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Before we jump in with anything crazy, let's make some nodes with some vanilla data structures.

import node #

You will need to import node from kedro.pipeline to start creating nodes.








        

from kedro.pipeline import node

func #

The func is a callable that will take the inputs and create the outputs.

inputs / outputs #

Inputs and outputs can be None, a single catalog entry as a string, mutiple catalog entries as a List of strings, or a dictionary of strings where the key is the keyword argument of the func and the value is the catalog entry to use for that keyword.

our first node #

Sometimes in our pipelines our data is coming from an api where we already have python functions built to pull with. Thats ok, kedro supposrts that with inputs=None.








        

def create_range():
    return range(100)

make_range = node(
    func=create_range,
    inputs=None,
    outputs='range'
    )

second node #

Now we have some data to work from, lets use that as our input.








        

def square_range():
    return [i**2 for i in range]

square_range = node(
    func=square_range,
    inputs='range',
    outputs='range_squared'
    )

Multiple Inputs #

Kedro can take lists or dicts as either input or output when your function needs more than one input or output.








        

def concat(range, range_two):
    return [*range, *range_two]

concat_ranges = node(
    func=concat,
    inputs=['range', 'range_squared']
    outputs='concat'
    )

## inputs could also be defined as a dict
concat_ranges = node(
    func=concat,
    inputs={'range': 'range', 'range_two': 'range_squared'}
    outputs='concat'
    )

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