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Any example on how to use DSSFilterBuilder ?

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gnaldi62
Neuron
Neuron
Any example on how to use DSSFilterBuilder ?

Hi all, 
  we'd need to automatically change the dates related to the split between train and test of a visual ML model.
  So far we've been able to get the raw details of the split via code similar to the following:

...
client = dataiku.api_client()
current_project = client.get_default_project()
my_model = current_project.get_ml_task('myAnalysisID', 'myTaskId')
split_params = my_model.get_settings().get_split_params().get_raw()

We then would need to change the values of a couple of dates in order to reflect a new split, but we are stuck here.
It seems we would need to use the class dataikuapi.dss.utils.DSSFilterBuilder, but we cannot find anywhere a reference on how to initialize nor to use it. Any ideas/suggestions ?
Thanks for your help. Best Regards.

Giuseppe

P.S.: we would like to keep the visual analysis rather than translating everything into a Python recipe.

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1 Solution
Clément_Stenac
Dataiker
Dataiker

Hi,

For updating an existing filter, it's easier, you can access the current definition of the filter in:

 

split_params.get_raw()["efsdTrain"]["filter"]["uiData"]

 

Ditto for "efsdTest".

"efsdTrain/efsdTest" are used for "Explicit Filter Single Dataset". If you are using "Explicit Filter Two Datasets", you need to use "eftdTrain" and "eftdTest"

For example, a "Pclass contains 1" filter translates to this value for uiData:

 

{
  "mode": "&&",
  "conditions": [
    {
      "input": "Pclass",
      "operator": "contains",
      "string": "1"
    }
  ]
}

 

 

So switching that to "2" would be:

 

settings = mltask.get_settings()
split_params = settings.get_split_params()

split_params.get_raw()["efsdTrain"]["filter"]["uiData"]["conditions"][0]["string"] = "2"

settings.save()

 

 

Hope this helps

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2 Replies
Clément_Stenac
Dataiker
Dataiker

Hi,

For updating an existing filter, it's easier, you can access the current definition of the filter in:

 

split_params.get_raw()["efsdTrain"]["filter"]["uiData"]

 

Ditto for "efsdTest".

"efsdTrain/efsdTest" are used for "Explicit Filter Single Dataset". If you are using "Explicit Filter Two Datasets", you need to use "eftdTrain" and "eftdTest"

For example, a "Pclass contains 1" filter translates to this value for uiData:

 

{
  "mode": "&&",
  "conditions": [
    {
      "input": "Pclass",
      "operator": "contains",
      "string": "1"
    }
  ]
}

 

 

So switching that to "2" would be:

 

settings = mltask.get_settings()
split_params = settings.get_split_params()

split_params.get_raw()["efsdTrain"]["filter"]["uiData"]["conditions"][0]["string"] = "2"

settings.save()

 

 

Hope this helps

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gnaldi62
Neuron
Neuron
Author

Hi Clémemt,
thanks for the quick reply. Best Regards.

Giuseppe

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