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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 8eafaadd74cc74dd605f3c2239f36ae7
arch x86_64
build py310h06a4308_0
depends airflow >=2.3.3,<2.3.4.0a0, authlib >=0.14,<1.0.0, flask-appbuilder, python >=3.10,<3.11.0a0
license Apache-2.0
md5 8eafaadd74cc74dd605f3c2239f36ae7
name airflow-with-google_auth
platform linux
sha1 2b789ceff3fc5c75f67bca1b7f642f57a41cb397
sha256 d995db73ead858f082d30faaeb94d23508a7eba4b14a25976dcbda9ca6d8e440
size 12917
subdir linux-64
timestamp 1659884068631
version 2.3.3