github
html_url | issue_url | id | node_id | user | created_at | updated_at | author_association | body | reactions | issue | performed_via_github_app |
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https://github.com/simonw/datasette/issues/276#issuecomment-391505930 | https://api.github.com/repos/simonw/datasette/issues/276 | 391505930 | MDEyOklzc3VlQ29tbWVudDM5MTUwNTkzMA== | 45057 | 2018-05-23T21:41:37Z | 2018-05-23T21:41:37Z | CONTRIBUTOR | > I'm not keen on anything that modifies the SQLite file itself on startup Ah I didn't mean that - I meant altering the SELECT query to fetch the data so that it ran a spatialite function to transform that specific column. I think that's less useful as a general-purpose plugin hook though, and it's not that hard to parse the WKB in Python (my default approach would be to use [shapely](https://github.com/Toblerity/Shapely), which is great, but geomet looks like an interesting pure-python alternative). | { "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
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https://github.com/simonw/datasette/issues/276#issuecomment-391504757 | https://api.github.com/repos/simonw/datasette/issues/276 | 391504757 | MDEyOklzc3VlQ29tbWVudDM5MTUwNDc1Nw== | 9599 | 2018-05-23T21:37:07Z | 2018-05-23T21:37:18Z | OWNER | That said, it looks like we may be able to use a library like https://github.com/geomet/geomet to run the conversion from WKB entirely in Python space. | { "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
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https://github.com/simonw/datasette/issues/276#issuecomment-391504199 | https://api.github.com/repos/simonw/datasette/issues/276 | 391504199 | MDEyOklzc3VlQ29tbWVudDM5MTUwNDE5OQ== | 9599 | 2018-05-23T21:35:17Z | 2018-05-23T21:35:17Z | OWNER | I'm not keen on anything that modifies the SQLite file itself on startup - part of the datasette contract is that it should work with any SQLite file you throw at it without having any side-effects. A neat thing about SQLite is that because everything happens in the same process there's very little additional overhead involved in executing extra SQL queries - even if we ran a query-per-row to transform data in one specific column it shouldn't add more than a few ms to the total page load time (whereas with MySQL all of the extra query overhead would kill us). | { "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
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