Auto-generated Diagrams from Airflow DAGs.
Project description
airflow-diagrams
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.
Before | After |
---|---|
🚀 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:
Examples of generated diagrams can be found in the examples directory.
🤔 How it Works
- 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). - 🪄 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. - 🎨 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
Release history Release notifications | RSS feed
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-2.0.0.tar.gz
(15.0 kB
view hashes)
Built Distribution
Close
Hashes for airflow_diagrams-2.0.0-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 2010867f20c9ab473aa5e163607d63c12bd710d5f30af0d014157fb22ed90e34 |
|
MD5 | a737f1248f6b043819c7944ebbabab2a |
|
BLAKE2b-256 | 4d0bc274046c3a199abb012545080eff046cb133a71b42ad67be2079ac965777 |