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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 20:40:45 2025
md5 checksum 0183aa7d5039148c888e935c5cfac045
arch x86_64
build py310h06a4308_0
depends airflow >=2.3.3,<2.3.4.0a0, python >=3.10,<3.11.0a0, requests >=2.26.0
license Apache-2.0
md5 0183aa7d5039148c888e935c5cfac045
name airflow-with-deprecated-api
platform linux
sha1 21e137fb60b283ab767fcfcdf4e8f76e322250ae
sha256 6eec2fa3cc0b748f0395d9e8982f842424224558eed9945c7f8f9ebc96c1620e
size 12903
subdir linux-64
timestamp 1659884024307
version 2.3.3