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org/pypi/apache-airflow (Run pip install apache-airflow)
Changelog - https://github
from the top result below
https://airflow.apache.org/announcements/
org/project/apache-airflow-ctl/
đź“š Docs: https://airflow
https://airflow.apache.org/blog/airflow-1.10.10/
You can pull them from the Apache Airflow Dockerhub repository and start using it
https://airflow.apache.org/docs/docker-stack/index.html
Y - the versioned Airflow image with specific Python version
The Apache Airflow image provided as convenience package is optimized for size, and it provides just a bare minimal set of the extras and dependencies installed and in most cases you want to either extend or customize the image
https://airflow.apache.org/blog/airflow-2.6.0/
I am excited to announce that Apache Airflow 2
https://airflow.apache.org/blog/airflow-2.8.0/
Contributors
Thanks to everyone who contributed to this release, including Amogh Desai, Andrey Anshin, Bolke de Bruin, Daniel DylÄ…g, Daniel Standish, Ephraim Anierobi, Hussein Awala, Jarek Potiuk, Jed Cunningham, Jens Scheffler, mhenc, Miroslav Ĺ edivĂ˝, Pankaj Koti, Tzu-ping Chung, Vincent, and everyone else who
https://airflow.apache.org/blog/airflow-2.7.0/
It has been implemented by moving the openlineage-airflow package from the OpenLineage project to an apache-airflow-providers-openlineage provider in the base Airflow Docker image, where it can be easily enabled by configuration
https://airflow.apache.org/docs/apache-airflow-providers/index.html
com/apache/airflow/blob/main/providers/MANAGING_PROVIDERS_LIFECYCLE
https://airflow.apache.org/blog/airflow-2.9.0/
I’m happy to announce that Apache Airflow 2
https://airflow.apache.org/docs/apache-airflow-providers-apache-tinkerpop/stable/index.html
Apache TinkerPop is a graph computing framework for both graph databases (OLTP) and graph analytic systems (OLAP) and Gremlin is its graph traversal language
https://airflow.apache.org/docs/apache-airflow-providers-apache-druid/stable/index.html
Installation¶
You can install this package on top of an existing Airflow installation via pip install apache-airflow-providers-apache-druid
https://airflow.apache.org/docs/apache-airflow-providers-apache-impala/stable/index.html
Installation¶
You can install this package on top of an existing Airflow installation via pip install apache-airflow-providers-apache-impala
https://airflow.apache.org/blog/airflow-2.10.0/
I’m happy to announce that Apache Airflow 2
https://airflow.apache.org/docs/apache-airflow-providers-apache-livy/stable/index.html
Installation¶
You can install this package on top of an existing Airflow installation via pip install apache-airflow-providers-apache-livy
https://airflow.apache.org/docs/apache-airflow-providers-apache-hive/stable/index.html
Installation¶
You can install this package on top of an existing Airflow installation via pip install apache-airflow-providers-apache-hive
https://airflow.apache.org/docs/apache-airflow-providers-apache-kylin/stable/index.html
Installation¶
You can install this package on top of an existing Airflow installation via pip install apache-airflow-providers-apache-kylin
https://airflow.apache.org/docs/apache-airflow-providers-apache-pinot/stable/index.html
Installation¶
You can install this package on top of an existing Airflow installation via pip install apache-airflow-providers-apache-pinot
https://airflow.apache.org/docs/apache-airflow-providers-apache-pig/stable/index.html
Installation¶
You can install this package on top of an existing Airflow installation via pip install apache-airflow-providers-apache-pig
https://airflow.apache.org/docs/apache-airflow-providers-apache-kafka/stable/index.html
Installation¶
You can install this package on top of an existing Airflow installation via pip install apache-airflow-providers-apache-kafka
https://airflow.apache.org/docs/apache-airflow-providers-apache-flink/stable/index.html
Installation¶
You can install this package on top of an existing Airflow installation via pip install apache-airflow-providers-apache-flink
https://airflow.apache.org/docs/apache-airflow-providers-apache-drill/stable/index.html
Installation¶
You can install this package on top of an existing Airflow installation via pip install apache-airflow-providers-apache-drill
https://airflow.apache.org/docs/apache-airflow-providers-apache-spark/stable/index.html
Installation¶
You can install this package on top of an existing Airflow installation via pip install apache-airflow-providers-apache-spark
https://airflow.apache.org/docs/apache-airflow-providers-apache-hdfs/stable/index.html
Installation¶
You can install this package on top of an existing Airflow installation via pip install apache-airflow-providers-apache-hdfs
https://airflow.apache.org/docs/apache-airflow-providers-apache-iceberg/stable/index.html
Installation¶
You can install this package on top of an existing Airflow installation via pip install apache-airflow-providers-apache-iceberg
https://airflow.apache.org/docs/apache-airflow-providers-apache-cassandra/stable/index.html
Installation¶
You can install this package on top of an existing Airflow installation via pip install apache-airflow-providers-apache-cassandra
https://airflow.apache.org/docs/apache-airflow-providers-apache-beam/stable/index.html
Installation¶
You can install this package on top of an existing Airflow installation via pip install apache-airflow-providers-apache-beam
https://airflow.apache.org/docs/apache-airflow-providers-amazon/stable/index.html
Installation¶
You can install this package on top of an existing Airflow installation via pip install apache-airflow-providers-amazon
https://airflow.apache.org/docs/apache-airflow-providers-akeyless/stable/index.html
Installation¶
You can install this package on top of an existing Airflow installation via pip install apache-airflow-providers-akeyless
https://airflow.apache.org/blog/airflow-3.1.0/
com/api/v2/dags/{dag_id}/dagRuns")
run_id = r
https://airflow.apache.org/blog/airflow-3.2.0/
We’re proud to announce the release of Apache Airflow 3
https://airflow.apache.org/blog/airflow-2.5.0/
Usability improvements to the Datasets UI
When we released Dataset aware scheduling in September we knew that the tools we gave to manage the Datasets were very much a Minimum Viable Product, and in the last two months the committers and contributors have been hard at work at making the UI much more usable when it