issue_comments
1 row where issue = 243964948 and user = 18172466 sorted by updated_at descending
This data as json, CSV (advanced)
Suggested facets: created_at (date), updated_at (date)
issue 1
- Support for jagged array · 1 ✖
| id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1014487633 | https://github.com/pydata/xarray/issues/1482#issuecomment-1014487633 | https://api.github.com/repos/pydata/xarray/issues/1482 | IC_kwDOAMm_X848d9pR | fmfreeze 18172466 | 2022-01-17T12:51:45Z | 2022-01-17T12:51:45Z | NONE | As I am not aware of implementation details I am not sure there is a useful link, but maybe progress in #3213 supporting sparse arrays can solve also the jagged array issue. Long time ago I asked there a question about how xarray supports sparse arrays. But what I actually meant were "Jagged Arrays". I just was not aware of that term and stumbled over it some days ago the very first time. |
{
"total_count": 1,
"+1": 1,
"-1": 0,
"laugh": 0,
"hooray": 0,
"confused": 0,
"heart": 0,
"rocket": 0,
"eyes": 0
} |
Support for jagged array 243964948 |
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