issue_comments
3 rows where author_association = "MEMBER", issue = 662505658 and user = 1217238 sorted by updated_at descending
This data as json, CSV (advanced)
Suggested facets: reactions
issue 1
- jupyter repr caching deleted netcdf file · 3 ✖
id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
---|---|---|---|---|---|---|---|---|---|---|---|
774774033 | https://github.com/pydata/xarray/issues/4240#issuecomment-774774033 | https://api.github.com/repos/pydata/xarray/issues/4240 | MDEyOklzc3VlQ29tbWVudDc3NDc3NDAzMw== | shoyer 1217238 | 2021-02-07T21:48:38Z | 2021-02-07T21:48:38Z | MEMBER | I have a tentative fix for this in https://github.com/pydata/xarray/pull/4879. It would be great if someone could give this a try to verify that it resolve the issue. |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
jupyter repr caching deleted netcdf file 662505658 | |
663794065 | https://github.com/pydata/xarray/issues/4240#issuecomment-663794065 | https://api.github.com/repos/pydata/xarray/issues/4240 | MDEyOklzc3VlQ29tbWVudDY2Mzc5NDA2NQ== | shoyer 1217238 | 2020-07-25T02:05:18Z | 2020-07-25T02:05:18Z | MEMBER | Probably the easiest work around is to call I believe it only gets activated by |
{ "total_count": 1, "+1": 1, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
jupyter repr caching deleted netcdf file 662505658 | |
663790991 | https://github.com/pydata/xarray/issues/4240#issuecomment-663790991 | https://api.github.com/repos/pydata/xarray/issues/4240 | MDEyOklzc3VlQ29tbWVudDY2Mzc5MDk5MQ== | shoyer 1217238 | 2020-07-25T01:33:36Z | 2020-07-25T01:33:36Z | MEMBER | Thanks for the clear example! This happens dues to xarray's caching logic for files: https://github.com/pydata/xarray/blob/b1c7e315e8a18e86c5751a0aa9024d41a42ca5e8/xarray/backends/file_manager.py#L50-L76 This means that when you open the same filename, xarray doesn't actually reopen the file from disk -- instead it points to the same file object already cached in memory. I can see why this could be confusing. We do need this caching logic for files opened from the same |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
jupyter repr caching deleted netcdf file 662505658 |
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