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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 20:40:53 2025
md5 checksum 13c1aab5054f4140243ec9d3f7bf30f3
arch x86_64
build py310h06a4308_0
depends airflow >=2.4.3,<2.4.4.0a0, authlib >=0.14,<1.0.0, flask-appbuilder, python >=3.10,<3.11.0a0
license Apache-2.0
license_family Apache
md5 13c1aab5054f4140243ec9d3f7bf30f3
name airflow-with-google_auth
platform linux
sha1 e50aadc490793abd9db60bae76cd11c0f8f740b5
sha256 a441759a715ca38981da1314a18c18c330d7e8f281aa2768817c89fba46fdc0e
size 13562
subdir linux-64
timestamp 1671227196463
version 2.4.3