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2 rows where author_association = "NONE", issue = 323223872 and user = 596279 sorted by updated_at descending

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  • zaneselvans · 2 ✖

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  • Validate metadata.json on startup · 2 ✖

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  • NONE · 2 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions issue performed_via_github_app
1235079469 https://github.com/simonw/datasette/issues/260#issuecomment-1235079469 https://api.github.com/repos/simonw/datasette/issues/260 IC_kwDOBm6k_c5JndEt zaneselvans 596279 2022-09-02T05:24:59Z 2022-09-02T05:24:59Z NONE

@zschira is working with Pydantic while converting between and validating JSON frictionless datapackage descriptors that annotate an SQLite DB (extracted from FERC's XBRL data) and the Datasette YAML metadata so we can publish them with Datasette. Maybe there's some overlap? We've been loving Pydantic.

 
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 Validate metadata.json on startup 323223872  
1051473892 https://github.com/simonw/datasette/issues/260#issuecomment-1051473892 https://api.github.com/repos/simonw/datasette/issues/260 IC_kwDOBm6k_c4-rDfk zaneselvans 596279 2022-02-26T02:24:15Z 2022-02-26T02:24:15Z NONE

Is there already functionality that can be used to validate the metadata.json file? Is there a JSON Schema that defines it? Or a validation that's available via datasette with Python? We're working on automatically building the metadata in CI and when we deploy to cloud run, and it would be nice to be able to check whether the the metadata we're outputting is valid in our tests.

 
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 Validate metadata.json on startup 323223872  

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   [issue_url] TEXT,
   [id] INTEGER PRIMARY KEY,
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   [author_association] TEXT,
   [body] TEXT,
   [reactions] TEXT,
   [issue] INTEGER REFERENCES [issues]([id])
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