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YellowDog Provider for Apache Airflow

The YellowDog Provider for Apache Airflow provides:

  • A Hook to support YellowDog Application credentials as Airflow Connections
  • Operator classes to create and manage YellowDog Work Requirements and Worker Pools
  • Sensor classes to monitor the states of YellowDog Work Requirements and Worker Pools

Documentation

The main documentation is found at: https://docs.yellowdog.ai/airflow-provider/index.html

Requirements

Requires Apache Airflow v2.10.0 or later, Python 3.10 or later, and the YellowDog SDK.

Installation

Install from PyPI as package yellowdog-airflow-provider, e.g.:

pip install -U yellowdog-airflow-provider

Usage

Please see the documentation at https://docs.yellowdog.ai/airflow-provider/index.html.

Testing and Experimentation

Starting a Local Airflow Instance

The script start-airflow-container.sh will start a local container running Airflow, including installing the YellowDog Airflow provider and creating YellowDog Connections.

Run this script from the top-level repo. directory, i.e.:

bin/start-airflow-command.sh

Please inspect the script for instructions on its customisation and use.

Running an Example DAG

There's an example DAG that exercises all the YellowDog Provider components at yd-provider-test.py. The DAG's directory is automatically loaded by the Airflow container above.

Inspect/update the variables at beginning of the DAG module to customise the DAG for your environment.

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