issue_comments
1 row where author_association = "NONE", issue = 435532136 and user = 4992424 sorted by updated_at descending
This data as json, CSV (advanced)
Suggested facets: created_at (date), updated_at (date)
issue 1
- Support from reading unformatted Fortran files · 1 ✖
| id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 485272748 | https://github.com/pydata/xarray/issues/2911#issuecomment-485272748 | https://api.github.com/repos/pydata/xarray/issues/2911 | MDEyOklzc3VlQ29tbWVudDQ4NTI3Mjc0OA== | darothen 4992424 | 2019-04-21T18:32:56Z | 2019-04-21T18:32:56Z | NONE | Hi @tomchor, it's not too difficult to take the readers that you already have and two wrap them in such a way that you can interact with them via xarray; you can check out the packages xgcm or xbpch for examples of this can work in practice. I'm not sure if a more generic reader is within or beyond the scope of the core xarray project, though... although example implementations and writeups would make a great contribution to the community! |
{
"total_count": 0,
"+1": 0,
"-1": 0,
"laugh": 0,
"hooray": 0,
"confused": 0,
"heart": 0,
"rocket": 0,
"eyes": 0
} |
Support from reading unformatted Fortran files 435532136 |
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