issue_comments

Table actions

1 row where author_association = "COLLABORATOR" and issue = 1548948097 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

Suggested facets: created_at (date), updated_at (date)

user 1

issue 1

  • Typing of internal datatypes · 1 ✖

author_association 1

  • COLLABORATOR · 1 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1397469153 https://github.com/pydata/xarray/issues/7457#issuecomment-1397469153 https://api.github.com/repos/pydata/xarray/issues/7457 IC_kwDOAMm_X85TS6_h headtr1ck 43316012 2023-01-19T19:05:08Z 2023-01-19T19:05:08Z COLLABORATOR

Doesn't the python array api standard effort have some type of duck array protocol we could import? I feel like this has been mentioned before. Then we would start with @Illviljan 's suggestion and replace it with the correct duck array protocol later.

But then da.data will be of this protocol type and not the array class that you assume it has. For internal type checking this is what we want but for the user this will be confusing.

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Typing of internal datatypes 1548948097

Advanced export

JSON shape: default, array, newline-delimited, object

CSV options: 

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]);