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Development of the adapter

Dependencies

A recent version of Docker.

Python 3.11

Create a virtual environment to properly isolate your Python dependencies. Here is an example of how to do so using the pyenv CLI:

pyenv install 3.11.6
pyenv virtualenv 3.11.6 dbt-sqlserver
pyenv activate dbt-sqlserver

Install the development dependencies and pre-commit and get information about possible make commands:

make dev
make help

Pre-commit helps us to maintain a consistent style and code quality across the entire project. After running make dev, pre-commit will automatically validate your commits and fix any formatting issues whenever possible.

Testing

The functional tests require a running SQL Server instance. We'll spin one up using Docker Compose. First, copy the example .env.test.sample to create a new file .env.test, which contains the environment variables that will be read by Docker Compose:

cp test.env.sample test.env

If desired, you can tweak the contents of test.env to test against a different database.

Now, you can easily spin up a local SQL Server instance:

make server

This will use Docker Compose to fetch the image and run the container.

Note that we need 3 users to be able to run tests related to the grants. The 3 users are defined by the following environment variables containing their usernames.

  • DBT_TEST_USER_1
  • DBT_TEST_USER_2
  • DBT_TEST_USER_3

You can use the following commands to run the unit and the functional tests respectively:

make unit
make functional

CI/CD

We use Docker images that have all the things we need to test the adapter in the CI/CD workflows. The Dockerfile is located in the devops directory and pushed to GitHub Packages to this repo. There is one tag per supported Python version.

All CI/CD pipelines are using GitHub Actions. The following pipelines are available:

  • publish-docker: publishes the image we use in all other pipelines.
  • unit-tests: runs the unit tests for each supported Python version.
  • integration-tests-azure: runs the integration tests for Azure SQL Server.
  • integration-tests-sqlserver: runs the integration tests for SQL Server.
  • release-version: publishes the adapter to PyPI.

There is an additional Pre-commit pipeline that validates the code style.

Azure integration tests

The following environment variables are available:

  • DBT_AZURESQL_SERVER: full hostname of the server hosting the Azure SQL database
  • DBT_AZURESQL_DB: name of the Azure SQL database
  • DBT_AZURESQL_UID: username of the SQL admin on the server hosting the Azure SQL database
  • DBT_AZURESQL_PWD: password of the SQL admin on the server hosting the Azure SQL database
  • DBT_AZURE_TENANT: Azure tenant ID
  • DBT_AZURE_SUBSCRIPTION_ID: Azure subscription ID
  • DBT_AZURE_RESOURCE_GROUP_NAME: Azure resource group name
  • DBT_AZURE_SP_NAME: Client/application ID of the service principal used to connect to Azure AD
  • DBT_AZURE_SP_SECRET: Password of the service principal used to connect to Azure AD

Releasing a new version

Make sure the version number is bumped in __version__.py. Then, create a git tag named v<version> and push it to GitHub. A GitHub Actions workflow will be triggered to build the package and push it to PyPI.

If you're releasing support for a new version of dbt-core, also bump the dbt_version in setup.py.