This repository contains two branches, master and develop.
The master branch requires Pull Requests and code reviews to merge code into
it. It deploys automatically to the Production (Sandbox) Airflow deployment.
The develop branch accepts pushes directly, or via Pull Request, and deploys
automatically to the Development Airflow.
We're not happy with this strategy, and are looking for an alternative that doesn't have us deploying and inadvertently running code in multiple places by accident, but haven't come up with anything yet.
If you have Docker available, by far the easiest development setup is to use Docker Compose.
First, initialise some environment variables:
python -c 'from cryptography.fernet import Fernet; print("FERNET_KEY=" + Fernet.generate_key().decode())' > .env
echo UID=`id -u` >> .env
echo GID=`id -g` >> .envThen start up docker-compose:
docker-compose upDAGs can be locally edited and validated. Development can be done in conda or venv according to developer preference. Grab everything airflow and write DAGs. Use autopep8 and pylint to achieve import validation and consistent formatting as the CI pipeline for this repository matures.
pip install apache-airflow[aws,kubernetes,postgres,redis,ssh,celery]
pip install pylint pylint-airflow
pylint dags pluginsA pre-commit config is provided to automatically format and check your code changes. This allows you to immediately catch and fix issues before you raise a failing pull request (which run the same checks under Travis).
If you don't use Conda, install pre-commit from pip:
pip install pre-commit
If you do use Conda, install from conda-forge (required because the pip version uses virtualenvs which are incompatible with Conda's environments)
conda install pre_commit
Now install the pre-commit hook to the current repository:
pre-commit install
Your code will now be formatted and validated before each commit. You can also
invoke it manually by running pre-commit run --all-files