sqlite-utils 4.0rc1 adds migrations and nested transactions

21st June 2026

sqlite-utils is my combined Python library and CLI tool for working with SQLite databases. It provides an extensive set of higher-level operations on top of Python’s default sqlite3 package, including support for complex table transformations, automatic table creation from JSON data and a whole lot more.

I released sqlite-utils 4.0rc1, the first release candidate for sqlite-utils v4. The major version bump indicates some (minor) backwards incompatible changes, so I’m interested in having people try this out before I commit to a stable release.

New feature: migrations

There are two significant new features in this RC compared to the previous 4.0 alphas.

The first is support for database migrations. This isn’t a completely new implementation—it’s a slightly modified port of the sqlite-migrate package I released a few years ago. I think that package has proved itself over time, so I’m now ready to bundle it with sqlite-utils directly.

Here’s what a set of migrations in a migrations.py file looks like:

from sqlite_utils import Database, Migrations

migrations = Migrations("creatures")

@migrations() def create_table(db): db["creatures"].create( {"id": int, "name": str, "species": str}, pk="id", )

@migrations() def add_weight(db): db["creatures"].add_column("weight", float)

This defines a set of two migrations, one creating the creatures table and another adding a column to it.

You can then run those migrations either using Python:

db = Database("creatures.db") migrations.apply(db)

Or with the command-line migrate command:

sqlite-utils migrate creatures.db migrations.py

The system is deliberately small: it doesn’t provide reverse migrations, so any mistakes you make should be fixed by deploying a fresh migration to undo them.

Its predecessor has been used by LLM and various other projects for several years, so I’m confident that the design is stable and works well.

The new migrations feature is documented here.

New feature: db.atomic() transactions

This feature is a lot less exercised than migrations, so it deserves more attention from testers.

Previously, sqlite-utils mostly left transaction management up to its users, via a with db.conn: construct that reused the sqlite3 mechanism directly.

SQLite supports nested transactions in the form of savepoints, so I wanted an abstraction that could make those as easy to use as possible.

I borrowed the terminology “atomic” from Django and Peewee. Here’s what the new API looks like:

with db.atomic(): db.table("dogs").insert({"id": 1, "name": "Cleo"}, pk="id") try: with db.atomic(): db.table("dogs").insert({"id": 2, "name": "Pancakes"}) raise ValueError("skip this one") except ValueError: pass db.table("dogs").insert({"id": 3, "name": "Marnie"})

More details in the documentation.

Backwards incompatible changes

The backwards incompatible changes in v4 were described in the alpha release notes. For 4.0a0:

• Upsert operations now use SQLite’s INSERT ... ON CONFLICT SET syntax on all SQLite versions later than 3.23.1. This is a very slight breaking change for apps that depend on the previous INSERT OR IGNORE followed by UPDATE behavior. (#652)
• Python library users can opt-in to the previous implementation by passing use_old_upsert=True to the Database() constructor, see Alternative upserts using INSERT OR IGNORE.
• Dropped support for Python 3.8, added support for Python 3.13. (#646)
• sqlite-utils tui is now provided by the sqlite-utils-tui plugin. (#648)
• Test suite now also runs against SQLite 3.23.1, the last version (from 2018-04-10) before the new INSERT ... ON CONFLICT SET syntax was added. (#654)

And for 4.0a1:

• Breaking change: The db.table(table_name) method now only works with tables. To access a SQL view use db.view(view_name) instead. (#657)
• The table.insert_all() and table.upsert_all() methods can now accept an iterator of lists or tuples as an alternative to dictionaries. The first item should be a list/tuple of column names. See Inserting data from a list or tuple iterator for details. (#672)
• Breaking change: The default floating point column type has been changed from FLOAT to REAL, which is the correct SQLite type for floating point values. This affects auto-detected columns when inserting data. (#645)
• Now uses pyproject.toml in place of setup.py for packaging. (#675)
• Tables in the Python API now do a much better job of remembering the primary key and other schema details from when they were first created. (#655)
• Breaking change: The table.convert() and sqlite-utils convert mechanisms no longer skip values that evaluate to False. Previously the --skip-false option was needed, this has been removed. (#542)
• Breaking change: Tables created by this library now wrap table and column names in "double-quotes" in the schema. Previously they would use [square-braces]. (#677)
• The --functions CLI argument now accepts a path to a Python file in addition to accepting a string full of Python code. It can also now be specified multiple times. (#659)
• Breaking change: Type detection is now the default behavior for the insert and upsert CLI commands when importing CSV or TSV data. Previously all columns were treated as TEXT unless the --detect-types flag was passed. Use the new --no-detect-types flag to restore the old behavior. The SQLITE_UTILS_DETECT_TYPES environment variable has been removed. (#679)

Try it out

You can install the new RC like this:

pip install sqlite-utils==4.0rc1

Or try the CLI version directly with uvx like this:

uvx --with sqlite-utils==4.0rc1 sqlite-utils --help

Come chat with us about it in the sqlite-utils Discord channel, or file any bugs in GitHub Issues.