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        "description": "# airduct\nSimple Pipeline Scheduler in Python\n\n![Airduct Screenshot](docs/screenshot.png)\n\n## Links\n\n- [Github](https://github.com/alairock/airduct)\n- [Documentation](https://airduct.readthedocs.io)\n\n## Installing\n    $ pip install airduct\n\nor\n\n    $ poetry add airduct\n\n## Quickstart\n\nCreate a file and put into a folder/python-module.\n\n```python\nfrom airduct import schedule, task\n\n\nschedule(\n    name='ExampleFlow',\n    run_at='* * * * *',\n    flow=[\n        task('e1f1'),\n        [task('e1f2'), task('e1f3', can_fail=True)],\n        [task('e1f4')]\n    ]\n)\n\nasync def e1f1():\n    print('e1f1 - An async function!')\n\ndef e1f2():\n    print('e1f2 - Regular functions work too')\n\nasync def e1f3():\n    print('e1f3')\n\nasync def e1f4():\n    print('e1f4')\n```\n\nRun: `$ airduct schedule --path /path/to/folder`\n\nBy default it uses a sqlite in-memory database. If using the in-memory database, it will also automatically run as a worker, in addition to a scheduler. If you wish to use a non in-memory sqlite database, you will need to also run a worker (could be on same box, or separate) See the documentation for more info.\n\n",
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