issue_comments
1 row where issue = 466750687 and user = 2443309 sorted by updated_at descending
This data as json, CSV (advanced)
Suggested facets: created_at (date), updated_at (date)
issue 1
- black formatting · 1 ✖
id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
---|---|---|---|---|---|---|---|---|---|---|---|
511038269 | https://github.com/pydata/xarray/issues/3092#issuecomment-511038269 | https://api.github.com/repos/pydata/xarray/issues/3092 | MDEyOklzc3VlQ29tbWVudDUxMTAzODI2OQ== | jhamman 2443309 | 2019-07-12T21:25:14Z | 2019-07-12T21:25:14Z | MEMBER | If we do this, which I am +1 on, we should add a pre-commit hook so we don't have to think about the manual applications. We should probably just copy the dask approach: https://github.com/dask/dask/pull/4983. |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
black formatting 466750687 |
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, [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]);
user 1