issues

Table actions

4 rows where user = 31115101 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

Suggested facets: created_at (date), updated_at (date), closed_at (date)

state 2

type 1

repo 1

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
376167325 MDExOlB1bGxSZXF1ZXN0MjI3NDQ3NjUz 2533 Check shapes of coordinates and data during DataArray construction lilyminium 31115101 open 0     11 2018-10-31T21:28:04Z 2022-06-09T14:50:17Z   CONTRIBUTOR   0 pydata/xarray/pulls/2533
  • [x] Closes #2529 (remove if there is no corresponding issue, which should only be the case for minor changes)
  • [x] Tests added (for all bug fixes or enhancements)
  • [ ] Fully documented, including whats-new.rst for all changes and api.rst for new API (remove if this change should not be visible to users, e.g., if it is an internal clean-up, or if this is part of a larger project that will be documented later)

This sets DataArrayGroupBy.reduce(shortcut=False), as the shortcut first constructs a DataArray with the previous coordinates and the new mutated data before updating the coordinates; this order of events now raises a ValueError.

 
{
    "url": "https://api.github.com/repos/pydata/xarray/issues/2533/reactions",
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
     xarray 13221727 pull
376116903 MDExOlB1bGxSZXF1ZXN0MjI3NDA3NTM2 2530 Manually specify chunks in open_zarr lilyminium 31115101 closed 0     6 2018-10-31T19:04:05Z 2019-04-18T14:35:21Z 2019-04-18T14:34:29Z CONTRIBUTOR   0 pydata/xarray/pulls/2530
  • [x] Addresses #2423
  • [x] Tests added (for all bug fixes or enhancements)
  • [x] Fully documented, including whats-new.rst

This adds a chunks parameter that is analogous to Dataset.chunk. auto_chunk is kept for backwards compatibility and is equivalent to chunks='auto'. It seems reasonable that anyone manually specifying chunks may want to rewrite the dataset in those chunks, and the error that arises when the encoded Zarr chunks mismatch the variable Dask chunks may quickly get annoying. overwrite_encoded_chunks=True sets the encoded chunks to None so there is no clash. 

{
    "url": "https://api.github.com/repos/pydata/xarray/issues/2530/reactions",
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
     xarray 13221727 pull
369935730 MDExOlB1bGxSZXF1ZXN0MjIyNzM3ODA5 2487 Zarr chunking (GH2300) lilyminium 31115101 closed 0     5 2018-10-14T19:35:06Z 2018-11-02T04:59:19Z 2018-11-02T04:59:04Z CONTRIBUTOR   0 pydata/xarray/pulls/2487
  • [x] Band-aid for #2300
  • [x] Test added to check that zarr-originating array can save
  • [x] Updated whats-new

I don't fully understand the ins-and-outs of Zarr, but it seems that if it can be serialised with a smaller end-chunk to begin with, then saving a Dataset constructed from Zarr should not have an issue with that either. 

{
    "url": "https://api.github.com/repos/pydata/xarray/issues/2487/reactions",
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
     xarray 13221727 pull
369934524 MDExOlB1bGxSZXF1ZXN0MjIyNzM3MDMx 2486 Zarr determine chunks lilyminium 31115101 closed 0     1 2018-10-14T19:21:10Z 2018-10-14T19:26:40Z 2018-10-14T19:26:40Z CONTRIBUTOR   0 pydata/xarray/pulls/2486
  • [ ] Quick band-aid for #2300
  • [ ] Test added to check that a zarr-originating dataset can be saved
 
{
    "url": "https://api.github.com/repos/pydata/xarray/issues/2486/reactions",
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
     xarray 13221727 pull

Advanced export

JSON shape: default, array, newline-delimited, object

CSV options: 

CREATE TABLE [issues] (
   [id] INTEGER PRIMARY KEY,
   [node_id] TEXT,
   [number] INTEGER,
   [title] TEXT,
   [user] INTEGER REFERENCES [users]([id]),
   [state] TEXT,
   [locked] INTEGER,
   [assignee] INTEGER REFERENCES [users]([id]),
   [milestone] INTEGER REFERENCES [milestones]([id]),
   [comments] INTEGER,
   [created_at] TEXT,
   [updated_at] TEXT,
   [closed_at] TEXT,
   [author_association] TEXT,
   [active_lock_reason] TEXT,
   [draft] INTEGER,
   [pull_request] TEXT,
   [body] TEXT,
   [reactions] TEXT,
   [performed_via_github_app] TEXT,
   [state_reason] TEXT,
   [repo] INTEGER REFERENCES [repos]([id]),
   [type] TEXT
);
CREATE INDEX [idx_issues_repo]
    ON [issues] ([repo]);
CREATE INDEX [idx_issues_milestone]
    ON [issues] ([milestone]);
CREATE INDEX [idx_issues_assignee]
    ON [issues] ([assignee]);
CREATE INDEX [idx_issues_user]
    ON [issues] ([user]);