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Use airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command line utilities make performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress, and troubleshoot issues when needed. When workflows are defined as code, they become more maintainable, versionable, testable, and collaborative.

Uploaded Mon Mar 31 20:40:58 2025
md5 checksum d943d88eafd1776d6f0375dbf8da75b0
arch x86_64
build 0
depends airflow >=1.10.7,<1.10.8.0a0, python-jenkins >=1.0.0
license Apache 2.0
md5 d943d88eafd1776d6f0375dbf8da75b0
name airflow-with-jenkins
platform linux
sha1 c83a15b610392da52752d8d28ba6747c8c9b2e59
sha256 24b858c4805075e8a3d2ddf3319885a8e1815c9b95039fe429ee88ff3fae228c
size 18498
subdir linux-64
timestamp 1579721403292
version 1.10.7