issue_comments

Table actions

1 row where issue = 956103236 and user = 165551 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

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

user 1

  • hodgestar · 1 ✖

issue 1

  • Duck array compatibility meeting · 1 ✖

author_association 1

id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
924808439 https://github.com/pydata/xarray/issues/5648#issuecomment-924808439 https://api.github.com/repos/pydata/xarray/issues/5648 IC_kwDOAMm_X843H3T3 hodgestar 165551 2021-09-22T10:41:01Z 2021-09-22T10:41:01Z NONE

I'd like to attend on behalf of QuTiP. I'll likely mostly listen -- QuTiP is not directly affected in the way that xarray, Dask, cupy, etc are, but we're users of potentially all of these array types (and already explicitly support numpy, CuPy, and our own sparse array format) and we are facing similar issues of our own (i.e. users of QuTiP are asking us to develop a __qutip_qobj__ style protocol similar to numpy's and we would like to learn the lessons of the last decade of numpy rather than repeat the steps ourselves in the coming one).

 
{
    "total_count": 1,
    "+1": 1,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Duck array compatibility meeting 956103236

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]);