issue_comments

Table actions

1 row where author_association = "NONE" and "created_at" is on date 2022-06-14 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

author_association 1

  • NONE · 1 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions issue performed_via_github_app
1155515426 https://github.com/simonw/sqlite-utils/issues/441#issuecomment-1155515426 https://api.github.com/repos/simonw/sqlite-utils/issues/441 IC_kwDOCGYnMM5E38Qi betatim 1448859 2022-06-14T17:53:43Z 2022-06-14T17:53:43Z NONE

That would be handy (additional where filters) but I think the trick with the with statement is already an order of magnitude better than what I had thought of, so my problem is solved by it (plus I got to learn about with today!)

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
 Combining `rows_where()` and `search()` to limit which rows are searched 1257724585  

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,
   [issue] INTEGER REFERENCES [issues]([id])
, [performed_via_github_app] TEXT);
CREATE INDEX [idx_issue_comments_issue]
                ON [issue_comments] ([issue]);
CREATE INDEX [idx_issue_comments_user]
                ON [issue_comments] ([user]);