alvassin/alembic-quickstart

Migrations testing and Alembic usage examples.

Prepared for "Databases: models, migrations, testing" lection at Yandex Backend Development school and "How to develop & test database migrations with Alembic" presentation at Moscow Python meetup №69 (videos are in Russian).

Code & examples are updated from time to time, please browse files at 7b804f8371bc14bbc35991654a37fc90b7fe4358 commit if you need exact code shown at Moscow Python meetup.

🇷🇺 Russian translation is available for this document.

What's inside

Aiohttp application with couple migrations and two commands: staff-db to control database state (Alembic wrapper) and staff-api (REST API aiohttp service).

Execute make devenv command to prepare development environment. It will create virtual environment in ./env folder and install all dependencies (execute make for all available commands).

How to control database state

Alembic provides alembic command to control database state (apply, rollback migrations, etc). In some cases it has the following disadvantages:

• alembic command requires alembic.ini configuration file, which is searched at current working directory. It is possible to specify path to alembic.ini using command-line argument --config, but it is easier to call the command from any folder without additional parameters.
• To connect Alembic to specific database it is required to change sqlalachemy.url parameter in alembic.ini. Sometimes (e.g. if the application is distributed via Docker container) it is much more convenient to specify the database URL with an environment variable and/or a command-line argument.
• Some applications need to extend standard Alembic arguments (e.g. to support working in different PostgreSQL schemas).

They can be solved by using Alembic wrapper. For example, staff-db provides ability to specify database URL using environment variable STAFF_PG_URL or --pg-url argument, resolves the path to alembic.ini using its location, rather than the current working directory.

How to prepare database for tests

Very often tests require the database. You can create separate database for each test using pytest fixture (see postgres fixture), this approach allows to isolate tests from each other.

In most cases, tests require already prepared database with migrations applied. Since it is expensive to run migrations when creating a database for each test, you could do it once to prepare database, and then use it as template to create new databases.

Template database is created using migrated_postgres_template fixture within session scope. Databases for tests are created using migrated_postgres fixture.

How to test migrations

Stairway test

Simple and efficient method to check that migration does not have typos and rolls back all schema changes. Does not require maintenance - you can add this test to your project once and forget about it.

In particular, test detects the data types, that were previously created by upgrade() method and were not removed by downgrade(): when creating a table/column, Alembic automatically creates custom data types specified in columns (e.g. enum), but does not delete them when deleting table or column - developer has to do it manually.

How it works

Test retrieves all migrations list, and for each migration executes upgrade, downgrade, upgrade Alembic commands. See test_stairway.py for example.

Data-migration test

Some migrations don't just add new columns or tables, but change the data in some way.

In addition to checking that the migration correctly rolls back changes to the data structure (stairway test), you need to check that the data is correctly changed by the upgrade() method and returned to the previous state by the downgrade() method.

This test does not guarantee that there are no bugs - it is very difficult to provide data sets for all cases. But data-altering migrations code is often very complex, errors are more common, and errors in such migrations can have the most serious consequences.

How it works

The test applies all migrations up to the one being tested and adds a dataset to the database that will be modified by the migration being tested. Then test executes the upgrade() method and checks that the data was changed correctly. After this, test calls downgrade() method and checks that all data was returned to its initial state. See test_data_migrations.py for example.