ata-db-models

ata-db-models

Database models and migrations for Automating the Ask.

Usage

As a package

We use SQLModel, a layer on top of SQLAlchemy with Pydantic, to define our tables. This is useful because we can import this package to interact with the tables AND have Pydantic objects in Python that correspond to a row in the table.

To install the package from PyPi, run: pip install ata-db-models. Check existing versions here.

Initialize a new cluster

If you want to initialize a fresh database cluster, pass in the env vars to connect to the cluster and run init_db. If the target cluster has IP restrictions, make sure your IP address is a valid access point.

An example run with fake credentials (from the root dir of this project with the virtual env activated): HOST=fakehost USER=fakeuser PASSWORD=fakepw DB_NAME=postgres python ata_db_models/db_init_stages/_0_init_db.py

This should run the most up-to-date SQLModel definitions of the tables, which means you are safe to then run any additional changes in role, access, and policy changes. So you can run the rest of the steps in db_init_stages, one after the other in ascending numerical order.

No PORT is passed because the default port is 5432, the standard for Postgres.

Migrations

So you made some changes to what tables there are, what columns there are, indices, etc. and you'd like to update the databases. This is what alembic is for!

To generate a new revision after you've updated the models:

1. Run this from the root of the project: DB_CONNECTION_STRING='postgresql://user:password@host:port/db_name' alembic revision --autogenerate -m "message"
2. Check the /alembic/versions/ directory for the new revision and verify that it does what you want it to
3. Run this from the root of the project: DB_CONNECTION_STRING='postgresql://user:password@host:port/db_name' alembic upgrade head
4. Note that you only need to generate the revision file (step 1) once because we want the same content in each environment's database, but you do need to run the upgrade head command once for each database (change the DB_NAME to the desired target).

To make new users, grant privileges, etc., follow the patterns used in db_init_stages along with the helpers under ata_db_models.

1. Create a new file under db_init_stages that does what you want and is prefixed with _X_, where X is the next number (it has no function, it's just nice to keep track of the step order).
2. Run the file. You can run it like so: HOST=fakehost USER=fakeuser PASSWORD=fakepw DB_NAME=postgres python ata_db_models/db_init_stages/_X_fake_file.py
3. I'd recommend that you then connect to the cluster and verify your changes took place.

Note that you must provide valid host, user, password, and database name environment variables for it to work. The PORT env var has a default value of 5432, so it is omitted here. The only other env var you might need (if you are creating new roles/users that have credentials) is the ENABLE_SSM env var. By default it is FALSE but if you set it to TRUE then it will make sure to upload any new credentials to the SSM parameter store.

Development

This project uses Poetry to manage dependencies. It also helps with pinning dependency and python versions. We also use pre-commit with hooks for isort, black, and flake8 for consistent code style and readability. Note that this means code that doesn't meet the rules will fail to commit until it is fixed.

We use mypy for static type checking. This can be run manually, and the CI runs it on PRs to the main branch. We also use pytest to run our tests. This can be run manually and the CI runs it on PRs to the main branch.

Setup

1. Install Poetry.
2. Run poetry install --no-root
3. Run source $(poetry env list --full-path)/bin/activate && pre-commit install && deactivate to set up pre-commit

You're all set up! Your local environment should include all dependencies, including dev dependencies like black. This is done with Poetry via the poetry.lock file.

Run Code Format and Linting

To manually run isort, black, and flake8 all in one go, simply run pre-commit run --all-files. Explore the pre-commit docs (linked above) to see more options.

Run Static Type Checking

To manually run mypy, simply run mypy from the root directory of the project. It will use the default configuration specified in pyproject.toml.

Update Dependencies

To update dependencies in your local environment, make changes to the pyproject.toml file then run poetry update from the root directory of the project.

Run Tests

To manually run rests, you need to have a Postgres instance running locally on port 5432. One way to do this is to run a Docker container, then run the tests while it is active.

1. (If you don't already have the image locally) Run docker pull postgres
2. Run docker run --rm --name postgres -e POSTGRES_PASSWORD=postgres -e POSTGRES_HOST_AUTH_METHOD=trust -p 127.0.0.1:5432:5432/tcp postgres
3. Run DB_NAME=postgres pytest tests from the root directory of the project. Explore the pytest docs (linked above) to see more options.

Note that if you decide to run the Postgres container with different credentials (a different password, port, etc.) or via a different method, you will likely need to update the test file to point to the correct Postgres instance.

Additionally, if you want to re-run the tests, you want to make sure you start over from a fresh Postgres instance. If you run Postgres via Docker, you can simply ctrl-C to stop the image and start a new one.