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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 20:41:46 2025
md5 checksum 56e47754b4ddc56ef440e83fa4b83372
arch x86_64
build h06a4308_0
depends airflow >=1.10.12,<1.10.13.0a0, python-hdfs >=0.5.1
license Apache 2.0
md5 56e47754b4ddc56ef440e83fa4b83372
name airflow-with-webhdfs
platform linux
sha1 53ffd726ac59c0249872ef36ba2f9358323de577
sha256 6c76e2574c1c187e0c4ec0c2f897f25f794fb50eb14e04f5b9d8a0d8c58a84ee
size 20298
subdir linux-64
timestamp 1605878160246
version 1.10.12