Jupyter Notebook: Difference between dataiku.Dataset("XX") and get_dataset("XX")

Thomas_K

I have this code:

ds1 = dataiku.Dataset("T73RM067")

ds2 = dataiku.api_client().get_project("AIIMEINKAUF").get_dataset("T73RM067")

print(type(ds1))

print(type(ds2))

Which returns

<type 'instance'>

<class 'dataikuapi.dss.project.DSSProject'>

How do these differ? Is there any documentation about what I can do with those? If I change anything in them, will the changes be reflected onto the original dataset?

Clément_Stenac

The first variant only works within DSS and gives you a class of the Python internal API:
https://doc.dataiku.com/dss/latest/api/python/datasets.html#api-reference-the-dataset-class



The second variant can also be used outside of DSS, has much less features for reading and writing data, but is more geared towards interaction with settings, and is documented here:
https://doc.dataiku.com/dss/latest/api/public/client-python/reference.html#dataikuapi.dss.dataset.DSSDataset