issue_comments
1 row where issue = 285168503 and user = 173848 sorted by updated_at descending
This data as json, CSV (advanced)
Suggested facets: created_at (date), updated_at (date)
issue 1
- Add GraphQL endpoint · 1 ✖
id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | issue | performed_via_github_app |
---|---|---|---|---|---|---|---|---|---|---|---|
356161672 | https://github.com/simonw/datasette/issues/176#issuecomment-356161672 | https://api.github.com/repos/simonw/datasette/issues/176 | MDEyOklzc3VlQ29tbWVudDM1NjE2MTY3Mg== | yozlet 173848 | 2018-01-09T02:35:35Z | 2018-01-09T02:35:35Z | NONE | @wulfmann I think I disagree, except I'm not entirely sure what you mean by that first paragraph. The JSON API that Datasette currently exposes is quite different to GraphQL. Furthermore, there's no "just" about connecting micro-graphql to a DB; at least, no more "just" than adding any other API. You still need to configure the schema, which is exactly the kind of thing that Datasette does for JSON API. This is why I think that GraphQL's a good fit here. |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
Add GraphQL endpoint 285168503 |
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