issue_comments

Table actions

3 rows where author_association = "CONTRIBUTOR", issue = 421546944 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 · 3 ✖

issue 1

  • Datasette Library · 3 ✖

author_association 1

  • CONTRIBUTOR · 3 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions issue performed_via_github_app
752098906 https://github.com/simonw/datasette/issues/417#issuecomment-752098906 https://api.github.com/repos/simonw/datasette/issues/417 MDEyOklzc3VlQ29tbWVudDc1MjA5ODkwNg== psychemedia 82988 2020-12-29T14:34:30Z 2020-12-29T14:34:50Z CONTRIBUTOR

FWIW, I had a look at watchdog for a datasette powered Jupyter notebook search tool: https://github.com/ouseful-testing/nbsearch/blob/main/nbsearch/nbwatchdog.py

Not a production thing, just an experiment trying to explore what might be possible...

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
 Datasette Library 421546944  
586599424 https://github.com/simonw/datasette/issues/417#issuecomment-586599424 https://api.github.com/repos/simonw/datasette/issues/417 MDEyOklzc3VlQ29tbWVudDU4NjU5OTQyNA== psychemedia 82988 2020-02-15T15:12:19Z 2020-02-15T15:12:33Z CONTRIBUTOR

So could the polling support also allow you to call sqlite_utils to update a database with csv files? (Though I'm guessing you would only want to handle changed files? Do your scrapers check and cache csv datestamps/hashes?)

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
 Datasette Library 421546944  
474280581 https://github.com/simonw/datasette/issues/417#issuecomment-474280581 https://api.github.com/repos/simonw/datasette/issues/417 MDEyOklzc3VlQ29tbWVudDQ3NDI4MDU4MQ== psychemedia 82988 2019-03-19T10:06:42Z 2019-03-19T10:06:42Z CONTRIBUTOR

This would be really interesting but several possibilities in use arise, I think?

For example:

  • I put a new CSV file into the import dir and a new table is created therefrom
  • I put a CSV file into the import dir that replaces a previous file / table of the same name as a pre-existing table (eg files that contain monthly data in year to date). The data may also patch previous months, so a full replace / DROP on the original table may well be in order.
  • I put a CSV file into the import dir that updates a table of the same name as a pre-existing table (eg files that contain last month's data)

CSV files may also have messy names compared to the table you want. Or for an update CSV, may have the form MYTABLENAME-February2019.csv etc

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
 Datasette Library 421546944  

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]);