This means that pip install apache-airflow will not work from time to time or will Our dependencies as open as possible (in setup.py) so users can install different versions of libraries Libraries usually keep their dependencies open, andĪpplications usually pin them, but we should do neither and both simultaneously. Installing it however might be sometimes trickyīecause Airflow is a bit of both a library and application. We publish Apache Airflow as apache-airflow package in PyPI. Note: If you're looking for documentation for the main branch (latest development branch): you can find it on s./airflow-docs.įor more information on Airflow Improvement Proposals (AIPs), visitĭocumentation for dependent projects like provider packages, Docker image, Helm Chart, you'll find it in the documentation index. Visit the official Airflow website documentation (latest stable release) for help with Is used in the Community managed DockerHub image is The only distro that is used in our CI tests and that You should only use Linux-based distros as "Production" execution environmentĪs this is the only environment that is supported. The work to add Windows support is tracked via #10388, but On Windows you can run it via WSL2 (Windows Subsystem for Linux 2) or via Linux Containers. Tested on fairly modern Linux Distros and recent versions of macOS. Note: Airflow currently can be run on POSIX-compliant Operating Systems. Using the latest stable version of SQLite for local development. Running multiple schedulers - please see the Scheduler docs. Note: MySQL 5.x versions are unable to or have limitations with ** Discontinued soon, not recommended for the new installation The rich user interface makes it easy to visualize pipelines running in production, monitor progress, and troubleshoot issues when needed. Rich command line utilities make performing complex surgeries on DAGs a snap. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. When workflows are defined as code, they become more maintainable, versionable, testable, and collaborative. Apache Airflow (or simply Airflow) is a platform to programmatically author, schedule, and monitor workflows.
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