- Python 99.7%
- C 0.2%
- Just 0.1%
The line under "Custom transformations with .transform_sql()" said
`.transform()` "does not automatically upgrade indexes, views or triggers".
All three parts are wrong, and the trigger one is wrong in the dangerous
direction. Measured on current main:
rename a column triggers ['trg'] -> [] views kept indexes kept
change a type triggers ['trg'] -> [] views kept indexes kept
drop a column triggers ['trg'] -> [] views kept indexes kept
* Indexes *are* handled. `transform_sql()` captures each one before the old
table is dropped and reissues its CREATE INDEX, rewriting a renamed
column: `CREATE INDEX "idx" ON "t" ("new_name")`.
* Views are kept, and were already documented accurately under "Tables
referenced by views" -- so the old sentence also contradicted a section
four paragraphs above it.
* Triggers are not merely "not upgraded". They are **dropped**. SQLite
deletes a table's triggers with the table, and `transform_sql()` never
captures them. A reader told the trigger was not *upgraded* would expect
it to still exist, possibly stale. It is gone.
Replaces the sentence with an "Indexes and triggers" section covering what
actually happens, including the `UNIQUE`-constraint index case (not
reissued, because the constraint is reproduced in the new CREATE TABLE) and
the TransformError raised for any other index without stored SQL.
The trigger part carries a recipe using `table.triggers_dict`, with the
caveat that a captured trigger body still names the old columns. Both the
recipe and every claim above were run against main before being written.
Docs build clean under `sphinx-build -W`.
Closes #849
|
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|---|---|---|
| .github | ||
| docs | ||
| sqlite_utils | ||
| tests | ||
| .gitignore | ||
| .readthedocs.yaml | ||
| codecov.yml | ||
| Justfile | ||
| LICENSE | ||
| MANIFEST.in | ||
| mypy.ini | ||
| pyproject.toml | ||
| README.md | ||
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
- Manage database migrations using Python migration files and the
sqlite-utils migratecommand - Install plugins to add custom SQL functions and additional features
Upgrading from sqlite-utils 3.x? See the 4.0 upgrade guide.
Read more on my blog, in this series of posts on New features in sqlite-utils and other entries tagged sqlite-utils.
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