issue_comments
2 rows where issue = 302718231 and user = 5635139 sorted by updated_at descending
This data as json, CSV (advanced)
issue 1
- einsum for xarray · 2 ✖
| id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 371378353 | https://github.com/pydata/xarray/pull/1968#issuecomment-371378353 | https://api.github.com/repos/pydata/xarray/issues/1968 | MDEyOklzc3VlQ29tbWVudDM3MTM3ODM1Mw== | max-sixty 5635139 | 2018-03-08T04:52:41Z | 2018-03-08T04:52:41Z | MEMBER | Do you know why the tests are failing? Do you want me to have a look? The arrays look the same: https://travis-ci.org/pydata/xarray/jobs/350640898#L5182. Would |
{
"total_count": 0,
"+1": 0,
"-1": 0,
"laugh": 0,
"hooray": 0,
"confused": 0,
"heart": 0,
"rocket": 0,
"eyes": 0
} |
einsum for xarray 302718231 | |
| 371377944 | https://github.com/pydata/xarray/pull/1968#issuecomment-371377944 | https://api.github.com/repos/pydata/xarray/issues/1968 | MDEyOklzc3VlQ29tbWVudDM3MTM3Nzk0NA== | max-sixty 5635139 | 2018-03-08T04:49:24Z | 2018-03-08T04:49:24Z | MEMBER | This is awesome. Beautiful code, immediately impactful, and the API is so simple - a testament to the benefits of named dims Thank you @fujiisoup ! |
{
"total_count": 0,
"+1": 0,
"-1": 0,
"laugh": 0,
"hooray": 0,
"confused": 0,
"heart": 0,
"rocket": 0,
"eyes": 0
} |
einsum for xarray 302718231 |
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