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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 20:40:42 2025
md5 checksum d5cb2523e596ad34e6c80987d401c0a1
arch x86_64
build 0
depends airflow >=1.10.7,<1.10.8.0a0, requests >=2.20.0,<3
license Apache 2.0
md5 d5cb2523e596ad34e6c80987d401c0a1
name airflow-with-databricks
platform linux
sha1 7f48224bfcf02766c92aa0c1655abd2e33524340
sha256 90580bcf033fc0c699c2f7286478a6d64a00e23386ff84f801bf24f89415ec10
size 18516
subdir linux-64
timestamp 1579721389323
version 1.10.7