issue_comments
1 row where issue = 322787470 and "updated_at" is on date 2018-05-25 sorted by updated_at descending
This data as json, CSV (advanced)
Suggested facets: created_at (date), updated_at (date)
issue 1
- inspect() should detect many-to-many relationships · 1 ✖
id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | issue | performed_via_github_app |
---|---|---|---|---|---|---|---|---|---|---|---|
392212119 | https://github.com/simonw/datasette/issues/259#issuecomment-392212119 | https://api.github.com/repos/simonw/datasette/issues/259 | MDEyOklzc3VlQ29tbWVudDM5MjIxMjExOQ== | simonw 9599 | 2018-05-25T23:22:26Z | 2018-05-25T23:22:26Z | OWNER | This should detect any table which can be linked to the current table via some other table, based on the other table having a foreign key to them both. These join tables could be arbitrarily complicated. They might have foreign keys to more than two other tables, maybe even multiple foreign keys to the same column. Ideally M2M defection would catch all of these cases. Maybe the resulting inspect data looks something like this:
Let's ignore compound primary keys: we k it detect m2m relationships where the join table has foreign keys to a single primary key on the other two tables. |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
inspect() should detect many-to-many relationships 322787470 |
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]);
user 1