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Python CLI utility and library for manipulating SQLite databases
https://sqlite-utils.datasette.io
- Python 99.7%
- C 0.2%
* Add comprehensive type annotations - mypy.ini: expanded configuration with module-specific settings - hookspecs.py: type annotations for hook functions - plugins.py: typed get_plugins() return value - recipes.py: full type annotations for parsedate, parsedatetime, jsonsplit - utils.py: extensive type annotations including Row type alias, TypeTracker, ValueTracker, and all utility functions - db.py: type annotations for Database methods (__exit__, ensure_autocommit_off, tracer, register_function, etc.) and Queryable class methods - tests/test_docs.py: updated to match new signature display format * Fix type errors caught by ty check - Add type: ignore comments for external library type stub limitations (csv.reader, click.progressbar, IOBase.name, Callable.__name__) - Change Iterable to Sequence for SQL where_args parameters - Use db.table() instead of db[name] for proper Table return type - Fix rebuild_fts return type from None to Table - Update test_tracer to expect fewer queries (optimization side effect) * Fix mypy type errors - Add type: ignore comments for runtime-valid patterns mypy can't verify - Fix new_column_types annotation to Dict[str, Set[type]] - Add type: ignore for Default sentinel values passed to create_table * mypy skip tests directory * Fix CI: exclude typing imports from recipe docs, skip mypy on tests - Add Callable and Optional to exclusion list in _generate_convert_help() - Regenerate docs/cli-reference.rst with cog - Add [mypy-tests.*] ignore_errors = True to skip test type errors --------- Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com> |
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sqlite-utils
Python CLI utility and library for manipulating SQLite databases.
Some feature highlights
- Pipe JSON (or CSV or TSV) directly into a new SQLite database file, automatically creating a table with the appropriate schema
- Run in-memory SQL queries, including joins, directly against data in CSV, TSV or JSON files and view the results
- Configure SQLite full-text search against your database tables and run search queries against them, ordered by relevance
- Run transformations against your tables to make schema changes that SQLite
ALTER TABLEdoes not directly support, such as changing the type of a column - Extract columns into separate tables to better normalize your existing data
- Install plugins to add custom SQL functions and additional features
Read more on my blog, in this series of posts on New features in sqlite-utils and other entries tagged sqliteutils.
Installation
pip install sqlite-utils
Or if you use Homebrew for macOS:
brew install sqlite-utils
Using as a CLI tool
Now you can do things with the CLI utility like this:
$ sqlite-utils memory dogs.csv "select * from t"
[{"id": 1, "age": 4, "name": "Cleo"},
{"id": 2, "age": 2, "name": "Pancakes"}]
$ sqlite-utils insert dogs.db dogs dogs.csv --csv
[####################################] 100%
$ sqlite-utils tables dogs.db --counts
[{"table": "dogs", "count": 2}]
$ sqlite-utils dogs.db "select id, name from dogs"
[{"id": 1, "name": "Cleo"},
{"id": 2, "name": "Pancakes"}]
$ sqlite-utils dogs.db "select * from dogs" --csv
id,age,name
1,4,Cleo
2,2,Pancakes
$ sqlite-utils dogs.db "select * from dogs" --table
id age name
---- ----- --------
1 4 Cleo
2 2 Pancakes
You can import JSON data into a new database table like this:
$ curl https://api.github.com/repos/simonw/sqlite-utils/releases \
| sqlite-utils insert releases.db releases - --pk id
Or for data in a CSV file:
$ sqlite-utils insert dogs.db dogs dogs.csv --csv
sqlite-utils memory lets you import CSV or JSON data into an in-memory database and run SQL queries against it in a single command:
$ cat dogs.csv | sqlite-utils memory - "select name, age from stdin"
See the full CLI documentation for comprehensive coverage of many more commands.
Using as a library
You can also import sqlite_utils and use it as a Python library like this:
import sqlite_utils
db = sqlite_utils.Database("demo_database.db")
# This line creates a "dogs" table if one does not already exist:
db["dogs"].insert_all([
{"id": 1, "age": 4, "name": "Cleo"},
{"id": 2, "age": 2, "name": "Pancakes"}
], pk="id")
Check out the full library documentation for everything else you can do with the Python library.
Related projects
- Datasette: A tool for exploring and publishing data
- csvs-to-sqlite: Convert CSV files into a SQLite database
- db-to-sqlite: CLI tool for exporting a MySQL or PostgreSQL database as a SQLite file
- dogsheep: A family of tools for personal analytics, built on top of
sqlite-utils