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html_url id node_id tag_name target_commitish name draft author prerelease created_at published_at body repo reactions
https://github.com/simonw/sqlite-utils/releases/tag/3.10 44904928 MDc6UmVsZWFzZTQ0OTA0OTI4 3.10 main 3.10 0 9599 0 2021-06-19T16:09:29Z 2021-06-19T16:13:11Z

This release introduces the sqlite-utils memory command, which can be used to load CSV or JSON data into a temporary in-memory database and run SQL queries (including joins across multiple files) directly against that data.

Also new: sqlite-utils insert --detect-types, sqlite-utils dump, table.use_rowid plus some smaller fixes.

sqlite-utils memory

This example of sqlite-utils memory retrieves information about the all of the repositories in the Dogsheep organization on GitHub using this JSON API, sorts them by their number of stars and outputs a table of the top five (using -t):

``` $ curl -s 'https://api.github.com/users/dogsheep/repos'\ | sqlite-utils memory - ' select full_name, forks_count, stargazers_count from stdin order by stargazers_count desc limit 5 ' -t full_name forks_count stargazers_count


dogsheep/twitter-to-sqlite 12 225 dogsheep/github-to-sqlite 14 139 dogsheep/dogsheep-photos 5 116 dogsheep/dogsheep.github.io 7 90 dogsheep/healthkit-to-sqlite 4 85 ```

The tool works against files on disk as well. This example joins data from two CSV files:

$ cat creatures.csv species_id,name 1,Cleo 2,Bants 2,Dori 2,Azi $ cat species.csv id,species_name 1,Dog 2,Chicken $ sqlite-utils memory species.csv creatures.csv ' select * from creatures join species on creatures.species_id = species.id ' [{"species_id": 1, "name": "Cleo", "id": 1, "species_name": "Dog"}, {"species_id": 2, "name": "Bants", "id": 2, "species_name": "Chicken"}, {"species_id": 2, "name": "Dori", "id": 2, "species_name": "Chicken"}, {"species_id": 2, "name": "Azi", "id": 2, "species_name": "Chicken"}]

Here the species.csv file becomes the species table, the creatures.csv file becomes the creatures table and the output is JSON, the default output format.

You can also use the --attach option to attach existing SQLite database files to the in-memory database, in order to join data from CSV or JSON directly against your existing tables.

Full documentation of this new feature is available in Querying data directly using an in-memory database. (#272)

sqlite-utils insert --detect-types

The sqlite-utils insert command can be used to insert data from JSON, CSV or TSV files into a SQLite database file. The new --detect-types option (shortcut -d), when used in conjunction with a CSV or TSV import, will automatically detect if columns in the file are integers or floating point numbers as opposed to treating everything as a text column and create the new table with the corresponding schema. See Inserting CSV or TSV data for details. (#282)

Other changes

  • Bug fix: table.transform(), when run against a table without explicit primary keys, would incorrectly create a new version of the table with an explicit primary key column called rowid. (#284)
  • New table.use_rowid introspection property, see .use_rowid. (#285)
  • The new sqlite-utils dump file.db command outputs a SQL dump that can be used to recreate a database. (#274)
  • -h now works as a shortcut for --help, thanks Loren McIntyre. (#276)
  • Now using pytest-cov and Codecov to track test coverage - currently at 96%. (#275)
  • SQL errors that occur when using sqlite-utils query are now displayed as CLI errors.
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