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CONTRIBUTING.md

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Development of the adapter

The Synapse adapter uses the dbt-sqlserver adapter underneath. This repository mostly contains a set of macros that override the behavior of dbt-sqlserver so that it works with Synapse.

Python 3.10 is used for developing the adapter. To get started, bootstrap your environment as follows:

Create a virtual environment, pyenv is used in the example:

pyenv install 3.10.7
pyenv virtualenv 3.10.7 dbt-synapse
pyenv activate dbt-synapse

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 Synapse Dedicated SQL Pool instance. You can configure the connection to this instance with the file test.env in the root of the project. You can use the provided test.env.sample as a base.

cp test.env.sample test.env

You can use the following command to run the functional tests:

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 and image are part of the dbt-sqlserver repository.

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

  • integration-tests-azure: runs the integration tests for Azure 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_SYNAPSE_SERVER: Name of the Synapse workspace
  • DBT_SYNAPSE_DB: Name of the Synapse dedicated SQL pool
  • 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.

Make sure that the dependency to dbt-sqlserver is bumped to a compatible version in setup.py.

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