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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.

 
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}
 Reconsider the Datasette first-run experience 1410305897  

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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]);