issue_comments
1 row where user = 18221871
This data as json, CSV (advanced)
Suggested facets: created_at (date), updated_at (date)
id ▼ | html_url | issue_url | node_id | user | created_at | updated_at | author_association | body | reactions | issue | performed_via_github_app |
---|---|---|---|---|---|---|---|---|---|---|---|
751476406 | https://github.com/simonw/datasette/issues/1150#issuecomment-751476406 | https://api.github.com/repos/simonw/datasette/issues/1150 | MDEyOklzc3VlQ29tbWVudDc1MTQ3NjQwNg== | noklam 18221871 | 2020-12-27T14:51:39Z | 2020-12-27T14:51:39Z | NONE | I like the idea of _internal, it's a nice way to get a data catalog quickly. I wonder if this trick applies to db other than SQLite. | {"total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0} | Maintain an in-memory SQLite table of connected databases and their tables 770436876 |
Advanced export
JSON shape: default, array, newline-delimited, object
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]);