issue_comments
1 row where author_association = "CONTRIBUTOR" and issue = 479190812 sorted by updated_at descending
This data as json, CSV (advanced)
Suggested facets: created_at (date), updated_at (date)
issue 1
- open_mfdataset memory leak, very simple case. v0.12 · 1 ✖
| id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue | 
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1416446874 | https://github.com/pydata/xarray/issues/3200#issuecomment-1416446874 | https://api.github.com/repos/pydata/xarray/issues/3200 | IC_kwDOAMm_X85UbUOa | deeplycloudy 1325771 | 2023-02-03T21:52:57Z | 2023-02-03T21:52:57Z | CONTRIBUTOR | I was iterating today over a large dataset loaded with  I can confirm that  
 | {
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
} | open_mfdataset memory leak, very simple case. v0.12 479190812 | 
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