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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 fe6848102429dc6a7788cc4635982cfc
arch x86_64
build h06a4308_0
depends airflow >=1.10.12,<1.10.13.0a0, python-jenkins >=1.0.0
license Apache 2.0
md5 fe6848102429dc6a7788cc4635982cfc
name airflow-with-jenkins
platform linux
sha1 fcd9848c242d747cb695cdbd2b90f7790239e8d4
sha256 cd3f85f2055033e9ef97eac071ab7969adbd79acf1dfa4c1765bacc92952c855
size 20284
subdir linux-64
timestamp 1605878140505
version 1.10.12