datajoely
02/23/2022, 7:11 PMpypeaday
02/23/2022, 7:12 PMpypeaday
02/23/2022, 7:13 PMwaylonwalker
02/23/2022, 7:31 PMamos
02/23/2022, 9:45 PMamos
02/23/2022, 9:46 PMdatajoely
02/24/2022, 9:34 AMpython
from some_package import kedro_pipeline
from kedro.io import DataCatalog
from kedro.runner import SequentialRunner
catalog = DataCatalog(data_sets=datasets, feed_dict={"params:split_args": params})
output = runner.run(pipe, catalog)
datajoely
02/24/2022, 9:35 AMmicropackaging
is what you you are looking for
https://kedro.readthedocs.io/en/latest/06_nodes_and_pipelines/04_micro_packaging.htmldeepyaman
02/24/2022, 12:26 PMdatajoely
02/24/2022, 12:27 PMavan-sh
02/24/2022, 1:01 PMantony.milne
02/24/2022, 1:51 PMantony.milne
02/24/2022, 2:05 PMkedro package
on your project (let's say its Python package name is xyz
) then you can actually do this:
from xyz import __main__
__main__.main()
which will be equivalent to python -m xyz
. This does seem a little ugly though. IIRC @User wrote the stuff on __main__
not so long ago so might know a better way of doing this (or if there isn't one then maybe we should expose the main
function so I can do from xyz import main
directly)williamc
02/24/2022, 4:38 PMdatajoely
02/24/2022, 4:41 PMafter_pipeline_run
hook might be bestwilliamc
02/24/2022, 4:42 PMamos
02/24/2022, 5:14 PMdatajoely
02/24/2022, 5:19 PMamos
02/24/2022, 5:21 PMdatajoely
02/24/2022, 5:22 PMamos
02/24/2022, 5:25 PMamos
02/24/2022, 6:08 PMdatajoely
02/24/2022, 6:09 PMdatajoely
02/24/2022, 6:09 PMkedro run --params param_key1:value1,param_key2:2.0
datajoely
02/24/2022, 6:10 PMamos
02/24/2022, 6:10 PMdatajoely
02/24/2022, 6:11 PMamos
02/24/2022, 6:11 PMdatajoely
02/24/2022, 6:11 PMdatajoely
02/24/2022, 6:11 PM