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1 row where "created_at" is on date 2018-05-28 and issue = 276091279 sorted by updated_at descending

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  • apsw as alternative sqlite3 binding (for full text search) · 1 ✖

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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
392606044 https://github.com/simonw/datasette/issues/144#issuecomment-392606044 https://api.github.com/repos/simonw/datasette/issues/144 MDEyOklzc3VlQ29tbWVudDM5MjYwNjA0NA== simonw 9599 2018-05-28T21:29:42Z 2018-05-28T21:29:42Z OWNER

The other major limitation of APSW is its treatment of unicode: https://rogerbinns.github.io/apsw/types.html - it tells you that it is your responsibility to ensure that TEXT columns in your SQLite database are correctly encoded.

Since Datasette is designed to work against ANY SQLite database that someone may have already created, I see that as a show-stopping limitation.

Thanks to https://github.com/coleifer/sqlite-vtfunc I now have a working mechanism for virtual tables (I've even built a demo plugin with them - https://github.com/simonw/datasette-sql-scraper ) which was the main thing that interested me about APSW.

I'm going to close this as WONTFIX - I think Python's built-in sqlite3 is good enough, and is now so firmly embedded in the project that making it pluggable would be more trouble than it's worth.

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apsw as alternative sqlite3 binding (for full text search) 276091279  

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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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