issue_comments

Table actions

where issue = 528701910 and user = 2448579 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

These facets timed out: author_association, issue

user 1

  • dcherian · 3 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
567077240 https://github.com/pydata/xarray/issues/3574#issuecomment-567077240 https://api.github.com/repos/pydata/xarray/issues/3574 MDEyOklzc3VlQ29tbWVudDU2NzA3NzI0MA== dcherian 2448579 2019-12-18T15:21:19Z 2019-12-18T15:21:19Z MEMBER

Right the xarray solution is to set meta = np.ndarray if vectorize is True else None if the user doesn't explicitly provide meta. Or am I missing something? 

{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   apply_ufunc with dask='parallelized' and vectorize=True fails on compute_meta 528701910
566640524 https://github.com/pydata/xarray/issues/3574#issuecomment-566640524 https://api.github.com/repos/pydata/xarray/issues/3574 MDEyOklzc3VlQ29tbWVudDU2NjY0MDUyNA== dcherian 2448579 2019-12-17T16:29:35Z 2019-12-17T16:29:35Z MEMBER

meta should be passed to blockwise through _apply_blockwise with default None (I think) and np.ndarray if vectorize is True. You'll have to pass the vectorize kwarg down to this level I think.

https://github.com/pydata/xarray/blob/6ad59b93f814b48053b1a9eea61d7c43517105cb/xarray/core/computation.py#L579-L593

 
{
    "total_count": 1,
    "+1": 1,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   apply_ufunc with dask='parallelized' and vectorize=True fails on compute_meta 528701910
565194778 https://github.com/pydata/xarray/issues/3574#issuecomment-565194778 https://api.github.com/repos/pydata/xarray/issues/3574 MDEyOklzc3VlQ29tbWVudDU2NTE5NDc3OA== dcherian 2448579 2019-12-12T21:28:39Z 2019-12-12T21:28:39Z MEMBER

@shoyer's option 1 should be a relatively simple xarray PR is one of you is up for it.

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   apply_ufunc with dask='parallelized' and vectorize=True fails on compute_meta 528701910

Advanced export

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

CSV options: 

CREATE TABLE [issue_comments] (
   [html_url] TEXT,
   [issue_url] TEXT,
   [id] INTEGER PRIMARY KEY,
   [node_id] TEXT,
   [user] INTEGER REFERENCES [users]([id]),
   [created_at] TEXT,
   [updated_at] TEXT,
   [author_association] TEXT,
   [body] TEXT,
   [reactions] TEXT,
   [performed_via_github_app] TEXT,
   [issue] INTEGER REFERENCES [issues]([id])
);
CREATE INDEX [idx_issue_comments_issue]
    ON [issue_comments] ([issue]);
CREATE INDEX [idx_issue_comments_user]
    ON [issue_comments] ([user]);