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architectSAP
Active Contributor
When accessing a file from the SAP Data Intelligence Jupyter Lab, code leveraging the SAP Data Intelligence Machine Learning Python SDK is generated:


To use this SDK in a custom SAP Data Intelligence Operator, I add the sapdi Tag:


Which draws the com.sap.dsp.linuxx86_64/dsp-core-operators-docker Docker File:


That allows me to use the same code to access my file as from the Jupyter Lab and I output its head respectively:


Putting my Custom Operator in a simple Data Pipeline:


I get the expected result in my Wiretap:


Of course, this is only a simple example and the Python SDK provides a lot more functionality around:

  • Create and access ML scenarios and their versions, as well as to retrieve and update metadata

  • Create configurations, and start executions and deployments

  • Create and update pipelines and bind them to ML scenarios

  • Access artifacts from training containers

  • Report metrics through the ML Tracking SDK

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