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