issue_comments
1 row where "created_at" is on date 2022-09-02 and reactions = "{"total_count": 1, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 1}" sorted by author_association
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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 |
---|---|---|---|---|---|---|---|---|---|---|---|
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](https://github.com/catalyst-cooperative/ferc-xbrl-extractor)) and the Datasette YAML metadata [so we can publish them with Datasette](https://github.com/catalyst-cooperative/pudl/pull/1831). Maybe there's some overlap? We've been loving Pydantic. | {"total_count": 1, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 1} | Validate metadata.json on startup 323223872 |
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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]);
reactions 1 ✖