JSON is a lightweight data interchange format for representing and exchanging data between a server and a web application. Its popularity has led to its widespread use in applications based on InterSystems technology, as well as demand for a converter that transforms globals to JSON and back. Therefore, @Evgeny Shvarov suggested developing Global->JSON->Global converter. Implementing such a converter is important to ensure interoperability, simplify data exchange, support web services, and provide a standardized approach to data representation across different software ecosystems. This article, the second in the "Implemented Ideas" series, focuses on several projects created by the legend of InterSystems Developer Community @Robert Cemper that deal with this task:

• GlobalToJSON-Compact
• GlobalToJSON-Efficient
• GlobalToJSON-Academic
• GlobalToJSON-embeddedPython
• GlobalToJSON-ePython-pure
• GlobalToJSON-XLA
• JSONfile-to-Global.

There is an interesting new feature in the recently announced 2024.1 preview, JSON_TABLE. JSON_TABLE is one of a family of functions introduced by the 2016 version of the SQL Standard (ISO Standard, published in early 2017). It allows for JSON values to be mapped to columns and queried using SQL. JSON_TABLE is valid in the FROM clause of some SQL statements.

The syntax of JSON_TABLE is quite large, allowing for exceptional conditions where the provided JSON values don't match expectations, nested structures and so on.

The architect of the JSON schema (MS) asked if IRIS could perform schema validation. I asked on Discord objectscript channel how we could validate a Dynamic Object against a JSON schema. Dmitry Maslennikov replied that probably the easiest way would be to use python, but it would require converting ObjectScript JSON to Python dict.

An App that converts HL7 messages to JSON objects. About a year ago I started a GitHub repo for collecting stuff related to HL7. Recently my team added an HL7 interface to our Interoperability Production and we were asked to persist HL7 messages. We created a Kafka topic to receive HL7 messages. We use Kafka Bridges to send messages to Kafka topics. Kafka messages are sent to the Kafka Bridge in JSON format.

We have a yummy dataset with recipes written by multiple Reddit users, however most of the information is free text as the title or description of a post. Let's find out how we can very easily load the dataset, extract some features and analyze it using features from OpenAI large language model within Embedded Python and the Langchain framework.

The Lo-Code Challenge

Imagine the scene. You are working happily at Widgets Direct, the internet's premier retailer of Widgets and Widget Accessories. Your boss has some devastating news, some customers might not be fully happy with their widgets, and we need a helpdesk application to track these complaints. To makes things interesting, he wants this with a very small code footprint and challenges you to deliver an application in less than 150 lines of code using InterSystems IRIS. Is this even possible?

How can IRIS productions be deployed more quickly and with greater peace of mind?

The aim of interoperability productions is to enable you to connect systems in order to transform and route messages between them. To connect systems, you develop, configure, deploy and manage productions that integrate several software systems.

Hi Community,
In this article, I will demonstrate below steps to create your own chatbot by using spaCy (spaCy is an open-source software library for advanced natural language processing, written in the programming languages Python and Cython):

• Step1: Install required libraries

• Step2: Create patterns and responses file

• Step3: Train the Model

• Step4: Create ChatBot Application based on the trained model

So Let us start.

In this article, I walk through the %JSON.Adaptor class.

Methods written in ObjectScript can use pass-by-reference arguments to return information to the caller. Python doesn’t support pass-by-reference arguments, so Embedded Python in IRIS doesn’t support them either. That's it, that's the end of the post, hope you liked it. 😉 But wait, what about the Classic Rock & Roll?

Saw the other day an article with the usage of the %ZEN package when working with JSON and decided to write an article describing a more modern approach. At some recent point, there was a big switch from using %ZEN.Auxiliary.* to dedicated JSON classes. This allowed to work with JSONs more organically.

Thus, at this point there are basically 3 main classes to work with JSON:

• %Library.DynamicObject - provides a simple and efficient way to encapsulate and work with standard JSON documents. Also, there is a possibility instead of writing the usual code for creating an instance of a class like

set obj = ##class(%Library.DynamicObject).%New()

it is possible to use the following syntax

set obj = {}

• %Library.DynamicArray - provides a simple yet efficient way to encapsulate and work with standard JSON arrays. With arrays you can use the same approach as with objects, meaning that yu can either create an instance of the class

set array = ##class(%DynamicArray).%New()

set array = []

Foreword

InterSystems IRIS versions 2022.2 and newer feature a redesigned functionality for JSON web tokens (JWTs). Once housed under the %OAuth2 class package, the JWT class, along with other JSON web classes (JWCs), now live under %Net.JSON. This migration occured in order to modularize the JWCs. Before, they were closely intertwined with the implementation for the OAuth 2.0 framework. Now, they can be maintained and used separately from OAuth2.

Why I've decided to write this

Once again I had a challenge that costed me some time and a lot of testing to reach the best solution. And now that I've managed to solve it, I'd like to share a little bit of my knowledge.

What happened?

In a namespace there were a lot of similar classes, so to make them simpler there were a superclass with comon properties. Also, there are relationships between them. I had to export one of them to JSON, but I couldn't change the superclasses, or I would break down the flow of many other integrations.

The similarity between JSON objects + arrays and Globals in IRIS or Caché is evident.
With small and medium size JSON objects navigation across %Dynamic Objects is comfortable.
But with large and/or deep cascaded objects it becomes a challenge.

The presented tool offers 3 variants

• loading an already existing %Dyamic object or Array into a global of your choice
• loading a %Stream containing a JSON object into a global of your choice
• loading an external File containing a JSON object into a global of your choice