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Not yet. Where are you looking to use this? As documentation? or?

yes, basically for documentation

yep makes sense — this change might require a bit of surgery on the viz side to be able to “group nodes” since it takes the Hamilton graph verbatim…

I see

🤔 actually yeah that might be the easier way about it.

So yes, what @Stefan Krawczyk said. Some thoguhts I had typed out then ended up in a call. There are a few workarounds, and its a good idea (open an issue)? Basically you have a few approaches: 1. removing check_output conditionally (assign check_output in fucntion_modifiers to be a lambda/pass-through when importing — its a hack but it could get you the graph) 2. mess with the function graph itself — this is an internal API but you could remove nodes — downside is the internal state might not be the best 3. edit the

.dot

file to remove any edges/dependencies you want The trick here is to know that the tags on the variables will indicate whether its a data quality node — you should be able to use these to handle it: https://github.com/DAGWorks-Inc/hamilton/blob/6dd192854b082d7f697f2bb9607250e64e181ae3/data_quality.md?plain=1#L142

yeah I think we just need to short-circuit here https://github.com/DAGWorks-Inc/hamilton/blob/main/hamilton/function_modifiers/validation.py#L25-L29 based on some configuration that is passed in somehow — @Michal Siedlaczek you could at least locally just make this return the input node, and I think it should create things without the validator nodes.

If you wanted a quick hack and you’re running it all in a script you could do something like:

from hamilton import function_modifiers
function_modifiers.check_output = lambda x: x

If you do that before any imports it might just disable them, and do that conditionally

interesting, I'll try that

(no guarentees, and definitely not the right long-term solution, but could unblock you 🙂 )

ok, the simplest one-off solution was to go to module and run

:g/@check_output/d

in vim 😂

Love it

I'm sorted for now