pull_requests: 196786848
This data as json
| id | node_id | number | state | locked | title | user | body | created_at | updated_at | closed_at | merged_at | merge_commit_sha | assignee | milestone | draft | head | base | author_association | auto_merge | repo | url | merged_by |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 196786848 | MDExOlB1bGxSZXF1ZXN0MTk2Nzg2ODQ4 | 2246 | closed | 0 | Small error in open_zarr docs | 5635139 | I tried setting this up on GCS as an experiment, and found there's no `mode` kwarg to `open_zarr`. I'm not sure whether there are broader issues but thought I'd put this in regardless (also - if anyone has any experience in deploying xarray over https://github.com/dask/dask-kubernetes and GCS, I'd be interested in your experience. We're currently working with either a) BigQuery for big data or b) in-memory xarray for small data, and I was interested whether there's a way of retaining the xarray model for bigger data without too much overhead) | 2018-06-22T16:30:14Z | 2018-06-22T22:57:50Z | 2018-06-22T22:00:06Z | 2018-06-22T22:00:06Z | 9491318e29b478234e6f96c3547d724504b4a1bb | 0 | 979f401cb142ca22abd0211e05c4d53b5c98c274 | 73b476e4db6631b2203954dd5b138cb650e4fb8c | MEMBER | 13221727 | https://github.com/pydata/xarray/pull/2246 |
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