issue_comments: 869074182

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https://github.com/simonw/datasette/issues/1384#issuecomment-869074182 https://api.github.com/repos/simonw/datasette/issues/1384 869074182 MDEyOklzc3VlQ29tbWVudDg2OTA3NDE4Mg== 2670795 2021-06-26T23:37:42Z 2021-06-26T23:37:42Z CONTRIBUTOR

Hmmm... that's tricky, since one of the most obvious ways to use this hook is to load metadata from database tables using SQL queries.
@brandonrobertz do you have a working example of using this hook to populate metadata from database tables I can try?

Answering my own question: here's how Brandon implements it in his datasette-live-config plugin: https://github.com/next-LI/datasette-live-config/blob/72e335e887f1c69c54c6c2441e07148955b0fc9f/datasette_live_config/__init__.py#L50-L160

That's using a completely separate SQLite connection (actually wrapped in sqlite-utils) and making blocking synchronous calls to it.

This is a pragmatic solution, which works - and likely performs just fine, because SQL queries like this against a small database are so fast that not running them asynchronously isn't actually a problem.

But... it's weird. Everywhere else in Datasette land uses await db.execute(...) - but here's an example where users are encouraged to use blocking calls instead.

Ideally this hook would be asynchronous, but when I started down that path I quickly realized how large of a change this would be, since metadata gets used synchronously across the entire Datasette codebase. (And calling async code from sync is non-trivial.)

In my live-configuration implementation I use synchronous reads using a persistent sqlite connection. This works pretty well in practice, but I agree it's limiting. My thinking around this was to go with the path of least change as Datasette.metadata() is a critical core function.

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