Hello, I was exploring the following code example: https://developer.dataiku.com/latest/tutorials/data-engineering/sql-in-code/index.html#code-recipe-examples But I got an error from the exec_recipe_fragment method (attached below). I tried both options of the overwrite_output_schema parameter but did not succeed. Any help…
Has anyone got any best practices they can recommend for development, testing and deploying real-time API services? At the moment we have considered documenting and testing under load. Does the community know of anything else we can add?
Hi team, I currently have a dataset that connects to an online sharepoint, with the scenario function it is now autorefreshed weekly. I would like to build a new dataset to append all the versions to compare the changes/ evolution. Could you help with some guidance? many thanks
Inside an Application, I define an "Edit project Variables" section, followed by my variable definitions: an "INT" and a "STRING". =========== [ { "name": "welcome", "label": "on", "defaultValue": "5.2 is my game", "mandatory": true, "canSelectForeign": false, "markCreatedAsBuilt": false, "allowDuplicates": true,…
For example, I can find the function train_model(model_id, project_key=None, build_mode='RECURSIVE_BUILD', step_name=None, async=False, fail_fatal=True) But how could I know what kind of object this function returns, and how can I use with that returned value? From the sample code, I found function…
can we use evaluation store output for further processing using python recipe.
I'm using a connection to my ElasticSearch cluster to write some of my datasets into index. If I use the default mapping , the types of the schema are well mapped (date into date, string into text, integer into long, boolean) but text have not keyword subfield. I know I can generate for ext field the keyword subfield by…
How to call the dataset in Python function from API designer? im using Python function, and in the function, I'm using below function: def testing_example(parameter1): dataset = dataiku.Dataset("datasetname",project_key="project_id") df = dataset.get_dataframe() But it fails. Any idea how to solve this?
Hi there, I'm currently using Dataiku to train a model for a prediction task. I need to impose directionality constraints on certain columns, but the current version of xgboost in Dataiku doesn't support these kinds of constraints. I've learned that we can write custom Python models with monotonic constraints as detailed…
My recipe failed to resolve a pip package I installed on code env. The same code runs well on Notebook area but failed on recipe using the same code env. I suspect the recipe uses old version of the code env but I have no way of forcing it to use the latest code env build. How? Operating system used: Windows Operating…
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