dynamic-dags-tutorial

This repo contains an Astronomer project with multiple examples showing how to dynamically generate DAGs in Airflow. A guide discussing these concepts in depth will be published shortly.

DAG Overview

This repo contains DAGs and supporting Python scripts that dynamically generate DAGs using multiple methods. They are described here, organized by folder.

dags

• dynamic-dags-connections.py generates DAGs based on Airflow connections.
• dynamic-dags-loop.py generates DAGs based on a simple range() loop.
• dynamic-dags-variable.py generates DAGs based on an Airflow variables.
• dag_file_1.py and dag_file_2.py are actual DAG files that were dynamically generated using scripts in the include/ directory, described below.

include

• dag-config/ contains two Json configuration files with parameters used to dynamically generate Python files for dag_file_1.py and dag_file_2.py.
• dag-template.py contains the starting DAG template from which other DAG files are dynamically generated.
• generate-dag-files.py contains a script to dynamically generate a DAG file for each config file in dag-config/ by making a copy of dag-template.py and replacing key parameters from the config file.

Getting Started

The easiest way to run these example DAGs is to use the Astronomer CLI to get an Airflow instance up and running locally:

1. Install the Astronomer CLI
2. Clone this repo somewhere locally and navigate to it in your terminal
3. Initialize an Astronomer project by running astro dev init
4. Start Airflow locally by running astro dev start
5. Navigate to localhost:8080 in your browser and you should see the tutorial DAGs there