Skip to main content

Auto-generated Diagrams from Airflow DAGs.

Project description

airflow-diagrams

pre-commit.ci status test workflow codeql-analysis workflow codecov PyPI version License PyPI - Python Version PyPI version

Auto-generated Diagrams from Airflow DAGs. 🔮 🪄

This project aims to easily visualise your Airflow DAGs on service level from providers like AWS, GCP, Azure, etc. via diagrams.

demo

Before After
dag diagram

🚀 Get started

To install it from PyPI run:

pip install airflow-diagrams

NOTE: Make sure you have Graphviz installed.

Then just call it like this:

usage

Examples of generated diagrams can be found in the examples directory.

🤔 How it Works

  1. ℹ️ It connects, by using the official Apache Airflow Python Client, to your Airflow installation to retrieve all DAGs (in case you don't specify any dag_id) and all Tasks for the DAG(s).
  2. 🪄 It processes every DAG and its Tasks and 🔮 tries to find a diagram node for every DAGs task, by using Fuzzy String Matching, that matches the most. If you are unhappy about the match you can also provide a mapping.yml file to statically map from Airflow task to diagram node.
  3. 🎨 It renders the results into a python file which can then be executed to retrieve the rendered diagram. 🎉

❤️ Contributing

Contributions are very welcome. Please go ahead and raise an issue if you have one or open a PR. Thank you.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

airflow-diagrams-2.1.0.tar.gz (14.8 kB view hashes)

Uploaded Source

Built Distribution

airflow_diagrams-2.1.0-py3-none-any.whl (16.3 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page