issue_comments

Table actions

1 row where author_association = "NONE", "created_at" is on date 2022-09-15 and user = 82988 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

  • psychemedia · 1 ✖

author_association 1

  • NONE · 1 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions issue performed_via_github_app
1248440137 https://github.com/simonw/sqlite-utils/issues/406#issuecomment-1248440137 https://api.github.com/repos/simonw/sqlite-utils/issues/406 IC_kwDOCGYnMM5Kaa9J psychemedia 82988 2022-09-15T18:13:50Z 2022-09-15T18:13:50Z NONE

I was wondering if you have any more thoughts on this? I have a tangible use case now: adding a "vector" column to a database to support semantic search using doc2vec embeddings (example; note that the vtfunc package may no longer be reliable...).

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
 Creating tables with custom datatypes 1128466114  

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,
   [issue] INTEGER REFERENCES [issues]([id])
, [performed_via_github_app] TEXT);
CREATE INDEX [idx_issue_comments_issue]
                ON [issue_comments] ([issue]);
CREATE INDEX [idx_issue_comments_user]
                ON [issue_comments] ([user]);