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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 20:41:28 2025
md5 checksum 7388cbb7dc103424cfc65862e152eaa8
arch x86_64
build h06a4308_0
depends airflow >=1.10.12,<1.10.13.0a0, redis-py >=3.2.0
license Apache 2.0
md5 7388cbb7dc103424cfc65862e152eaa8
name airflow-with-redis
platform linux
sha1 a6eb4241f5b453aed0c073aee1ebe0030de27f21
sha256 d74d7dc6bb10994dd641d03a96714af40c57a78f9e90ed5101278857d1d65965
size 20288
subdir linux-64
timestamp 1605878151857
version 1.10.12