issue_comments

Table actions

where issue = 565626748 and user = 14808389 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

These facets timed out: author_association, issue

user 1

  • keewis · 1 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
587130487 https://github.com/pydata/xarray/issues/3770#issuecomment-587130487 https://api.github.com/repos/pydata/xarray/issues/3770 MDEyOklzc3VlQ29tbWVudDU4NzEzMDQ4Nw== keewis 14808389 2020-02-17T19:29:27Z 2020-02-17T19:29:27Z MEMBER

The docs state that the builtin bool returns True for all objects unless __bool__ is defined or __len__ returns 0 (function objects don't define either so they use the fallback). I'm not sure why, but I suspect it is the way it is to make python if obj: ... equivalent to python if obj is not None: ...

That said I really like the callable support of pandas (e.g. Series.where), so maybe we should add that too?

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   `where` ignores incorrectly typed arguments 565626748

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]);