We have this massive script that is super important to our day to day operations, and I'm looking to convert this into a prefect-cloud oriented setup so that I can connect it with a slack webhook and also have access to logs anywhere/everywhere. But I'm having trouble setting this up correctly, for a few reasons: 1. These tasks in the graph are inter-twined, meaning that a lot of these tasks are called within a "task" itself. Example:

def fnRunTask(parameter1,  parameter2, parameter3 .... parameter10):
    df1, df2 = fnRunSubTask(parameter3, parameter5)
    dfTmp = fnRunSubTask2(df1, parameter1, parameter7, parameter9)

2. As shown above, each subfunction requires different parameters, and the number of parameters for each function can vary. Essentially this is all headache from converting a bunch of stuff that was defined under "if name == _main_:" into a prefect setup. I've played around with passing in one large dictionary at the start, but wanted to ask here before I continued debugging that (didn't work on tries #1-20 lol) Also wanted to ask about the task interconnectivity, as I was a bit confused about upstream/downstream tasks since some of them are "at the same time" within the task that calls them.

Hey @Joseph Loss! What error do you see when you pass a large dictionary? This person seemed to pass in a gigantic one. A bit unclear about interconnectivity, is there a problem with the DAG that was setup? Should

print_df

not be hooked up by multiple upstream tasks? This looks messy, but I think this can work.

let me grab a few snips of the functions, that will help explain I think

This is massive man…wow! Yes you can leave constant inputs alone. They will work. That will probably make you life a lot easier cuz you’ll need to pass in less

sorry for the delayed response, yes this is working perfectly dude thank you so much for the advice!

No worries at all about the delayed response! Good you’re making progress.