#Embedded Python

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Embedded Python refers to the integration of the Python programming language into the InterSystems IRIS kernel, allowing developers to operate with data and develop business logic for server-side applications using Python.

Documentation.

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One objective of vectorization is to render unstructured text more machine-usable. Vector embeddings accomplish this by encoding the semantics of text as high-dimensional numeric vectors, which can be employed by advanced search algorithms (normally an approximate nearest neighbor algorithm like Hierarchical Navigable Small World). This not only improves our ability to interact with unstructured text programmatically but makes it searchable by context and by meaning beyond what is captured literally by keyword.

In this article I will walk through a simple vector search implementation that Kwabena Ayim-Aboagye and I fleshed out using embedded python in InterSystems IRIS for Health. I'll also dive a bit into how to use embedded python and dynamic SQL generally, and how to take advantage of vector search features offered natively through IRIS.

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Hi everyone,
I'm getting prepared to take the following certification exam: "InterSystems IRIS Development Professional".

Can you give some advice on how to prepare (aside from the official course page: https://www.intersystems.com/certifications/intersystems-iris-development-professional/ )?
Do you have examples of quiz questions that simulate the real exam or any material that helped you getting prepared?

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