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Simple Pipeline Scheduler in Python

Project description

airduct

Simple Pipeline Scheduler in Python

Airduct Screenshot

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Installing

$ pip install airduct

or

$ poetry add airduct

Quickstart

Create a file and put into a folder/python-module.

from airduct import schedule, task


schedule(
    name='ExampleFlow',
    run_at='* * * * *',
    flow=[
        task('e1f1'),
        [task('e1f2'), task('e1f3', can_fail=True)],
        [task('e1f4')]
    ]
)

async def e1f1():
    print('e1f1 - An async function!')

def e1f2():
    print('e1f2 - Regular functions work too')

async def e1f3():
    print('e1f3')

async def e1f4():
    print('e1f4')

Run: $ airduct schedule --path /path/to/folder

By 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.

Project details


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airduct-0.1.22.tar.gz (9.1 kB view hashes)

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