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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 20:40:54 2025
md5 checksum 5bdd89f72bb61e798bb1bdc3a5011f09
arch x86_64
build py310h06a4308_1
build_number 1
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 5bdd89f72bb61e798bb1bdc3a5011f09
name airflow-with-google_auth
platform linux
sha1 fadfb677f1a7c1838a087103c60d79ad2422f1fa
sha256 0e15efa14d1d8e798176832f879472dfcea669a5f47e234075be55ed3d6df6a8
size 12925
subdir linux-64
timestamp 1659935007815
version 2.3.3