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  • davidbgk · 5 ✖

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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
1339916064 https://github.com/simonw/datasette/pull/1931#issuecomment-1339916064 https://api.github.com/repos/simonw/datasette/issues/1931 IC_kwDOBm6k_c5P3X8g davidbgk 3556 2022-12-06T19:42:45Z 2022-12-06T19:42:45Z CONTRIBUTOR

The "return": true option is really nice!

 
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 /db/table/-/upsert 1473814539  
1339906969 https://github.com/simonw/datasette/issues/1929#issuecomment-1339906969 https://api.github.com/repos/simonw/datasette/issues/1929 IC_kwDOBm6k_c5P3VuZ davidbgk 3556 2022-12-06T19:34:20Z 2022-12-06T19:34:20Z CONTRIBUTOR

I confirm that it works 👍 

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 Incorrect link from the API explorer to the JSON API documentation 1473659191  
1309650806 https://github.com/simonw/datasette/issues/1871#issuecomment-1309650806 https://api.github.com/repos/simonw/datasette/issues/1871 IC_kwDOBm6k_c5OD692 davidbgk 3556 2022-11-10T01:38:58Z 2022-11-10T01:38:58Z CONTRIBUTOR

Realized the API explorer doesn't need the API key piece at all - it can work with standard cookie-based auth.

This also reflects how most plugins are likely to use this API, where they'll be adding JavaScript that uses fetch() to call the write API directly.

I agree (that's what I did with the previous insert plugin), maybe a complete example using fetch() in the documentation would be valuable as a “Getting started with the API” or similar?

 
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 API explorer tool 1427293909  
996229007 https://github.com/simonw/datasette/issues/1552#issuecomment-996229007 https://api.github.com/repos/simonw/datasette/issues/1552 IC_kwDOBm6k_c47YT-P davidbgk 3556 2021-12-16T22:04:39Z 2021-12-16T22:04:39Z CONTRIBUTOR

Wow, that was fast, thank you so much @simonw !

I'm also not convinced that this configuration syntax is right. It's a bit weird having a "facets" list that can either by column-name-strings or {"type-of-facet": "column-name"} objects. Maybe there's a better design for this?

I agree that it's not ideal, my initial naive approach was to detect if it's an array, like what is done here:

https://github.com/simonw/datasette/blob/2c07327d23d9c5cf939ada9ba4091c1b8b2ba42d/datasette/facets.py#L312-L313

But it requires an extra query to determine the type, which is a bit problematic, especially for big tables I guess.

Taking a look at #510, I wonder if a facet_delimiter should be defined for that kind of columns (that would help our team not to have an intermediary conversion step from foo|bar to ["foo","bar"] for instance).

To be consistent with the --extract-column parameter, maybe an explicit casting/delimiter would be useful: --set-column 'Foo:Array:|'.

Throwing a lot of ideas without knowing the big picture… but sometimes newcomers have superpowers :).

 
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 Allow to set `facets_array` in metadata (like current `facets`) 1078702875  
995296725 https://github.com/simonw/datasette/issues/1552#issuecomment-995296725 https://api.github.com/repos/simonw/datasette/issues/1552 IC_kwDOBm6k_c47UwXV davidbgk 3556 2021-12-15T23:29:32Z 2021-12-15T23:29:32Z CONTRIBUTOR

@simonw thank you for your fast answer and your guidance!

While digging into the code, I found an undocumented way of doing it:

yaml facets: ["Facet for a column", {"array": "Facet for an array"}]

The only remaining problem with that solution is here: https://github.com/simonw/datasette/blob/250db8192cb8aba5eb8cd301ccc2a49525bc3d24/datasette/facets.py#L33

We have:

python type, metadata_config = metadata_config.items()[0]

But it requires to cast the dict_items as a list prior to access the first element:

python type, metadata_config = list(metadata_config.items())[0]

I guess it's an unspotted bug? (I mean, independently of the facets-with-arrays issue.)

 
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 Allow to set `facets_array` in metadata (like current `facets`) 1078702875  

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