue="https://object-store.cloud.muni.cz/swift/v1/foss4g-catalogue/c_gls_NDVI-LTS_1999-2019.json" LTS = xr.open_mfdataset( "reference://", engine="zarr", backend_kwargs={ "storage_options": { "fo":catalogue }, "consolidated": False } )

MVCE confirmation

  • [ ] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
  • [ ] Complete example — the example is self-contained, including all data and the text of any traceback.
  • [X] Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
  • [ ] New issue — a search of GitHub Issues suggests this is not a duplicate.

Relevant log output

Python `ValueError: Cannot specify both fs and storage_options`

Anything else we need to know?

Seems to be related to zarr's version: if tested with <= 2.12 it works but with the latest versions > 2.12 it doesn't.

Environment

xarray version 2023.7.0 zarr >2.12 
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   completed xarray 13221727 issue
478398026 MDU6SXNzdWU0NzgzOTgwMjY= 3192 Cloud Storage Buckets pl-marasco 22492773 closed 0     1 2019-08-08T10:58:05Z 2022-04-09T01:51:09Z 2022-04-09T01:51:09Z NONE      

Following the instruction to create cloud storage here I stumbled with the fact that seems gcsfs doesn't anymore implement.mapping in the example is used as : gcsfs.mapping.GCSMap('<bucket-name>', gcs=fs, check=True, create=False)

Is it the example correct or must be rewritten? 

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   completed xarray 13221727 issue

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