github
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https://github.com/simonw/sqlite-utils/issues/403#issuecomment-1032976720 | https://api.github.com/repos/simonw/sqlite-utils/issues/403 | 1032976720 | IC_kwDOCGYnMM49kflQ | 9599 | 2022-02-08T19:23:05Z | 2022-02-08T19:23:27Z | OWNER | This is already possible using `sqlite-utils transform` like so: ``` % echo '[{"name": "Barry"}, {"name": "Sandra"}]' | sqlite-utils insert rowid.db records - % sqlite-utils schema rowid.db CREATE TABLE [records] ( [name] TEXT ); % sqlite-utils rows rowid.db records [{"name": "Barry"}, {"name": "Sandra"}] % sqlite-utils transform rowid.db records --pk id % sqlite-utils rows rowid.db records [{"id": 1, "name": "Barry"}, {"id": 2, "name": "Sandra"}] % sqlite-utils schema rowid.db CREATE TABLE "records" ( [id] INTEGER PRIMARY KEY, [name] TEXT ); % echo '[{"name": "Barry 2"}, {"name": "Sandra 2"}]' | sqlite-utils insert rowid.db records - % sqlite-utils rows rowid.db records [{"id": 1, "name": "Barry"}, {"id": 2, "name": "Sandra"}, {"id": 3, "name": "Barry 2"}, {"id": 4, "name": "Sandra 2"}] ``` It's not covered in the documentation though: https://sqlite-utils.datasette.io/en/3.23/cli.html#transforming-tables | { "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/sqlite-utils/issues/402#issuecomment-1032296717 | https://api.github.com/repos/simonw/sqlite-utils/issues/402 | 1032296717 | IC_kwDOCGYnMM49h5kN | 9599 | 2022-02-08T07:35:46Z | 2022-02-08T07:35:46Z | OWNER | I'm going to write the documentation for this first, before the implementation, so I can see if it explains cleanly enough that the design appears to be sound. | { "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/sqlite-utils/issues/402#issuecomment-1032294365 | https://api.github.com/repos/simonw/sqlite-utils/issues/402 | 1032294365 | IC_kwDOCGYnMM49h4_d | 9599 | 2022-02-08T07:32:09Z | 2022-02-08T07:34:41Z | OWNER | I have an idea for how that third option could work - the one that creates a new column using values from the existing ones: ```python db["places"].insert( { "name": "London", "lng": -0.118092, "lat": 51.509865, }, conversions={"point": LongitudeLatitude("lng", "lat")}, ) ``` How about specifying that the values in that `conversion=` dictionary can be: - A SQL string fragment (as currently implemented) - A subclass of `Conversion` as described above - Or... a callable function that takes the row as an argument and returns either a `Conversion` subclass instance or a literal value to be jnserted into the database (a string, int or float) Then you could do this: ```python db["places"].insert( { "name": "London", "lng": -0.118092, "lat": 51.509865, }, conversions={ "point": lambda row: LongitudeLatitude( row["lng"], row["lat"] ) } ) ``` Something I really like about this is that it expands the abilities of `conversions=` beyond the slightly obscure need to customize the SQL fragment into something that can solve other data insertion cleanup problems too. | { "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
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