You may think it isn’t too difficult to get from label+offset^routine to the actual source line responsible for the error.  For an expert it isn't that hard... most of the time.  But there are enough oddities and special rules that even an expert can get it wrong, whilst spending a lot of time trying to get there.

gj :: locate is the latest tool from George James Software – it debugs any error, class or routine by converting the location of an error in compiled .int code to the corresponding location in your source, and then taking you right there.

Image this scenario…

The latest release of Serenji by George James Software introduces zero configuration debugging, so it's ready to go in just one click - no matter where you are or what you're doing, your on-the-spot debugger is ready to go. 

We have introduced a host of new features to enhance the debugging experience so you can focus on identifying and fixing errors, without losing focus by spending time setting up a launch configuration. 

Check out the new features in our release notes. 

If you've already started using Serenji 3.2.0 let us know how you're getting on! 

Hi guys.

That time I'll show you a way to use a machine learning model implemented using IntegradeML as source for an IRIS analytics cube dimension.

Creating the ML model:

Execute this SQL in order to create a new ML model using IntegratedML SQL extension:

IRIS and Caché / Ensemble offer the possibility to add Languages Extension as SystemFunctions,  SystemVariables,  SystemCommands

The related documentation tells you where to add the system-wide extension. Parameter passing is not covered explicitly.

Introduction

With the growing popularity of smart phones and tablet computers, consumers are coming to expect that software solutions will be presented as "apps" on their mobile devices. The challenge for most application developers is to find ways to make their existing solutions run on modern mobile platforms without incurring the delay and cost of a complete rewrite.

Let's assume that we have already connected a data source to Adaptive Analytics, created a project and added tables there.

Presenter: Paul Dayan
Task: Upgrade with minimal downtime
Approach: Provide examples of planning minimal-downtime upgrades from a variety of starting scenarios

When upgrading Caché, Ensemble or your application on your business-critical system, you want zero or minimum downtime. This session explores the problems and options when upgrading, and how mirroring can reduce or eliminate business disruption, with practical steps and a demonstration.

Content related to this session, including slides, video and additional learning content can be found here.

A business case for the transition from eGate to InterSystems EnsembleÆ From interface engine to integration platform Healthcare IT is evolving so rapidly that the term "HL7 interface engine" may soon become extinct. Forces driving this evolution include:

Hi Developers!

Suppose you published your application on Open Exchange with version 1.00. And then you've added a new outstanding feature and you make a new release.

You can also make a new release of your application on Open Exchange.

Why make releases on Open Exchange? 

This the way for you to highlight the new features of your application. When you publish a new release the following happens:

Release notes appear on the News page of Open Exchange

The version of your app changes

Version History tab is updated

Application to import 12 Datasets along with 43 tables dynamically by using  LOAD DATA command which loads data from a source into an IRIS SQL table. 
List of Datasets

What is Selective Build?

Selective Build is a BI feature in InterSystems IRIS (introduced in version 2020.1). Selective Build allows you to build specific elements of your cube while keeping your cube online.

What is special about Selective Build?

Before getting into the details of Selective Build, a brief recap of the different phases during a regular cube build is important. Here are the phases in a regular cube build:
1) Delete existing data in cube
2) Populate cube with full set of data
3) Build all indices in the cube

Hi Community,

Imagine enabling your application to read text to your customer? This is now possible with the new IRIS feature, Embedded Python. With this new functionality IRIS can natively run any open source or commercial Python libraries natively. gTTS (https://pypi.org/project/gTTS/) is a free library that transforms text into audio using the Google Translate service.

I have created a package that offers a utility to load a Global into JSON object and reverse     
to create a Global from this type of JSON object. Academic refers to the structure created.
Each logical node of the Global is presented separately with all its descendants.
Even if they don't contain any stored data.

I compiled some data about past InterSystems DC constest. Some statistics:

• 64 applications (17% of all current apps into OEX - 377 apps in december/2020)
• 08 contests
• 29 developers

See the summary: