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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 20:41:10 2025
md5 checksum 7eafa8d867583352d96c6fd1883e6fa3
arch x86_64
build h06a4308_0
depends airflow >=1.10.12,<1.10.13.0a0, pymssql >=2.1.1,<2.2.0
license Apache 2.0
md5 7eafa8d867583352d96c6fd1883e6fa3
name airflow-with-mssql
platform linux
sha1 cdfb89256d48c20e1f81718c5365e3ac6ebf5404
sha256 bf7eb2db132085cf9bbfc89f17e0aa44e064f629f832793bd07672d8d081e766
size 20279
subdir linux-64
timestamp 1605878145614
version 1.10.12