778216384475693066 #beginners-need-help

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advanced-need-help

job-posting

welcome

ende

12/10/2021, 11:26 PM

Is it conceivable to have multiple sets of dependencies (in the form of say different virtual environments even) within a single kedro project? Or is that so ridiculous I should just purge the silly thought from my head? 😛

datajoely

12/11/2021, 5:45 PM

So it is possible for source code, but not for execution. Do we do support requirements.txt living within a particular modular pipeline folder for pull/push packaging

datajoely

12/11/2021, 5:46 PM

But it is an advanced pattern and I’d only suggest you do it if there are no other options

Rroger

12/13/2021, 10:15 PM

I have a node a that just executes sql. Where would be the best place to store the script? In parameters?

j c h a r l e s

12/13/2021, 10:34 PM

Random follow up question - is it possible or common that a data source is a SQL table?

j c h a r l e s

12/13/2021, 10:43 PM

I'm trying to find an example of how to use credentials for a kedro project. Where is the recommended place to initialize something like an api client for pipelines?

Copy code

from kedro.config import ConfigLoader, MissingConfigException

conf_paths = ["conf/base", "conf/local"]
conf_loader = ConfigLoader(conf_paths)

try:
    credentials = conf_loader.get("credentials*", "credentials*/**")
except MissingConfigException:
    credentials = {}

j c h a r l e s

12/13/2021, 10:43 PM

Do I initialize this in a node? in a pipeline? In a utility library file somewhere? It seems like I can run this code... anywhere? Curious what this group recommends

j c h a r l e s

12/13/2021, 10:47 PM

Generally, do you have each node initialize things like api clients? Or do you create context objects which store these types of things, and pass them through to each node?

j c h a r l e s

12/13/2021, 11:42 PM

I ended up using the following for the ConfigLoader to run as expected

Copy code

conf_loader = ConfigLoader("conf", "local")
credentials = conf_loader.get("credentials*", "credentials*/**")

. Also am calling this directly from a helper function within a specific node for now

j c h a r l e s

12/13/2021, 11:48 PM

Another question - is there any concept of appending output data as a run continues. I have a node that iterates over a large amount of data (list of entities in a

raw

dataset. For each entity, it takes between 15 minutes and 1 hour to process that specific entity. I have a node that is looping over each entity, processing that entity, and then merging all of these entities together. What's the best way to split up this node so that I can process each user as its own node? The number of desired nodes would be one node per entity in the original dataset.

Rroger

12/14/2021, 12:09 AM

As suggested in https://discord.com/channels/778216384475693066/846330075535769601/914271328037658635, you can create a loop to create many nodes.

j c h a r l e s

12/14/2021, 12:13 AM

So it's possible to use a data set as an initial input, and then create nodes dynamically based on the contents of the dataframe?

j c h a r l e s

12/14/2021, 12:14 AM

I can have a node that outputs a list of nodes as a result? e.g.

j c h a r l e s

12/14/2021, 12:16 AM

I think I'm a bit confused at how to do this... I assumed any output for a computation on a dataset would be another dataset and couldnt really be a list of nodes?

j c h a r l e s

12/14/2021, 12:18 AM

Copy code

def create_pipeline(**kwargs):
    build_list_of_entity_nodes = node(
        func=generate_nodes_from_entities,
        inputs="entities_csv",
        outputs="list_of_entity_nodes"
    )
    ## 
    #  How do I run my_expensive_entity_function across this list of nodes,
    #  which is determined through the contents of entities_csv
    return Pipeline([build_list_of_entity_nodes])

Rroger

12/14/2021, 12:44 AM

This is what I have in mind, there could be a better way. Rather than outputting a list of nodes, I think you need to first create the list of nodes then pass that list into the Pipeline object. Each node in the list would have a specific entity as input, which means you’d also have you split the csv yourself into separate entities.

j c h a r l e s

12/14/2021, 12:58 AM

Seems like this pattern is discouraged in the two places I’ve found so far online: https://stackoverflow.com/questions/68253274/kedro-create-a-dynamic-node and

j c h a r l e s

12/14/2021, 12:59 AM

Although Jinja2 is a very powerful and extremely flexible template engine, which comes with a wide range of features, we do not recommend using it to template your configuration unless absolutely necessary. The flexibility of dynamic configuration comes at a cost of significantly reduced readability and much higher maintenance overhead. We believe that, for the majority of analytics projects, dynamically compiled configuration does more harm than good.

j c h a r l e s

12/14/2021, 1:07 AM

It seems like there should be some way of outputting a partitioned dataset?

Rroger

12/14/2021, 2:00 AM

If a node doesn’t have an output, can this node be made into a dependency of another node? Eg

node1

executes a sql script in a db producing

table1

, then

node2

executes another sql script on

table1

datajoely

12/14/2021, 10:13 AM

Hi @User and @User we have some updates in 0.17.6: - We have updated

pandas.QueryDataSet

to so that it takes a reference to a SQL file - We have introduced

spark.DeltaTableDataSet

and some tutorials on how to do 'out of dag operations' which may translate here: https://kedro.readthedocs.io/en/latest/11_tools_integration/01_pyspark.html#spark-and-delta-lake-interaction

datajoely

12/14/2021, 10:14 AM

I'm not sure if all of your questions are answered and perhaps we can split them into different threads we can talk about them in detail

12/14/2021, 2:51 PM

Is there a way for a node to output a parameter that can be used by a subsequent node?

datajoely

12/14/2021, 2:52 PM

Could you just return the parameter as an output and re-use it in the next node?

datajoely

12/14/2021, 2:53 PM

you don't need to declare it in the catalog, but you need to use the same key name in the pipeline definition

12/14/2021, 2:54 PM

Right, that’s how I’ve been doing it so far. Just was wondering if there is a way to make it explicitly a parameter and referred to later as ‘params:xxx’.

datajoely

12/14/2021, 2:56 PM

So we err on the side of explicit rather than implicit so we reserve that type of thing for the human input parts. What you could do is declare a

YAMLDataSet

for the parameters you generate at runtime for safe keeping, then either an automatic or manual process outside of Kedro could mirror those in you actual

paramerters.yml

12/14/2021, 2:58 PM

Ahh, great idea, thank you! 😀

datajoely

12/14/2021, 2:58 PM

Yeah the balance between readability and dynamism is super hard to find

datajoely

12/14/2021, 2:58 PM

but I think that works okay