issue_comments

Table actions

3 rows where issue = 1410305897 sorted by updated_at descending

✖
✖

✎ View and edit SQL

This data as json, CSV (advanced)

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

user 3

author_association 2

issue 1

  • Reconsider the Datasette first-run experience · 3 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions issue performed_via_github_app
1279924827 https://github.com/simonw/datasette/issues/1845#issuecomment-1279924827 https://api.github.com/repos/simonw/datasette/issues/1845 IC_kwDOBm6k_c5MShpb kindly 30636 2022-10-16T08:54:53Z 2022-10-16T08:54:53Z NONE

It was part of a larger idea I was exploring around ensuring Datasette could be used to start interacting with CSV/JSON data out-of-the-box, without needing to first convert that data into SQLite using separate tools.

This would be great. My organization deals with very nested JSON open data and I have been wanting to find a way to hook into datasette so that the analysts do not have to first convert to sqlite first.

This can kind of be done with datasette-lite.

From this random nested JSON API: https://api.nobelprize.org/v1/prize.json

You can use the API of https://flatterer.herokuapp.com to return a multi table sqlite database:

https://lite.datasette.io/?url=https://flatterer.herokuapp.com/api/convert?output_format=sqlite%26file_url=https://api.nobelprize.org/v1/prize.json

This is great and fun, but it would be great if there was some plugin mechanism that you could feed a local datasette a nested JSON file directly, possibly hooking into other flattening tools for this.

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
 Reconsider the Datasette first-run experience 1410305897  
1279846110 https://github.com/simonw/datasette/issues/1845#issuecomment-1279846110 https://api.github.com/repos/simonw/datasette/issues/1845 IC_kwDOBm6k_c5MSObe ocdtrekkie 4399499 2022-10-15T22:49:00Z 2022-10-15T22:49:00Z NONE

I think there's probably some core plugins a new user should just "get" maybe. I feel our Sandstorm package has really reasonable defaults, the ability to bring data in for instance. However, you also have to know that's in the hamburger menu, it's not necessarily intuitive where to start.

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
 Reconsider the Datasette first-run experience 1410305897  
1279842912 https://github.com/simonw/datasette/issues/1845#issuecomment-1279842912 https://api.github.com/repos/simonw/datasette/issues/1845 IC_kwDOBm6k_c5MSNpg simonw 9599 2022-10-15T22:22:58Z 2022-10-15T22:22:58Z OWNER

I think this mechanism could go a long way towards helping here: - https://github.com/simonw/datasette/issues/1160

It was part of a larger idea I was exploring around ensuring Datasette could be used to start interacting with CSV/JSON data out-of-the-box, without needing to first convert that data into SQLite using separate tools.

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
 Reconsider the Datasette first-run experience 1410305897  

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]);