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1 row where issue = 459882902 and user = 701 sorted by updated_at descending

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  • jokull · 1 ✖

issue 1

  • Stream all results for arbitrary SQL and canned queries · 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
810943882 https://github.com/simonw/datasette/issues/526#issuecomment-810943882 https://api.github.com/repos/simonw/datasette/issues/526 MDEyOklzc3VlQ29tbWVudDgxMDk0Mzg4Mg== jokull 701 2021-03-31T10:03:55Z 2021-03-31T10:03:55Z NONE

+1 on using nested queries to achieve this! Would be great as streaming CSV is an amazing feature.

Some UX/DX details:

I was expecting it to work to simply add &_stream=on to custom SQL queries because the docs say

Any Datasette table, view or custom SQL query can be exported as CSV.

After a bit of testing back and forth I realized streaming only works for full tables.

Would love this feature because I'm using pandas.read_csv to paint graphs from custom queries and the graphs are cut off because of the 1000 row limit.

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Stream all results for arbitrary SQL and canned queries 459882902  

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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]);
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