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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 7ed22f7d5e86645bda52876633d9d802
arch x86_64
build h06a4308_0
depends airflow >=1.10.12,<1.10.13.0a0, requests >=2.20.0,<3
license Apache 2.0
md5 7ed22f7d5e86645bda52876633d9d802
name airflow-with-databricks
platform linux
sha1 1733365af8a7eaf5d6025943458a58b44b696343
sha256 be5a6bf87c3a64f2920e05d165b8141624c1689211596dc5c4cb86e374fabceb
size 20299
subdir linux-64
timestamp 1605878132239
version 1.10.12