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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 20:40:47 2025
md5 checksum e3674a191a3b0c9468b417c49f0fe69c
arch x86_64
build h06a4308_0
depends airflow >=1.10.12,<1.10.13.0a0, pydruid >=0.4.1,<=0.5.8
license Apache 2.0
md5 e3674a191a3b0c9468b417c49f0fe69c
name airflow-with-druid
platform linux
sha1 324a89cf1aef05b27eda84bbe080f9c3627de64a
sha256 f61d8366c87f1546722a8a98a13a23bac7ff505f8341485fa6fbefdade0c2909
size 20287
subdir linux-64
timestamp 1605878135342
version 1.10.12