Dynamic Entities (objects and arrays) in IRIS are incredibly useful in situations where you are having to transform JSON data into an Object Model for storage to the database, such as in REST API endpoints hosted within IRIS. This is because these dynamic objects and arrays can easily serve as a point of conversion from one data structure to the other.

With the advent of Embedded Python, a myriad of use cases are now possible from within IRIS directly using Python libraries for more complex operations. One such operation is the use of natural language processing tools such as textual similarity comparison.

Setting up Embedded Python to Use the Sentence Transformers Library

Note: For this article, I will be using a Linux system with IRIS installed.

Has anyone come across a good using Embedded Python to convert a Python List object to an IRIS %List object?

My use case is I want to open an SQL entry with an Objectscript class method, then pass some information from that row into a separate Python class method which will then create a Python List object, then have the Python class method return that list back to the Objectscript class method in such a way that the Python List can be converted to an IRIS %List object for me to then use in the Objectscript code.

Our company is in the process of converting our software for use in Intersystems IRIS and one of the major sections of the software makes use of a custom statically-linked C library using the $ZF("function-name") functionality. During this, I found out that the process for setting up the C library to be used within the database platform has changed significantly between Cache and IRIS.

Is it possible using MS Excel VBA to execute and retrieve data from a Cache custom class query? If so, how?