Hi team, Iooking for some assistance with the python SDK; • I'm trying to use the SDK to to generate an LDM via the

load_and_put_declarative_ldm method

• I would like to validate the LDM before pushing it up to my workspace - what is the recommended way to do this via the python SDK? I can see that there's a validate_ldm() method but the usage is unclear Thanks!

Hi Anant, I can confirm that this method validates that data source IDs specified in LDM actually exist in GoodData. Would this be helpful for your sue-case or are you looking for a different type of validation, please?

Hello Anant, We are following up on Ivana's response regarding your query about validating the LDM using the Python SDK's

validate_ldm()

method. Please provide us with any additional details regarding your validation needs.

Hi @Mauricio Cabezas - thanks for following up! I understand that the validate_ldm() method checks to see if data source IDs actually exist, but I'm trying to figure out if I can perform other forms of validation as well, e.g. is the structure of the JSON/YAML correct, are relationships between models set up correctly, do tables/fields referenced actually exist, etc. Ideally, I would like to fully validate an LDM before PUT-ing it in a workspace (right now, even if the PUT is successful, there may be other issues which only visible in the GoodData UI)

Hi Anant, this is not something that is currently possible as you have mentioned the UI catches any of the other layout errors. We can certainly mark this down for product feedback on your behalf.

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